scripts de harmonizacion de David

README.txt

+empty_cell_fixer.r + add_missing_values.r
+
+Cambia las casillas vacías, puntos, "NA", y "Unknowns" por missing, y en el "_numeric" acorde lo cambia por un 999
+
+dora_test.r
+
+Ejecuta la función personalizada que calcula el score derivado de las variables
+
+full_quality_report.r
+
+Genera un documento word con los hospitales y las variables especificadas dónde se ordenan de mayor a menor varianza entre los hosptiales
+
+survival_curve.r
+
+Genera una curva de supervivencia
+
+table1_script.r + necessary_functions_table1_v2_subset.r
+
+Muestra una tabla que muestra la información sobre los hospitales y las variables indicadas.
+
+valid_variables_script.r
+
+Comprueba que los valores de las variables del hospital indicado estén dentro de los rangos
+(Se puede cambiar para que refleje lo que se desea obtener)
+
+treatment_heatmap.r
+
+Devuelve un mapa de calor que indica el porcentaje de pacientes que han recibido cada tratamiento spearados por olas.
+
+ressourceCleaner.r
+
+Deja los datos con Yes/No Male/Female etc
+
+ressourceHarmonizer.r
+
+Deriva las variables "_numeric"
\ No newline at end of file

add_missing_values.r

+setwd("C:/Users/victor/Documents/TFG/r-analytics-master")
+codebook <- read.csv("new_harmon.csv", sep = ",")
+
+binary <- unlist(codebook[codebook["Variable.type"] == "Binary",]["Harmonised.variable.name"])
+categorical <- unlist(codebook[codebook["Variable.type"] == "Categorical",]["Harmonised.variable.name"])
+continuous <- unlist(codebook[codebook["Variable.type"] == "Continuous",]["Harmonised.variable.name"])
+
+categoric_vars <- c(binary, categorical)
+
+replace_with_Missing_categoric <- function(column){
+  
+  for (i in 1:length(column)){
+    
+    x <- column[i]
+    
+    if (is.na(x)){
+      x <- "Missing"
+      
+    }else{
+      
+      if(x == "" | x == "NA" | x == "Unknown")
+        x <- "Missing"
+    }
+    
+    column[i] <- x
+    
+  }
+  
+  return (column)
+}
+
+replace_with_Missing_num_categoric <- function(column){
+  
+  for (i in 1:length(column)){
+    
+    x <- column[i]
+    
+    if (is.na(x)){
+      x <- 9999
+      
+    }else{
+      
+      if(x == "" | x == "NA" | x == "Unknown")
+        x <- 9999
+    }
+    
+    column[i] <- x
+    
+  }
+  
+  return (column)
+}
+
+
+replace_with_Missing_continuous <- function(column){
+  
+  for (i in 1:length(column)){
+    
+    x <- column[i]
+    
+    if (is.na(x)){
+      x <- ""
+      
+    }else{
+      
+      if(x == "NA" | x == "Unknown")
+        x <- ""
+    }
+    
+    column[i] <- x
+    
+  }
+  
+  return (column)
+  
+}
+
+
+add_missing_values <- function(path_to_file){
+  
+  
+  setwd("C:/Users/victor/Documents/TFG/r-analytics-master/ressources/current_db")
+  data <- read.csv(path_to_file, sep = ",")
+  
+  data_colnames <- colnames(data)
+  
+  num_categoric <- data_colnames[grepl("_numeric", data_colnames)]
+  
+  aux <- length(data_colnames)
+  
+  for (i in 1:aux){
+    colname <- data_colnames[i]
+    
+    progress <- round((100*i/aux),digits = 0)
+    print(paste(progress,"%", sep = ""))
+    
+    if(colname %in% categoric_vars){
+      column <- unlist(data[colname])
+      data[colname] <- replace_with_Missing_categoric(column)
+    }
+    
+    if(colname %in% num_categoric){
+      column <- unlist(data[colname])
+      data[colname] <- replace_with_Missing_num_categoric(column)
+    }
+    
+    if(colname %in% continuous){
+      column <- unlist(data[colname])
+      data[colname] <- replace_with_Missing_continuous(column)
+    }
+    
+    
+  }
+  
+  return(data)
+  
+  
+}
+
+

admissions_histogram.R

+
+
+rm(list=ls())
+
+setwd("C:/Users/victor/Documents/TFG/r-analytics-master")
+
+
+source("dependency_installer.R")
+source("connection_parameters.R")
+source("necessary_functions_graph.R")
+
+dep_list = c( "stringr","DSI","DSOpal","DSLite", "fields", "metafor", "ggplot2", "gridExtra", "data.table", "dsBaseClient")
+install_dependencies(dep_list)
+
+dir.create("./admissions_analysis", showWarnings = FALSE)
+setwd("./admissions_analysis")
+
+aux <- connect()
+connections <- aux[[1]]
+inp <- aux[[2]]
+
+
+obtain_admissions_graph(connections,inp)
+
+

connection_parameters.R

+
+
+hospital_names <- c(    #Añadir Los de Baskent y sacrocuore
+  "Princesa",
+  "CIPH",
+  "UMF_Iasis",
+  "SMUC",
+  "HM",
+  "Porto",
+  "FJD",
+  "Coimbra",
+  "UNAV",
+  "TU",
+  "Ankara Impatient",
+  "Konya Impatient",
+  "Istambul Impatient",
+  "Izmir Impatient",
+  "Alanya Impatient",
+  "Adana Impatient",
+  "Ankara Outpatient",
+  "Konya Outpatient",
+  "Istambul Outpatient",
+  "Izmir Outpatient",
+  "Alanya Outpatient",
+  "Sacrocuore Emergency",
+  "Sacrocuore Employees",
+  "Sacrocuore Verona",
+  "Sacrocuore Isaric",
+  "TUDublin",
+  "UMF_Cluj",
+  "UdeA",
+  "Inantro",
+  "UNSA",
+  "UZA"
+)
+
+project_names <- c(
+  "FIBHULP",
+  "CIPH_unCoVer",
+  "umfiasi",
+  "SMUC",
+  "FiHM",
+  "uncover-up",
+  "IISFJD",
+  "IPC",
+  "unCOVer-UNAV",
+  "TU_Uncover",
+  "BU",
+  "BU",
+  "BU",
+  "BU",
+  "BU",
+  "BU",
+  "BU",
+  "BU",
+  "BU",
+  "BU",
+  "BU",
+  "S_uncover",
+  "S_uncover",
+  "S_uncover",
+  "S_uncover",
+  "TUDublin",
+  "UMF_Cluj",
+  "INS_Data",
+  "INANTRO",
+  "UnCoVer-BiH-Final",
+  "UZA"
+)
+
+resource_names <- c(
+  "Harmonized_variables_2",
+  "CIPH_numeric_derivated",
+  "20220719_HarmonisedUMFIasi",
+  "SMUC_resource",
+  "20220720_HarmonisedHM",
+  "Resource_derived",
+  "IISFJD_Harmonized_1",
+  "IPC_Harmonized",
+  "UNAV_rsc",
+  "TU_Harmonized",
+  "inpatient_ankara",
+  "inpatient_konya",
+  "inpatient_istanbul",
+  "inpatient_izmir",
+  "inpatient_alanya",
+  "inpatient_adana",
+  "outpatient_ankara",
+  "outpatient_konya",
+  "outpatient_istanbul",
+  "outpatient_izmir",
+  "outpatient_alanya",
+  "emergency",
+  "employees",
+  "verona",
+  "isaric",
+  "TUDublin_harmonised",
+  "Romania",
+  "colombia_all",
+  "Inantro",
+  "20220722_HarmonizedUNSA",
+  "UZA_prelim"
+)
+
+urls <- c(
+  "https://192.168.1.200:8001",
+  "https://192.168.1.200:8002",
+  "https://192.168.1.200:8003",
+  "https://192.168.1.200:8006",
+  "https://192.168.1.50:9002",
+  "https://192.168.1.102",
+  "https://uncover.itg.be",
+  "https://uncover.itg.be",
+  "https://192.168.1.50:9001",
+  "https://192.168.1.200:8004",
+  "https://192.168.1.101:8443",
+  "https://192.168.1.101:8443",
+  "https://192.168.1.101:8443",
+  "https://192.168.1.101:8443",
+  "https://192.168.1.101:8443",
+  "https://192.168.1.101:8443",
+  "https://192.168.1.101:8443",
+  "https://192.168.1.101:8443",
+  "https://192.168.1.101:8443",
+  "https://192.168.1.101:8443",
+  "https://192.168.1.101:8443",
+  "https://192.168.1.50:8890",
+  "https://192.168.1.50:8890",
+  "https://192.168.1.50:8890",
+  "https://192.168.1.50:8890",
+  "https://uncover.itg.be",
+  "https://192.168.1.200:8005",
+  "https://fenfisdi.udea.edu.co/opal",
+  "https://192.168.1.200:8007",
+  "https://192.168.1.200:8008",
+  "https://uncover.itg.be"
+  
+)
+
+users <- c(
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "emertens",
+  "emertens",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "emertens",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "user_analisis",
+  "emertens"
+)
+
+pass <- c(
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "3^z4AV.)hG5~PT/]",
+  "3^z4AV.)hG5~PT/]",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "3^z4AV.)hG5~PT/]",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "Ekfl07UUgz",
+  "3^z4AV.)hG5~PT/]"
+)

dependency_installer.R

+
+# This function receives a list of packages to be installed before the execution of a script.
+# For each package provided, it verifies that it is not installed already. If so, it proceeds to
+# install it.
+# ToDo: exception control for unexistent/misspelled packages.
+
+install_dependencies <- function(dep_list) {
+  
+  # Deprecated since executing server is Ubuntu.
+  #if(Sys.info()["sysname"] == "Windows"){
+  #  dep_list[length(dep_list)+1] = "Rtools"
+  #}
+  for(p in dep_list){
+
+    if(require(p, character.only = T) == FALSE){
+      if(p == "dsBaseClient"){
+        library(remotes)
+        install_github("datashield/dsBaseClient", dependencies = TRUE)
+      }else{
+        if(p == "DSI"){
+           library(remotes)
+           install_github('datashield/DSI', ref = '1.3.3', dependencies = TRUE)
+        }else{
+           install.packages(p, dependencies = TRUE, repos = "https://cran.us.r-project.org")
+        }
+      }  
+    }
+    if(p != "Rtools"){
+      library(p, character.only = T)
+    }   
+  }  
+  
+}
+

dora_test.R

+rm(list=ls())
+
+setwd("C:/Users/victor/Documents/TFG/r-analytics-master")
+
+source("dependency_installer.R")
+
+
+dep_list = c("magrittr","officer","dplyr","stringr","DSI","DSOpal","DSLite","dsBaseClient")
+install_dependencies(dep_list)
+
+#,"DSI","DSOpal","DSLite"
+
+source("connection_parameters.R")
+source("necessary_functions_connection.R")
+
+auxConnections <- connect()
+connections <- auxConnections[[1]]
+inp <- auxConnections[[2]]
+
+calltext <- call("DORA_scoresDS", "data")
+newobj <- "DORA_table"
+datashield.assign(connections, newobj, calltext)
+
+ds.colnames("DORA_table")
+ds.table("DORA_table$DORA_class")
+
+datashield.logout(connections)

empty_cell_fixer.r

+
+setwd("C:/Users/victor/Documents/TFG/r-analytics-master")
+source("add_missing_values.R")
+
+list_of_files <- list.files("C:/Users/victor/Documents/TFG/r-analytics-master/ressources/current_db")[-6]
+
+#ist_of_files <- "Harmonized_LIH.csv"
+
+for (i in 1:length(list_of_files)) {
+  
+  file_name <- list_of_files[i]
+  
+  print(paste ("Fixing file:", file_name))
+  
+  setwd("C:/Users/victor/Documents/TFG/r-analytics-master/ressources/current_db")
+  
+  ready_file <- add_missing_values(file_name)
+  
+  setwd("C:/Users/victor/Documents/TFG/r-analytics-master/ressources/current_db/ready")
+  
+  write.csv(x=ready_file, file = file_name, row.names = FALSE)
+  
+}

full_quality_report.R

+rm(list=ls())
+
+setwd("/home/david/Documentos/Uncover/ScriptsVictor")
+
+source("dependency_installer.R")
+
+
+dep_list = c("magrittr","officer","dplyr","stringr","DSI","DSOpal","DSLite","dsBaseClient")
+install_dependencies(dep_list)
+
+#,"DSI","DSOpal","DSLite"
+
+source("connection_parameters.R")
+source("necessary_functions_connection.R")
+
+codebook <- data.frame(read.csv("new_harmon.csv", sep = ","))
+codebook_variable_names <- codebook[,2]
+
+namesDescMes <- codebook[,c(2,4,6)]
+
+categoric_vars = c(
+  #Si&Sympt
+  "CSXCTR","SMXASAH","SMXCOA","SMXSTA","SMXSBA","SMXRNA","SMXSEA","SMXMYA","SMXARA","SMXCPA","SMXAPA","SMXINA","SMXNAA","SMXDIA","SMXFAA","SMXHEA","SMXCNA","SMXACA","SMXSLA","SMXTLA","SMXSYA","SMXWHA","SMXLYA","SMXANA","SMXIWA","SMXSRA","SMXBLA","CSXCOT",
+  
+  #Com&RF
+  "CMXPRG","CMXCVD","CMXCMP","CMXHT","CMXDI","CMXCKD","CMXCLD","CMXCPD","CMXASM","CMXCND","CMXRHE","CMXCCI","CMXCBD","CMXDE","CMXPU","CMXST","CMXLY","CMXAP","RFXSM","RFXFSM","RFXOB","RFXTB","RFXIMD","RFXHIV","RFXAIDS","RFXUI","RFXHC","RFXONC","RFXMN","CMXCHF","CMXVDP","CMXVDC","CMXCA","CMXVD","CMXABL","CMXAD","CMXNDP","CMXNDD","CMXCOPD","CMXPCD","CMXRI","CMXMLD","CMXNPM","CMXCLH","CMXMET","CMXTU","CMXMY","CMXNP","RFXMD","CMXANX","CMXBDO","CMXEPI","CMXOAR","CMXSPI","CMXSOT","CMXOKD","CMXUTI","CMXINC","CMXHPP","CMXHGL","RFXLC","RFXPM","RFXAP","CMXIHD","CMXATH",
+  
+  #Treatment
+  "TRXAV","TRXRIB","TRXLR","TRXRM","TRXIA","TRXIB","TRXCH","TRXAB","TRXCS","TRXHEP","TRXAF","TRXCP","TRXOT","TRXECM","TRXIV","TRXNIV","TRXNO","TRXOX","TRXRR","TRXTR","TRXVA","TRXPE","TRXPV","TRXIT","TRXNMB","TRXAC","TRXINA","TRXIS","TRXIM","TRXVC","TRXVD","TRXZN",
+  
+  #Dates
+  "DSXHO","DSXIC","DSXOS",
+  
+  #Home med
+  "HMRACI","HMRARB","HMRAHO","HMRNS","HMROS","HMRCS","HMRIS","HMRAV","HMRAB","HMRCOV","HMRANC","HMRAT","HMRINS",
+  
+  #Demographics
+  "DMRGENDR","DMRRETH1","DMROCCU","DMRHREDU",
+  
+  #Imaging Data
+  "IMDXCT","IMDXCTCR","IMDXCTTE","IMDXCTAB","IMDXXR","IMDXXRI","IMDXPN",
+  
+  #Complications
+  "COXRD","COXAR","COXPM","COXMOD","COXPT","COXEC","COXSH","COXIO","COXPE","COXST","COXDIC","COXRIO","COXKF","COXHF","COXBC","COXRF","COXLF","COXADE","COXSTN","COXNOC"
+  
+  
+)
+
+date_vars <- c("DATCOT","DATSO","DATAD","DATADI","DATDSI","DATDS","DATPR","DATOS")
+
+#Check which hospitals contain a given value
+hospitals_contains_variable <- function(variable){
+  
+  res <- c()
+  
+  for(i in seq_along(full_variable_list)){
+    if (variable %in% unlist(full_variable_list[i]))
+      res <- c(res, hospital_names[i])
+  }
+  
+  return(res)
+}
+
+get_working_hospitals <- function(errors){
+  
+  working <- c()
+  
+  for(i in seq_along(hosp_to_analyze)){
+    hosp_in_err <- grepl(hosp_to_analyze[i], errors, fixed = TRUE)
+    if(!(TRUE %in% hosp_in_err))
+      working <- c(working, hosp_to_analyze[i])
+  }
+  
+  return(working)
+}
+
+
+auxConnections <- connect()
+connections <- auxConnections[[1]]
+inp <- auxConnections[[2]]
+
+
+#--------------------------------------------------------
+
+#Extract the column names from the hospital datasets
+full_variable_list <- ds.colnames("data")
+data_dimentions <- head(ds.dim("data"),-1)
+data_dimentions <- lapply(data_dimentions, `[[`, 1)
+names(data_dimentions) <- names(full_variable_list)
+
+hospital_names <- names(full_variable_list)
+
+#Intersect the elements from the variables present in the hospitals and the ones in the codebook
+# COMPARAR LAS VARIABLES QUE TIENEN CADA HOSPITAL CON LAS DEL CODEBOOK Y ASI ELIMINAR LAS QUE NO ESTEN
+for(i in seq_along(full_variable_list)){
+  hospital_variable_list <- unlist(full_variable_list[i])
+  full_variable_list[[i]] <- Reduce(intersect, list(hospital_variable_list,codebook_variable_names))
+}
+
+#Make a list containing all the variables to analyze
+# HACES LA UNION DE LAS VARIABLES DE TODOS LOS HOSPITALES
+variables_to_analyze <- Reduce(union, full_variable_list)
+#aux_vars <- list("DMRAGEYR","LBXSBUA","LBXCRPA","LBXPLTSIA","CSXCHRA","CSXOSTA","LBXFIOA","SMXBLA","SMXSBA","SMXACA","RFXONC","LBXNENOA","LBXLYMNOA","LBXSBLA","LBXSCBA","DMRGENDR", "CSXRRA","CSXOSTA","SMXACA","LBXSBUA","LBXCRPA")
+# CON ESTOS SELECCIONAS LAS VARIABLES QUE QUIERES ANALIZAR
+aux_vars <- list("DMRGENDR", "SMXACA", "DMRAGEYR","CSXBTPA","CSXDIA","CSXOSTA","CSXRRA","LBXSBUA")
+vars_list <- as.list(variables_to_analyze)
+variables_to_analyze <- unlist(Reduce(intersect, list(aux_vars,vars_list)))
+
+df_list <- list()
+variances_list <- list()
+df_categoric_list <- list()
+variances_list_categoric <- list()
+
+for(i in seq_along(variables_to_analyze)){
+
+  #Select the variable to analyse
+  variable <- variables_to_analyze[i]
+  dataset_variable <- paste0("data$", variable)
+  is_categoric <- variable %in% categoric_vars
+  is_date <- variable %in% date_vars
+  print(variable)
+  
+  hosp_to_analyze <- hospitals_contains_variable(variable)
+  
+  
+  #If the variable is categoric
+  if(is_categoric){
+    print("categoric")
+    
+    OK <- FALSE
+    try({
+      categoric_table <- ds.table(dataset_variable, datasources = connections[hosp_to_analyze])
+      OK <- TRUE
+    })
+    
+    if(OK){
+      result <- TRUE
+      list_bool <- !grepl("failed", categoric_table[[1]])
+      list_bool <- c(TRUE, TRUE, TRUE)
+      for (i in seq_along(list_bool)){
+        result <- result & list_bool[i]
+      }
+      if(result){
+        
+        categoric_table <- as.data.frame(categoric_table[[1]][[2]])
+        categoric_table[,"column variance"] <- NA
+        
+        for( j in seq_len(nrow(categoric_table))){
+          
+          row_values <- as.numeric(as.vector(categoric_table[j,]))
+          row_variance <-  var(row_values[!is.na(row_values)])
+          categoric_table[j,"column variance"] <- row_variance
+        }
+        
+        
+        categoric_table <- categoric_table %>% mutate_if(is.numeric, round, 3)
+        categoric_table <- as.data.frame(t(categoric_table))
+        
+        #aux_df <- #INCLUIR UNA COLUMNA QUE TENGA LOS NOMBRES DE LOS HOSPITALES
+        categoric_table["Hospitals"] <- row.names(categoric_table)
+        aux_table <- categoric_table[c(ncol(categoric_table), 1:(ncol(categoric_table)-1))]
+        
+        aux_list <- list(aux_table)
+        names(aux_list) <- variable
+        df_categoric_list <- append(df_categoric_list, aux_list)
+        
+        vector_aux <- as.numeric(aux_table["column variance",][,-1])
+        mean_aux <- list(mean(vector_aux[!is.na(vector_aux)]))
+        names(mean_aux) <- variable
+        variances_list_categoric <- append(variances_list_categoric,mean_aux)
+        
+      }else{
+        print("This variable cannot be analyzed")
+        print(paste("Error in the hospitals:", aux_table["Hospitals"]))
+      }
+    }
+    
+  # If the variable is nuemric  
+  }else
+    if (!is_categoric & !is_date){
+    print("numeric")
+    
+    #Obtain the means and the missing values for each hospital
+    res <- tryCatch({
+      # OBTIENE LAS MEDIAS DE LOS HOSPITALES
+      means <- as.data.frame(ds.mean(dataset_variable, datasources = connections[hosp_to_analyze])[[1]])[c(1,2)]
+      working_hospitals <- hosp_to_analyze
+      follow <- TRUE
+      res<- list(follow, means, working_hospitals)
+      return(res)
+  
+    },error = function(e){
+      errors <- datashield.errors()
+      
+      #If all the hospitals that contain the variable give errors, the variable is skipped
+      if(length(errors) != length(hosp_to_analyze)){
+        working_hospitals <- get_working_hospitals(errors)
+        means <- as.data.frame(ds.mean(dataset_variable, datasources = connections[working_hospitals])[[1]])[c(1,2)]
+        follow <- TRUE
+        print("Hospitals that contain the variable:")
+        print(hosp_to_analyze)
+        print("Hospitals that do not give errors:")
+        print(working_hospitals)
+      }else{
+        err_mes <- paste("Unable to analyze data for the variable:", variable)
+        print(err_mes)
+        follow <- FALSE
+      }
+      
+      res<- list(follow, means, working_hospitals)
+      
+      return(res)
+    })
+    
+    follow <- unlist(res[1])
+    means <- as.data.frame(res[2])
+    working_hospitals <- unlist(res[3])
+    
+    if(follow == TRUE){
+      # PONES BONITO LOS VALORES MISSING
+      means["Hospital"] <- rownames(means)
+      df_aux <- means[,c(3,1,2)]
+      colnames(df_aux) <- c("Hospital", "Mean", "Missing")
+      df_aux$Mean<-format(round(df_aux$Mean,2),nsmall=2)
+      missing <- as.list(df_aux$Missing)
+      percentages <- lapply(mapply(FUN = `/`, missing, data_dimentions[working_hospitals], SIMPLIFY = FALSE), round, 4)
+      percentages <- lapply(percentages,"*", 100)
+      
+      for(j in 1:length(percentages)){
+        value <- paste(paste(paste(missing[j], "("),percentages[j],sep=""),"%)",sep="")
+        percentages[j] <- value
+      }
+      
+      df_aux$Missing <- unlist(percentages)
+    }
+    
+
+    means_var <- var(means[,1])
+    
+    #Store the obtained values
+    aux_list <- list(means_var)
+    names(aux_list) <- variable
+    variances_list<- append(variances_list,aux_list)
+    aux_list <- list(df_aux)
+    names(aux_list) <- variable
+    df_list<- append(df_list,aux_list)
+    
+  }else if (!is_categoric & is_date){
+    print("date")
+  }
+  
+}
+
+
+
+ datashield.logout(connections)
+
+
+
+
+
+
+
+
+doc_1 <- read_docx() %>%
+  body_add_par("Data quality report", style = "heading 1")%>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par(value = "This document contains information on every variable present in the hospital's datasets.", style = "Normal") %>% 
+  body_add_par("The variables will be displayed following a decreasing order of the means variance. If a variable is missing a hospital, it means that there has been an error analyzing that variable in that specific hospital.", style = "Normal")%>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("Numeric variables", style = "heading 1")%>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("", style = "Normal")%>%
+print(doc_1, target = "data_quality_report.docx") 
+  
+
+ordered_variance_list <- variances_list[order(unlist(variances_list), decreasing = TRUE)]
+ordered_variance_list_Not_NA <- ordered_variance_list[!is.na(ordered_variance_list)]
+ordered_variance_list_NA <- ordered_variance_list[is.na(ordered_variance_list)]
+ordered_names_Not_NA <- names(ordered_variance_list_Not_NA)
+ordered_names_NA <- names(ordered_variance_list_NA)
+
+
+# SOLO RECORRE LAS VARIABLES NUMERICAS QUE TIENE VARIANZA NO NULA
+for (i in 1:length(ordered_variance_list_Not_NA)) {
+  element <- ordered_names_Not_NA[i]
+  
+  tab1 <- df_list[[element]]
+  variance <- variances_list[[element]]
+  if(!is.na(variance))
+    variance <- format(round(variance, 2), nsmall = 2)
+  
+  print(element)
+  
+  codebook_entry <- subset(codebook, codebook$Harmonised.variable.name == element)
+  description <- unlist(codebook_entry[4])
+  unit <- str_split(unlist(codebook_entry[6]), " ")[[1]][1]
+  range <- codebook_entry[[7]]
+  mes_range <- paste("The range of possible values is:", range)
+  
+  mes_var <- paste("The means variance obtained for this variable is", variance)
+  mes_desc_unit <- paste(paste(paste("This variable represents", paste("'",paste(description,"'",sep=""), sep = "")), "and is measured in"),unit)
+  
+  
+  
+  doc_table <- read_docx(path = "data_quality_report.docx") %>%
+    body_add_par(element, style = "heading 2")%>%
+    body_add_par(mes_var)%>%
+    body_add_par(mes_desc_unit)%>%
+    body_add_par(mes_range)%>%
+    body_add_par("", style = "Normal")%>%
+    body_add_table(tab1, style = "Table Professional")%>%
+  print(doc_table, target = "data_quality_report.docx")
+  
+}  
+
+doc_table <- read_docx(path = "data_quality_report.docx") %>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("The following variables only appear in one hospital, the variance between the means will not be displayed.", style = "Normal")%>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("", style = "Normal")%>%
+print(doc_table, target = "data_quality_report.docx")
+
+
+
+for (i in 1:length(ordered_variance_list_NA)) {
+  
+  element <- ordered_names_NA[i]
+  
+  tab1 <- df_list[[element]]
+  
+  print(element)
+  
+  codebook_entry <- subset(codebook, codebook$Harmonised.variable.name == element)
+  description <- unlist(codebook_entry[4])
+  unit <- str_split(unlist(codebook_entry[6]), " ")[[1]][1]
+  range <- codebook_entry[[7]]
+  mes_range <- paste("The range of possible values is:", range)
+  
+  mes_desc_unit <- paste(paste(paste("This variable represents", paste("'",paste(description,"'",sep=""), sep = "")), "and is measured in"),unit)
+  
+  doc_table <- read_docx(path = "data_quality_report.docx") %>%
+    body_add_par(element, style = "heading 2")%>%
+    body_add_par(mes_desc_unit)%>%
+    body_add_par(mes_range)%>%
+    body_add_par("", style = "Normal")%>%
+    body_add_table(tab1, style = "Table Professional")%>%
+    print(doc_table, target = "data_quality_report.docx")
+  
+}  
+
+
+
+if (length(df_categoric_list) != 0){
+
+  doc_table <- read_docx(path = "data_quality_report.docx") %>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("Categoric variables", style = "heading 1")%>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("", style = "Normal")%>%
+  print(doc_table, target = "data_quality_report.docx")
+  categoric_names <- names(df_categoric_list)
+
+ordered_variance_list_categoric <- variances_list_categoric[order(unlist(variances_list_categoric), decreasing = TRUE)]
+ordered_variance_list_Not_NA_categoric <- ordered_variance_list_categoric[!is.na(ordered_variance_list_categoric)]
+ordered_variance_list_NA_categoric <- ordered_variance_list_categoric[is.na(ordered_variance_list_categoric)]
+ordered_names_Not_NA_categoric <- names(ordered_variance_list_Not_NA_categoric)
+ordered_names_NA_categoric <- names(ordered_variance_list_NA_categoric)
+
+for (i in 1:length(ordered_names_Not_NA_categoric)) {
+
+  element <- ordered_names_Not_NA_categoric[i]
+
+  tab1 <- as.data.frame(df_categoric_list[[element]])
+  var <- unlist(ordered_variance_list_Not_NA_categoric[element])
+
+  print(element)
+
+  codebook_entry <- subset(codebook, codebook$Harmonised.variable.name == element)
+  description <- unlist(codebook_entry[4])
+  unit <- str_split(unlist(codebook_entry[6]), " ")[[1]][1]
+
+  mes_desc_unit <- paste(paste(paste("This variable represents", paste("'",paste(description,"'",sep=""), sep = "")), "and the possible values are"),unit)
+  mes_var <- paste("The variance between rows is:", var)
+
+  doc_table <- read_docx(path = "data_quality_report.docx") %>%
+    body_add_par(element, style = "heading 2")%>%
+    body_add_par(mes_desc_unit)%>%
+    body_add_par(mes_var)%>%
+    body_add_par("", style = "Normal")%>%
+    body_add_table(tab1, style = "Table Professional")%>%
+    print(doc_table, target = "data_quality_report.docx")
+
+}
+
+doc_table <- read_docx(path = "data_quality_report.docx") %>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("The following variables only appear in one hospital, the variance between the means will not be displayed.", style = "Normal")%>%
+  body_add_par("", style = "Normal")%>%
+  body_add_par("", style = "Normal")%>%
+  print(doc_table, target = "data_quality_report.docx")
+
+
+if(length(ordered_names_NA_categoric)>0){
+  for (i in 1:length(ordered_names_NA_categoric)) {
+
+    element <- ordered_names_NA_categoric[i]
+
+    tab1 <- as.data.frame(df_categoric_list[[element]])
+
+    print(element)
+
+    codebook_entry <- subset(codebook, codebook$Harmonised.variable.name == element)
+    description <- unlist(codebook_entry[4])
+    unit <- str_split(unlist(codebook_entry[6]), " ")[[1]][1]
+
+    mes_desc_unit <- paste(paste(paste("This variable represents", paste("'",paste(description,"'",sep=""), sep = "")), "and the possible values are"),unit)
+
+    doc_table <- read_docx(path = "data_quality_report.docx") %>%
+      body_add_par(element, style = "heading 2")%>%
+      body_add_par(mes_desc_unit)%>%
+      body_add_par("", style = "Normal")%>%
+      body_add_table(tab1, style = "Table Professional")%>%
+      print(doc_table, target = "data_quality_report.docx")
+
+  }
+
+
+}
+}
+
+
+
+
+
+
+
+
+
+
+

general_histogram.R

+rm(list=ls())
+
+setwd("C:/Users/victor/Desktop/TFG/r-analytics-master")
+
+source("required_folder_checker.R")
+source("argument_hasher.R")
+source("dependency_installer.R")
+source("connection_parameters.R")
+source("necessary_function_table1s.R")
+
+dep_list = c("jsonlite", "stringr","DSI","DSOpal","DSLite", "fields", "metafor", "ggplot2", "gridExtra", "data.table", "dsBaseClient")
+install_dependencies(dep_list)
+
+
+dir.create("./demographic_analisis", showWarnings = FALSE)
+setwd("./demographic_analisis")
+
+
+aux <- connect()
+connections <- aux[[1]]
+inp <- aux[[2]]
+
+hasOutput  <- checkHasOutput(inp)
+
+name <- getHname(inp)
+
+png(paste(name,".png",sep=""),width=800, height=400)
+
+res <- obtainData(connections, hasOutput, inp)
+
+print(res)
+dev.off()
+
+datashield.logout(connections) 
+
+res
+
+

harmon.csv

+Harmonised variable name;Name Origin;Harmonised variable description;Harmonised data format/unit;,,,,,,,,,,,,,,,,
+DATSSA;SELF;Date of assessment during hospitalisation;dd/mm/yyyy;,,,,,,,,,,,,,,,,
+DATSSDHn;SELF;Time between admission and assessment;days;,,,,,,,,,,,,,,,,
+CSXBTPA;SELF;Body temperature at admission;°C;,,,,,,,,,,,,,,,,
+CSXBTPHn;SELF;Body temperature in hospital;°C;,,,,,,,,,,,,,,,,
+CSXOSTA;SELF;Oxygen Saturation at admission;%;,,,,,,,,,,,,,,,,
+CSXOSTHn;SELF;Oxygen Saturation in hospital;%;,,,,,,,,,,,,,,,,
+CSXCHRA;SELF;Heart Rate at admission;bpm;,,,,,,,,,,,,,,,,
+CSXCHRHn;SELF;Heart Rate in hospital;bpm;,,,,,,,,,,,,,,,,
+CSXRRA;SELF;Respiratory Rate at admission;breaths/min;,,,,,,,,,,,,,,,,
+CSXRRHn;SELF;Respiratory Rate in hospital;breaths/min;,,,,,,,,,,,,,,,,
+CSXRRI;SELF;Respiratory rate in ICU;breaths/min;,,,,,,,,,,,,,,,,
+CSXSYA;SELF;Systolic bp at admission;mmHg;,,,,,,,,,,,,,,,,
+CSXSYHn;SELF;Systolic bp in hospital;mmHg;,,,,,,,,,,,,,,,,
+CSXDIA;SELF;Diastolic bp at admission;mmHg;,,,,,,,,,,,,,,,,
+CSXDIHn;SELF;Diastolic bp in hospital;mmHg;,,,,,,,,,,,,,,,,
+SMXASAH;SELF;Asymptomatic during hospitalisation;Yes/No;,,,,,,,,,,,,,,,,
+SMXFEA;SELF;Fever at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMTFE;SELF;Fever duration;Days;,,,,,,,,,,,,,,,,
+SMXCOA;SELF;Cough at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMTCO;SELF;Cough duration;Days;,,,,,,,,,,,,,,,,
+SMXSTA;SELF;Sore throat at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMTST;SELF;Sore throat duration;Days;,,,,,,,,,,,,,,,,
+SMXSBA;SELF;Shortness of breath at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMTSB;SELF;Shortness of breath duration;Days;,,,,,,,,,,,,,,,,
+SMXRNA;SELF;Runny nose at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXSEA;SELF;Convulsions / Seizures;Days;,,,,,,,,,,,,,,,,
+SMXMYA;SELF;Myalgia at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXARA;SELF;Arthralgia at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXCPA;SELF;Chest pain at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXAPA;SELF;Abdominal pain at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXINA;SELF;Lower chest wall indrawing at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXNAA;SELF;Nausea / Vomiting at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXDIA;SELF;Diarrhoea at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXFAA;SELF;Fatigue at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXHEA;SELF;Headache at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXCNA;SELF;Conjunctivitis at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXACA;SELF;Confusion / Altered consciousness at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXSLA;SELF;Loss of smell at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXTLA;SELF;Loss of taste at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXSYA;SELF;Syncope / Fall at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXWHA;SELF;Wheezing at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXLYA;SELF;Lymphadenopathy at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXANA;SELF;Anorexia at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXIWA;SELF;Inability to walk at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXSRA;SELF;Skin rash at admission;Yes/No;,,,,,,,,,,,,,,,,
+SMXBLA;SELF;Bleeding / Haemorrhage at admission;Yes/No;,,,,,,,,,,,,,,,,
+CMXPRG;SELF;Pregnancy;Yes/No;,,,,,,,,,,,,,,,,
+CMXCVD;SELF;CVD;Yes/No;,,,,,,,,,,,,,,,,
+CMXHT;SELF;Hypertension;Yes/No;,,,,,,,,,,,,,,,,
+CMXDI;SELF;Diabetes;Yes/No;,,,,,,,,,,,,,,,,
+CMXCKD;SELF;Chronic kidney disease;Yes/No;,,,,,,,,,,,,,,,,
+CMXCLD;SELF;Chronic liver disease;Yes/No;,,,,,,,,,,,,,,,,
+CMXCPD;SELF;Chronic pulmonary disease;Yes/No;,,,,,,,,,,,,,,,,
+CMXASM;SELF;Asthma;Yes/No;,,,,,,,,,,,,,,,,
+CMXCND;SELF;Chronic neurological or neuromuscular disorder;Yes/No;,,,,,,,,,,,,,,,,
+CMXRHE;SELF;Rheumatism;Yes/No;,,,,,,,,,,,,,,,,
+CMXCCI;SELF;Chronic cognitive impairment;Yes/No;,,,,,,,,,,,,,,,,
+CMXDE;SELF;Dementia;Yes/No;,,,,,,,,,,,,,,,,
+CMXPU;SELF;Peptic Ulcer / Bleeding;Yes/No;,,,,,,,,,,,,,,,,
+CMXST;SELF;Solid tumour;Yes/No;,,,,,,,,,,,,,,,,
+CMXLY;SELF;Lymphoma;Yes/No;,,,,,,,,,,,,,,,,
+CMXAP;SELF;Asplenia;Yes/No;,,,,,,,,,,,,,,,,
+RFXSM;SELF;Smoking;Yes/No;,,,,,,,,,,,,,,,,
+RFXFSM;SELF;Former smoker;Yes/No;,,,,,,,,,,,,,,,,
+RFXOB;SELF;Obesity;Yes/No;,,,,,,,,,,,,,,,,
+RFXTB;SELF;TB;Yes/No;,,,,,,,,,,,,,,,,
+RFXIMD;SELF;Immunodeficiency;Yes/No;,,,,,,,,,,,,,,,,
+RFXOV;SELF;Overall;Yes/No;,,,,,,,,,,,,,,,,
+RFXHIV;SELF;HIV;Yes/No;,,,,,,,,,,,,,,,,
+RFXAIDS;SELF;AIDS;Yes/No;,,,,,,,,,,,,,,,,
+RFXHC;SELF;Haematological cancer;Yes/No;,,,,,,,,,,,,,,,,
+RFXONC;SELF;Oncology;Yes/No;,,,,,,,,,,,,,,,,
+RFXMN;SELF;Malnutrition;Yes/No;,,,,,,,,,,,,,,,,
+TRXAV;SELF;Antiviral or COVID-19 targeted;Yes/No;,,,,,,,,,,,,,,,,
+TRXRIB;SELF;Ribavirin;Yes/No;,,,,,,,,,,,,,,,,
+TRXLR;SELF;Lopinar / Ritonavir;Yes/No;,,,,,,,,,,,,,,,,
+TRXRM;SELF;Remdesivir;Yes/No;,,,,,,,,,,,,,,,,
+TRXIA;SELF;Interferon Alpha;Yes/No;,,,,,,,,,,,,,,,,
+TRXIB;SELF;Interferon Beta;Yes/No;,,,,,,,,,,,,,,,,
+TRXCH;SELF;Chloroquine / Hydroxychloroquine;Yes/No;,,,,,,,,,,,,,,,,
+TRXAB;SELF;Antibiotics;Yes/No;,,,,,,,,,,,,,,,,
+TRXCS;SELF;Corticosteroids;Yes/No;,,,,,,,,,,,,,,,,
+TRXHEP;SELF;Heparin;Yes/No;,,,,,,,,,,,,,,,,
+TRXAF;SELF;Antifungal;Yes/No;,,,,,,,,,,,,,,,,
+TRXCP;SELF;Convalescent plasma;Yes/No;,,,,,,,,,,,,,,,,
+TRXOT;SELF;High-flow nasal cannula oxygen therapy;Yes/No;,,,,,,,,,,,,,,,,
+TRXECM;SELF;ECMO;Yes/No;,,,,,,,,,,,,,,,,
+TRXIV;SELF;Invasive ventilation;Yes/No;,,,,,,,,,,,,,,,,
+TRXNIV;SELF;Non IV;Yes/No;,,,,,,,,,,,,,,,,
+TRXNO;SELF;Inhaled NO­2;Yes/No;,,,,,,,,,,,,,,,,
+TRXOX;SELF;Oxygen need;Yes/No;,,,,,,,,,,,,,,,,
+TRXRR;SELF;Renal replacement therapy;Yes/No;,,,,,,,,,,,,,,,,
+TRXTR;SELF;Tracheostomy;Yes/No;,,,,,,,,,,,,,,,,
+TRXVA;SELF;Vasopressor;Yes/No;,,,,,,,,,,,,,,,,
+TRXPE;SELF;PEEP;Yes/No;,,,,,,,,,,,,,,,,
+TRXPV;SELF;Prone ventilation;Yes/No;,,,,,,,,,,,,,,,,
+TRXIT;SELF;Intubation;Yes/No;,,,,,,,,,,,,,,,,
+TRXNMB;SELF;Neuromuscular blocking agent;Yes/No;,,,,,,,,,,,,,,,,
+TRXAC;SELF;Anticoagulant ;Yes/No;,,,,,,,,,,,,,,,,
+TRXINA;SELF;Inatropic;Yes/No;,,,,,,,,,,,,,,,,
+TRXIS;SELF;Immunosuppressor;Yes/No;,,,,,,,,,,,,,,,,
+TRXIM;SELF;Immunomodulator;Yes/No;,,,,,,,,,,,,,,,,
+TRXVC;SELF;Vitamin C;Yes/No;,,,,,,,,,,,,,,,,
+TRXVD;SELF;Vitamin D;Yes/No;,,,,,,,,,,,,,,,,
+TRXZN;SELF;Zinc;Yes/No;,,,,,,,,,,,,,,,,
+DATSO;SELF;Date of symptom onset;dd/mm/yyyy;,,,,,,,,,,,,,,,,
+DATAD;SELF;Date of admission;dd/mm/yyyy;,,,,,,,,,,,,,,,,
+DATADI;SELF;Date of admission to ICU;dd/mm/yyyy;,,,,,,,,,,,,,,,,
+DATDSI;SELF;Date of discharge from ICU;dd/mm/yyyy;,,,,,,,,,,,,,,,,
+DATDS;SELF;Date of discharge;dd/mm/yyyy;,,,,,,,,,,,,,,,,
+DATLGT;SELF;Length of stay in hospital;Days;,,,,,,,,,,,,,,,,
+DATLGTI;SELF;Length of stay in ICU;Days;,,,,,,,,,,,,,,,,
+DSXIC;SELF;Patient admitted to ICU;Yes/No;,,,,,,,,,,,,,,,,
+DSXOS;SELF;Outcome status;Recovered/Deceased/Transferred;,,,,,,,,,,,,,,,,
+HMRACI;SELF;ACE Inhibitors;Yes/No;,,,,,,,,,,,,,,,,
+HMRARB;SELF;ARBs;Yes/No;,,,,,,,,,,,,,,,,
+HMRAHO;SELF;Anti-hypertensive (other);Yes/No;,,,,,,,,,,,,,,,,
+HMRNS;SELF;NSAIDs;Yes/No;,,,,,,,,,,,,,,,,
+HMROS;SELF;Oral Steroids;Yes/No;,,,,,,,,,,,,,,,,
+HMRCS;SELF;Corticosteroids;Yes/No;,,,,,,,,,,,,,,,,
+HMRIS;SELF;Immunospressant;Yes/No;,,,,,,,,,,,,,,,,
+HMRAV;SELF;Antiviral;Yes/No;,,,,,,,,,,,,,,,,
+HMRAB;SELF;Antibiotic;Yes/No;,,,,,,,,,,,,,,,,
+HMRCOV;SELF;Other targeted COVID-19 medication ;Yes/No;,,,,,,,,,,,,,,,,
+DMRBORN;NHANES;Country of birth;;,,,,,,,,,,,,,,,,
+DMRAGEYR;SELF;Age;Years;,,,,,,,,,,,,,,,,
+DMRGENDR;SELF;Sex;Male/Female;,,,,,,,,,,,,,,,,
+DMXHT;NHANES;Height;;,,,,,,,,,,,,,,,,
+DMXWT;NHANES;Weight;;,,,,,,,,,,,,,,,,
+DMXBMI;NHANES;BMI;;,,,,,,,,,,,,,,,,
+DMRRETH1;NHANES;Ethnicity;;,,,,,,,,,,,,,,,,
+DMROCCU;SELF;Occupation;;,,,,,,,,,,,,,,,,
+DMRHREDU;NHANES;Education;;,,,,,,,,,,,,,,,,
+DATIM;SELF;Date tests performed;dd/mm/yyyy;,,,,,,,,,,,,,,,,
+DATIMD;SELF;Time between admission and assessment;days;,,,,,,,,,,,,,,,,
+IMDXCT;SELF;CT scan results;;,,,,,,,,,,,,,,,,
+IMDXCTCR;SELF;CT CO-RADS;;,,,,,,,,,,,,,,,,
+IMDXCTTE;SELF;CT thromboembolism;;,,,,,,,,,,,,,,,,
+IMDXCTLD;SELF;CT % lung damage;%;,,,,,,,,,,,,,,,,
+IMDXCTAB;SELF;CT abnormal at follow-up;;,,,,,,,,,,,,,,,,
+IMDXXR;SELF;X-ray result;;,,,,,,,,,,,,,,,,
+IMDXXRI;SELF;X-ray infiltrates;;,,,,,,,,,,,,,,,,
+IMDXPN;SELF;Pneumonia on x-ray or CT scan;;,,,,,,,,,,,,,,,,
+IMDXEQ;SELF;ECG QTc value;;,,,,,,,,,,,,,,,,
+COXRD;SELF;Acute Respiratory Distress Syndrom;Yes/No;,,,,,,,,,,,,,,,,
+COXAR;SELF;Arrhythmia;Yes/No;,,,,,,,,,,,,,,,,
+COXPM;SELF;Pneumonia;Yes/No;,,,,,,,,,,,,,,,,
+COXMOD;SELF;Multiple Organ Dysfunction;Yes/No;,,,,,,,,,,,,,,,,
+COXPT;SELF;Pneumothorax;Yes/No;,,,,,,,,,,,,,,,,
+COXEC;SELF;Endocarditis;Yes/No;,,,,,,,,,,,,,,,,
+COXSH;SELF;Shock;Yes/No;,,,,,,,,,,,,,,,,
+COXIO;SELF;Other infections;Yes/No;,,,,,,,,,,,,,,,,
+COXPE;SELF;Pulmonary embolism;Yes/No;,,,,,,,,,,,,,,,,
+COXST;SELF;Stroke (AVC);Yes/No;,,,,,,,,,,,,,,,,
+COXDIC;SELF;Disseminated intravascular coagulation;Yes/No;,,,,,,,,,,,,,,,,
+COXRIO;SELF;Other respiratory infections;Yes/No;,,,,,,,,,,,,,,,,
+COXKF;SELF;Kidney failure;Yes/No;,,,,,,,,,,,,,,,,
+COXHF;SELF;Heart failure;Yes/No;,,,,,,,,,,,,,,,,
+COXBC;SELF;Blood complications;Yes/No;,,,,,,,,,,,,,,,,
+DATLBHn;SELF;Date of assessment during hospitalisation;dd/mm/yyyy;For the nth assessment,,,,,,,,,,,,,,,,
+DATLBDHn;SELF;Time between admission and assessment during hospitalisation;days;,,,,,,,,,,,,,,,,
+LBXHGBA;NHANES;Haemoglobin at admission;g/dL;,,,,,,,,,,,,,,,,
+LBXHGBHn;NHANES;Haemoglobin during hospitalisation;g/dL;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXESRA;SELF;Erythrocyte Sedimentation Rate (ESR) at admission;mm/hr;,,,,,,,,,,,,,,,,
+LBXESRHn;SELF;Erythrocyte Sedimentation Rate (ESR) during hospitalisation;mm/hr;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXWBCSIA;NHANES;WBC count at admission;1000 cells/µL;,,,,,,,,,,,,,,,,
+LBXWBCSIHn;NHANES;WBC count during hospitalisation;1000 cells/µL;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXLYMNOA;NHANES;Lymphocyte count at admission;1000 cells/µL;,,,,,,,,,,,,,,,,
+LBXLYMNOHn;NHANES;Lymphocyte count during hospitalisation;1000 cells/µL;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXNENOA;NHANES;Neutrophil count at admission;1000 cells/µL;,,,,,,,,,,,,,,,,
+LBXNENOHn;NHANES;Neutrophil count during hospitalisation;1000 cells/µL;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXHCTA;NHANES;Haematocrit at admission;%;,,,,,,,,,,,,,,,,
+LBXHCTHn;NHANES;Haematocrit during admission;%;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXPLTSIA;NHANES;Platetelets at admission;100 cells/µl;,,,,,,,,,,,,,,,,
+LBXPLTSIHn;NHANES;Platetelets during hospitalisation;100 cells/µl;For the nth reading of the variable,,,,,,,,,,,,,,,,
+"LBXGHA;NHANES;HbA1c at admission;""nmol/mol; %"";",,,,,,,,,,,,,,,,
+"LBXGHHn;NHANES;HbA1c during hospitalisation;""nmol/mol; %"";For the nth reading of the variable",,,,,,,,,,,,,,,,
+LBXAPTTA;SELF;Partial Thromboplastin Time (APTT) at admission;;,,,,,,,,,,,,,,,,
+LBXAPTTHn;SELF;Partial Thromboplastin Time (APTT) during hospitalisation;;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXAPTRA;SELF;Activated Partial Thromboplastin Time Ratio (APTR) at admission;;,,,,,,,,,,,,,,,,
+LBXAPTRHn;SELF;Activated Partial Thromboplastin Time Ratio (APTR) during hospitalisation;;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXINRA;SELF;Prothrombin time (PT) / International Normalised Ratio (INR) at admission;;,,,,,,,,,,,,,,,,
+LBXINRHn;SELF;Prothrombin time (PT) / International Normalised Ratio (INR) during hospitalisation;;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSATSIA;NHANES;Alanine Aminotransferase Test (ALT/SGPT) at admission;U/L;,,,,,,,,,,,,,,,,
+LBXSATSIHn;NHANES;Alanine Aminotransferase Test (ALT/SGPT) during hospitalisation;U/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSTBA;NHANES;Total bilirubin at admission;mg/dL;,,,,,,,,,,,,,,,,
+LBXSTBHn;NHANES;Total bilirubin during hospitalisation;mg/dL;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSCBA;SELF;Conjugated bilirubin at admission;;,,,,,,,,,,,,,,,,
+LBXSCBHn;SELF;Conjugated bilirubin during hospitalisation;;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSUBA;SELF;Unconjugated bilirubin at admission;;,,,,,,,,,,,,,,,,
+LBXSUBHn;SELF;Unconjugated bilirubin during hospitalisation;;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSASSIA;NHANES;Aspartate Aminotransferase (AST/SGOT) at admission;U/L;,,,,,,,,,,,,,,,,
+LBXSASSIHn;NHANES;Aspartate Aminotransferase (AST/SGOT) during hospitalisation;U/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSGLA;NHANES;Glucose at admission;mg/dL;,,,,,,,,,,,,,,,,
+LBXSGLHn;NHANES;Glucose during hospitalisation;mg/dL;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSBUA;NHANES;Urea at admission;mg/dL;,,,,,,,,,,,,,,,,
+LBXSBUHn;NHANES;Urea during hospitalisation;mg/dL;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSBLA;SELF;Lactate at admission;mmol/L;,,,,,,,,,,,,,,,,
+LBXSBLHn;SELF;Lactate during hospitalisation;mmol/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+URXUCRA;NHANES;Creatinine at admission;mg/dL;,,,,,,,,,,,,,,,,
+URXUCRHn;NHANES;Creatinine during hospitalisation;mg/dL;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSCKA;NHANES;Creatinine phosphokinase (CPK) at admission;IU/L;,,,,,,,,,,,,,,,,
+LBXSCKHn;NHANES;Creatinine phosphokinase (CPK) during hospitalisation;IU/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSNASIA;NHANES;Sodium at admission;mmol/L;,,,,,,,,,,,,,,,,
+LBXSNASIHn;NHANES;Sodium during hospitalisation;mmol/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSCLSIA;NHANES;Chlorine at admission;mmol/L;,,,,,,,,,,,,,,,,
+LBXSCLSIHn;NHANES;Chlorine during hospitalisation;mmol/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSKSIA;NHANES;Potassium at admission;mmol/L;,,,,,,,,,,,,,,,,
+LBXSKSIHn;NHANES;Potassium during hospitalisation;mmol/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSPCA;SELF;Procalcitonin at admission;ng/ml;,,,,,,,,,,,,,,,,
+LBXSPCHn;SELF;Procalcitonin during hospitalisation;ng/ml;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXCRPA;NHANES;C-Reactive Protein (CRP) at admission;mg/dL;,,,,,,,,,,,,,,,,
+LBXCRPHn;NHANES;C-Reactive Protein (CRP) during hospitalisation;mg/dL;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSLDSIA;NHANES;Lactae dehydrogenase (LDH) at admission;U/L;,,,,,,,,,,,,,,,,
+LBXSLDSIHn;NHANES;Lactae dehydrogenase (LDH) during hospitalisation;U/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSCKA;NHANES;Creatinine Kinase / Creatinine phosphokinase at admission;IU/L;,,,,,,,,,,,,,,,,
+LBXSCKHn;NHANES;Creatinine Kinase / Creatinine phosphokinase during hospitalisation;IU/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXCTRA;SELF;Troponin at admission;ng/ml;,,,,,,,,,,,,,,,,
+LBXCTRHn;SELF;Troponin during hospitalisation;ng/ml;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXCDDA;SELF;D-dimer at admission;mg/L;,,,,,,,,,,,,,,,,
+LBXCDDHn;SELF;D-dimer during hospitalisation;mg/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXFERSIA;NHANES;Ferritin at admission;µg/L;,,,,,,,,,,,,,,,,
+LBXFERSIHn;NHANES;Ferritin during hospitalisation;µg/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXIL6A;SELF;IL-6 at admission;pg/dL;,,,,,,,,,,,,,,,,
+LBXIL6Hn;SELF;IL-6 during hospitalisation;pg/dL;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBDFBSIA;NHANES;Fibrinogen at admission;g/L;,,,,,,,,,,,,,,,,
+LBDFBSIHn;NHANES;Fibrinogen during hospitalisation;g/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBDSALSIA;NHANES;Albumin at admission;g/L;,,,,,,,,,,,,,,,,
+LBDSALSIHn;NHANES;Albumin during hospitalisation;g/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSAPSIA;NHANES;Alkaline phosphatase at admission;U/L;,,,,,,,,,,,,,,,,
+LBXSAPSIHn;NHANES;Alkaline phosphatase during hospitalisation;U/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSGTSIA;NHANES;GGT at admission;U/L;,,,,,,,,,,,,,,,,
+LBXSGTSIHn;NHANES;GGT during hospitalisation;U/L;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXCFDA;SELF;Calcifediol / 25-OH-vitamin D at admission;;,,,,,,,,,,,,,,,,
+LBXCFDHn;SELF;Calcifediol / 25-OH-vitamin D dutring hospitalisation;;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXFIOA;SELF;FiO2 at admission;mmHg;,,,,,,,,,,,,,,,,
+LBXFIOHn;SELF;FiO2 during hospitalisation;mmHg;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXPOA;SELF;PaO2 at admission;mmHg;,,,,,,,,,,,,,,,,
+LBXPOHn;SELF;PaO2 during hospitalisation;mmHg;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXPCOA;SELF;PaCO2 at admission;mmHg;,,,,,,,,,,,,,,,,
+LBXPCOHn;SELF;PaCO2 during hospitalisation;mmHg;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXSC3SIA;NHANES;HCO3 at admission;;,,,,,,,,,,,,,,,,
+LBXSC3SIHn;NHANES;HCO3 during hospitalisation;;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXPHA;SELF;pH at admission;pH;,,,,,,,,,,,,,,,,
+LBXPHHn;SELF;pH during hospitalisation;pH;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXBEH;SELF;Base excess at admission;;,,,,,,,,,,,,,,,,
+LBXBEHn;SELF;Base excess during hospitalisation;;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXA4A;SELF;APACHE IV at admission;;,,,,,,,,,,,,,,,,
+LBXA4Hn;SELF;APACHE IV during hospitalisation;;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXTCA;NHANES;Cholesterol at admission;mg/dL;,,,,,,,,,,,,,,,,
+LBXTCHn;NHANES;Cholesterol during hospitalisation;mg/dL;For the nth reading of the variable,,,,,,,,,,,,,,,,
+LBXTRA;NHANES;Triglyceride at admission;mg/dL;,,,,,,,,,,,,,,,,
+LBXTRHn;NHANES;Triglyceride during hospitalisation;mg/dL;For the nth reading of the variable,,,,,,,,,,,,,,,,

necessary_functions_connection.R

+
+connect <- function (){
+  
+  cat("\n\n\n----------------------------------------------------------------------------------------------------------")
+  cat("\nPlease select the number corresponding to the hospital you want to analyse, if you want to do a combined analysis select multiple hospitals")
+  cat("\n  
+        Princesa -> 1  
+        CIPH -> 2  
+        UMF_Iasis -> 3  
+        SMUC -> 4  
+        HM -> 5  
+        Porto -> 6  
+        FJD -> 7  
+        Coimbra -> 8  
+        UNAV -> 9 
+        TU -> 10 
+        
+          Baskent:
+          
+          Ankara Impatient -> 11
+          Konya Impatient -> 12
+          Istambul Impatient -> 13
+          Izmir Impatient -> 14
+          Alanya Impatient -> 15
+          Adana Impatient -> 16
+          
+          Ankara Outpatient -> 17
+          Konya Outpatient -> 18
+          Istambul Outpatient -> 19
+          Izmir Outpatient -> 20
+          Alanya Outpatient -> 21
+          
+        Sacrocuore:
+        
+          Emergency database -> 22
+          Employees database -> 23
+          Verona database -> 24
+          Isaric -> 25
+        
+        TU Dublin -> 26
+        UMF Cluj -> 27
+        UdeA -> 28
+        Inantro -> 29
+        UNSA -> 30
+        UZA -> 31
+          
+      ")
+  
+  inp <- scan()
+  
+  builder <- DSI::newDSLoginBuilder()
+  
+  
+  hospital_names <- hospital_names[inp]
+  project_names <- project_names[inp]
+  resource_names <- resource_names[inp]
+  urls <- urls[inp]
+  users <- users[inp]
+  pass <- pass[inp]
+  
+  print(hospital_names)
+  print(project_names)
+  print(resource_names)
+  print(urls)
+  print(users)
+  print(pass)
+  
+  url_ctr <- 0
+  for(i in 1:length(urls)){
+    print(paste("Connecting to Server with URL:", urls[i], sep=" "))
+    builder$append(server = hospital_names[i], url = urls[i],
+                   user = users[i], password = pass[i],
+                   resource = paste(project_names[i], resource_names[i], sep="."),
+                   driver = "OpalDriver", options="list(ssl_verifyhost=0,ssl_verifypeer=0)")
+    
+    url_ctr <- url_ctr+1
+  }
+  
+  logindata <- builder$build()
+  
+  connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D", failSafe = TRUE)
+  
+  
+  datashield.assign.expr(connections, symbol = 'data', expr = quote(as.resource.data.frame(D)))
+  #datashield.assign.expr(connections, symbol = 'auxDf', expr = quote(as.resource.data.frame(D)))
+  
+  
+  print("Successful connection to servers.")
+  
+  return(list(connections,inp))
+}

necessary_functions_table1_v2_subset.R

+
+connect <- function (){
+  
+  cat("\n\n\n----------------------------------------------------------------------------------------------------------")
+  cat("\nPlease select the number corresponding to the hospital you want to analyse, if you want to do a combined analysis select multiple hospitals")
+  cat("\n  
+        Princesa -> 1  
+        CIPH -> 2  
+        UMF_Iasis -> 3  
+        SMUC -> 4  
+        HM -> 5  
+        Porto -> 6  
+        FJD -> 7  
+        Coimbra -> 8  
+        UNAV -> 9 
+        TU -> 10 
+        
+          Baskent:
+          
+          Ankara Impatient -> 11
+          Konya Impatient -> 12
+          Istambul Impatient -> 13
+          Izmir Impatient -> 14
+          Alanya Impatient -> 15
+          Adana Impatient -> 16
+          
+          Ankara Outpatient -> 17
+          Konya Outpatient -> 18
+          Istambul Outpatient -> 19
+          Izmir Outpatient -> 20
+          Alanya Outpatient -> 21
+          
+        Sacrocuore:
+        
+          Emergency database -> 22
+          Employees database -> 23
+          Verona database -> 24
+          Isaric -> 25
+        
+        TU Dublin -> 26
+        UMF Cluj -> 27
+        UdeA -> 28
+        Inantro -> 29
+        UNSA -> 30
+        UZA -> 31
+          
+      ")
+  
+  inp <- scan()
+  
+  builder <- DSI::newDSLoginBuilder()
+  
+  
+  hospital_names <- hospital_names[inp]
+  project_names <- project_names[inp]
+  resource_names <- resource_names[inp]
+  urls <- urls[inp]
+  users <- users[inp]
+  pass <- pass[inp]
+  
+  print(hospital_names)
+  print(project_names)
+  print(resource_names)
+  print(urls)
+  print(users)
+  print(pass)
+  
+  url_ctr <- 0
+  for(i in 1:length(urls)){
+    print(paste("Connecting to Server with URL:", urls[i], sep=" "))
+    builder$append(server = hospital_names[i], url = urls[i],
+                   user = users[i], password = pass[i],
+                   resource = paste(project_names[i], resource_names[i], sep="."),
+                   driver = "OpalDriver", options="list(ssl_verifyhost=0,ssl_verifypeer=0)")
+    
+    url_ctr <- url_ctr+1
+  }
+  
+  logindata <- builder$build()
+  
+  connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D", failSafe = TRUE)
+  
+  
+  datashield.assign.expr(connections, symbol = 'data', expr = quote(as.resource.data.frame(D)))
+  
+  print("Successful connection to servers.")
+  
+  return(list(connections,inp))
+}
+
+
+getCountryHosp <- function(hospitals){
+  
+  Spain <- c("HM", "Princesa", "FJD", "UNAV")
+  Turkey <- c("Ankara Impatient", "Konya Impatient", "Adana Impatient", "Izmir Impatient", "Istambul Impatient", "Alanya Impatient", "Ankara Outpatient", "Konya Outpatient", "Izmir Outpatient", "Istambul Outpatient", "Alanya Outpatient")
+  Italy <- c("Sacrocuore Emergency",  "Sacrocuore Employees",  "Sacrocuore Verona", "Sacrocuore Isaric")
+  Portugal <- c("Porto", "Coimbra")
+  UK <- c("SMUC")
+  Ireland <- c("TUDublin")
+  Slovakia  <- c("TU")
+  Romania <- c("UMF_Iasis", "UMF_Cluj")
+  Croatia <- c("CIPH","Inantro")
+  Colombia <- c("UdeA")
+  Bosnia_Herzegovina <- c("UNSA")
+  Belgium <- c("UZA")
+  
+  Spain_Index <- c()
+  Turkey_Index <- c()
+  Italy_Index <- c()
+  Portugal_Index <- c()
+  UK_Index <- c()
+  Ireland_Index <- c()
+  Slovakia_Index <- c()
+  Romania_Index <- c()
+  Croatia_Index <- c()
+  Colombia_Index <- c()
+  Bosnia_Herzegovina_Index <- c()
+  Belgium_Index <- c()
+  
+  country_index <- list()
+  
+  for(i in 1:length(hospitals)){
+    
+    if(hospitals[i] %in% Spain){
+      Spain_Index <- c(Spain_Index, i)
+      
+    }else if(hospitals[i] %in% Turkey){
+      Turkey_Index <- c(Turkey_Index, i)
+      
+    }else if(hospitals[i] %in% Italy){
+      Italy_Index <- c(Italy_Index, i)
+      
+    }else if(hospitals[i] %in% Portugal){
+      Portugal_Index <- c(Portugal_Index, i)
+      
+    }else if(hospitals[i] %in% UK){
+      UK_Index <- c(UK_Index, i)
+      
+    }else if(hospitals[i] %in% Ireland){
+      Ireland_Index <- c(Ireland_Index, i)
+      
+    }else if(hospitals[i] %in% Slovakia){
+      Slovakia_Index <- c(Slovakia_Index, i)
+      
+    }else if(hospitals[i] %in% Romania){
+      Romania_Index <- c(Romania_Index, i)
+      
+    }else if(hospitals[i] %in% Croatia){
+      Croatia_Index <- c(Croatia_Index, i)
+      
+    }else if(hospitals[i] %in% Colombia){
+      Colombia_Index <- c(Colombia_Index, i)
+      
+    }else if(hospitals[i] %in% Bosnia_Herzegovina){
+      Bosnia_Herzegovina_Index <- c(Bosnia_Herzegovina_Index, i)
+      
+    }else if(hospitals[i] %in% Belgium){
+      Belgium_Index <- c(Belgium_Index, i)
+      
+    }
+    
+    
+    
+    
+  }
+  
+  if(length(Spain_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(Spain_Index)
+    names(country_index)[aux] <- "Spain"
+  }
+  
+  if(length(Turkey_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(Turkey_Index)
+    names(country_index)[aux] <- "Turkey"
+  }
+  
+  if(length(Italy_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(Italy_Index)
+    names(country_index)[aux] <- "Italy"
+  }
+  
+  if(length(Portugal_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(Portugal_Index)
+    names(country_index)[aux] <- "Portugal"
+  }
+  
+  if(length(UK_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(UK_Index)
+    names(country_index)[aux] <- "UK"
+  }
+  
+  if(length(Ireland_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(Ireland_Index)
+    names(country_index)[aux] <- "Ireland"
+  }
+  
+  if(length(Slovakia_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(Slovakia_Index)
+    names(country_index)[aux] <- "Slovakia"
+  }
+  
+  if(length(Romania_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(Romania_Index)
+    names(country_index)[aux] <- "Romania"
+  }
+  
+  if(length(Croatia_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(Croatia_Index)
+    names(country_index)[aux] <- "Croatia"
+  }
+  
+  if(length(Colombia_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(Colombia_Index)
+    names(country_index)[aux] <- "Colombia"
+  }
+  
+  if(length(Bosnia_Herzegovina_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(Bosnia_Herzegovina_Index)
+    names(country_index)[aux] <- "Bosnia & Herzegovina"
+  }
+  
+  if(length(Belgium_Index) != 0 ){
+    aux <- length(country_index)+1
+    country_index[aux] <- list(Belgium_Index)
+    names(country_index)[aux] <- "Belgium"
+  }
+  
+
+  
+  return(country_index)
+  
+}
+
+#Distinguish variable Types
+numeric <- c("DMRAGEYR","DMXHT","DMXWT","DMXBMI","DATLGT","DATLGTI","DATSSDHn","CSXBTPA","CSXBTPHn","CSXOSTA","CSXOSTHn","CSXCHRA","CSXCHRHn","CSXRRA","CSXRRHn","CSXRRI","CSXSYA","CSXSYHn","CSXDIA","CSXDIHn","SMTFE","SMTCO","SMTST","SMTSB","SMXSEA","DATIMD","IMDXCTLD","IMDXEQ","DATLBDHn","LBXHGBA","LBXHGBHn","LBXESRA","LBXESRHn","LBXWBCSIA","LBXWBCSIHn","LBXLYMNOA","LBXLYMNOHn","LBXNENOA","LBXNENOHn","LBXHCTA","LBXHCTHn","LBXPLTSIA","LBXPLTSIHn","LBXGHA","LBXGHHn","LBXAPTTA","LBXAPTTHn","LBXAPTRA","LBXAPTRHn","LBXPTA","LBXPRHn","LBXINRA","LBXINRHn","LBXSATSIA","LBXSATSIHn","LBXSTBA","LBXSTBHn","LBXSCBA","LBXSCBHn","LBXSUBA","LBXSUBHn","LBXSASSIA","LBXSASSIHn","LBXSGLA","LBXSGLHn","LBXSBUA","LBXSBUHn","LBXSBLA","LBXSBLHn","LBXSCRA","LBXSCRHn","LBXSNASIA","LBXSNASIHn","LBXSCLSIA","LBXSCLSIHn","LBXSKSIA","LBXSKSIHn","LBXSPCA","LBXSPCHn","LBXCRPA","LBXCRPHn","LBXSLDSIA","LBXSLDSIHn","LBXCTRA","LBXCTRHn","LBXCDDA","LBXCDDHn","LBXFERSIA","LBXFERSIHn","LBXIL6A","LBXIL6Hn","LBDFBSIA","LBDFBSIHn","LBDSALSIA","LBDSALSIHn","LBXSAPSIA","LBXSAPSIHn","LBXSGTSIA","LBXSGTSIHn","LBXCFDA","LBXCFDHn","LBXFIOA","LBXFIOHn","LBXPOA","LBXPOHn","LBXPCOA","LBXPCOHn","LBXSC3SIA","LBXSC3SIHn","LBXPHA","LBXPHHn","LBXBEH","LBXBEHn","LBXA4A","LBXA4Hn","LBXTCA","LBXTCHn","LBXTRA","LBXTRHn","LBXSCKA","LBXSCKHn","LBXPSCKA","LBXPSCKHn")
+categoric <- c("DMRGENDR", "DMRBORN", "DMRRETH1", "DMROCCU", "DMRHREDU", "DSXOS", "DSXHO", "DSXIC", "TRXAV","TRXRIB","TRXLR","TRXRM","TRXIA","TRXIB","TRXCH","TRXAB","TRXCS","TRXHEP","TRXAF","TRXCP","TRXOT","TRXECM","TRXIV","TRXNIV","TRXNO","TRXOX","TRXRR","TRXTR","TRXVA","TRXPE","TRXPV","TRXIT","TRXNMB","TRXAC","TRXINA","TRXIS","TRXIM","TRXVC","TRXVD","TRXZN",                         "CSXCOT","CSXCTR","SMXASAH","SMXFEA","SMXCOA","SMXSTA","SMXSBA","SMXRNA","SMXMYA","SMXARA","SMXCPA","SMXAPA","SMXINA","SMXNAA","SMXDIA","SMXFAA","SMXHEA","SMXCNA","SMXACA","SMXSLA","SMXTLA","SMXSYA","SMXWHA","SMXLYA","SMXANA","SMXIWA","SMXSRA","SMXBLA","CMXPRG","CMXCVD","CMXCMP","CMXHT","CMXDI","CMXCKD","CMXCLD","CMXCPD","CMXASM","CMXCND","CMXRHE","CMXCCI","CMXCBD","CMXDE","CMXPU","CMXST","CMXLY","CMXAP","RFXSM","RFXFSM","RFXOB","RFXTB","RFXIMD","RFXHIV","RFXAIDS","RFXUI","RFXHC","RFXONC","RFXMN",                         "HMRACI","HMRARB","HMRAHO","HMRNS","HMROS","HMRCS","HMRIS","HMRAV","HMRAB","HMRCOV","IMDXCT","IMDXCTCR","IMDXCTTE","IMDXCTAB","IMDXXR","IMDXPN",                         "COXRD","COXAR","COXPM","COXMOD","COXPT","COXEC","COXSH","COXIO","COXPE","COXST","COXDIC","COXRIO","COXKF","COXHF","COXBC")
+
+
+
+hospitals_contain_var <- function(hospitals_cols, variable, index){
+
+  res <- c()
+
+  for(i in 1: length(hospitals_cols)){
+
+    if(variable %in% unlist(hospitals_cols[i]))
+      res <- c(res, i)
+
+  }
+
+  if(is.null(res)){
+    return(NULL)
+  }else if(is.null(index)){
+    return (res)
+  }else{
+    return(index[res])
+  }
+
+}
+
+get_working_hosp <- function(index, connections, to_analyse){
+
+  new_index <- c()
+
+
+  for(i in 1:length(index)){
+
+
+    analysisRes <- NULL
+
+    try(analysisRes <- ds.table(to_analyse,datasources = connections[index[i]]))
+
+
+    if(!is.null(analysisRes)){
+      if(!grepl("Error", analysisRes[1])  & !grepl("failed", analysisRes[1]))
+      new_index <- c(new_index,index[i])
+    }
+
+  }
+
+  return(new_index)
+
+
+}
+
+obtain_table1 <- function(connections, inp, varToAnalize){
+
+
+  #Obtain the name of the hospitals and the corresoponding indexes according to country
+  hospitals_cols <- ds.colnames("data")
+  hospitals <- names(hospitals_cols)
+  country_Index_Total <- getCountryHosp(hospitals)
+
+  #Create empty result
+  result_df <- data.frame(matrix(ncol = 3, nrow = 1))
+  colnames(result_df) <- c('Codebook Variable', 'Description', 'Category/Units')
+
+  name_df <- result_df
+
+  #Add the necessary headers
+  for(i in 1:length(country_Index_Total)){
+
+    country <- names(country_Index_Total)[i]
+    country_Index <- unname(unlist(country_Index_Total[i]))
+    country_hospitals <- hospitals[country_Index]
+
+    nPatients <- ds.dim("data",datasources = connections[country_hospitals])
+
+    for(j in 1:length(country_Index)){
+
+      n_Patients_Hosp <- nPatients[[j]][1]
+      new_col_name <- paste(paste(paste(country_hospitals[j],"(N ="),n_Patients_Hosp),")",sep="")
+
+      result_df[new_col_name] <- NA
+      name_df[country_hospitals[j]] <- NA
+
+    }
+
+    new_col_name <- paste(paste(paste(paste("Total", country), "(N ="),nPatients[[j+1]][1]),")",sep="")
+    result_df[new_col_name] <- NA
+    name_df[country] <- NA
+
+  }
+
+  for(i in 1:length(varToAnalize)){
+
+    variable <- varToAnalize[i]
+    description <- subset(codebook$description,codebook$variable == variable)
+    if(length(description)== 0)
+      description <-  ""
+    category <- subset(codebook$unit,codebook$variable == variable)
+
+    to_analyse <- paste("data$",variable,sep="")
+
+
+
+    if(variable %in% categoric){
+
+      print("Categoric")
+
+      possible_vars <- c()
+
+      contain_var <- hospitals_contain_var(hospitals_cols, variable, NULL)
+
+      analysis <- NULL
+      analysis <- try(ds.table(to_analyse,datasources = connections[contain_var]))
+
+      
+      if(is.null(analysis)){
+        
+        new_index <- get_working_hosp(contain_var, connections, to_analyse)
+        if(length(new_index) > 0)
+          analysis <- try(ds.table(to_analyse,datasources = connections[new_index]))
+        if(is.null(new_index))
+          next
+        
+      }else if(grepl("Error", analysis[1]) | grepl("failed", analysis[1])){
+        
+        new_index <- get_working_hosp(contain_var, connections, to_analyse)
+        if(length(new_index) > 0)
+          analysis <- try(ds.table(to_analyse,datasources = connections[new_index]))
+        if(is.null(new_index))
+          next
+      }
+
+      if(!is.null(analysis) & !grepl("Error", analysis[1])){
+
+        auxAnalisis <- analysis[[1]]
+        auxAnalisis <- unlist(unname(auxAnalisis[length(auxAnalisis)]))
+
+        for(j in 1:length(auxAnalisis)){
+          possible_vars <- c(possible_vars, names(auxAnalisis[j]))
+        }
+
+        auxdf <- data.frame (matrix(ncol = length(colnames(name_df)), nrow = length(possible_vars)))
+        colnames(auxdf) <- colnames(name_df)
+        auxdf[1,"Codebook Variable"] <- variable
+        auxdf[1,"Description"] <- description
+
+        for(k in 1:length(country_Index_Total)){
+
+
+          countries_index <- unlist(country_Index_Total[k])
+          country <- names(country_Index_Total)[k]
+
+          print("Analysis for the country:")
+          print(country)
+
+          if(length(countries_index)>1)
+            contain_var <- hospitals_contain_var(hospitals_cols[countries_index], variable, countries_index)
+          else{
+            if(variable %in% unlist(hospitals_cols[countries_index]))
+              contain_var <- countries_index
+            else
+              next
+          }
+            
+
+          if(is.null(contain_var)){
+            print("No selected hospitals contain this variable in this country")
+            next
+          }
+          
+          for(j in 1:length(contain_var)){
+            
+            new_index <- contain_var[j]
+            hospital <- hospitals[new_index]
+            
+            print(hospital)
+            
+            analysis <- NULL
+            try(analysis <- ds.table(to_analyse,datasources = connections[new_index]))
+            
+            if(!is.null(analysis)){
+              if(!(grepl("Error", analysis[1]) | grepl("failed", analysis[1]))){
+                
+                auxAnalisis <- analysis[[1]]
+                auxAnalisis <- unlist(unname(auxAnalisis[length(auxAnalisis)]))
+
+                num_result_per_hosp <- as.data.frame(analysis[[1]][[3]])
+                prop_result_per_hosp <- as.data.frame(analysis[[1]][[2]])
+                
+                for(h in 1:length(possible_vars)){
+                  
+                  auxdf[h,"Category/Units"] <- possible_vars[h]
+                  
+                }
+                
+                
+                for(l in 1:dim(num_result_per_hosp)[[1]]){
+                  
+                  num_res <- num_result_per_hosp[hospital][[1]][l]
+                  position <- get_posVal_index(row.names(num_result_per_hosp)[l], possible_vars)
+                  
+                  if(is.na(num_res))
+                    auxdf[position,hospital] <- ""
+                  else{
+                    prop_res <- format(round(prop_result_per_hosp[hospital][[1]][l], 4), nsmall = 2)
+                    prop_res <- as.double(prop_res)*100
+                    res <- paste(paste(paste(num_res, "("),prop_res,sep=""),"%)",sep="")
+                    auxdf[position,hospital] <- res
+                  }
+                  
+                }
+                
+                
+              }
+            }
+          }
+          
+          try(analysis <- ds.table(to_analyse,datasources = connections[contain_var]))
+
+          if(is.null(analysis)){
+
+            new_index <- get_working_hosp(contain_var, connections, to_analyse)
+            if(length(new_index) > 0)
+              analysis <- try(ds.table(to_analyse,datasources = connections[new_index]))
+            if(is.null(new_index))
+              next
+
+          }else if(grepl("Error", analysis[1]) | grepl("failed", analysis[1])){
+
+            new_index <- get_working_hosp(contain_var, connections, to_analyse)
+            if(length(new_index) > 0)
+              analysis <- try(ds.table(to_analyse,datasources = connections[new_index]))
+            if(is.null(new_index))
+              next
+          }
+          
+          for(l in 1:length(possible_vars)){
+            
+            num_result_tot <- as.data.frame(analysis[[1]][[5]])
+            prop_result_tot <- as.data.frame(analysis[[1]][[4]])
+            num_res <- num_result_tot[[1]][l]
+            position <- get_posVal_index(row.names(num_result_tot)[l], possible_vars)
+            
+            if(is.na(num_res))
+              auxdf[position,country] <- ""
+            
+            else{
+              
+              prop_res <- format(round(prop_result_tot[[1]][l], 4), nsmall = 2)
+              prop_res <- as.double(prop_res)*100
+              res <- paste(paste(paste(num_res, "("),prop_res,sep=""),"%)",sep="")
+              
+              
+              auxdf[position,country] <- res
+            }
+          }
+
+        }
+        
+        colnames(auxdf) <- colnames(result_df)
+        result_df <- rbind(result_df,auxdf)
+
+        # auxdf <- name_df
+        # colnames(auxdf) <- colnames(result_df)
+        # result_df <- rbind(result_df,auxdf)
+      }else{
+        print("Unable to abtain data form the field:")
+        print(variable)
+      }
+
+    }else if (variable %in% numeric){
+
+      print("Numeric")
+
+      auxdf <- data.frame (matrix(ncol = length(colnames(name_df)), nrow = 1))
+      colnames(auxdf) <- colnames(name_df)
+      auxdf[1,"Codebook Variable"] <- variable
+      auxdf[1,"Description"] <- description
+      auxdf[1,"Category/Units"] <- category
+
+      for(k in 1:length(country_Index_Total)){
+
+        countries_index <- unlist(country_Index_Total[k])
+        country <- names(country_Index_Total)[k]
+        
+        print("Analysis for the country:")
+        print(country)
+
+        analyzedHosp <- hospitals[countries_index]
+
+        if(length(countries_index)>1)
+          contain_var <- hospitals_contain_var(hospitals_cols[countries_index], variable, countries_index)
+        else
+          contain_var <- countries_index
+
+        if(is.null(contain_var)){
+          print("No selected hospitals contain this variable in this country")
+          next
+        }
+
+        analysisMean <- NULL
+        try(analysisMean <- ds.mean(to_analyse,datasources = connections[contain_var]))
+        try(analysisVar <- ds.var(to_analyse,datasources = connections[contain_var]))
+
+        #If the variable exists
+        if(!is.null(analysisMean)){
+          if(!(grepl("Error", analysisMean[1]) | grepl("FAILED", analysisMean[3]))){
+            
+            means <- c()
+            
+            for(j in 1:length(contain_var)){
+              
+              
+              index_hosp <- contain_var[j]
+              hospital <- hospitals[index_hosp]
+              mean_res <- analysisMean[[1]][j]
+              var_res <- analysisVar[[1]][j]
+              
+              if(!is.na(mean_res) & mean_res !=0){
+                
+                
+                means <- c(means,mean_res)
+                mean_res <- format(round(mean_res, 2), nsmall = 2)
+                sd_res <- format(round(sqrt(var_res), 2), nsmall = 2)
+                res <- paste(paste(paste(mean_res, "(+-"),sd_res,sep=""),")",sep="")
+                auxdf[hospital] <- res
+              }else{
+                auxdf[hospital] <- NA
+              }
+              
+            }
+            
+            
+            if(length(means)!= 0){
+              res <- format(round(mean(means), 2), nsmall = 2)
+              auxdf[country] <- res
+            }else {
+              auxdf[country] <- NA
+            }
+            
+          }
+
+         
+
+        }
+
+      }
+
+      colnames(auxdf) <- colnames(result_df)
+      result_df <- rbind(result_df,auxdf)
+
+    }
+
+  }
+
+  for(i in 1:nrow(result_df)){
+    for (j in 1:ncol(result_df)){
+      if(is.na(result_df[i,j]))
+        result_df[i,j] <- ""
+    }
+  }
+
+  result_df <- result_df[-1,]
+
+  write.csv(x=result_df, file = "table1.csv", row.names = FALSE)
+
+
+  datashield.logout(connections)
+
+  saveRDS(result_df,file="table1_save.Rda")
+
+  return(result_df)
+  
+}
+
+
+
+apply_filters <- function(){
+  
+  cols <- ds.colnames("data")
+  posVarsCols <- Reduce(intersect, cols)
+  filters <- TRUE
+  
+  while(filters){
+    okvar <- FALSE
+    okval <- FALSE
+    okcountry <- FALSE
+    
+      
+      while(!okvar | !okcountry){
+        variableN <- readline("Please enter the variable you want to subset from > ")
+        if(variableN %in% categoric)
+          okvar <- TRUE
+        else{
+          okvar <- FALSE
+          print("Please enter a categoric variable")
+        }
+          
+        if(variableN %in% posVarsCols)
+          okcountry <- TRUE
+        else{
+          print("Please use a variable that is present in all datasets")
+          print("The variables that are present in all the datasets are the following")
+          print(posVarsCols)
+        }
+      }
+      
+      
+      
+    
+    
+    posvals <- strsplit(subset(codebook, codebook$variable == variableN)[1,3], split = "/")
+    variableN <- paste(variableN,"_numeric", sep="")
+    
+    while(!okval){
+      value<- readline("Please enter the desired value > ")
+      
+      if(value %in% unlist(posvals)){
+        okval <- TRUE
+      }else
+        print("Please enter a valid value")
+    }
+    
+    if(value == "Yes")
+      value <- "1"
+    if(value == "No")
+      value <- "0"
+    if(value == "Male")
+      value <- "0"
+    if(value == "Female")
+      value <- "1"
+    if(value == "Recovered")
+      value <- "0"
+    if(value == "Deceased")
+      value <- "1"
+    if(value == "Transferred")
+      value <- "2"
+    
+    #Only if you want to divide the subset
+    try(ds.dataFrameSubset(df.name = 'data', V1.name = paste("data$",variableN,sep=""), V2.name = value, Boolean.operator = "==", newobj = "data", datasources = connections))
+    
+    input <- readline("Do you wish to apply another filter? Yes=1 / No=0 > " )
+    if(input == "0")
+      filters <- FALSE
+  }
+  
+
+}
+
+
+get_posVal_index <- function(var, possible_vars){
+  
+  for(i in 1:length(possible_vars)){
+    
+    if(is.na(var)){
+      
+      if(is.na(possible_vars[i]))
+        return (i)
+      else if(possible_vars[i] == "NA"){
+        return (i)
+      }
+      
+    }else if(var == possible_vars[i])
+      return (i)
+    
+  }
+  
+}

new_harmon.csv

+Name Origin,Harmonised variable name,Variables in REDCap,Variable description,Variable type,Possible values,Possible values format
+NHANES,DMRBORN,,Country of birth,ISO country code,ISO 3166-1-alpha-2 English country name / missing,https://pkgstore.datahub.io/core/country-list/data_csv/data/d7c9d7cfb42cb69f4422dec222dbbaa8/data_csv.csv
+SELF,DMRDOB,,Date of birth,Calendar date,Date / Missing,yyyy-mm-dd / .
+SELF,DMRAGEYR,age_estimateyears,Age,Continuous,Years / Missing,0-150 / .
+SELF,DMRGENDR,sex,Sex,Binary,Male/Female / Missing,0 / 1 / .
+NHANES,DMXHT,taille,Height,Continuous,cm / Missing,40-250 / .
+NHANES,DMXWT,poids,Weight,Continuous,kg / Missing,0-440 / .
+NHANES,DMXBMI,bmi,BMI,Continuous,kg/m2 / Missing,11-130 / .
+NHANES,DMRRETH1,ethnic/other_ethnic,Ethnicity,Categorical,Asian/Black/Hispanic/White/Multiracial/Other / Missing,1 /2 / 3 / 4/ 5 / 6 / .
+SELF,DMROCCU,,Occupation,Categorical,Unemployed/Student/Employed/Self-employed/Retired / Missing,1 /2 / 3 / 4/ 5 / .
+NHANES,DMRHREDU,,Education,Categorical,High school/Bachelors/Postgraduate/Other / Missing,1 /2 / 3 / 4/ .
+SELF,CMXPRG,pregyn_rptestcd ,Pregnancy,Binary,No /Yes / Missing,0 / 1 / .
+SELF,CMXCVD,chroniccard_mhyn,CVD,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXCMP,,Cardiomyopathy,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXHT,hypertention_mhyn,Hypertension,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXDI,antec_two,Diabetes,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXCKD,renal_mhyn,Chronic kidney disease,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXCLD,,Chronic liver disease,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXCPD,chronicpul_mhyn,Chronic pulmonary disease,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXASM,asthma_mhyn,Asthma,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXCND,chronicneu_mhyn,Chronic neurological or neuromuscular disorder,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXRHE,rheumatology_mhyr,Rheumatism,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXCCI,,Chronic cognitive impairment,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXCBD,,Cerebrovascular disease,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXDE,dementia_mhyn,Dementia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXPU,,Peptic Ulcer / Bleeding,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXST,,Solid tumour,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXLY,,Lymphoma,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXAP,,Asplenia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXSM,smoking_mhyn,Smoking,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXFSM,,Former smoker,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXOB,obesity_mhyn,Obesity,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXTB,,TB,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXIMD,,Immunodeficiency,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXHIV,aidshiv_mhyn,HIV,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXAIDS,aidshiv_mhyn,AIDS,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXUI,,Immunodeficiency - unknown cause,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXHC,,Haematological cancer,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXONC,,Oncology,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXMN,malnutrition_mhyn,Malnutrition,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXCHF,,Congestive heart failure,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXVDP,,Peripheral vascular disease,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXVDC,,Collapsed vascular disease,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXCA,,Cardiac arrhythmia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXVD,,Valvular disease,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXABL,,Blood loss anaemia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXAD,,Deficiency anaemia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXNDP,,Psychosis,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXNDD,,Depression,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXCOPD,copd_mhyn,Chronic Obstructive Pulmonary Disease,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXPCD,,Pulmonary circulation disorder,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXRI,,Acute renal insufficiency,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXMLD,mildliv_mhyn,Mild liver disease,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXNPM,malignantneo_mhyn,Malignant neoplasia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXCLH,,Lymphatic or haematopoietic cancer,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXMET,,Metastases,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXTU,,Tumour without metastasis,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXMY,,Myeloma,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXNP,,Neutropenia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXMD,,Metabolic disorders,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXANX,,Anxiety disorder,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXBDO,,Obstruction of the bile duct,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXEPI,,Exocrine pancreatic insufficiency,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXOAR,,Osteoarthritis,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXSPI,,Spinal condition,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXSOT,,Soft tissue disorder,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXOKD,,Other disorder of the kidneys or ureter,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXUTI,,Urinary tract infection,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXINC,,Incontinence,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXHPP,,Hyperplasia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXHGL,,Hyperglycaemia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXLC,,Problems relating to living conditions,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXPM,,Pacemaker,Binary,No/Yes / Missing,0 / 1 / .
+SELF,RFXAP,,Angioplasty,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXIHD,,Ischaemic heart disease,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXATH,,Atherothrombotic disease,Binary,No/Yes / Missing,0 / 1 / .
+SELF,CMXLK,,Leukaemia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRACI,,ACE Inhibitors,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRARB,,ARBs,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRAHO,,Anti-hypertensive (other),Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRNS,,NSAIDs,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMROS,,Oral Steroids,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRCS,,Corticosteroids,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRIS,,Immunospressant,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRAV,,Antiviral,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRAB,,Antibiotic,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRCOV,,Other targeted COVID-19 medication ,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRANC,,Anticoagulant,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRAT,,Antithrombotic,Binary,No/Yes / Missing,0 / 1 / .
+SELF,HMRINS,,Insulin,Binary,No/Yes / Missing,0 / 1 / .
+SELF,DATSSA,hostdat,Date of assessment during hospitalisation,Calendar date,Date / Missing, yyy-mm-dd / .
+SELF,DATSSDHn,,Time between admission and assessment,Continuous,Days / Missing,0-180 / .
+SELF,CSXBTPA,temp_vsorres,Body temperature at admission,Continuous,C / Missing,25-43 / .
+SELF,CSXBTPHn,,Body temperature in hospital,Continuous,C / Missing,25-43 / .
+SELF,CSXOSTA,oxy_vsorresu,Oxygen Saturation at admission,Continuous,% / Missing,0-100 / .
+SELF,CSXOSTHn,,Oxygen Saturation in hospital,Continuous,% / Missing,0-100 / .
+SELF,CSXCHRA,,Heart Rate at admission,Continuous,bpm / Missing,0-288 / .
+SELF,CSXCHRHn,,Heart Rate in hospital,Continuous,bpm / Missing,0-288 / .
+SELF,CSXRRA,,Respiratory Rate at admission,Continuous,breaths/min / Missing,0-200 / .
+SELF,CSXRRHn,,Respiratory Rate in hospital,Continuous,breaths/min / Missing,0-200 / .
+SELF,CSXRRI,,Respiratory rate in ICU,Continuous,breaths/min / Missing,0-200 / .
+SELF,CSXSYA,sysbp_vsorres,Systolic bp at admission,Continuous,mmHg / Missing,74-270 / .
+SELF,CSXSYHn,,Systolic bp in hospital,Continuous,mmHg / Missing,74-270 / .
+SELF,CSXDIA,admission_diabp_vsorres,Diastolic bp at admission,Continuous,mmHg / Missing,0-124 / .
+SELF,CSXDIHn,,Diastolic bp in hospital,Continuous,mmHg / Missing,0-124 / .
+SELF,CSXMAPA,,Mean arterial pressure at admission,Continuous,mmHg / Missing,30-150 / .
+SELF,CSXMAPHn,,Mean arterial pressure during hospitalisation,Continuous,mmHg / Missing,30-150 / .
+SELF,CSXCOT,test_type,Received covid test,Categorical,PCR/antigen/other/unspecified / Missing,1 / 2 / 3 / 4 / .
+SELF,DATCOT,covidpos_dat1,Date of covid test,Calendar date,Date / Missing, yyy-mm-dd / .
+SELF,CSXCTR,,Covid test results,Binary,Negative / Positive / Missing,0 / 1 / .
+SELF,SMXASAH,,Asymptomatic during hospitalisation,Binary,No / Yes / Missing,0 / 1 / .
+SELF,SMXFEA,fever_ceoccur_two,Fever at admission,Binary,No / Yes / Missing,0 / 1 / .
+SELF,SMTFE,,Fever duration,Continuous,Days / Missing,0-180 / .
+SELF,SMXCOA,cough_ceoccur_two,Cough at admission,Binary,No / Yes / Missing,0 / 1 / .
+SELF,SMTCO,,Cough duration,Continuous,Days / Missing,0-180 / .
+SELF,SMXSTA,sorethroat_ceoccur_two,Sore throat at admission,Binary,No / Yes / Missing,0 / 1 / .
+SELF,SMTST,,Sore throat duration,Continuous,Days / Missing,0-180 / .
+SELF,SMXSBA,,Shortness of breath at admission,Binary,No / Yes / Missing,0 / 1 / .
+SELF,SMTSB,,Shortness of breath duration,Continuous,Days / Missing,0-180 / .
+SELF,SMXRNA,runnynose_ceoccur_two,Runny nose at admission,Binary,No / Yes / Missing,0 / 1 / .
+SELF,SMTRN,,Runny nose duration,Continuous,Days / Missing,0-180 / .
+SELF,SMXSEA,seizures_cecoccur_two,Convulsions / Seizures,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXMYA,myalgia_ceoccur_two,Myalgia at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXARA,jointpain_ceoccur_two,Arthralgia at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXCPA,chestpain_ceoccur_two,Chest pain at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXAPA,abdopain_ceoccur_two,Abdominal pain at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXINA,,Lower chest wall indrawing at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXNAA,vomit_ceoccur_two,Nausea / Vomiting at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXDIA,diarrhoea_ceoccur_two,Diarrhoea at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXFAA,fatigue_ceoccur_two,Fatigue at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXHEA,headache_ceoccur_two,Headache at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXCNA,conjunct_ceoccur_two,Conjunctivitis at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXACA,confusion_ceoccur_two,Confusion / Altered consciousness at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXSLA,,Loss of smell at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXTLA,,Loss of taste at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXSYA,,Syncope / Fall at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXWHA,wheeze_ceoccur_two,Wheezing at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXLYA,lymp_ceoccur_two,Lymphadenopathy at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXANA,,Anorexia at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXIWA,,Inability to walk at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXSRA,rash_ceoccur_two,Skin rash at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXBLA,bleed_ceterm_two,Bleeding / Haemorrhage at admission,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXURT,,Upper respiratory tract complaint,Binary,No/Yes / Missing,0 / 1 / .
+SELF,SMXGCS,daily_gcs_vsorres?,Glasgow Coma Scale,Continuous,Score / Missing,3-15/ .
+SELF,SMXAVPU,avpu_vsorres,AVPU,Categorical,Alert/Voice/Pain/Unresponsive / Missing,1 / 2 / 3 / 4 / .
+SELF,SMXSOFA,,qSOFA Score,Continuous,0 / 1 / 2 / 3 / Missing,1 / 2 / 3 /  .
+SELF,SMXRASS,rass_vsorres,Richmond Agitation Sedation Scale,Continuous,Score / Missing,-5 to +4 / .
+SELF,TRXOT,oxygen_cmoccur,High-flow nasal cannula oxygen therapy,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXECM,extracorp_prtrt,ECMO,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXIV,,Invasive ventilation,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXNIV,noninvasive_proccur,Non IV,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXNO,,Inhaled NO�2,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXOX,oxygen_proccur,Oxygen need,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXRR,rrt_prtrt,Renal replacement therapy,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXTR,tracheo_prtrt,Tracheostomy,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXVA,inotrop_cmtrt,Vasopressor,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXPE,,PEEP,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXPV,pronevent_prtrt,Prone ventilation,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXIT,,Intubation,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXNMB,,Neuromuscular blocking agent,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXAC,,Anticoagulant ,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXINA,,Inatropic,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXIS,,Immunosuppressor,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXIM,,Immunomodulator,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXVC,,Vitamin C,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXVD,,Vitamin D,Binary,No/Yes / Missing,0 / 1 / .
+SELF,TRXZN,,Zinc,Binary,No/Yes / Missing,0 / 1 / .
+SELF,DATLBHn,daily_lbdat?,Date of assessment during hospitalisation,Calendar date,Date / Missing,yyyy-mm-dd / .
+SELF,DATLBDHn,,Time between admission and assessment during hospitalisation,Continuous,Days / Missing,0-180 / .
+NHANES,LBXHGBA,daily_hb_lborres,Haemoglobin at admission,Continuous,g/dL / Missing,"7,5-19,7 / ."
+NHANES,LBXHGBHn,,Haemoglobin during hospitalisation,Continuous,g/dL / Missing,"7,5-19,7 / ."
+NHANES,LBXHGBM,,Mean haemoglobin during hospitalisation,Continuous,g/dL / Missing,"7,5-19,7 / ."
+SELF,LBXESRA,,Erythrocyte Sedimentation Rate (ESR) at admission,Continuous,mm/hr / Missing,0-120 / .
+SELF,LBXESRHn,,Erythrocyte Sedimentation Rate (ESR) during hospitalisation,Continuous,mm/hr / Missing,0-120 / .
+SELF,LBXESRM,,Mean Erythrocyte Sedimentation Rate (ESR) during hospitalisation,Continuous,mm/hr / Missing,0-120 / .
+NHANES,LBXWBCSIA,daily_wbc_lborres,WBC count at admission,Continuous,1000 cells/uL / Missing,1-84 / .
+NHANES,LBXWBCSIHn,,WBC count during hospitalisation,Continuous,1000 cells/uL / Missing,1-84 / .
+NHANES,LBXWBCSIM,,Mean WBC count during hospitalisation,Continuous,1000 cells/uL / Missing,1-84 / .
+NHANES,LBXMONOA,,Monocyte count at admission,Continuous,1000 cells/uL / Missing,
+NHANES,LBXMONOHn,,Monocyte count during hospitalisation,Continuous,1000 cells/uL / Missing,
+NHANES,LBXEONOA,,Eosinophil count at admission,Continuous,1000 cells/uL / Missing,
+NHANES,LBXEONOHn,,Eosinophil count during admission,Continuous,1000 cells/uL / Missing,
+NHANES,LBXBANOA,,Basophil count at admission,Continuous,1000 cells/uL / Missing,
+NHANES,LBXBANOHn,,Basophil count during admission,Continuous,1000 cells/uL / Missing,
+NHANES,LBXLYMNOA,,Lymphocyte count at admission,Continuous,1000 cells/uL / Missing,0-72 / .
+NHANES,LBXLYMNOHn,,Lymphocyte count during hospitalisation,Continuous,1000 cells/uL / Missing,0-72 / .
+NHANES,LBXLYMNOM,,Mean lymphocyte count during hospitalisation,Continuous,1000 cells/uL / Missing,0-72 / .
+NHANES,LBXNENOA,daily_neutro_lborres,Neutrophil count at admission,Continuous,1000 cells/uL / Missing,0-21 / .
+NHANES,LBXNENOHn,,Neutrophil count during hospitalisation,Continuous,1000 cells/uL / Missing,0-21 / .
+NHANES,LBXNENOM,,Mean neutrophil count during hospitalisation,Continuous,1000 cells/uL / Missing,0-21 / .
+NHANES,LBXHCTA,daily_haematocrit_lborres,Haematocrit at admission,Continuous,% / Missing,22-57 / .
+NHANES,LBXHCTHn,,Haematocrit during hospitalisation,Continuous,% / Missing,22-57 / .
+NHANES,LBXHCTM,,Mean haematocrit during hospitalisation,Continuous,% / Missing,22-57 / .
+NHANES,LBXPLTSIA,daily_plt_lborres,Platelets at admission,Continuous,1000 cells/uL / Missing,28-1000 / .
+NHANES,LBXPLTSIHn,,Platelets during hospitalisation,Continuous,1000 cells/uL / Missing,28-1000 / .
+NHANES,LBXPLTSIM,,Mean platetelets during hospitalisation,Continuous,1000 cells/uL / Missing,28-1000 / .
+NHANES,LBXGHA,,HbA1c at admission,Continuous,nmol/mol; % / Missing,2-16 / .
+NHANES,LBXGHHn,,HbA1c during hospitalisation,Continuous,nmol/mol; % / Missing,2-16 / .
+NHANES,LBXGHM,,Mean HbA1c during hospitalisation,Continuous,nmol/mol; % / Missing,2-16 / .
+SELF,LBXAPTTA,,Partial Thromboplastin Time (APTT) at admission,Continuous,s / Missing,20-120 / .
+SELF,LBXAPTTHn,,Partial Thromboplastin Time (APTT) during hospitalisation,Continuous,s / Missing,20-120 / .
+SELF,LBXAPTTM,,Mean partial Thromboplastin Time (APTT) during hospitalisation,Continuous,s / Missing,20-120 / .
+SELF,LBXAPTRA,,Activated Partial Thromboplastin Time Ratio (APTR) at admission,Continuous,Ratio / Missing,"0,5-3 / ."
+SELF,LBXAPTRHn,,Activated Partial Thromboplastin Time Ratio (APTR) during hospitalisation,Continuous,Ratio / Missing,"0,5-3 / ."
+SELF,LBXAPTRM,,Mean activated Partial Thromboplastin Time Ratio (APTR) during hospitalisation,Continuous,Ratio / Missing,"0,5-3 / ."
+SELF,LBXPRA,,Prothrombin time (PT),Continuous,s / Missing,1-100 / .
+SELF,LBXPRHn,,Prothrombin time (PT),Continuous,s / Missing,1-100 / .
+SELF,LBXPRM,,Mean Prothrombin time (PT),Continuous,s / Missing,1-100 / .
+SELF,LBXINRA,daily_inr_lborres,International Normalised Ratio (INR) at admission,Continuous,Ratio / Missing,0-10 / .
+SELF,LBXINRHn,,International Normalised Ratio (INR) at admission,Continuous,Ratio / Missing,0-10 / .
+SELF,LBXINRM,,Mean International Normalised Ratio (INR) at admission,Continuous,Ratio / Missing,0-10 / .
+NHANES,LBXSATSIA,daily_alt_lborres,Alanine Aminotransferase Test (ALT/SGPT) at admission,Continuous,U/L / Missing,4-890 / .
+NHANES,LBXSATSIHn,,Alanine Aminotransferase Test (ALT/SGPT) during hospitalisation,Continuous,U/L / Missing,4-890 / .
+NHANES,LBXSATSIM,,Mean Alanine Aminotransferase Test (ALT/SGPT) during hospitalisation,Continuous,U/L / Missing,4-890 / .
+NHANES,LBXSTBA,daily_bil_lborres,Total bilirubin at admission,Continuous,mg/dL / Missing,"0,1-4 / ."
+NHANES,LBXSTBHn,,Total bilirubin during hospitalisation,Continuous,mg/dL / Missing,"0,1-4 / ."
+NHANES,LBXSTBM,,Mean total bilirubin during hospitalisation,Continuous,mg/dL / Missing,"0,1-4 / ."
+SELF,LBXSCBA,,Conjugated bilirubin at admission,Continuous,mg/dL / Missing,0-1 / .
+SELF,LBXSCBHn,,Conjugated bilirubin during hospitalisation,Continuous,mg/dL / Missing,0-1 / .
+SELF,LBXSCBM,,Mean conjugated bilirubin during hospitalisation,Continuous,mg/dL / Missing,0-1 / .
+SELF,LBXSUBA,,Unconjugated bilirubin at admission,Continuous,mg/dL / Missing,0-3 / .
+SELF,LBXSUBHn,,Unconjugated bilirubin during hospitalisation,Continuous,mg/dL / Missing,0-3 / .
+SELF,LBXSUBM,,Mean unconjugated bilirubin during hospitalisation,Continuous,mg/dL / Missing,0-3 / .
+NHANES,LBXSASSIA,daily_ast_lborres,Aspartate Aminotransferase (AST/SGOT) at admission,Continuous,U/L / Missing,8-1034 / .
+NHANES,LBXSASSIHn,,Aspartate Aminotransferase (AST/SGOT) during hospitalisation,Continuous,U/L / Missing,8-1034 / .
+NHANES,LBXSASSIM,,Mean Aspartate Aminotransferase (AST/SGOT) during hospitalisation,Continuous,U/L / Missing,8-1034 / .
+NHANES,LBXSGLA,daily_glucose_lborres,Glucose at admission,Continuous,mg/dL / Missing,33-559 / .
+NHANES,LBXSGLHn,,Glucose during hospitalisation,Continuous,mg/dL / Missing,33-559 / .
+NHANES,LBXSGLM,,Mean glucose during hospitalisation,Continuous,mg/dL / Missing,33-559 / .
+NHANES,LBXSBUA,daily_bun_lborres,Urea at admission,Continuous,mg/dL / Missing,2-72 / .
+NHANES,LBXSBUHn,,Urea during hospitalisation,Continuous,mg/dL / Missing,2-72 / .
+NHANES,LBXSBUM,,Mean urea during hospitalisation,Continuous,mg/dL / Missing,2-72 / .
+SELF,LBXSBLA,,Lactate at admission,Continuous,mmol/L / Missing,0-3 / .
+SELF,LBXSBLHn,,Lactate during hospitalisation,Continuous,mmol/L / Missing,0-3 / .
+SELF,LBXSBLM,,Mean lactate during hospitalisation,Continuous,mmol/L / Missing,0-3 / .
+NHANES,LBXSCRA,daily_creat_lborres,Creatinine at admission,Continuous,mg/dL / Missing,"0,3-8,5 / ."
+NHANES,LBXSCRHn,,Creatinine during hospitalisation,Continuous,mg/dL / Missing,"0,3-8,5 / ."
+NHANES,LBXSCRM,,Mean creatinine during hospitalisation,Continuous,mg/dL / Missing,"0,3-8,5 / ."
+NHANES,LBXPSCKA,,Creatinine phosphokinase (CPK) at admission,Continuous,IU/L / Missing,15-3892 / .
+NHANES,LBXPSCKHn,,Creatinine phosphokinase (CPK) during hospitalisation,Continuous,IU/L / Missing,15-3892 / .
+NHANES,LBXPSCKM,,Mean creatinine phosphokinase (CPK) during hospitalisation,Continuous,IU/L / Missing,15-3892 / .
+NHANES,LBXSNASIA,daily_sodium_lborres,Sodium at admission,Continuous,mmol/L / Missing,114-160 / .
+NHANES,LBXSNASIHn,,Sodium during hospitalisation,Continuous,mmol/L / Missing,114-160 / .
+NHANES,LBXSNASIM,,Mean sodium during hospitalisation,Continuous,mmol/L / Missing,114-160 / .
+NHANES,LBXSCLSIA,,Chlorine at admission,Continuous,mmol/L / Missing,82-120 / .
+NHANES,LBXSCLSIHn,,Chlorine during hospitalisation,Continuous,mmol/L / Missing,82-120 / .
+NHANES,LBXSCLSIM,,Mean chlorine during hospitalisation,Continuous,mmol/L / Missing,82-120 / .
+NHANES,LBXSKSIA,daily_potassium_lborres,Potassium at admission,Continuous,mmol/L / Missing,"2,5-6 / ."
+NHANES,LBXSKSIHn,,Potassium during hospitalisation,Continuous,mmol/L / Missing,"2,5-6 / ."
+NHANES,LBXSKSIM,,Mean potassium during hospitalisation,Continuous,mmol/L / Missing,"2,5-6 / ."
+SELF,LBXSPCA,daily_procal_lborres,Procalcitonin at admission,Continuous,ng/ml / Missing,0-1 / .
+SELF,LBXSPCHn,,Procalcitonin during hospitalisation,Continuous,ng/ml / Missing,0-1 / .
+SELF,LBXSPCM,,Mean procalcitonin during hospitalisation,Continuous,ng/ml / Missing,0-1 / .
+NHANES,LBXCRPA,daily_crp_lborres,C-Reactive Protein (CRP) at admission,Continuous,mg/dL / Missing,"0,01-20 / ."
+NHANES,LBXCRPHn,,C-Reactive Protein (CRP) during hospitalisation,Continuous,mg/dL / Missing,"0,01-20 / ."
+NHANES,LBXCRPM,,Mean C-Reactive Protein (CRP) during hospitalisation,Continuous,mg/dL / Missing,"0,01-20 / ."
+NHANES,LBXSLDSIA,,Lactate dehydrogenase (LDH) at admission,Continuous,U/L / Missing,50-661 / .
+NHANES,LBXSLDSIHn,,Lactate dehydrogenase (LDH) during hospitalisation,Continuous,U/L / Missing,50-661 / .
+NHANES,LBXSLDSIM,,Mean lactate dehydrogenase (LDH) during hospitalisation,Continuous,U/L / Missing,50-661 / .
+NHANES,LBXSCKA,,Creatinine Kinase / Creatinine phosphokinase at admission,Continuous,IU/L / Missing,6-3966 / .
+NHANES,LBXSCKHn,,Creatinine Kinase / Creatinine phosphokinase during hospitalisation,Continuous,IU/L / Missing,6-3966 / .
+NHANES,LBXSCKM,,Mean Creatinine Kinase / Creatinine phosphokinase during hospitalisation,Continuous,IU/L / Missing,6-3966 / .
+SELF,LBXCTRA,,Troponin at admission,Continuous,ng/ml / Missing,0-100 / .
+SELF,LBXCTRHn,,Troponin during hospitalisation,Continuous,ng/ml / Missing,0-100 / .
+SELF,LBXCTRM,,Mean troponin during hospitalisation,Continuous,ng/ml / Missing,0-100 / .
+SELF,LBXCDDA,,D-dimer at admission,Continuous,ng/ml / Missing,0-1000 / .
+SELF,LBXCDDHn,,D-dimer during hospitalisation,Continuous,ng/ml / Missing,0-1000 / .
+SELF,LBXCDDM,,Mean D-dimer during hospitalisation,Continuous,ng/ml / Missing,0-1000 / .
+NHANES,LBXFERSIA,,Ferritin at admission,Continuous,�g/L / Missing,2-420 / .
+NHANES,LBXFERSIHn,,Ferritin during hospitalisation,Continuous,�g/L / Missing,2-420 / .
+NHANES,LBXFERSIM,,Mean ferritin during hospitalisation,Continuous,�g/L / Missing,2-420 / .
+SELF,LBXIL6A,,IL-6 at admission,Continuous,pg/ml / Missing,0-10000 / .
+SELF,LBXIL6Hn,,IL-6 during hospitalisation,Continuous,pg/ml / Missing,0-10000 / .
+SELF,LBXIL6M,,Mean IL-6 during hospitalisation,Continuous,pg/ml / Missing,0-10000 / .
+NHANES,LBDFBSIA,,Fibrinogen at admission,Continuous,g/L / Missing,1-10 / .
+NHANES,LBDFBSIHn,,Fibrinogen during hospitalisation,Continuous,g/L / Missing,1-10 / .
+NHANES,LBDFBSIM,,Mean fibrinogen during hospitalisation,Continuous,g/L / Missing,1-10 / .
+NHANES,LBDSALSIA,,Albumin at admission,Continuous,g/L / Missing,12-55 / .
+NHANES,LBDSALSIHn,,Albumin during hospitalisation,Continuous,g/L / Missing,12-55 / .
+NHANES,LBDSALSIM,,Mean albumin during hospitalisation,Continuous,g/L / Missing,12-55 / .
+NHANES,LBXSAPSIA,,Alkaline phosphatase at admission,Continuous,U/L / Missing,14-679 / .
+NHANES,LBXSAPSIHn,,Alkaline phosphatase during hospitalisation,Continuous,U/L / Missing,14-679 / .
+NHANES,LBXSAPSIM,,Mean alkaline phosphatase during hospitalisation,Continuous,U/L / Missing,14-679 / .
+NHANES,LBXSGTSIA,,Gamma Glutamyl Transferase (GGT) at admission,Continuous,U/L / Missing,4-892 / .
+NHANES,LBXSGTSIHn,,Gamma Glutamyl Transferase (GGT) during hospitalisation,Continuous,U/L / Missing,4-892 / .
+NHANES,LBXSGTSIM,,Mean Gamma Glutamyl Transferase (GGT) during hospitalisation,Continuous,U/L / Missing,4-892 / .
+SELF,LBXCFDA,,Calcifediol / 25-OH-vitamin D at admission,Continuous,ng/ml / Missing,0-200 / .
+SELF,LBXCFDHn,,Calcifediol / 25-OH-vitamin D dutring hospitalisation,Continuous,ng/ml / Missing,0-200 / .
+SELF,LBXCFDM,,Mean calcifediol / 25-OH-vitamin D dutring hospitalisation,Continuous,ng/ml / Missing,0-200 / .
+SELF,LBXFIOA,,FiO2 at admission,Continuous,Fraction / Missing,0-1 / .
+SELF,LBXFIOHn,,FiO2 during hospitalisation,Continuous,Fraction / Missing,0-1 / .
+SELF,LBXFIOM,,Mean FiO2 during hospitalisation,Continuous,Fraction / Missing,0-1 / .
+SELF,LBXPOA,,PaO2 at admission,Continuous,mmHg / Missing,0-250 / .
+SELF,LBXPOHn,,PaO2 during hospitalisation,Continuous,mmHg / Missing,0-250 / .
+SELF,LBXPOM,,Mean PaO2 during hospitalisation,Continuous,mmHg / Missing,0-250 / .
+SELF,LBXPCOA,,PaCO2 at admission,Continuous,mmHg / Missing,0-150 / .
+SELF,LBXPCOHn,,PaCO2 during hospitalisation,Continuous,mmHg / Missing,0-150 / .
+SELF,LBXPCOM,,Mean PaCO2 during hospitalisation,Continuous,mmHg / Missing,0-150 / .
+NHANES,LBXSC3SIA,,HCO3 at admission,Continuous,mmol/l / Missing,10-40 / .
+NHANES,LBXSC3SIHn,,HCO3 during hospitalisation,Continuous,mmol/l / Missing,10-40 / .
+NHANES,LBXSC3SIM,,Mean HCO3 during hospitalisation,Continuous,mmol/l / Missing,10-40 / .
+SELF,LBXPHA,,pH at admission,Continuous,pH / Missing,7-8 / .
+SELF,LBXPHHn,,pH during hospitalisation,Continuous,pH / Missing,7-8 / .
+SELF,LBXPHM,,Mean pH during hospitalisation,Continuous,pH / Missing,7-8 / .
+SELF,LBXBEA,,Base excess at admission,Continuous,mEq/l / Missing,-20 - +20 / .
+SELF,LBXBEHn,,Base excess during hospitalisation,Continuous,mEq/l / Missing,-20 - +20 / .
+SELF,LBXBEM,,Mean Base excess during hospitalisation,Continuous,mEq/l / Missing,-20 - +20 / .
+SELF,LBXA4A,,APACHE IV at admission,Continuous,Score / Missing,0-286 / .
+SELF,LBXA4Hn,,APACHE IV during hospitalisation,Continuous,Score / Missing,0-286 / .
+SELF,LBXA4M,,Mean APACHE IV during hospitalisation,Continuous,Score / Missing,0-286 / .
+NHANES,LBXTCA,,Cholesterol at admission,Continuous,mg/dL / Missing,74-453 / .
+NHANES,LBXTCHn,,Cholesterol during hospitalisation,Continuous,mg/dL / Missing,74-453 / .
+NHANES,LBXTCM,,Mean cholesterol during hospitalisation,Continuous,mg/dL / Missing,74-453 / .
+NHANES,LBXTRA,,Triglyceride at admission,Continuous,mg/dL / Missing,16-3281 / .
+NHANES,LBXTRHn,,Triglyceride during hospitalisation,Continuous,mg/dL / Missing,16-3281 / .
+NHANES,LBXTRM,,Mean triglyceride during hospitalisation,Continuous,mg/dL / Missing,16-3281 / .
+SELF,LBXUFRA,,Urine flow rate at admission,Continuous,mL/s / Missing,0-30 / .
+SELF,LBXUFRHn,,Urine flow rate during hospitalisation,Continuous,mL/s / Missing,0-30 / .
+SELF,COXRD,ards_ceterm,Acute Respiratory Distress Syndrom,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXAR,arrhythmia_ceterm,Arrhythmia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXPM,"viralpneu_ceterm, bactpneu_ceterm",Pneumonia,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXMOD,,Multiple Organ Dysfunction,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXPT,pneumothorax_ceterm,Pneumothorax,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXEC,endocarditis_aeterm,Endocarditis,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXSH,,Shock,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXIO,,Other infections,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXPE,,Pulmonary embolism,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXST,stroke_ceterm,Stroke (AVC),Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXDIC,coagulo_ceterm,Disseminated intravascular coagulation,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXRIO,respiratory_infect_yn_two/other_mbyn,Other respiratory infections,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXKF,renalinjury_ceterm,Kidney failure,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXHF,heartfailure_ceterm,Heart failure,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXBC,,Blood complications,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXRF,,Respiratory failure,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXLF,liverdysfunction_ceterm,Hepatic failure,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXADE,,Adverse drug effect,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXSTN,,Stenosis,Binary,No/Yes / Missing,0 / 1 / .
+SELF,COXNOC,,Nosocomial condition,Binary,No/Yes / Missing,0 / 1 / .
+SELF,DATIM,,Date tests performed,Calendar date,Date / Missing, yyyy-mm-dd / .
+SELF,DATIMD,,Time between admission and assessment,Continuous,Days / Missing,0-180 / .
+SELF,IMDIT,xray_prperf?,Imaging test performed ,Binary,No/Yes / Missing,0 / 1 / .
+SELF,IMDXCT,,CT scan results,Categorical, 1. Normal / 2. Groundglass / 3. Crazy paving / 4. Bronchiectasis / 5. Reticulations  / 6. Micronodules / 7. Consolidation / 8. Pleural effusion / 9. Other / Missing,1 / 2 / 3 /4 / 5/ 6 / 7/ 8 / 9 /.
+SELF,IMDXCTCR,,CT CO-RADS,Categorical,1. CO-RADS1No / 2. CO-RADS2Low / 3. CO-RADS3Intermediate / 4. CO-RADS4High / 5. CO-RADS5Very high / 6. CO-RADS 6PCR+ / Missing,1 / 2 / 3 /4 / 5/ 6 / .
+SELF,IMDXCTTE,,CT thromboembolism,Binary,No/Yes / Missing,0 / 1 / .
+SELF,IMDXCTLD,,CT % lung damage,Continuous,% / Missing,0-100 / .
+SELF,IMDXCTAB,,CT abnormal at follow-up,Binary,No/Yes / Missing,0 / 1 / .
+SELF,IMDXXR,,X-ray result,Categorical,1. Normal   2. Intersitial Syndrome   3. Pleural Effusion   4. Alveolar Consolidation   5. Cardiomegaly   6. Other / Missing,1-6 / .
+SELF,IMDXXRI,infiltrates_faorres,X-ray infiltrates,Binary,No/Yes / Missing,0 / 1 / .
+SELF,IMDXPN,,Pneumonia on x-ray or CT scan,Binary,No/Yes / Missing,0 / 1 / .
+SELF,IMDXEQ,,ECG QTc value,,,
+SELF,DRXIDT,ISO_hdiet,How important is it to you to maintain a healthy diet in social isolation/quarantine? ,Categorical,0. No / 1. Yes / Missing,1-5 / .
+SELF,DRXIFDT,ISO_FAMSUP_hdiet,How important is it for you that your family/partner(s) support you in maintaining a healthy diet in social isolation/quarantine? ,Categorical,Number,1-5 / .
+SELF,DRXFPR,ISO_FAMSUP_hdiet2,How often do your family members/partner(s) in social isolation/quarantine [praise your attempt to follow a healthy diet? ,Categorical,0. No / 1. Yes / Missing,0 / 1 / 2 / 3 / . 
+SELF,DRXFGLT,ISO_FAMSUP_glt,How often do your family members/partner(s) in social isolation/quarantine [make you feel guilty when you don't eat healthy?] ,Categorical,Number,0 / 1 / 2 / 3 / . 
+SELF,DRXFVG,ISO_FAMSUP_veg,How often do your family members/partner(s) in social isolation/quarantine [encourage you to consume vegetables?] ,Categorical,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXFFR,ISO_FAMSUP_fr,How often do your family members/partner(s) in social isolation/quarantine [encourage you to consume fruit?] ,Categorical,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXFFN,ISO_FAMSUP_nut,How often do your family members/partner(s) in social isolation/quarantine [talk to you about food and nutrition?] ,Categorical,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXFHF,ISO_FAMSUP_homehf,How often do your family members/partner(s) in social isolation/quarantine [bring healthy food home?] ,Categorical,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXFHFR,ISO_FAMSUP_homefr,How often do your family members/partner(s) in social isolation/quarantine [bring fruit home?] ,Categorical,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXFHVG,ISO_FAMSUP_homeveg,How often do your family members/partner(s) in social isolation/quarantine [bring vegetables home?] ,,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXWK,ISO_regime,What regime do you have in a period of social isolation/quarantine? ,,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXHCG,,Did you look after someone isolating from covid?,,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / .
+SELF,DRXQUI,ISO_alone,Are you in social isolation/quarantine alone? ,Binary,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / .
+SELF,DRXQUA,ISO_countadult,"Not counting yourself, how many adults (aged 18 and over) are with you in social isolation/quarantine? ",Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0-100 / .
+SELF,DRXFSP,DMXspouse,Do you live with a spouse? ,Binary,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / .
+SELF,DRXQUC,ISO_countchild,How many children under the age of 18 are with you in social isolation/quarantine? ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0-100 / .
+SELF,DRXMS,ISO_DIET_milk_skim,Milk and dairy products - in a period of social isolation/quarantine [Skim milk (250ml / lunch cup)] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXMSS,ISO_DIET_milk_semi,Milk and dairy products - in a period of social isolation/quarantine [Semi-skimmed milk (250ml / lunch cup)] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXMW,ISO_DIET_milk_whole,Milk and dairy products - in a period of social isolation/quarantine [Whole milk (250ml / lunch cup)] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXMY,ISO_DIET_milk_yog,Milk and dairy products - in a period of social isolation/quarantine [Yogurt (200 grams)] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXMIC,ISO_DIET_milk_ice,Milk and dairy products - in a period of social isolation/quarantine [Milk Ice Cream (125 grams)] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXMC,ISO_DIET_milk_cheese,Milk and dairy products - in a period of social isolation/quarantine [Cheese (40gr or 2 slices)] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXMFC,ISO_DIET_milk_frche,Milk and dairy products - in a period of social isolation/quarantine [Fresh cheese (50 grams)] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXMCC,ISO_DIET_milk_crcheese,Milk and dairy products - in a period of social isolation/quarantine [cream cheese (100 grams)] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXMB,ISO_DIET_milk_butter,Milk and dairy products - in a period of social isolation/quarantine [Butter excluding that used in food production (15 grams/1 dessert spoon)] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXFRA,ISO_DIET_fr_apples,Fruit - in a period of social isolation/quarantine [Apples and/or pears] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXFRO,ISO_DIET_fr_orange,Fruit - in a period of social isolation/quarantine [Oranges] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXFRJ,ISO_DIET_fr_juice,Fruit - in a period of social isolation/quarantine [Natural fruit juice (small glass)] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXFRB,ISO_DIET_fr_banana,Fruit - in a period of social isolation/quarantine [Bananas] ,Continuous,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXFROF,ISO_DIET_fr_other,Fruit - in a period of social isolation/quarantine [Others fresh fruit] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXFRCF,ISO_DIET_fr_canned,Fruit - in a period of social isolation/quarantine [Canned fruit] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXVR,ISO_DIET_veg_raw,Vegetables - in a period of social isolation/quarantine [Raw vegetables (180 grams)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXVC,ISO_DIET_veg_cooked,Vegetables - in a period of social isolation/quarantine [Cooked vegetables (140 grams)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXVS,ISO_DIET_veg_soup,Vegetables - in a period of social isolation/quarantine [Vegetable soup (250 ml)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXVD,ISO_DIET_leg_dried,"Vegetables - in period of social isolation/quarantine [Dried cooked vegetables eg beans, beans, lentils (80 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXVF,ISO_DIET_leg_fresh,"Legumes - in period of social isolation/quarantine [Fresh cooked legumes eg peas, broad beans (80 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXPE,ISO_DIET_mfe_egg,"Meat, fish and eggs - in a period of social isolation/quarantine [1 egg (medium size)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXPCS,ISO_DIET_mfe_chickenskinn,"Meat, fish and eggs - in a period of social isolation/quarantine [Chicken or turkey with skin (100 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXPC,ISO_DIET_mfe_chicken,"Meat, fish and eggs - in a period of social isolation/quarantine [Skinless chicken or turkey (100 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXPB,ISO_DIET_mfe_bacon,"Meat, fish and eggs - in a period of social isolation/quarantine [Bacon (2 slices)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXPTM,ISO_DIET_mfe_pmeat,"Meat, fish and eggs - in a period of social isolation/quarantine [Transformed meat (sausages, salami, etc.)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXPL,ISO_DIET_mfe_liver,"Meat, fish and eggs - in a period of social isolation/quarantine [Liver (85 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXPBU,ISO_DIET_mfe_burger,"Meat, fish and eggs - in a period of social isolation/quarantine [Burger (1 unit)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXPRM,ISO_DIET_mfe_rmeat,"Meat, fish and eggs - in a period of social isolation/quarantine [Beef, pork or lamb (main dish)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXPF,ISO_DIET_mfe_fish,"Meat, fish and eggs - in a period of social isolation/quarantine [Fish (110 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXSCH,ISO_DIET_swe_choco,"Sweets, cakes and snacks - in a period of social isolation/quarantine [Chocolate (30grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXSNCH,ISO_DIET_swe_sweets,"Sweets, cakes and snacks - in a period of social isolation/quarantine [Sweets without chocolate (30 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXSSP,ISO_DIET_swe_pie,"Sweets, cakes and snacks - in a period of social isolation/quarantine [Sweet pie (1 slice)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXSCA,ISO_DIET_swe_cake,"Sweets, cakes and snacks - in a period of social isolation/quarantine [Cake (1 slice)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXSCO,ISO_DIET_swe_cookie,"Sweets, cakes and snacks - in a period of social isolation/quarantine [Cookies] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXSSC,ISO_DIET_swe_cereal,"Sweets, cakes and snacks - in a period of social isolation/quarantine [Sweet cereals] ",,Frequency,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXSCP,ISO_DIET_swe_chips,"Sweets, cakes and snacks - in a period of social isolation/quarantine [chips] ",,Frequency,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXSO,ISO_DIET_swe_others,"Sweets, cakes and snacks - in a period of social isolation/quarantine [Others] ",,Frequency,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXDC,ISO_DIET_drink_coffee,Drinks - in a period of social isolation/quarantine [Coffee (1 cup)] ,,0. Don't know or don't cook / 1. Olive oil / 2. Vegetable oil / 3. Butter / 4. Margarine / 5. Lard / Missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXDT,ISO_DIET_drink_tea,Drinks - in a period of social isolation/quarantine [Tea (1 mug)] ,,0. Don't know or don't cook / 1. Olive oil / 2. Vegetable oil / 3. Butter / 4. Margarine / 5. Lard / Missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXDB,ISO_DIET_drink_beer,Drinks - in a period of social isolation/quarantine [Beer (20cl)] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. daily / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXDWI,ISO_DIET_drink_wine,Drinks - in a period of social isolation/quarantine [Wine (10cl)] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. daily / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXDL,ISO_DIET_drink_liquor,"Drinks - in a period of social isolation/quarantine [Liquor, whiskey, gin, etc. (5cl)] ",,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. daily / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXDDS,ISO_DIET_drink_dietsoft,Drinks - in a period of social isolation/quarantine [Calorie-reduced carbonated drinks] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. daily / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXDSS,ISO_DIET_drink_soft,Drinks - in a period of social isolation/quarantine [Sparkling drinks with sugar] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. daily / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXDF,ISO_DIET_drink_juice,Drinks - in a period of social isolation/quarantine [Fruit juices (no fresh)] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. daily / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXDWA,ISO_DIET_drink_water,Drinks - in a period of social isolation/quarantine [Water] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. daily / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXDTS,ISO_DIET_drink_sugar,How many teaspoons of sugar do you add to your drinks daily? (in a period of social isolation/quarantine) ,,0. Little or none / 1. Shared equally (50%) / 2. Most or always / missing,
+SELF,DRXVT,ISO_DIET_vit,Do you take any vitamin supplements? (in a period of social isolation/quarantine) ,,0. Little or none / 1. Shared equally (50%) / 2. Most or always / missing,
+SELF,DRXRMF,ISO_DIET_rmeatfat,"When you eat red meat (beef, pork, lamb, etc.) does it remove visible fat on the plate? (in a period of social isolation/quarantine) ",,0. Little or none / 1. Shared equally (50%) / 2. Most or always / missing,
+SELF,DRXFASF,ISO_DIET_fat_stirfry,What kind of fat do you use to stir-fry food at home? (in a period of social isolation/quarantine) ,,0. 0-1 days per week / 1. 2-3 days per week / 2. 4-5 days per week / 3. 6-7 days per week / missing,0 / 1 / 2 / 3 / 4 / 5 / .
+SELF,DRXFAC,ISO_DIET_fat_cook,What kind of fat do you use to cook food at home? (in a period of social isolation/quarantine) ,,0. 0-1 days per week / 1. 2-3 days per week / 2. 4-5 days per week / 3. 6-7 days per week / missing,0 / 1 / 2 / 3 / 4 / 5 / .
+SELF,DRXFF,ISO_DIET_fried,How often do you eat fried foods? (in a period of social isolation/quarantine) ,,0. 0-1 days per week / 1. 2-3 days per week / 2. 4-5 days per week / 3. 6-7 days per week / missing,0 / 1 / 2 / 3 / .
+SELF,DRXCSF,ISO_FOODPREP_stuf,Methods of confection used (in a period of social isolation/quarantine) [Stuffed] ,,0.Never / 1.Rarely / 2. Occasionally / 3.Often,0 / 1 / 2 / 3 / .
+SELF,DRXCSW,ISO_FOODPREP_stew,Methods of confection used (in a period of social isolation/quarantine) [Stew] ,,0.Never / 1.Rarely / 2. Occasionally / 3.Often,0 / 1 / 2 / 3 / .
+SELF,DRXCR,ISO_FOODPREP_roast,Methods of confection used (in a period of social isolation/quarantine) [Roasting] ,,0.Never / 1.Rarely / 2. Occasionally / 3.Often,0 / 1 / 2 / 3 / .
+SELF,DRXCMC,ISO_FOODPREP_cook,Cooking methods used (in a period of social isolation/quarantine) [Cooked] ,,0.Never / 1.Rarely / 2. Occasionally / 3.Often,0 / 1 / 2 / 3 / .
+SELF,DRXMG,ISO_FOODPREP_grill,Preparation methods used (in a period of social isolation/quarantine) [Grilled] ,,0.Never / 1.Rarely / 2. Occasionally / 3.Often,0 / 1 / 2 / 3 / .
+SELF,DRXMSF,ISO_FOODPREP_stirfry,Methods of confection used (in a period of social isolation/quarantine) [Stir-fry] ,,0.Never / 1.Rarely / 2. Occasionally / 3.Often,0 / 1 / 2 / 3 / .
+SELF,DRXRSM,ISO_RESP_supermarket,What is your responsibility for (in a period of social isolation/quarantine) [Going to the supermarket to buy food?] ,,0.Never / 1.Rarely / 2. Occasionally / 3.Often,0 / 1 / 2 / .
+SELF,DRXRMPL,ISO_RESP_mplan,What is your responsibility for (in a period of social isolation/quarantine) [Planning meals] ,,0.Never / 1.Rarely / 2. Occasionally / 3.Often,0 / 1 / 2 / .
+SELF,DRXRMPR,ISO_RESP_mprep,What is your responsibility for (in a period of social isolation/quarantine) [Preparing meals] ,,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / .
+SELF,DRXBSB,BEF_SHARE_breakfast,"Before the quarantine period, in a typical week, how often would you share the meals below with people who are with you in social isolation/quarantine? [Breakfast] ",,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / .
+SELF,DRXBSL,BEF_SHARE_lunch,"Before the quarantine period, in a typical week, how often would you share the meals below with people who are with you in social isolation/quarantine? [Lunch] ",,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / .
+SELF,DRXBSD,BEF_SHARE_dinner,"Before the quarantine period, in a typical week, how often would you share the meals below with people who are with you in social isolation/quarantine? [Dinner] ",,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / .
+SELF,DRXBFPR,BEF_FAMSUP_hdiet2,"Prior to the period of social isolation/quarantine, how often did your family members/partners [praise your attempt to follow a healthy diet?] ",,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXBFGLT,BEF_FAMSUP_glt,"Prior to the period of social isolation/quarantine, how often did your relatives/partners [make you feel guilty when you ate healthy] ",,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXBFVG,BEF_FAMSUP_veg,"Before the period of social isolation/quarantine, how often did your family members/partners [encourage you to consume vegetables?] ",,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXBFFR,BEF_FAMSUP_fr,"Before the period of social isolation/quarantine, how often did your family members/partners [encourage you to consume fruit?] ",,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXBFFN,BEF_FAMSUP_nut,"Before the period of social isolation/quarantine, how often did your family members/partners [talk to you about food and nutrition?] ",,0. Never / 1. 1 time per week / 2. 2-4 times per week / 3. 5-6 times per week / 4. 7+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXBFHF,BEF_FAMSUP_homehf,"Prior to the period of social isolation/quarantine, how often did your family members/partners [bring healthy food home?] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXBFHFR,BEF_FAMSUP_homefr,"Before the period of social isolation/quarantine, how often did your family members/partners [bring fruit home?] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXBFHVG,BEF_FAMSUP_homeveg,"Before the period of social isolation/quarantine, how often did your family members/partners [bring vegetables home?] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / . 
+SELF,DRXBMS,BEF_DIET_milk_skim,Milk and dairy products (before the period of social isolation/quarantine) [skimmed milk (250ml / lunch cup)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBMSS,BEF_DIET_milk_semi,Milk and dairy products (before the period of social isolation/quarantine) [Semi-skimmed milk (250ml / lunch cup)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBMW,BEF_DIET_milk_whole,Milk and dairy products (before the period of social isolation/quarantine) [Whole milk (250ml / lunch cup)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBMY,BEF_DIET_milk_yog,Milk and dairy products (before the period of social isolation/quarantine) [Yogurt (200 grams)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBMIC,BEF_DIET_milk_ice,Milk and dairy products (before the period of social isolation/quarantine) [Ice Cream (125 grams)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBMC,BEF_DIET_milk_cheese,Milk and dairy products (before the period of social isolation/quarantine) [Cheese (40gr or 2 slices)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBMFC,BEF_DIET_milk_frche,Milk and dairy products (before the period of social isolation/quarantine) [Fresh cheese (50 grams)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBMCC,BEF_DIET_milk_crcheese,Milk and dairy products (before the period of social isolation/quarantine) [Cream cheese (100 grams)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBMB,BEF_DIET_milk_butter,Milk and dairy products (before the period of social isolation/quarantine) [Butter excluding that used in food production (15 grams/1 dessert spoon)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBFRA,BEF_DIET_fr_apples,Fruit (before the social isolation/quarantine period) [Apples and/or pears] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBFRO,BEF_DIET_fr_orange,Fruit (before the social isolation/quarantine period) [Oranges] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBFRJ,BEF_DIET_fr_juice,Fruit (before the social isolation/quarantine period) [Natural fruit juice (small glass)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBFRB,BEF_DIET_fr_banana,Fruit (before the social isolation/quarantine period) [Bananas] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBFROF,BEF_DIET_fr_other,Fruit (before the social isolation/quarantine period) [Others fresh fruit] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBFRCF,BEF_DIET_fr_canned,Fruit (before the social isolation/quarantine period) [Canned fruit] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBVR,BEF_DIET_veg_raw,Vegetables (before the period of social isolation/quarantine) [Raw vegetables (180 grams)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBVC,BEF_DIET_veg_cooked,Vegetables (before the period of social isolation/quarantine) [Cooked vegetables (140 grams)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBVS,BEF_DIET_veg_soup,Vegetables (before the period of social isolation/quarantine) [Vegetable soup (250 ml)] ,,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBVD,BEF_DIET_leg_dried,"Legumes (before the period of social isolation/quarantine) [Dried cooked legumes eg beans, beans, lentils (80 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBVF,BEF_DIET_leg_fresh,"Legumes (before the period of social isolation/quarantine) [Fresh cooked legumes eg peas, broad beans (80 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBPE,BEF_DIET_mfe_egg,"Meat, fish and eggs (before the period of social isolation/quarantine) [1 egg (medium size)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBPCS,BEF_DIET_mfe_chickenskinn,"Meat, fish and eggs (before the period of social isolation/quarantine) [Chicken or turkey with skin (100 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBPC,BEF_DIET_mfe_chicken,"Meat, fish and eggs (before the period of social isolation/quarantine) [Skinless chicken or turkey (100 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBPB,BEF_DIET_mfe_bacon,"Meat, fish and eggs (before the period of social isolation/quarantine) [Bacon (2 slices)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBPTM,BEF_DIET_mfe_pmeat,"Meat, fish and eggs (before the period of social isolation/quarantine) [Processed meat (sausages, salami, etc.)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBPL,BEF_DIET_mfe_liver,"Meat, fish and eggs (before the period of social isolation/quarantine) [Liver (85 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBPB,BEF_DIET_mfe_burger,"Meat, fish and eggs (before the period of social isolation/quarantine) [Burger (1 unit)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBPRM,BEF_DIET_mfe_rmeat,"Meat, fish and eggs (before the period of social isolation/quarantine) [Beef, pork or lamb (main dish)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBPF,BEF_DIET_mfe_fish,"Meat, fish and eggs (before the period of social isolation/quarantine) [Fish (110 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBSCH,BEF_DIET_swe_choco,"Sweets, cakes and snacks (before the period of social isolation/quarantine) [Chocolate (30 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBSNCH,BEF_DIET_swe_sweets,"Sweets, cakes and snacks (before the period of social isolation/quarantine) [Sweets without chocolate (30 grams)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBSSP,BEF_DIET_swe_pie,"Sweets, cakes and snacks (before the period of social isolation/quarantine) [Sweet tart (1 slice)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBSCA,BEF_DIET_swe_cake,"Sweets, cakes and snacks (before the period of social isolation/quarantine) [Cake (1 slice)] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBSCO,BEF_DIET_swe_cookie,"Sweets, cakes and snacks (before the period of social isolation/quarantine) [Cookies] ",,0. Never / 1. 1 time per week / 2. 2-3 times per week / 3. 4-5 times per week / 4. 6+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBSSC,BEF_DIET_swe_cereal,"Sweets, cakes and snacks (before the period of social isolation/quarantine) [Sweet cereals] ",,Frequency,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBSCP,BEF_DIET_swe_chips,"Sweets, cakes and snacks (before the period of social isolation/quarantine) [chips] ",,Frequency,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBSO,BEF_DIET_swe_others,"Sweets, cakes and snacks (before the period of social isolation/quarantine) [Others] ",,Frequency,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBDC,BEF_DIET_drink_coffee,Drinks (before the social isolation/quarantine period) [Coffee (1 cup)] ,,0. Don't know or don't cook / 1. Olive oil / 2. Vegetable oil / 3. Butter / 4. Margarine / 5. Lard / 6. Don't eat at home / Missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBDT,BEF_DIET_drink_tea,Drinks (before the social isolation/quarantine period) [Tea (1 mug)] ,,0. Don't know or don't cook / 1. Olive oil / 2. Vegetable oil / 3. Butter / 4. Margarine / 5. Lard / 6. Don't eat at home Missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBDB,BEF_DIET_drink_beer,Drinks (before the social isolation/quarantine period) [Beer (20cl)] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. 7+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBDWI,BEF_DIET_drink_wine,Drinks (before the social isolation/quarantine period) [Wine (10cl)] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. 7+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBDL,BEF_DIET_drink_liquor,"Drinks (before the social isolation/quarantine period) [Liquor, whiskey, gin, etc. (5cl)] ",,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. 7+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBDDS,BEF_DIET_drink_dietsoft,Drinks (before the social isolation/quarantine period) [Calorie-reduced carbonated drinks] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. 7+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBDSS,BEF_DIET_drink_soft,Drinks (before the social isolation/quarantine period) [Sparkling drinks with sugar] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. 7+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBDF,BEF_DIET_drink_juice,Drinks (before the social isolation/quarantine period) [Fruit juices (No fresh)] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. 7+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBDWA,BEF_DIET_drink_water,Drinks (before the social isolation/quarantine period) [Water] ,,0. 0-1 time per week / 1. 2-3 times per week / 2. 4-6 times per week / 3. 7+ times per week / missing,0 / 1 / 2 / 3 / 4 / .
+SELF,DRXBDTS,BEF_DIET_drink_sugar,How many teaspoons of sugar did you add to your Daily drinks? (before the period of social isolation/quarantine) ,,Frequency,
+SELF,DRXBVT,BEF_DIET_vit,Did you take any vitamin supplements? (before the period of social isolation/quarantine) ,,Frequency,
+,DRXBRMF,BEF_DIET_rmeatfat,"When you ate red meat (beef, pork, lamb, etc.) did you remove the visible fat on the plate? (before the period of social isolation/quarantine) ",,Frequency,
+,DRXBFASF,BEF_DIET_fat_stirfry,What kind of fat did you use to stir-fry food at home? (before the period of social isolation/quarantine) ,,0. no como / 1. At home / 2. Outside of home / missing,0 / 1 / 2 / 3 / 4 / 5 / 6 / .
+,DRXBFAC,BEF_DIET_fat_cook,What kind of fat did you use to make food? (before the period of social isolation/quarantine) ,,0. no como / 1. At home / 2. Outside of home / missing,0 / 1 / 2 / 3 / 4 / 5 / 6 / .
+,DRXBFF,BEF_DIET_fried,How often did you eat fried foods? (before the period of social isolation/quarantine) ,,0. no como / 1. At home / 2. Outside of home / missing,0 / 1 / 2 / 3 / .
+,DRXBCSF,BEF_FOODPREP_stuf,Methods of confection used (before the period of social isolation/quarantine) [Stuffed] ,,0. No change / 1. Increase / 2. Decrease / missing,0 / 1 / 2 / 3 / .
+,DRXBCSW,BEF_FOODPREP_stew,Methods of confection used (before the period of social isolation/quarantine) [Stew] ,,0. No change / 1. Increase / 2. Decrease / missing,0 / 1 / 2 / 3 / .
+,DRXBCR,BEF_FOODPREP_roast,Methods of confection used (before the period of social isolation/quarantine) [Roasting] ,,0. No change / 1. Increase / 2. Decrease / missing,0 / 1 / 2 / 3 / .
+,DRXBCMC,BEF_FOODPREP_cook,Cooking methods used (before the period of social isolation/quarantine) [Cooked] ,,0. No change / 1. Increase / 2. Decrease / missing,0 / 1 / 2 / 3 / .
+,DRXBMG,BEF_FOODPREP_grill,Preparation methods used (before the period of social isolation/quarantine) [Grilled] ,,0. No change / 1. Increase / 2. Decrease / missing,0 / 1 / 2 / 3 / .
+,DRXBMSF,BEF_FOODPREP_stirfry,Methods of confection used (before the period of social isolation/quarantine) [Stir-fry] ,,0. No change / 1. Increase / 2. Decrease / missing,0 / 1 / 2 / 3 / .
+,DRXBRSM,BEF_RESP_supermarket,What is your responsibility for (before the period of social isolation/quarantine) [Going to the supermarket to buy food?] ,,0. No change / 1. Increase / 2. Decrease / missing,
+,DRXBRMPL,BEF_RESP_mplan,What is your responsibility for (before the period of social isolation/quarantine) [Planning meals] ,,0. No change / 1. Increase / 2. Decrease / missing,
+,DRXBRMPR,BEF_RESP_mprep,What is your responsibility for (before the social isolation/quarantine period) [Preparing meals] ,,0. No change / 1. Increase / 2. Decrease / missing,
+,DRXBBSB,BEF_breakfast,"In a typical week, where you mostly have the following meals (before the social isolation/quarantine period) [Breakfast] ",,0. No change / 1. Increase / 2. Decrease / missing,0 / 1 / 2 / .
+,DRXBBSL,BEF_lunch,"In a typical week, where you mostly have the following meals (before the social isolation/quarantine period) [Lunch] ",,0. No change / 1. Increase / 2. Decrease / missing,0 / 1 / 2 / .
+,DRXBBSD,BEF_dinner,"In a typical week, where you mostly have the following meals (before the social isolation/quarantine period) [Dinner] ",,0. No change / 1. Increase / 2. Decrease / missing,0 / 1 / 2 / .
+,DRQTFT,FCM_taste,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [The taste of food] ,,0. No change / 1. Increase / 2. Decrease / missing,0 / 1 / 2 / .
+,DRQTFH,FCM_heal,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Trying to eat healthy] ,,0. No change / 1. Increase / 2. Decrease / missing,0 / 1 / 2 / .
+,DRQTFP,FCM_pric,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Food price] ,,,0 / 1 / 2 / .
+,DRQTFR,FCM_habit,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Habit or routine] ,,,0 / 1 / 2 / .
+,DRQTFA,FCM_avail,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Availability of food] ,,,0 / 1 / 2 / .
+,DRQTFQ,FCM_qual,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Quality or freshness of food] ,,,0 / 1 / 2 / .
+,DRQTFO,FCM_otherperson,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Other person decides most of the food  que eu como],,,0 / 1 / 2 / .
+,DRQTFE,FCM_conv,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Ease or convenience of preparation] ,,,0 / 1 / 2 / .
+,DRQTFW,FCM_weco,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Control weight] ,,,0 / 1 / 2 / .
+,DRQTFD,FCM_dietphy,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Diet advised by the physician] ,,,0 / 1 / 2 / .
+,DRQTFPR,FCM_pack,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Presentation or packaging] ,,,0 / 1 / 2 / .
+,DRQTFAD,FCM_natu,"Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Content in additives, dyes or preservatives] ",,,0 / 1 / 2 / .
+,DRQTFCR,FCM_cult,"Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [My cultural, religious or ethnic roots] ",,,0 / 1 / 2 / .
+,DRQTFV,FCM_vegediet,Select the 3 factors that have the greatest influence on the choice of foods you consume in the context of social isolation/quarantine. [Vegetarian food or eating habits  espec�ficos],,,0 / 1 / 2 / .
+SELF,DATSO,cestdat,Date of symptom onset,Calendar date,yyyy-mm-dd / Missing, / .
+SELF,DATAD,,Date of admission,Calendar date,yyyy-mm-dd / Missing, / .
+SELF,DATADI,icu_hostdat??,Date of admission to ICU,Calendar date,yyyy-mm-dd / Missing, / .
+SELF,DATDSI,,Date of discharge from ICU,Calendar date,yyyy-mm-dd / Missing, / .
+SELF,DATDS,hoendat,Date of discharge,Calendar date,yyyy-mm-dd / Missing, / .
+SELF,DATPR,,Date of drug prescription,Calendar date,yyyy-mm-dd / Missing, / .
+SELF,DATLGT,,Length of stay in hospital,Continuous,Days / Missing,0-180 / .
+SELF,DATLGTI,hodur,Length of stay in ICU,Continuous,Days / Missing,0-180 / .
+SELF,DSXHO,,Patient admitted to hospital,Binary,No/Yes / Missing,0/1/ .
+SELF,DSXIC,icu_hoterm,Patient admitted to ICU,Binary,No/Yes / Missing,0/1 / .
+SELF,DSXOS,dsterm,Outcome status,Categorical,Recovered/Deceased/Transferred / Missing,0/1/2 / .
+SELF,DATOS,dsstdtcyn,Date of outcome status,Calendar date,yyyy-mm-dd / Missing, / .

ressourceCleaner.R

+
+rm(list=ls())
+
+setwd("C:/Users/Victor/Documents/TFG/r-analytics-master/ressources")
+setwd(("C:/Users/Victor/Documents/TFG/r-analytics-master/ressources/new_res_baskent/outpatient"))
+
+#Cambiarlo por el nombre del ressource que se desea limpiar
+hospital <- data.frame(read.csv("konya_outpatient.csv", sep=","))
+
+
+hospital <- hospital %>% select(-contains("numeric"))
+
+# hospital["NOT.HARMONISED"] <- NULL
+# 
+# names <- colnames(hospital)
+# for (i in 1:length(names)){
+# 
+#   if(grepl("NOT.HARMONISED", names[i])){
+#     hospital[names[i]] <- NULL
+#     print(paste("quito ", names[i]))
+#   }
+# 
+# }
+# hospital <- hospital[-1,]
+
+setwd("C:/Users/Victor/Documents/TFG/r-analytics-master/harmonised_data")
+
+ComAndRF <- data.frame(read.csv("Com&RF.csv", sep=","))[1:64,1:5]
+Complications <- data.frame(read.csv("Complications.csv", sep=";"))[1:20,1:5]
+Dates <-  data.frame(read.csv("Dates.csv", sep=";"))[1:12,1:5]
+Demographics <-  data.frame(read.csv("Demographics.csv", sep=";"))[1:9,1:5]
+Home_med <-  data.frame(read.csv("Home_med.csv", sep=";"))[1:13,1:5]
+Imaging_data <-  data.frame(read.csv("Imaging_data.csv", sep=";"))[1:11,1:5]
+Labo <-  data.frame(read.csv("Labo.csv", sep=";"))[1:143,1:5]
+SiAndSympt <-  data.frame(read.csv("Si&Sympt.csv", sep=";"))[1:50,1:5]
+Treatment <-  data.frame(read.csv("Treatment.csv", sep=";"))[1:32,1:5]
+LifestyleAndDiet <-  data.frame(read.csv("Lifestyle&Diet.csv", sep=";"))[1:165,1:5]
+
+
+harmonised_data <- rbind(SiAndSympt,ComAndRF)
+harmonised_data <- rbind(harmonised_data,Treatment)
+
+harmonised_data <- rbind(harmonised_data,Dates)
+harmonised_data <- rbind(harmonised_data,Demographics)
+harmonised_data <- rbind(harmonised_data,Home_med)
+harmonised_data <- rbind(harmonised_data,Imaging_data)
+harmonised_data <- rbind(harmonised_data,Complications)
+harmonised_data <- rbind(harmonised_data,Labo)
+harmonised_data <- rbind(harmonised_data,LifestyleAndDiet)
+
+rm(list=c("SiAndSympt",
+          "Complications",
+          "ComAndRF",
+          "Dates",
+          "Demographics",
+          "Home_med",
+          "Imaging_data",
+          "Complications",
+          "Labo",
+          "LifestyleAndDiet"))
+
+noYesValues <- subset(harmonised_data, harmonised_data$Harmonised.data.format.unit == "No/Yes / missing" | harmonised_data$Harmonised.data.format.unit == "No/Yes / Missing")
+noYesValues <- noYesValues$Harmonised.variable.name
+noYesValues <- c(noYesValues,"CSXCOTAB","CSXCOTAG","IMDIT","RFXHIV_RFXAIDS", "SMXASAH", "CMXATH", "CMXNO")
+
+categoric_vars = c("CMXATH", "CMXNO", "SMXASAH","CSXCOTAB","CSXCOTAG","IMDIT","RFXHIV_RFXAIDS","DMRGENDR", "DMRBORN", "DMRRETH1", "DMROCCU", "DMRHREDU", "DSXOS", "DSXHO", "DSXIC", "TRXAV","TRXRIB","TRXLR","TRXRM","TRXIA","TRXIB","TRXCH","TRXAB","TRXCS","TRXHEP","TRXAF","TRXCP","TRXOT","TRXECM","TRXIV","TRXNIV","TRXNO","TRXOX","TRXRR","TRXTR","TRXVA","TRXPE","TRXPV","TRXIT","TRXNMB","TRXAC","TRXINA","TRXIS","TRXIM","TRXVC","TRXVD","TRXZN",                         "CSXCOT","CSXCTR","SMXASAH","SMXFEA","SMXCOA","SMXSTA","SMXSBA","SMXRNA","SMXMYA","SMXARA","SMXCPA","SMXAPA","SMXINA","SMXNAA","SMXDIA","SMXFAA","SMXHEA","SMXCNA","SMXACA","SMXSLA","SMXTLA","SMXSYA","SMXWHA","SMXLYA","SMXANA","SMXIWA","SMXSRA","SMXBLA","CMXPRG","CMXCVD","CMXCMP","CMXHT","CMXDI","CMXCKD","CMXCLD","CMXCPD","CMXASM","CMXCND","CMXRHE","CMXCCI","CMXCBD","CMXDE","CMXPU","CMXST","CMXLY","CMXAP","RFXSM","RFXFSM","RFXOB","RFXTB","RFXIMD","RFXHIV","RFXAIDS","RFXUI","RFXHC","RFXONC","RFXMN",                         "HMRACI","HMRARB","HMRAHO","HMRNS","HMROS","HMRCS","HMRIS","HMRAV","HMRAB","HMRCOV","IMDXCT","IMDXCTCR","IMDXCTTE","IMDXCTAB","IMDXXR","IMDXPN",                         "COXRD","COXAR","COXPM","COXMOD","COXPT","COXEC","COXSH","COXIO","COXPE","COXST","COXDIC","COXRIO","COXKF","COXHF","COXBC")
+
+personalized <- c("DMRGENDR", "DSXOS", "CSXCTR", "SMXFEA", "CSXCOT")
+
+is_number <- function(x){
+  res <- FALSE
+  
+  if(length(x)!=0){
+    x <- str_replace(x,",",".")
+    
+    aux <- as.numeric(x)
+    
+    if(!is.na(aux))
+      res <- TRUE
+  }
+  return(res)
+}
+
+
+replaceNoYesValues <- function(x){
+  
+  #Replace the value with Yes or No
+    if(is.na(x))
+      x <- ""
+    else if (x==0 | x =="No" | x ==" No" | x =="NO")
+      x <- "No"
+    else if (x==1 | x == "Yes" |  x == " Yes" | x=="SI")
+      x <- "Yes"
+    else
+      x <- ""
+    
+    return (x)
+  
+}
+
+fixNonCategoric <- function(x){
+  
+  if(!is_number(x)){
+    x <- ""
+  }else{
+    x <- str_replace(x,",",".")
+  }
+  
+  return(x)
+  
+}
+
+personalizedFun <- function(x, colname){
+  
+  if(colname == "DMRGENDR"){
+    if(is.na(x))
+      x <- ""
+    else if(x == 1 | x == "F"| x == "f" | x== "Female")
+      x <- "Female"
+    else if (x == 0 | x =="M" | x == "m" | x== "Male")
+      x <- "Male"
+  }
+  
+  if(colname == "CSXCTR"){
+    if(is.na(x))
+      x <- ""
+    else if(x == 1 | x == "positive" | x=="PositivM" | x=="POSITIVM" | x =="POS?T?VM" | x =="NMGAT?VM")
+      x <- "Positive"
+    else if (x == 0 | x == "negative" | x=="negativM" | x=="NMGATIVM" | x=="NAGATIVM" | x =="NMGATIV" | x =="negativeM" | x == "NAGAT?VM" | x =="NMGAT?V")
+      x <- "Negative"
+  }
+
+  if(colname == "SMXFEA"){
+    if(is.na(x))
+      x <- ""
+    else if(x == 1)
+      x <- "Yes"
+    else if (x == 0)
+      x <- "No"
+    else if (x == ".")
+      x <- ""
+  }
+  
+  if(colname == "DMRRETH1"){
+    if(is.na(x))
+      x <- ""
+    else if(x ==1)
+      x <- "Asian"
+    else if (x == 2)
+      x <- "Black"
+    else if (x == 3)
+      x <- "Hispanic"
+    else if (x == 4)
+      x <- "White"
+    else if (x == 5)
+      x <- "Multiracial"
+    else if (x == 6)
+      x <- "Other"
+  }
+  
+  if(colname == "DMROCCU"){
+    if(is.na(x))
+      x <- ""
+    else if(x ==1)
+      x <- "Unemployed"
+    else if (x == 2)
+      x <- "Student"
+    else if (x == 3)
+      x <- "Employed"
+    else if (x == 4)
+      x <- "Self-employed"
+    else if (x == 5)
+      x <- "Retired"
+    else if (x == 6)
+      x <- ""
+  }
+  
+  if(colname == "DMRHREDU"){
+    if(is.na(x))
+      x <- ""
+    else if(x ==1)
+      x <- "High School"
+    else if (x == 2)
+      x <- "Bachelors"
+    else if (x == 3)
+      x <- "Postgraduate"
+    else if (x == 4)
+      x <- "Other"
+  }
+  
+  if(colname =="DSXOS"){
+    
+    if(is.na(x))
+      x <- ""
+    else if (x==0 | x == "Recovered")
+      x <- "Recovered"
+    else if (x==1 | x == "Deceased")
+      x <- "Deceased"
+    else if (x==2 | x == "Transferred")
+      x <- "Transferred"
+    else
+      x <- ""
+  }
+  
+  if(colname =="CSXCOT"){
+    if(is.na(x))
+      x <- ""
+    else if (x==1 )
+      x <- "PCR"
+    else if (x==2 )
+      x <- "antigen"
+    else if (x==3 )
+      x <- "other"
+    else
+      x <- ""
+  }
+  
+
+  return(x)
+  
+}
+
+dotToBar <- function (x){
+  
+  if (grepl(".", x, fixed = TRUE))
+    res <- format(as.Date(x, format = "%d.%m.%Y"), "%d/%m/%Y")
+  else res <- x
+  return(res)
+  
+}
+
+
+
+rm(newDf)
+
+newDf <- hospital
+
+
+
+names <- colnames(hospital)
+
+
+for (j in 1:ncol(hospital)){
+  
+  percentage <- trunc(j/ncol(hospital)*100)
+  mes <- paste(toString(percentage),"% completed", sep="")
+  print(mes)
+  
+  print(names[j])
+  
+  for(i in 1:nrow(hospital)){
+    
+    if(names[j] %in% noYesValues){
+      newDf[i,j] <- replaceNoYesValues(hospital[i,j])
+    }else if(!(names[j] %in% categoric_vars) & names[j] != "DMRBORN" & !grepl("DAT",names[j], fixed=TRUE)){
+      newDf[i,j] <- fixNonCategoric(hospital[i,j])
+    }
+    
+    if(names[j] %in% personalized){
+      newDf[i,j] <- personalizedFun(hospital[i,j],names[j])
+    }
+    
+    if (is.na(hospital[i,j]))
+      newDf[i,j] <- ""
+    
+    else if (hospital[i,j] == ".")
+      newDf[i,j] <- ""
+    
+  }
+}
+
+setwd("C:/Users/Victor/Documents/TFG/r-analytics-master/ressources/newRessources")
+setwd(("C:/Users/Victor/Documents/TFG/r-analytics-master/ressources/new_res_baskent/outpatient/clean"))
+
+
+
+
+write.csv(x=newDf, file = "konya_outpatient.csv", row.names = FALSE)
+
+

ressourceHarmonizer.R

+
+rm(list=ls())
+
+setwd("C:/Users/Victor/Documents/TFG/r-analytics-master/ressources/newRessources")
+setwd(("C:/Users/Victor/Documents/TFG/r-analytics-master/ressources/new_res_baskent/outpatient/clean"))
+
+
+hospital <- data.frame(read.csv("konya_outpatient.csv", sep=","))
+
+
+setwd("C:/Users/Victor/Documents/TFG/r-analytics-master/harmonised_data")
+
+ComAndRF <- data.frame(read.csv("Com&RF.csv", sep=","))
+Complications <- data.frame(read.csv("Complications.csv", sep=";"))[1:20,1:5]
+Dates <-  data.frame(read.csv("Dates.csv", sep=";"))[1:12,1:5]
+Demographics <-  data.frame(read.csv("Demographics.csv", sep=";"))[1:9,1:5]
+Home_med <-  data.frame(read.csv("Home_med.csv", sep=";"))[1:13,1:5]
+Imaging_data <-  data.frame(read.csv("Imaging_data.csv", sep=";"))[1:11,1:5]
+Labo <-  data.frame(read.csv("Labo.csv", sep=";"))[1:143,1:5]
+SiAndSympt <-  data.frame(read.csv("Si&Sympt.csv", sep=";"))[1:50,1:5]
+Treatment <-  data.frame(read.csv("Treatment.csv", sep=";"))[1:32,1:5]
+LifestyleAndDiet <-  data.frame(read.csv("Lifestyle&Diet.csv", sep=";"))[1:165,1:5]
+
+
+harmonised_data <- rbind(SiAndSympt,ComAndRF)
+harmonised_data <- rbind(harmonised_data,Treatment)
+harmonised_data <- rbind(harmonised_data,Dates)
+harmonised_data <- rbind(harmonised_data,Demographics)
+harmonised_data <- rbind(harmonised_data,Home_med)
+harmonised_data <- rbind(harmonised_data,Imaging_data)
+harmonised_data <- rbind(harmonised_data,Complications)
+harmonised_data <- rbind(harmonised_data,Labo)
+harmonised_data <- rbind(harmonised_data,LifestyleAndDiet)
+
+rm(list=c("SiAndSympt",
+          "Complications",
+          "ComAndRF",
+          "Dates",
+          "Demographics",
+          "Home_med",
+          "Imaging_data",
+          "Complications",
+          "Labo",
+          "LifestyleAndDiet"))
+
+noYesValues <- subset(harmonised_data, harmonised_data$Harmonised.data.format.unit == "No/Yes / missing" | harmonised_data$Harmonised.data.format.unit == "No/Yes / Missing")
+noYesValues <- noYesValues$Harmonised.variable.name
+noYesValues <- c(noYesValues,"CSXCOTAB","CSXCOTAG","IMDIT","RFXHIV_RFXAIDS", "SMXASAH", "CMXATH", "CMXNO","SMXFEA")
+
+categoric_vars = c("CMXATH", "CMXNO", "SMXASAH","CSXCOTAB","CSXCOTAG","IMDIT","RFXHIV_RFXAIDS","DMRGENDR", "DMRBORN", "DMRRETH1", "DMROCCU", "DMRHREDU", "DSXOS", "DSXHO", "DSXIC", "TRXAV","TRXRIB","TRXLR","TRXRM","TRXIA","TRXIB","TRXCH","TRXAB","TRXCS","TRXHEP","TRXAF","TRXCP","TRXOT","TRXECM","TRXIV","TRXNIV","TRXNO","TRXOX","TRXRR","TRXTR","TRXVA","TRXPE","TRXPV","TRXIT","TRXNMB","TRXAC","TRXINA","TRXIS","TRXIM","TRXVC","TRXVD","TRXZN",                         "CSXCOT","CSXCTR","SMXASAH","SMXFEA","SMXCOA","SMXSTA","SMXSBA","SMXRNA","SMXMYA","SMXARA","SMXCPA","SMXAPA","SMXINA","SMXNAA","SMXDIA","SMXFAA","SMXHEA","SMXCNA","SMXACA","SMXSLA","SMXTLA","SMXSYA","SMXWHA","SMXLYA","SMXANA","SMXIWA","SMXSRA","SMXBLA","CMXPRG","CMXCVD","CMXCMP","CMXHT","CMXDI","CMXCKD","CMXCLD","CMXCPD","CMXASM","CMXCND","CMXRHE","CMXCCI","CMXCBD","CMXDE","CMXPU","CMXST","CMXLY","CMXAP","RFXSM","RFXFSM","RFXOB","RFXTB","RFXIMD","RFXHIV","RFXAIDS","RFXUI","RFXHC","RFXONC","RFXMN",                         "HMRACI","HMRARB","HMRAHO","HMRNS","HMROS","HMRCS","HMRIS","HMRAV","HMRAB","HMRCOV","IMDXCT","IMDXCTCR","IMDXCTTE","IMDXCTAB","IMDXXR","IMDXPN",                         "COXRD","COXAR","COXPM","COXMOD","COXPT","COXEC","COXSH","COXIO","COXPE","COXST","COXDIC","COXRIO","COXKF","COXHF","COXBC")
+
+personalized <- c("DMRGENDR", "DMRRETH1", "DMROCCU", "DMRHREDU",  "DSXOS")
+
+is_number <- function(x){
+  res <- FALSE
+
+  if(length(x)!=0){
+    x <- str_replace(x,",",".")
+
+    aux <- as.numeric(x)
+
+    if(!is.na(aux))
+      res <- TRUE
+  }
+  return(res)
+}
+
+fixNonCategoric <- function(x){
+
+  if(!is_number(x)){
+    x <- ""
+  }
+  return(x)
+
+}
+
+getNumericValue <- function (x,colname) {
+  
+  
+  if(colname %in% noYesValues){
+    if(is.na(x))
+      x <- ""
+    else if (x == "No")
+      x <- 0
+    else if (x == "Yes")
+      x <- 1
+  }
+  
+  if(colname == "DMRGENDR"){
+    if(x == "Female")
+      x <- 1
+    else if (x == "Male")
+      x <- 0
+  }
+  
+  if(colname == "DSXOS"){
+    
+    if(is.na(x))
+      x<- ""
+    else if (x == "Missing")
+      x <- ""
+    else if (x == "Recovered")
+      x <- 0
+    else if (x == "Deceased")
+      x <- 1
+    else if (x == "Transferred")
+      x <- 2
+  }
+  
+  if(colname == "DMRRETH1"){
+    if(is.na(x))
+      x <- ""
+    else if(x =="Asian")
+      x <- 1
+    else if (x == "Black")
+      x <- 2
+    else if (x == "Hispanic")
+      x <- 3
+    else if (x == "White")
+      x <- 4
+    else if (x == "Multiracial")
+      x <- 5
+    else if (x == "Other")
+      x <- 6
+  }
+  
+  if(colname == "DMROCCU"){
+    if(is.na(x))
+      x <- ""
+    else if(x == "Unemployed")
+      x <- 1
+    else if (x == "Student")
+      x <- 2
+    else if (x == "Employed")
+      x <- 3
+    else if (x == "Self-employed")
+      x <- 4
+    else if (x == "Retired")
+      x <- 5
+  }
+  
+  if(colname == "DMRHREDU"){
+    if(is.na(x))
+      x <- ""
+    else if(x =="High School")
+      x <- 1
+    else if (x == "Bachelors")
+      x <- 2
+    else if (x == "Postgraduate")
+      x <- 3
+    else if (x == "Other")
+      x <- 4
+  }
+  
+  if(colname =="CSXCOT"){
+    if(is.na(x))
+      x <- ""
+    else if (x=="PCR" )
+      x <- 1
+    else if (x=="antigen" )
+      x <- 2
+    else if (x=="other" )
+      x <- 3
+    else
+      x <- ""
+  }
+  
+  
+  return(x)
+  
+}
+
+noNa <- function(x){
+  
+  if(is.na(x))
+    x <- ""
+  
+  return(x)
+}
+
+
+
+rm(newDf)
+
+newDf <- hospital
+
+names <- colnames(hospital)
+
+list_numeric <- c()
+
+for(k in 1:length(names)){
+  
+  mes <- paste(names[k], "_numeric",sep ="")
+  
+  if(names[k] %in% noYesValues){
+    list_numeric <- c(list_numeric,mes)
+  }else if(names[k] %in% personalized){
+    list_numeric <- c(list_numeric,mes)
+  }
+  
+}
+
+
+numericDf <- data.frame(matrix(NA, nrow = nrow(hospital), ncol = length(list_numeric)))
+colnames(numericDf) <-  list_numeric
+
+
+newDf<-bind_cols(newDf,numericDf)
+
+
+#newDf[,"DMRGENDR_numeric"] <- NA
+
+
+
+
+for (j in 1:ncol(hospital)){
+  
+  percentage <- trunc(j/ncol(hospital)*100)
+  mes <- paste(toString(percentage),"% completed", sep="")
+  print(mes)
+  
+  numeric_col <- paste(names[j], "_numeric", sep="")
+  
+  print(names[j])
+  
+  for(i in 1:nrow(hospital)){
+    
+    if(i %% 10000 == 0)
+    print(i)
+    
+    if(numeric_col %in% list_numeric){
+      newDf[i,numeric_col] <- getNumericValue(hospital[i,j],names[j])
+    }
+    
+    if(is.na(hospital[i,j]))
+      newDf[i,j] <- ""
+    
+  }
+}
+
+
+
+setwd("C:/Users/Victor/Documents/TFG/r-analytics-master/ressources/newRessources/Numeric_derived")
+setwd(("C:/Users/Victor/Documents/TFG/r-analytics-master/ressources/new_res_baskent/outpatient/clean/harmonized"))
+
+
+write.csv(x=newDf, file = "konya_outpatient.csv", row.names = FALSE)
+
+
+
+
+
+

survival_curve.R

+
+source("dependency_installer.R")
+source("required_folder_checker.R")
+source("argument_hasher.R")
+
+dep_list = c("survival", "lubridate", "survminer", "stringr", "DSI", "DSOpal", "DSLite", "fields", "hrbrthemes", "metafor", "ggplot2", "gridExtra", "data.table", "dsBaseClient")
+install_dependencies(dep_list)
+
+
+image_format <- ".png"
+
+args <- commandArgs(trailingOnly = TRUE)
+
+hospital_names <- c("HM","Princesa")
+project_names <- c("RESOURCE_GUIDE","RESOURCE_GUIDE")
+resource_names <- c("HM_rs", "Princesa_rs")
+urls <- c("https://192.168.1.50:8844","https://192.168.1.50:8844")
+users <- c("opal_admin","opal_admin")
+pass <- c("5f%R!&wfbUF*7gZ14mg","5f%R!&wfbUF*7gZ14mg")
+
+hospital_names <- hospital_names[2]
+project_names <- project_names[2]
+resource_names <- resource_names[2]
+urls <- urls[2]
+users <- users[2]
+pass <- pass[2]
+
+# project_names_o <- args[1]
+# project_names <- str_split(project_names_o, ";")[[1]]
+# 
+# resource_names_o <- args[2]
+# resource_names <- str_split(resource_names_o, ";")[[1]]
+# 
+# urls_o <- args[3]
+# urls <- str_split(urls_o, ";")[[1]]
+# 
+# users_o <- args[4]
+# users <- str_split(users_o, ";")[[1]]
+# 
+# pass_o <- args[5]
+# pass <- str_split(pass_o, ";")[[1]]
+# 
+# hospital_name <- args[6]
+# extra_filter <- args[7]
+
+
+
+
+json_output <- c()
+
+
+builder <- DSI::newDSLoginBuilder()
+
+url_ctr <- 0
+for(i in 1:length(urls)){
+  print(paste("Connecting to Server with URL:", urls[i], sep=" "))
+  builder$append(server = paste("study", url_ctr, sep=""), url = urls[i],
+                 user = users[i], password = pass[i],
+                 resource = paste(project_names[i], resource_names[i], sep="."),
+                 driver = "OpalDriver", options="list(ssl_verifyhost=0,ssl_verifypeer=0)")
+  
+  url_ctr <- url_ctr+1
+}
+
+logindata <- builder$build()
+connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D")
+
+datashield.assign.expr(connections, symbol = 'data', expr = quote(as.resource.data.frame(D)))
+datastructure_name <- "data"
+ds.colnames(x=datastructure_name, datasources= connections)
+
+data_dim <- ds.dim(x=datastructure_name, datasources= connections)
+data_dim_rows <- data_dim$`dimensions of data in combined studies`[1]
+data_dim_cols <- data_dim$`dimensions of data in combined studies`[2]
+
+
+get_reconstructed_population <- function(df, var, size){
+  
+  data_dim <- ds.dim(x=df, datasources= connections)
+  data_dim_rows <- data_dim[[length(data_dim)]][1]
+  data_dim_cols <- data_dim[[length(data_dim)]][2]
+  
+  quantile_data <- ds.quantileMean(x=paste(df, var, sep="$"), datasources = connections)
+  
+  est_min <- round(quantile_data[[1]])
+  est_q1 <- round(quantile_data[[3]])
+  est_median <- round(quantile_data[[4]])
+  est_q3 <- round(quantile_data[[5]])
+  est_max <- round(quantile_data[[7]])
+  
+  combined_mean <- quantile_data[[8]]
+  
+  nn <- size
+  quantiles <- c(est_min, est_q1, est_median, est_q3, est_max)
+  
+  set.seed(1)
+  reconstructed_population <- c(
+    runif(nn/4,quantiles[1],quantiles[2]),
+    runif(nn/4,quantiles[2],quantiles[3]),
+    runif(nn/4,quantiles[3],quantiles[4]),
+    runif(nn/4,quantiles[4],quantiles[5]))
+  
+  return(reconstructed_population)
+}
+
+ds.dataFrameSubset(df.name = datastructure_name, V1.name = "data$DSXOS_numeric", V2.name = "1", Boolean.operator = "==", newobj = "OutFilteredDEATH")
+ds.dataFrameSubset(df.name = datastructure_name, V1.name = "data$DSXOS_numeric", V2.name = "0", Boolean.operator = "==", newobj = "OutFilteredALIVE")
+
+data_dim_DEATH <- ds.dim(x="OutFilteredDEATH", datasources= connections)
+data_dim_DEATH <- data_dim_DEATH[[length(data_dim_DEATH)]][1]
+data_dim_ALIVE <- ds.dim(x="OutFilteredALIVE", datasources= connections)
+data_dim_ALIVE <- data_dim_ALIVE[[length(data_dim_ALIVE)]][1]
+
+reconstr_pop_time_outcome_death <- get_reconstructed_population("OutFilteredDEATH", "DATLGT", data_dim_DEATH)
+
+df_death <- data.frame(reconstr_pop_time_outcome_death)
+df_death["status"] = "death"
+colnames(df_death) = c("out_time", "status")
+
+
+reconstr_pop_time_outcome_alive <- get_reconstructed_population("OutFilteredALIVE", "DATLGT", data_dim_ALIVE)
+df_alive <- data.frame(reconstr_pop_time_outcome_alive)
+df_alive["status"] = "alive"
+colnames(df_alive) = c("out_time", "status")
+
+
+full_status_df <- rbind(df_alive, df_death)
+
+filtercol <- c()
+samplenum <- sample(0:100000, nrow(full_status_df), replace = T)
+for( i in 1:length(samplenum) ) {
+  
+  if(samplenum[i] %% 2 == 0){
+    filtercol[length(filtercol)+1] <- "MALE"
+  }else{
+    filtercol[length(filtercol)+1] <- "FEMALE"
+  }
+  
+}
+
+full_status_df[extra_filter] = filtercol
+full_status_df["status_surv"] = 1
+full_status_df[full_status_df$status == "alive" ,"status_surv"] = 0
+
+
+#filename <- paste0(hospital_name, "survival_curve", sep="")
+#filename <- paste(filename, "outcome", sep="_")
+#filename <- paste(filename, image_format, sep="")
+
+dir.create("./survAlberto", showWarnings = FALSE)
+setwd("./survAlberto")
+
+print("survival_curve.png")
+png("survival_curve.png", width = 750, height = 500)
+
+survplot <- ggsurvplot(
+  fit = survfit(Surv(out_time, status_surv) ~ 1, data = full_status_df), 
+  xlab = "Days", 
+  ylab = "Overall survival probability")
+
+survplot
+dev.off()
+
+
+
+
+datashield.logout(connections) 
+
+

table1_script.R

+
+
+rm(list=ls())
+
+setwd("C:/Users/victor/Documents/TFG/r-analytics-master")
+
+#Obtain the data from the codebook
+codebook <- read.csv("harmon.csv", sep = ";")
+codebook <- codebook[,c(1,3,4)]
+colnames(codebook) <- c("variable", "description", "unit")
+
+source("dependency_installer.R")
+source("connection_parameters_aux.R")
+source("necessary_functions_table1_v2_subset.R")
+
+dep_list = c("DSI","DSOpal","DSLite", "dsBaseClient")
+install_dependencies(dep_list)
+
+dir.create("./table_1", showWarnings = FALSE)
+setwd("./table_1")
+
+
+#Create the connection
+auxConnections <- connect()
+connections <- auxConnections[[1]]
+inp <- auxConnections[[2]]
+
+#Only do this if you want to subset the data for a specific value of a categoric variable
+apply_filters()
+
+#Select the variables to be analized (Add the ones you consider relevant and remove the ones that you do not)
+varToAnalize <- c("DMRGENDR","DMRAGEYR","DSXOS", "RFXSM", "TRXAV",  "CMXCVD", "RFXOB")
+varToAnalize <- c("DMRGENDR","DMRAGEYR")
+
+table1 <- obtain_table1(connections, inp, varToAnalize)
+
+#datashield.logout(connections)
+
+library(gridExtra)
+png("table1TFGFiltro.png", height = 30*nrow(table1), width = 150*ncol(table1))
+grid.table(table1)
+dev.off()

treatment_heatmap_script.r

+
+
+rm(list=ls())
+
+library("ggplot2")
+
+setwd("C:/Users/Victor/Documents/TFG/r-analytics-master/harmonised_data")
+
+Treatments <-  data.frame(read.csv("Treatment.csv", sep=";"))[1:32,1:5]
+descriptions <- Treatments[, c(1,3)]
+rownames(descriptions) <- descriptions$Harmonised.variable.name
+Treatments <- Treatments$Harmonised.variable.name
+
+setwd("C:/Users/victor/Documents/TFG/r-analytics-master")
+
+
+source("dependency_installer.R")
+source("connection_parameters.R")
+source("necessary_functions_treatments_heatmap.R")
+
+dep_list = c("DSI","DSOpal","DSLite", "ggplot2", "dsBaseClient")
+install_dependencies(dep_list)
+
+
+#Create the connection
+auxConnections <- connect()
+connections <- auxConnections[[1]]
+inp <- auxConnections[[2]]
+
+
+get_treatments_map(connections, inp)
+
+
+
+ds.colnames("data")

valid_variables_script.R

+rm(list=ls())
+
+setwd("C:/Users/Victor/Documents/TFG/r-analytics-master")
+
+source("required_folder_checker.R")
+source("argument_hasher.R")
+source("dependency_installer.R")
+
+# install.packages("https://cran.r-project.org/src/contrib/Archive/DSI/DSI_1.2.0.tar.gz", repos=NULL, type="source")
+# install.packages("https://cran.r-project.org/src/contrib/Archive/DSOpal/DSOpal_1.2.0.tar.gz", repos=NULL, type="source")
+# install.packages("https://cran.r-project.org/src/contrib/Archive/DSLite/DSLite_1.2.0.tar.gz", repos=NULL, type="source")
+# install.packages("https://cran.r-project.org/src/contrib/Archive/opalr/opalr_2.1.0.tar.gz", repos=NULL, type="source")
+
+
+dep_list = c("jsonlite", "stringr","DSI","DSOpal","DSLite", "fields", "metafor", "ggplot2", "gridExtra", "data.table", "dsBaseClient")
+install_dependencies(dep_list)
+
+#,"DSI","DSOpal","DSLite"
+
+setwd("C:/Users/victor/Documents/TFG/r-analytics-master")
+source("connection_parameters.R")
+source("necessary_functions_connection.R")
+
+
+setwd("C:/Users/Victor/Documents/TFG/r-analytics-master/harmonised_data")
+
+
+ComAndRF <- data.frame(read.csv("Com&RF.csv", sep=","))[1:64,1:5]
+Complications <- data.frame(read.csv("Complications.csv", sep=";"))[1:20,1:5]
+Dates <-  data.frame(read.csv("Dates.csv", sep=";"))[1:12,1:5]
+Demographics <-  data.frame(read.csv("Demographics.csv", sep=";"))[1:9,1:5]
+Home_med <-  data.frame(read.csv("Home_med.csv", sep=";"))[1:13,1:5]
+Imaging_data <-  data.frame(read.csv("Imaging_data.csv", sep=";"))[1:11,1:5]
+Labo <-  data.frame(read.csv("Labo.csv", sep=";"))[1:143,1:5]
+SiAndSympt <-  data.frame(read.csv("Si&Sympt.csv", sep=";"))[1:50,1:5]
+Treatment <-  data.frame(read.csv("Treatment.csv", sep=";"))[1:32,1:5]
+LifestyleAndDiet <-  data.frame(read.csv("Lifestyle&Diet.csv", sep=";"))[1:165,1:5]
+
+
+
+harmonised_data <- rbind(SiAndSympt,ComAndRF)
+harmonised_data <- rbind(harmonised_data,Treatment)
+harmonised_data <- rbind(harmonised_data,Dates)
+harmonised_data <- rbind(harmonised_data,Demographics)
+harmonised_data <- rbind(harmonised_data,Home_med)
+harmonised_data <- rbind(harmonised_data,Imaging_data)
+harmonised_data <- rbind(harmonised_data,Complications)
+harmonised_data <- rbind(harmonised_data,Labo)
+harmonised_data <- rbind(harmonised_data,LifestyleAndDiet)
+
+rm(list=c("SiAndSympt",
+          "Complications",
+          "ComAndRF",
+          "Dates",
+          "Demographics",
+          "Home_med",
+          "Imaging_data",
+          "Complications",
+          "Labo",
+          "LifestyleAndDiet"))
+
+categoric_vars = c("DMRGENDR", "DMRBORN", "DMRRETH1", "DMROCCU", "DMRHREDU", "DSXOS", "DSXHO", "DSXIC", "TRXAV","TRXRIB","TRXLR","TRXRM","TRXIA","TRXIB","TRXCH","TRXAB","TRXCS","TRXHEP","TRXAF","TRXCP","TRXOT","TRXECM","TRXIV","TRXNIV","TRXNO","TRXOX","TRXRR","TRXTR","TRXVA","TRXPE","TRXPV","TRXIT","TRXNMB","TRXAC","TRXINA","TRXIS","TRXIM","TRXVC","TRXVD","TRXZN",                         "CSXCOT","CSXCTR","SMXASAH","SMXFEA","SMXCOA","SMXSTA","SMXSBA","SMXRNA","SMXMYA","SMXARA","SMXCPA","SMXAPA","SMXINA","SMXNAA","SMXDIA","SMXFAA","SMXHEA","SMXCNA","SMXACA","SMXSLA","SMXTLA","SMXSYA","SMXWHA","SMXLYA","SMXANA","SMXIWA","SMXSRA","SMXBLA","CMXPRG","CMXCVD","CMXCMP","CMXHT","CMXDI","CMXCKD","CMXCLD","CMXCPD","CMXASM","CMXCND","CMXRHE","CMXCCI","CMXCBD","CMXDE","CMXPU","CMXST","CMXLY","CMXAP","RFXSM","RFXFSM","RFXOB","RFXTB","RFXIMD","RFXHIV","RFXAIDS","RFXUI","RFXHC","RFXONC","RFXMN",                         "HMRACI","HMRARB","HMRAHO","HMRNS","HMROS","HMRCS","HMRIS","HMRAV","HMRAB","HMRCOV","IMDXCT","IMDXCTCR","IMDXCTTE","IMDXCTAB","IMDXXR","IMDXPN",                         "COXRD","COXAR","COXPM","COXMOD","COXPT","COXEC","COXSH","COXIO","COXPE","COXST","COXDIC","COXRIO","COXKF","COXHF","COXBC")
+
+
+#----------------------------------------------------------------------------
+
+#Test if column names are valid
+check_column_names <- function(x){
+  
+  str_res <- "The column names:"
+  
+  for(i in 1:(nrow(data_colnames))){
+    if(!check_valid_name(data_colnames[i,1])){
+      str_res<- paste(str_res, data_colnames[i,1], sep=" ")
+    }
+  }
+  
+  str_res<- paste(str_res,"are not registered in the harmonized data codebook \n", sep=" ")
+  
+  return (str_res)
+  
+}
+
+#Test if a single variable name is valid
+check_valid_name <- function(x){
+  
+  valid <- FALSE
+  
+  aux <- as.data.frame(strsplit(x , split = "_"))
+  
+  if(aux[1,1] %in% harmonised_data$Harmonised.variable.name)
+    valid <- TRUE
+  
+  return (valid)
+  
+}
+
+valid_data_colnames <- function(x){
+  
+  valid_colnames = c()
+  
+  for(i in  1:(nrow(data_colnames))){
+    if(check_valid_name(data_colnames[i,1])){
+      valid_colnames = c(valid_colnames,data_colnames[i,1])
+    }
+  }
+  
+  
+  return(valid_colnames)
+}
+
+remove_space <- function(x){
+  searchString <- ' '
+  replacementString <- ''
+  res = sub(searchString,replacementString,x)
+  return(res)
+}
+
+remove_spaces_from_ds <- function(ds){
+  
+  res<- lapply(ds,remove_space )
+  
+  return(as.data.frame(res))
+  
+}
+
+is_number <- function(x){
+  res <- FALSE
+  
+  
+  if(length(x)!=0){
+    x <- str_replace(x,",",".")
+    
+    aux <- as.numeric(x)
+
+    
+    if(!is.na(aux))
+      res <- TRUE
+  }
+  
+  
+  return(res)
+  
+}
+
+check_values_not_categoric <- function(values, colname){
+  
+  valid_vals <- values
+  
+  possible_vals <- possible_values(colname)
+  
+  for(i in  1:length(values)){
+    
+    res<- FALSE
+    
+    value <- values[[i]]
+    
+    if(is_number(value)){
+      value <- str_replace(value,",",".")
+      value <- as.numeric(value)
+    }
+    
+    if(is.null(value)){
+      res <- TRUE
+    }
+      
+    else if( value == "NA" | value == "nan" | value == ".")
+      res <- TRUE
+    else{
+      
+      if(nrow(possible_vals) == 2 & (!grepl("DAT",colname, fixed=TRUE)) & colname !="CSXCTR"){
+        
+        if(colname=="LBXBEH" | colname=="LBXBEHn" | colname=="LBXBEM"){
+          lower = possible_vals[1,1][[1]]
+          higher = possible_vals[2,1][[1]]
+          
+        }else{
+          bounds <- as.data.frame(strsplit(possible_vals[1,1], '-'))
+          lowerAux <- str_replace(bounds [1,1],",",".")
+          higherAux <- str_replace(bounds [2,1],",",".")
+          lower <- as.numeric(remove_space(lowerAux))
+          higher <- as.numeric(remove_space(higherAux))
+        }
+        
+        
+        if ((value >= lower & value <= higher))
+          res <- TRUE
+      }
+      
+      if(nrow(possible_vals) == 3 | colname=="CSXCTR"){
+        if(value == 0 | value == 1)
+          res <- TRUE
+      }
+      
+      if(nrow(possible_vals) > 3){
+        
+        lower <- strtoi(remove_space(possible_vals[1,1]))
+        higher_b <- nrow(possible_vals)-1
+        higher <- strtoi(remove_space(possible_vals[higher_b,1]))
+        
+        if ((value >= lower & value <= higher))
+          res <- TRUE
+      }
+    }
+    
+    if(res == FALSE)
+      valid_vals[i] <- res
+    
+    
+  }
+  
+  return(valid_vals)
+}
+
+possible_values <- function(x){
+  
+  if(x=="LBXBEH" | x=="LBXBEHn" | x=="LBXBEM")
+    res <- t(as.data.frame(list(-20,20)))
+  
+  else{
+    
+    possible_value <- subset(harmonised_data,harmonised_data$Harmonised.variable.name==x)[1,5]
+    res <- strsplit(x=possible_value,split="/")
+  }
+  
+  return(as.data.frame(res))
+}
+
+possible_values_categoric <- function(x){
+  
+  possible_value <- subset(harmonised_data,harmonised_data$Harmonised.variable.name==x)[1,4]
+  res <- strsplit(x=possible_value,split="/")
+  
+  return(as.data.frame(res))
+}
+
+check_values_categoric <- function(values, colname){
+  
+  possible_vals <- possible_values_categoric(colname)
+  
+  res <- TRUE
+  
+  for(i in 1:length(values)){
+    if(!(values[[i]] %in% as.matrix(remove_spaces_from_ds(possible_vals)))){
+      res <- FALSE
+    }
+    
+  }
+  
+  return(res)
+  
+}
+
+
+get_values_from_quantiles <- function(x){
+  
+  data_summary <- ds.summary(x)
+  
+  low_quantile <- data_summary[[1]][3][[1]][[1]]
+  
+  high_quantile <- data_summary[[1]][3][[1]][[7]]
+  
+  return(list(low_quantile,high_quantile))
+  
+  
+}
+
+notify_error <- function(invalid_name_list,invalid_value_list,wrong_categoric, wrong_categoric_values, missing_numeric){
+  
+  res <- ""
+  
+  if(length(invalid_name_list) !=0){
+    res <- "There are invalid values in the numeric fields:"
+    
+    
+    for(i in 1:length(invalid_name_list)){
+      res <- paste(res, invalid_name_list[i], sep=" ")
+    }
+    
+    res <- paste(res, "\n", sep="")
+    
+    for(i in 1:length(invalid_name_list)){
+      res <- paste(res, error_message(invalid_name_list[i], invalid_value_list[[i]]), sep=" ")
+    }
+  }
+  
+  
+  if(length(wrong_categoric)!=0){
+    
+    res <- paste(res, "\n############################################################################ \n", sep="")
+    
+    res <- paste(res,"\nThe following categoric values are invalid:", sep=" ")
+    
+    for(i in 1:length(wrong_categoric)){
+      res <- paste(res, wrong_categoric[i], sep=" ")
+    }
+    
+    res <- paste(res, "\n", sep="")
+    
+    for(i in 1:length(wrong_categoric)){
+      res <- paste(res, error_message_categoric(wrong_categoric[i], wrong_categoric_values[[i]]), sep=" ")
+    }
+  }
+  
+  if(length(missing_numeric)!=0){
+    
+    res <- paste(res, "\n############################################################################ \n", sep="")
+    
+    res<- paste(res, "\nThe following fields are missing a numeric field:")
+    
+    for(i in 1:length(wrong_categoric)){
+      res <- paste(res, missing_numeric[i], sep=" ")
+    }
+  }
+  
+  res <- paste(res, "\n", sep="")
+  
+  
+  return(res)
+  
+}
+
+error_message_categoric <- function(colname, invalid_values){
+  
+  res<- "\nValues in the field"
+  res<- paste(res, colname, sep=" ")
+  res<- paste(res, "should be", sep=" ")
+  
+  range <- possible_values_categoric(colname)
+  
+  for(i in 1:nrow(range)){
+    res <- paste(res, remove_space(range[i,1]), sep=" ")
+  }
+  
+  
+  res<- paste(res, "\nBut values were:", sep=" ")
+  
+  for(j in 1:length(invalid_values)){
+    res<- paste(res, invalid_values[[j]], sep=" ")
+  }
+  
+  res<- paste(res, "\n\n", sep="")
+  
+  
+  return(res)
+  
+}
+
+error_message <- function(colname, invalid_values){
+  
+  res<- "\nValues in the field"
+  res<- paste(res, colname, sep=" ")
+  res<- paste(res, "should be", sep=" ")
+  
+  if(grepl("numeric", colname,fixed=TRUE))
+    new_colname <- strsplit(x=colname,split="_")[[1]][1]
+  else
+    new_colname <- colname
+  
+  range <- subset(harmonised_data, harmonised_data$Harmonised.variable.name == new_colname)
+  range <- range[5]
+  range <- as.data.frame(strsplit(range[1,1], '/'))
+  
+  #Range of values or null
+  if(nrow(range) == 2 & !grepl("DAT",colname, fixed=TRUE)){
+    bounds <- as.data.frame(strsplit(range[1,1], '-'))
+    lower <- remove_space(bounds [1,1])
+    higher <- remove_space(bounds [2,1])
+    res<- paste(res, "numbers between", sep=" ")
+    res<- paste(res, lower, sep=" ")
+    res<- paste(res, "and", sep=" ")
+    res<- paste(res, higher, sep=" ")
+    res<- paste(res, "(both included)", sep=" ")
+  }
+  
+  if(nrow(range) == 3){
+    res<- paste(res, "0 or 1", sep=" ")
+  }
+  
+  if(nrow(range) > 3){
+    lower <- strtoi(remove_space(range[1,1]))
+    higher_b <- nrow(range)-1
+    higher <- strtoi(remove_space(range[higher_b,1]))
+    res<- paste(res, "numbers between", sep=" ")
+    res<- paste(res, lower, sep=" ")
+    res<- paste(res, "and", sep=" ")
+    res<- paste(res, higher, sep=" ")
+    res<- paste(res, "(both included)", sep=" ")
+  }
+  
+  if(grepl("DAT",colname, fixed=TRUE)){
+    res<- paste(res, "dates with the following format: dd/mm/yyyy", sep=" ")
+  }
+  
+  
+  res<- paste(res, "\nBut values were:", sep=" ")
+  
+  for(j in 1:length(invalid_values)){
+    res<- paste(res, invalid_values[[j]], sep=" ")
+  }
+  
+  res<- paste(res, "\n", sep="")
+  
+  if(!is_number(invalid_values[[1]]))
+    res<- paste(res, "(It's missing a \"numeric\" field)", sep="")
+  
+  res<- paste(res, "\n", sep="")
+  
+  return(res)
+  
+}
+
+check_valid_values <- function(){
+  
+  invalid_name_list <- c()
+  cannot_analyse_list <- c()
+  invalid_values_list <- list()
+  wrong_categoric_values <- list()
+  wrong_categoric <- c()
+  missing_numeric <- c()
+  j<- 1
+  k <- 1
+  
+  for(i in  1:(nrow(valid_colnames))){
+    
+    data_table ="empty"
+    
+    if(!grepl("DMRBORN",valid_colnames[i,1], fixed=TRUE) & (!grepl("DAT",valid_colnames[i,1], fixed=TRUE)) & (!grepl("ISO",valid_colnames[i,1], fixed=TRUE))& (!grepl("BEF",valid_colnames[i,1], fixed=TRUE))){
+      
+      column <- "data$"
+      column <- paste(column, valid_colnames[i,1], sep="")
+      
+      tryCatch(
+        error = function(cnd) {
+          print("Unable to analyse data")
+          res <- FALSE
+        },
+        data_table <- as.data.frame(ds.table(column))
+      )
+      
+      if(data_table == "empty"){
+        
+        cannot_analyse_list <- c(cannot_analyse_list,valid_colnames[i,1])
+        
+      }else{
+        
+        
+        if (data_table[[1]] == "All studies failed for reasons identified below")
+          values <- get_values_from_quantiles(column)
+        else
+          values <- row.names(data_table)
+        
+        numeric_col<- paste(valid_colnames[i,1],"_numeric", sep="")
+        
+        if( valid_colnames[i,1] %in% categoric_vars ){
+          
+          #is_numeric <- grepl("numeric",valid_colnames[i,1], fixed=TRUE)
+          has_numeric <-  numeric_col %in% valid_colnames$`valid_data_colnames(data_colnames)`
+          
+          if(!has_numeric)
+            missing_numeric <- c(missing_numeric, valid_colnames[i,1])
+          
+          
+          if (data_table[[1]] == "All studies failed for reasons identified below"){
+            
+            cannot_analyse_list <- c(cannot_analyse_list,valid_colnames[i,1])
+            
+          }else  if(!check_values_categoric(values,valid_colnames[i,1])){
+            
+            print("Wrong categoric value:")
+            print(valid_colnames[i,1])
+            
+            wrong_categoric <- c(wrong_categoric, valid_colnames[i,1])
+            wrong_categoric_values[[k]] <- values
+            k <- k+1
+          }
+          
+          # if((!is_numeric & !has_numeric) | is_numeric)
+        }else{
+          
+          if(grepl("numeric", valid_colnames[i,1],fixed=TRUE))
+            new_colname <- strsplit(x=valid_colnames[i,1],split="_")[[1]][1]
+          else
+            new_colname <- valid_colnames[i,1]
+          
+          valid <- check_values_not_categoric(values, new_colname)
+          
+          if (FALSE %in% valid){
+            invalid_name_list <- c(invalid_name_list,valid_colnames[i,1])
+            invalid_values_list[[j]] <- values
+            j <- j+1
+          }
+          
+          
+          #print(valid_colnames[i,1])
+          #print(values)
+          
+        }#else
+        # print("This variable has a numeric version")
+      }
+      
+      
+    }
+  }
+  
+  missing_numeric
+  if(length(invalid_name_list)>0 | length(wrong_categoric)>0 | length(missing_numeric)>0){
+    res <- notify_error(invalid_name_list, invalid_values_list, wrong_categoric, wrong_categoric_values, missing_numeric)
+  }else{
+    res <- "All values are valid \n"
+  }
+  
+  if(length(cannot_analyse_list)>0){
+    res <- paste(res, "\n############################################################################ \n", sep="")
+    
+    res <- paste(res, notify_unable_analyse(cannot_analyse_list), sep="\n" )
+  }
+    
+  
+  
+  
+  return(res)
+  
+}
+
+notify_unable_analyse <- function(x){
+  
+  res <- "\nCould not obtain data from the fields:"
+  
+  for(i in 1:length(x)){
+    res <- paste(res, x[i], sep=" ")
+  }
+  
+  return (res)
+  
+  
+}
+
+auxConnections <- connect()
+connections <- auxConnections[[1]]
+inp <- auxConnections[[2]]
+
+#Conexión a la base de datos
+
+ds.dim("data", datasources = connections)
+ds.colnames("data")
+
+#----------------------------------------------------------------------------
+
+#Check valid column names
+datastructure_name <- "data"
+data_colnames <- ds.colnames(x=datastructure_name, datasources= connections)
+
+data_colnames <- as.data.frame(data_colnames)
+
+check_valid_columns <- check_column_names(data_colnames)
+
+valid_colnames <- as.data.frame(valid_data_colnames(data_colnames))
+
+
+
+#possible_values("CSXCTR")
+result <- ""
+result<-check_valid_values()
+print(check_valid_columns)
+datashield.logout(connections) 
+cat(result)
+
+
+
+# ds.dataFrameSubset(df.name = "data", V1.name = "data$DMXWT", "400" , Boolean.operator = '>', newobj = "columna")
+# # 
+# ds.summary("columna$DMXWT")
+# ds.dim("columna$DMXWT")
+# ds.table("columna$DMXWT")
+
+file_name<- paste(hospital_name,"_invalid_values.txt", sep="")
+
+#ds.heatmapPlot("data$LBDSALSIA", "data$RFXHC_numeric",type="combine", datasources = connections)
+
+
+#setwd("C:/Users/victor/Desktop/TFG/r-analytics-master/invalid_values")
+dir.create("../invalid_values", showWarnings = FALSE)
+setwd("../invalid_values")
+
+
+cat(check_valid_columns,file=file_name,sep="\n")
+cat(result,file=file_name,append=TRUE)
+
+datashield.logout(connections) 
+