extras/TestCode.R
In OHDSI/FeatureExtraction: Generating Features for a Cohort
library(FeatureExtraction)
options(andromedaTempFolder = "s:/andromedaTemp")
# Pdw ---------------------------------------------------------------------
connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = "pdw",
server = keyring::key_get("pdwServer"),
port = keyring::key_get("pdwPort"))
cdmDatabaseSchema <- "CDM_IBM_MDCR_V1192.dbo"
cohortDatabaseSchema <- "scratch.dbo"
cohortTable <- "ohdsi_celecoxib_prediction"
oracleTempSchema <- NULL
cdmVersion <- "5"
# PostgreSQL --------------------------------------------------------------
dbms <- "postgresql"
user <- "postgres"
pw <- Sys.getenv("pwPostgres")
server <- "localhost/ohdsi"
connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = dbms,
server = server,
user = user,
password = pw)
cdmDatabaseSchema <- "cdm_synpuf"
cohortDatabaseSchema <- "scratch"
cohortTable <- "ohdsi_celecoxib_prediction"
oracleTempSchema <- NULL
# RedShift ---------------------------------
dbms <- "redshift"
user <- Sys.getenv("redShiftUser")
pw <- Sys.getenv("redShiftPassword")
cdmDatabaseSchema <- "cdm"
cohortDatabaseSchema <- "scratch_mschuemi"
cohortTable <- "informed_priors"
oracleTempSchema <- NULL
connectionString <- Sys.getenv("mdcrRedShiftConnectionString")
connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = dbms,
connectionString = connectionString,
user = user,
password = pw)
cdmVersion <- "5"
outputFolder <- "S:/temp/CelecoxibPredictiveModelsPg"
# Popular drug: 1118084
# Medium drug: 945286
# Rare drug: 1125443
conn <- DatabaseConnector::connect(connectionDetails)
### Populate cohort table ###
sql <- "IF OBJECT_ID('@cohort_database_schema.@cohort_table', 'U') IS NOT NULL
DROP TABLE @cohort_database_schema.@cohort_table;
SELECT drug_concept_id AS cohort_definition_id, person_id AS subject_id, drug_era_start_date AS cohort_start_date, drug_era_end_date AS cohort_end_date, ROW_NUMBER() OVER (ORDER BY person_id, drug_era_start_date) AS row_id
INTO @cohort_database_schema.@cohort_table FROM @cdm_database_schema.drug_era
WHERE drug_concept_id IN (740910, 945286);"
sql <- SqlRender::render(sql,
cdm_database_schema = cdmDatabaseSchema,
cohort_database_schema = cohortDatabaseSchema,
cohort_table = cohortTable)
sql <- SqlRender::translate(sql, targetDialect = connectionDetails$dbms)
DatabaseConnector::executeSql(conn, sql)
sql <- "SELECT cohort_definition_id, COUNT(*) FROM @cohort_database_schema.@cohort_table GROUP BY cohort_definition_id;"
sql <- SqlRender::render(sql,
cohort_database_schema = cohortDatabaseSchema,
cohort_table = cohortTable)
sql <- SqlRender::translate(sql, targetDialect = connectionDetails$dbms)
DatabaseConnector::querySql(conn, sql)
DatabaseConnector::disconnect(conn)
### Create covariateSettings ###
celecoxibDrugs <- 1118084
# x <- c(252351201, 2514584502, 2615790602, 440424201, 2212134701, 433950202, 40163038301, 42902283302, 380411101, 19115253302, 141508101, 2109262501, 440870101, 40175400301, 2212420701, 253321102, 2616540601, 40490966204, 198249204, 19003087302, 77069102, 259848101, 1201620402, 19035388301, 444084201, 2617130602, 40223423301, 4184252201, 2212996701, 40234152302, 19125485301, 21602471403, 4060101801, 442313204, 439502101, 1326303402, 440920202, 19040158302, 2414379501, 2313884502, 4204187204, 2721698801, 739209301, 376225102, 42742566701, 43021157201, 314131101, 2005962502, 133298201, 4157607204)
settings <- createCovariateSettings(useDemographicsGender = TRUE,
useDemographicsAge = TRUE,
useDemographicsAgeGroup = TRUE,
useDemographicsRace = TRUE,
useDemographicsEthnicity = TRUE,
useDemographicsIndexYear = TRUE,
useDemographicsIndexMonth = TRUE,
useDemographicsPriorObservationTime = TRUE,
useDemographicsPostObservationTime = TRUE,
useDemographicsTimeInCohort = TRUE,
useConditionOccurrenceAnyTimePrior = TRUE,
useConditionOccurrenceLongTerm = TRUE,
useConditionOccurrenceMediumTerm = TRUE,
useConditionOccurrenceShortTerm = TRUE,
useConditionEraAnyTimePrior = TRUE,
useConditionEraLongTerm = TRUE,
useConditionEraMediumTerm = TRUE,
useConditionEraShortTerm = TRUE,
useConditionEraOverlapping = TRUE,
useConditionEraStartLongTerm = TRUE,
useConditionEraStartMediumTerm = TRUE,
useConditionEraStartShortTerm = TRUE,
useConditionGroupEraAnyTimePrior = TRUE,
useConditionGroupEraLongTerm = TRUE,
useConditionGroupEraMediumTerm = TRUE,
useConditionGroupEraShortTerm = TRUE,
useConditionGroupEraOverlapping = TRUE,
useConditionGroupEraStartLongTerm = TRUE,
useConditionGroupEraStartMediumTerm = TRUE,
useConditionGroupEraStartShortTerm = TRUE,
useConditionOccurrencePrimaryInpatientLongTerm = TRUE,
useDrugExposureAnyTimePrior = TRUE,
useDrugExposureLongTerm = TRUE,
useDrugExposureMediumTerm = TRUE,
useDrugExposureShortTerm = TRUE,
useDrugEraAnyTimePrior = TRUE,
useDrugEraLongTerm = TRUE,
useDrugEraMediumTerm = TRUE,
useDrugEraShortTerm = TRUE,
useDrugEraOverlapping = TRUE,
useDrugEraStartLongTerm = TRUE,
useDrugEraStartMediumTerm = TRUE,
useDrugEraStartShortTerm = TRUE,
useDrugGroupEraAnyTimePrior = TRUE,
useDrugGroupEraLongTerm = TRUE,
useDrugGroupEraMediumTerm = TRUE,
useDrugGroupEraShortTerm = TRUE,
useDrugGroupEraOverlapping = TRUE,
useDrugGroupEraStartLongTerm = TRUE,
useDrugGroupEraStartMediumTerm = TRUE,
useDrugGroupEraStartShortTerm = TRUE,
useProcedureOccurrenceAnyTimePrior = TRUE,
useProcedureOccurrenceLongTerm = TRUE,
useProcedureOccurrenceMediumTerm = TRUE,
useProcedureOccurrenceShortTerm = TRUE,
useDeviceExposureAnyTimePrior = TRUE,
useDeviceExposureLongTerm = TRUE,
useDeviceExposureMediumTerm = TRUE,
useDeviceExposureShortTerm = TRUE,
useMeasurementAnyTimePrior = TRUE,
useMeasurementLongTerm = TRUE,
useMeasurementMediumTerm = TRUE,
useMeasurementShortTerm = TRUE,
useMeasurementValueAnyTimePrior = TRUE,
useMeasurementValueLongTerm = TRUE,
useMeasurementValueMediumTerm = TRUE,
useMeasurementValueShortTerm = TRUE,
useMeasurementRangeGroupAnyTimePrior = TRUE,
useMeasurementRangeGroupLongTerm = TRUE,
useMeasurementRangeGroupMediumTerm = TRUE,
useMeasurementRangeGroupShortTerm = TRUE,
useObservationAnyTimePrior = TRUE,
useObservationLongTerm = TRUE,
useObservationMediumTerm = TRUE,
useObservationShortTerm = TRUE,
useCharlsonIndex = TRUE,
useDcsi = TRUE,
useChads2 = TRUE,
useChads2Vasc = TRUE,
useDistinctConditionCountLongTerm = TRUE,
useDistinctConditionCountMediumTerm = TRUE,
useDistinctConditionCountShortTerm = TRUE,
useDistinctIngredientCountLongTerm = TRUE,
useDistinctIngredientCountMediumTerm = TRUE,
useDistinctIngredientCountShortTerm = TRUE,
useDistinctProcedureCountLongTerm = TRUE,
useDistinctProcedureCountMediumTerm = TRUE,
useDistinctProcedureCountShortTerm = TRUE,
useDistinctMeasurementCountLongTerm = TRUE,
useDistinctMeasurementCountMediumTerm = TRUE,
useDistinctMeasurementCountShortTerm = TRUE,
useVisitCountLongTerm = TRUE,
useVisitCountMediumTerm = TRUE,
useVisitCountShortTerm = TRUE,
longTermStartDays = -365,
mediumTermStartDays = -180,
shortTermStartDays = -30,
endDays = 0,
includedCovariateConceptIds = c(),
addDescendantsToInclude = FALSE,
excludedCovariateConceptIds = c(),
addDescendantsToExclude = FALSE,
includedCovariateIds = c())
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(740910, 945286),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = settings,
aggregated = TRUE)
covs$covariateRef %>%
filter(covariateId > 15000)
covs$covariates[covs$covariates$covariateId == 4329847210, ]
# Exclude: sum = 2.883000e+03
# Not exclude: sum = 2.883000e+03
# Exclude after fix: sum = 2.538000e+03
system.time(
saveCovariateData(covs, "s:/temp/covsHuge.zip")
)
saveCovariateData(covs, "s:/temp/covsAgg")
covariateData <- loadCovariateData("s:/temp/covsHuge.zip")
covariateData
print(covariateData)
summary(covariateData)
tidyCovs <- tidyCovariateData(covariateData)
tempCovariateData <- loadCovariateData("c:/temp/covs2.zip")
covs2 <- aggregateCovariates(covs)
settings2 <- createCovariateSettings(useDemographicsGender = TRUE)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(1),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = list(settings, settings2),
aggregated = TRUE)
print(covs)
summary(covs)
print(covs$covariateRef, n = 100)
# Temporal covariates -----------------------------------------------
covariateSettings <- createTemporalCovariateSettings(useDemographicsGender = TRUE,
useMeasurementValue = TRUE)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(1),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = covariateSettings,
aggregated = TRUE)
saveCovariateData(covs, "c:/temp/tempCovs")
covariateData <- loadCovariateData("c:/temp/tempCovs")
tidyCovs <- tidyCovariateData(covariateData)
agg <- aggregateCovariates(covs)
saveCovariateData(tidyCovs, "c:/temp/tidyCovs.zip")
# Aggregation ---------------------------------------------------------------------------------
covariateSettings <- createCovariateSettings(useDemographicsAge = TRUE,
= TRUE)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(1),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = covariateSettings,
aggregated = FALSE)
saveCovariateData(covs, "c:/temp/unaggregatedCovs.zip")
aggCovs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(1),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = covariateSettings,
aggregated = TRUE)
saveCovariateData(aggCovs, "c:/temp/aggregatedCovs.zip")
covariateData <- loadCovariateData("c:/temp/unaggregatedCovs.zip")
aggCovs2 <- aggregateCovariates(covariateData)
aggCovs <- loadCovariateData("c:/temp/aggregatedCovs.zip")
aggCovs$covariates %>% collect()
aggCovs2$covariates %>% collect()
aggCovs$covariatesContinuous %>% collect()
aggCovs2$covariatesContinuous %>% collect()
# Storing data on server -----------------------------------------------------------------------
settings <- createCovariateSettings(useDemographicsGender = TRUE,
useDemographicsAgeGroup = TRUE)
conn <- DatabaseConnector::connect(connectionDetails)
getDbDefaultCovariateData(connection = conn,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortTable = paste(cohortDatabaseSchema, cohortTable, sep = "."),
cohortIds = c(-1),
rowIdField = "row_id",
covariateSettings = settings,
targetCovariateTable = "#my_covs",
targetCovariateRefTable = "#my_cov_ref",
targetAnalysisRefTable = "#my_analysis_ref",
aggregated = FALSE)
querySql(conn, "SELECT TOP 100 * FROM #my_covs")
querySql(conn, "SELECT TOP 100 * FROM #my_cov_ref")
querySql(conn, "SELECT TOP 100 * FROM #my_analysis_ref")
DatabaseConnector::disconnect(conn)
covariateSettings <- createDefaultCovariateSettings()
covariateSettings <- FeatureExtraction::createTemporalCovariateSettings(useDemographicsGender = TRUE,
useDemographicsIndexYear = FALSE,
useDemographicsAge = FALSE,
useDemographicsIndexMonth = FALSE,
useConditionOccurrence = TRUE,
useConditionEraStart = FALSE,
useConditionEraOverlap = FALSE,
useConditionEraGroupStart = FALSE,
useConditionEraGroupOverlap = FALSE,
useDrugExposure = FALSE,
useDrugEraStart = FALSE,
useDrugEraOverlap = FALSE,
useDrugEraGroupStart = FALSE,
useDrugEraGroupOverlap = FALSE,
useProcedureOccurrence = FALSE,
useDeviceExposure = FALSE,
useMeasurement = FALSE,
useObservation = FALSE,
useCharlsonIndex = FALSE,
temporalStartDays = -365:-1,
temporalEndDays = -365:-1,
includedCovariateConceptIds = c(),
addDescendantsToInclude = FALSE,
excludedCovariateConceptIds = c(),
addDescendantsToExclude = FALSE,
includedCovariateIds = c())
# covariateSettings <- convertPrespecSettingsToDetailedSettings(covariateSettings)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = 1,
cohortTableIsTemp = FALSE,
covariateSettings = covariateSettings,
aggregated = TRUE)
analysisDetails <- createAnalysisDetails(analysisId = 1,
sqlFileName = "DemographicsGender.sql",
parameters = list(analysisId = 1,
analysisName = "Gender",
domainId = "Demographics"),
includedCovariateConceptIds = c(),
addDescendantsToInclude = FALSE,
excludedCovariateConceptIds = c(),
addDescendantsToExclude = FALSE,
includedCovariateIds = c())
covariateSettings <- createDetailedCovariateSettings(analyses = list(analysisDetails))
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = 1,
cohortTableIsTemp = FALSE,
covariateSettings = covariateSettings,
aggregated = TRUE)
# Table 1 -----------------------------------------------------------------
settings <- createCovariateSettings(useDemographicsAgeGroup = TRUE,
useDemographicsGender = TRUE,
useDemographicsEthnicity = TRUE,
useConditionGroupEraLongTerm = TRUE,
useDrugGroupEraLongTerm = TRUE,
useCharlsonIndex = TRUE,
useChads2Vasc = TRUE,
useDcsi = TRUE)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(1),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = settings,
aggregated = TRUE)
saveCovariateData(covs, "c:/temp/covsTable1")
covariateData1 <- loadCovariateData("c:/temp/covsTable1")
tables <- createTable1(covariateData1, output = "one column", showCounts = T, showPercent = F)
tables <- createTable1(covariateData1, output = "two columns", showCounts = T, showPercent = F)
tables <- createTable1(covariateData1, covariateData1, output = "one column", showCounts = F, showPercent = T)
tables <- createTable1(covariateData1, covariateData1, output = "two columns", showCounts = T, showPercent = F)
write.csv(tables$part1, "c:/temp/table1Part1.csv", row.names = FALSE)
write.csv(tables$part2, "c:/temp/table1Part2.csv", row.names = FALSE)
print(tables$part1)
covariateData1 <- covariateData
covariateData2 <- covariateData
# Eunomia ------------------------------------------------------
library(FeatureExtraction)
library(Eunomia)
options(andromedaTempFolder = "c:/andromedaTemp")
connectionDetails <- getEunomiaConnectionDetails()
createCohorts(connectionDetails)
settings <- createCovariateSettings(useDemographicsGender = TRUE,
useDemographicsAge = FALSE,
useDemographicsAgeGroup = FALSE,
useDemographicsRace = FALSE,
useDemographicsEthnicity = FALSE,
useDemographicsIndexYear = FALSE,
useDemographicsIndexMonth = FALSE,
useDemographicsPriorObservationTime = FALSE,
useDemographicsPostObservationTime = FALSE,
useDemographicsTimeInCohort = FALSE,
useConditionOccurrenceAnyTimePrior = FALSE,
useConditionOccurrenceLongTerm = FALSE,
useConditionOccurrenceMediumTerm = FALSE,
useConditionOccurrenceShortTerm = FALSE,
useConditionEraAnyTimePrior = FALSE,
useConditionEraLongTerm = FALSE,
useConditionEraMediumTerm = FALSE,
useConditionEraShortTerm = FALSE,
useConditionEraOverlapping = FALSE,
useConditionEraStartLongTerm = FALSE,
useConditionEraStartMediumTerm = FALSE,
useConditionEraStartShortTerm = FALSE,
useConditionGroupEraAnyTimePrior = FALSE,
useConditionGroupEraLongTerm = FALSE,
useConditionGroupEraMediumTerm = FALSE,
useConditionGroupEraShortTerm = FALSE,
useConditionGroupEraOverlapping = FALSE,
useConditionGroupEraStartLongTerm = FALSE,
useConditionGroupEraStartMediumTerm = FALSE,
useConditionGroupEraStartShortTerm = FALSE,
useConditionOccurrencePrimaryInpatientLongTerm = FALSE,
useDrugExposureAnyTimePrior = FALSE,
useDrugExposureLongTerm = FALSE,
useDrugExposureMediumTerm = FALSE,
useDrugExposureShortTerm = FALSE,
useDrugEraAnyTimePrior = FALSE,
useDrugEraLongTerm = FALSE,
useDrugEraMediumTerm = FALSE,
useDrugEraShortTerm = FALSE,
useDrugEraOverlapping = FALSE,
useDrugEraStartLongTerm = FALSE,
useDrugEraStartMediumTerm = FALSE,
useDrugEraStartShortTerm = FALSE,
useDrugGroupEraAnyTimePrior = FALSE,
useDrugGroupEraLongTerm = FALSE,
useDrugGroupEraMediumTerm = FALSE,
useDrugGroupEraShortTerm = FALSE,
useDrugGroupEraOverlapping = FALSE,
useDrugGroupEraStartLongTerm = FALSE,
useDrugGroupEraStartMediumTerm = FALSE,
useDrugGroupEraStartShortTerm = FALSE,
useProcedureOccurrenceAnyTimePrior = FALSE,
useProcedureOccurrenceLongTerm = FALSE,
useProcedureOccurrenceMediumTerm = FALSE,
useProcedureOccurrenceShortTerm = FALSE,
useDeviceExposureAnyTimePrior = FALSE,
useDeviceExposureLongTerm = FALSE,
useDeviceExposureMediumTerm = FALSE,
useDeviceExposureShortTerm = FALSE,
useMeasurementAnyTimePrior = FALSE,
useMeasurementLongTerm = FALSE,
useMeasurementMediumTerm = FALSE,
useMeasurementShortTerm = FALSE,
useMeasurementValueAnyTimePrior = FALSE,
useMeasurementValueLongTerm = FALSE,
useMeasurementValueMediumTerm = FALSE,
useMeasurementValueShortTerm = FALSE,
useMeasurementRangeGroupAnyTimePrior = FALSE,
useMeasurementRangeGroupLongTerm = FALSE,
useMeasurementRangeGroupMediumTerm = FALSE,
useMeasurementRangeGroupShortTerm = FALSE,
useObservationAnyTimePrior = FALSE,
useObservationLongTerm = FALSE,
useObservationMediumTerm = FALSE,
useObservationShortTerm = FALSE,
useCharlsonIndex = FALSE,
useDcsi = FALSE,
useChads2 = FALSE,
useChads2Vasc = FALSE,
useDistinctConditionCountLongTerm = FALSE,
useDistinctConditionCountMediumTerm = FALSE,
useDistinctConditionCountShortTerm = FALSE,
useDistinctIngredientCountLongTerm = FALSE,
useDistinctIngredientCountMediumTerm = FALSE,
useDistinctIngredientCountShortTerm = FALSE,
useDistinctProcedureCountLongTerm = FALSE,
useDistinctProcedureCountMediumTerm = FALSE,
useDistinctProcedureCountShortTerm = FALSE,
useDistinctMeasurementCountLongTerm = FALSE,
useDistinctMeasurementCountMediumTerm = FALSE,
useDistinctMeasurementCountShortTerm = FALSE,
useVisitCountLongTerm = FALSE,
useVisitCountMediumTerm = FALSE,
useVisitCountShortTerm = FALSE,
longTermStartDays = -365,
mediumTermStartDays = -180,
shortTermStartDays = -30,
endDays = 0,
includedCovariateConceptIds = c(),
addDescendantsToInclude = FALSE,
excludedCovariateConceptIds = c(),
addDescendantsToExclude = FALSE,
includedCovariateIds = c())
covs <- getDbCovariateData(connectionDetails = connectionDetails,
cdmDatabaseSchema = "main",
cohortDatabaseSchema = "main",
cohortTable = "cohort",
cohortIds = c(2^34),
covariateSettings = settings,
aggregated = TRUE)
collect(covs$covariatesContinuous)
collect(covs$covariates)
collect(covs$covariateRef) %>% filter(covariateId %% 1000 == 3)
x <- collect(covs$covariateRef)
View(x)
settings <- createTemporalCovariateSettings(useDemographicsGender = TRUE,
useDemographicsAge = TRUE,
useDemographicsAgeGroup = TRUE,
useDemographicsRace = TRUE,
useDemographicsEthnicity = TRUE,
useDemographicsIndexYear = TRUE,
useDemographicsIndexMonth = TRUE,
useDemographicsPriorObservationTime = TRUE,
useDemographicsPostObservationTime = TRUE,
useDemographicsTimeInCohort = TRUE,
useDemographicsIndexYearMonth = TRUE,
useConditionOccurrence = TRUE,
useConditionOccurrencePrimaryInpatient = TRUE,
useConditionEraStart = TRUE,
useConditionEraOverlap = TRUE,
useConditionEraGroupStart = TRUE,
useConditionEraGroupOverlap = TRUE,
useDrugExposure = TRUE,
useDrugEraStart = TRUE,
useDrugEraOverlap = TRUE,
useDrugEraGroupStart = TRUE,
useDrugEraGroupOverlap = TRUE,
useProcedureOccurrence = TRUE,
useDeviceExposure = TRUE,
useMeasurement = TRUE,
useMeasurementValue = TRUE,
useMeasurementRangeGroup = TRUE,
useObservation = TRUE,
useCharlsonIndex = TRUE,
useDcsi = TRUE,
useChads2 = TRUE,
useChads2Vasc = TRUE,
useHfrs = TRUE,
useDistinctConditionCount = TRUE,
useDistinctIngredientCount = TRUE,
useDistinctProcedureCount = TRUE,
useDistinctMeasurementCount = TRUE,
useDistinctObservationCount = TRUE,
useVisitCount = TRUE,
useVisitConceptCount = TRUE)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
cdmDatabaseSchema = "main",
cohortDatabaseSchema = "main",
cohortTable = "cohort",
cohortIds = c(1,2),
covariateSettings = settings,
aggregated = TRUE)
connection <- connect(connectionDetails)
querySql(connection, "SELECT * FROM main.cohort LIMIT 100")
OHDSI/FeatureExtraction documentation built on June 9, 2025, 10:56 a.m.
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library(FeatureExtraction)
options(andromedaTempFolder = "s:/andromedaTemp")
# Pdw ---------------------------------------------------------------------
connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = "pdw",
server = keyring::key_get("pdwServer"),
port = keyring::key_get("pdwPort"))
cdmDatabaseSchema <- "CDM_IBM_MDCR_V1192.dbo"
cohortDatabaseSchema <- "scratch.dbo"
cohortTable <- "ohdsi_celecoxib_prediction"
oracleTempSchema <- NULL
cdmVersion <- "5"
# PostgreSQL --------------------------------------------------------------
dbms <- "postgresql"
user <- "postgres"
pw <- Sys.getenv("pwPostgres")
server <- "localhost/ohdsi"
connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = dbms,
server = server,
user = user,
password = pw)
cdmDatabaseSchema <- "cdm_synpuf"
cohortDatabaseSchema <- "scratch"
cohortTable <- "ohdsi_celecoxib_prediction"
oracleTempSchema <- NULL
# RedShift ---------------------------------
dbms <- "redshift"
user <- Sys.getenv("redShiftUser")
pw <- Sys.getenv("redShiftPassword")
cdmDatabaseSchema <- "cdm"
cohortDatabaseSchema <- "scratch_mschuemi"
cohortTable <- "informed_priors"
oracleTempSchema <- NULL
connectionString <- Sys.getenv("mdcrRedShiftConnectionString")
connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = dbms,
connectionString = connectionString,
user = user,
password = pw)
cdmVersion <- "5"
outputFolder <- "S:/temp/CelecoxibPredictiveModelsPg"
# Popular drug: 1118084
# Medium drug: 945286
# Rare drug: 1125443
conn <- DatabaseConnector::connect(connectionDetails)
### Populate cohort table ###
sql <- "IF OBJECT_ID('@cohort_database_schema.@cohort_table', 'U') IS NOT NULL
DROP TABLE @cohort_database_schema.@cohort_table;
SELECT drug_concept_id AS cohort_definition_id, person_id AS subject_id, drug_era_start_date AS cohort_start_date, drug_era_end_date AS cohort_end_date, ROW_NUMBER() OVER (ORDER BY person_id, drug_era_start_date) AS row_id
INTO @cohort_database_schema.@cohort_table FROM @cdm_database_schema.drug_era
WHERE drug_concept_id IN (740910, 945286);"
sql <- SqlRender::render(sql,
cdm_database_schema = cdmDatabaseSchema,
cohort_database_schema = cohortDatabaseSchema,
cohort_table = cohortTable)
sql <- SqlRender::translate(sql, targetDialect = connectionDetails$dbms)
DatabaseConnector::executeSql(conn, sql)
sql <- "SELECT cohort_definition_id, COUNT(*) FROM @cohort_database_schema.@cohort_table GROUP BY cohort_definition_id;"
sql <- SqlRender::render(sql,
cohort_database_schema = cohortDatabaseSchema,
cohort_table = cohortTable)
sql <- SqlRender::translate(sql, targetDialect = connectionDetails$dbms)
DatabaseConnector::querySql(conn, sql)
DatabaseConnector::disconnect(conn)
### Create covariateSettings ###
celecoxibDrugs <- 1118084
# x <- c(252351201, 2514584502, 2615790602, 440424201, 2212134701, 433950202, 40163038301, 42902283302, 380411101, 19115253302, 141508101, 2109262501, 440870101, 40175400301, 2212420701, 253321102, 2616540601, 40490966204, 198249204, 19003087302, 77069102, 259848101, 1201620402, 19035388301, 444084201, 2617130602, 40223423301, 4184252201, 2212996701, 40234152302, 19125485301, 21602471403, 4060101801, 442313204, 439502101, 1326303402, 440920202, 19040158302, 2414379501, 2313884502, 4204187204, 2721698801, 739209301, 376225102, 42742566701, 43021157201, 314131101, 2005962502, 133298201, 4157607204)
settings <- createCovariateSettings(useDemographicsGender = TRUE,
useDemographicsAge = TRUE,
useDemographicsAgeGroup = TRUE,
useDemographicsRace = TRUE,
useDemographicsEthnicity = TRUE,
useDemographicsIndexYear = TRUE,
useDemographicsIndexMonth = TRUE,
useDemographicsPriorObservationTime = TRUE,
useDemographicsPostObservationTime = TRUE,
useDemographicsTimeInCohort = TRUE,
useConditionOccurrenceAnyTimePrior = TRUE,
useConditionOccurrenceLongTerm = TRUE,
useConditionOccurrenceMediumTerm = TRUE,
useConditionOccurrenceShortTerm = TRUE,
useConditionEraAnyTimePrior = TRUE,
useConditionEraLongTerm = TRUE,
useConditionEraMediumTerm = TRUE,
useConditionEraShortTerm = TRUE,
useConditionEraOverlapping = TRUE,
useConditionEraStartLongTerm = TRUE,
useConditionEraStartMediumTerm = TRUE,
useConditionEraStartShortTerm = TRUE,
useConditionGroupEraAnyTimePrior = TRUE,
useConditionGroupEraLongTerm = TRUE,
useConditionGroupEraMediumTerm = TRUE,
useConditionGroupEraShortTerm = TRUE,
useConditionGroupEraOverlapping = TRUE,
useConditionGroupEraStartLongTerm = TRUE,
useConditionGroupEraStartMediumTerm = TRUE,
useConditionGroupEraStartShortTerm = TRUE,
useConditionOccurrencePrimaryInpatientLongTerm = TRUE,
useDrugExposureAnyTimePrior = TRUE,
useDrugExposureLongTerm = TRUE,
useDrugExposureMediumTerm = TRUE,
useDrugExposureShortTerm = TRUE,
useDrugEraAnyTimePrior = TRUE,
useDrugEraLongTerm = TRUE,
useDrugEraMediumTerm = TRUE,
useDrugEraShortTerm = TRUE,
useDrugEraOverlapping = TRUE,
useDrugEraStartLongTerm = TRUE,
useDrugEraStartMediumTerm = TRUE,
useDrugEraStartShortTerm = TRUE,
useDrugGroupEraAnyTimePrior = TRUE,
useDrugGroupEraLongTerm = TRUE,
useDrugGroupEraMediumTerm = TRUE,
useDrugGroupEraShortTerm = TRUE,
useDrugGroupEraOverlapping = TRUE,
useDrugGroupEraStartLongTerm = TRUE,
useDrugGroupEraStartMediumTerm = TRUE,
useDrugGroupEraStartShortTerm = TRUE,
useProcedureOccurrenceAnyTimePrior = TRUE,
useProcedureOccurrenceLongTerm = TRUE,
useProcedureOccurrenceMediumTerm = TRUE,
useProcedureOccurrenceShortTerm = TRUE,
useDeviceExposureAnyTimePrior = TRUE,
useDeviceExposureLongTerm = TRUE,
useDeviceExposureMediumTerm = TRUE,
useDeviceExposureShortTerm = TRUE,
useMeasurementAnyTimePrior = TRUE,
useMeasurementLongTerm = TRUE,
useMeasurementMediumTerm = TRUE,
useMeasurementShortTerm = TRUE,
useMeasurementValueAnyTimePrior = TRUE,
useMeasurementValueLongTerm = TRUE,
useMeasurementValueMediumTerm = TRUE,
useMeasurementValueShortTerm = TRUE,
useMeasurementRangeGroupAnyTimePrior = TRUE,
useMeasurementRangeGroupLongTerm = TRUE,
useMeasurementRangeGroupMediumTerm = TRUE,
useMeasurementRangeGroupShortTerm = TRUE,
useObservationAnyTimePrior = TRUE,
useObservationLongTerm = TRUE,
useObservationMediumTerm = TRUE,
useObservationShortTerm = TRUE,
useCharlsonIndex = TRUE,
useDcsi = TRUE,
useChads2 = TRUE,
useChads2Vasc = TRUE,
useDistinctConditionCountLongTerm = TRUE,
useDistinctConditionCountMediumTerm = TRUE,
useDistinctConditionCountShortTerm = TRUE,
useDistinctIngredientCountLongTerm = TRUE,
useDistinctIngredientCountMediumTerm = TRUE,
useDistinctIngredientCountShortTerm = TRUE,
useDistinctProcedureCountLongTerm = TRUE,
useDistinctProcedureCountMediumTerm = TRUE,
useDistinctProcedureCountShortTerm = TRUE,
useDistinctMeasurementCountLongTerm = TRUE,
useDistinctMeasurementCountMediumTerm = TRUE,
useDistinctMeasurementCountShortTerm = TRUE,
useVisitCountLongTerm = TRUE,
useVisitCountMediumTerm = TRUE,
useVisitCountShortTerm = TRUE,
longTermStartDays = -365,
mediumTermStartDays = -180,
shortTermStartDays = -30,
endDays = 0,
includedCovariateConceptIds = c(),
addDescendantsToInclude = FALSE,
excludedCovariateConceptIds = c(),
addDescendantsToExclude = FALSE,
includedCovariateIds = c())
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(740910, 945286),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = settings,
aggregated = TRUE)
covs$covariateRef %>%
filter(covariateId > 15000)
covs$covariates[covs$covariates$covariateId == 4329847210, ]
# Exclude: sum = 2.883000e+03
# Not exclude: sum = 2.883000e+03
# Exclude after fix: sum = 2.538000e+03
system.time(
saveCovariateData(covs, "s:/temp/covsHuge.zip")
)
saveCovariateData(covs, "s:/temp/covsAgg")
covariateData <- loadCovariateData("s:/temp/covsHuge.zip")
covariateData
print(covariateData)
summary(covariateData)
tidyCovs <- tidyCovariateData(covariateData)
tempCovariateData <- loadCovariateData("c:/temp/covs2.zip")
covs2 <- aggregateCovariates(covs)
settings2 <- createCovariateSettings(useDemographicsGender = TRUE)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(1),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = list(settings, settings2),
aggregated = TRUE)
print(covs)
summary(covs)
print(covs$covariateRef, n = 100)
# Temporal covariates -----------------------------------------------
covariateSettings <- createTemporalCovariateSettings(useDemographicsGender = TRUE,
useMeasurementValue = TRUE)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(1),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = covariateSettings,
aggregated = TRUE)
saveCovariateData(covs, "c:/temp/tempCovs")
covariateData <- loadCovariateData("c:/temp/tempCovs")
tidyCovs <- tidyCovariateData(covariateData)
agg <- aggregateCovariates(covs)
saveCovariateData(tidyCovs, "c:/temp/tidyCovs.zip")
# Aggregation ---------------------------------------------------------------------------------
covariateSettings <- createCovariateSettings(useDemographicsAge = TRUE,
= TRUE)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(1),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = covariateSettings,
aggregated = FALSE)
saveCovariateData(covs, "c:/temp/unaggregatedCovs.zip")
aggCovs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(1),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = covariateSettings,
aggregated = TRUE)
saveCovariateData(aggCovs, "c:/temp/aggregatedCovs.zip")
covariateData <- loadCovariateData("c:/temp/unaggregatedCovs.zip")
aggCovs2 <- aggregateCovariates(covariateData)
aggCovs <- loadCovariateData("c:/temp/aggregatedCovs.zip")
aggCovs$covariates %>% collect()
aggCovs2$covariates %>% collect()
aggCovs$covariatesContinuous %>% collect()
aggCovs2$covariatesContinuous %>% collect()
# Storing data on server -----------------------------------------------------------------------
settings <- createCovariateSettings(useDemographicsGender = TRUE,
useDemographicsAgeGroup = TRUE)
conn <- DatabaseConnector::connect(connectionDetails)
getDbDefaultCovariateData(connection = conn,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortTable = paste(cohortDatabaseSchema, cohortTable, sep = "."),
cohortIds = c(-1),
rowIdField = "row_id",
covariateSettings = settings,
targetCovariateTable = "#my_covs",
targetCovariateRefTable = "#my_cov_ref",
targetAnalysisRefTable = "#my_analysis_ref",
aggregated = FALSE)
querySql(conn, "SELECT TOP 100 * FROM #my_covs")
querySql(conn, "SELECT TOP 100 * FROM #my_cov_ref")
querySql(conn, "SELECT TOP 100 * FROM #my_analysis_ref")
DatabaseConnector::disconnect(conn)
covariateSettings <- createDefaultCovariateSettings()
covariateSettings <- FeatureExtraction::createTemporalCovariateSettings(useDemographicsGender = TRUE,
useDemographicsIndexYear = FALSE,
useDemographicsAge = FALSE,
useDemographicsIndexMonth = FALSE,
useConditionOccurrence = TRUE,
useConditionEraStart = FALSE,
useConditionEraOverlap = FALSE,
useConditionEraGroupStart = FALSE,
useConditionEraGroupOverlap = FALSE,
useDrugExposure = FALSE,
useDrugEraStart = FALSE,
useDrugEraOverlap = FALSE,
useDrugEraGroupStart = FALSE,
useDrugEraGroupOverlap = FALSE,
useProcedureOccurrence = FALSE,
useDeviceExposure = FALSE,
useMeasurement = FALSE,
useObservation = FALSE,
useCharlsonIndex = FALSE,
temporalStartDays = -365:-1,
temporalEndDays = -365:-1,
includedCovariateConceptIds = c(),
addDescendantsToInclude = FALSE,
excludedCovariateConceptIds = c(),
addDescendantsToExclude = FALSE,
includedCovariateIds = c())
# covariateSettings <- convertPrespecSettingsToDetailedSettings(covariateSettings)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = 1,
cohortTableIsTemp = FALSE,
covariateSettings = covariateSettings,
aggregated = TRUE)
analysisDetails <- createAnalysisDetails(analysisId = 1,
sqlFileName = "DemographicsGender.sql",
parameters = list(analysisId = 1,
analysisName = "Gender",
domainId = "Demographics"),
includedCovariateConceptIds = c(),
addDescendantsToInclude = FALSE,
excludedCovariateConceptIds = c(),
addDescendantsToExclude = FALSE,
includedCovariateIds = c())
covariateSettings <- createDetailedCovariateSettings(analyses = list(analysisDetails))
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = 1,
cohortTableIsTemp = FALSE,
covariateSettings = covariateSettings,
aggregated = TRUE)
# Table 1 -----------------------------------------------------------------
settings <- createCovariateSettings(useDemographicsAgeGroup = TRUE,
useDemographicsGender = TRUE,
useDemographicsEthnicity = TRUE,
useConditionGroupEraLongTerm = TRUE,
useDrugGroupEraLongTerm = TRUE,
useCharlsonIndex = TRUE,
useChads2Vasc = TRUE,
useDcsi = TRUE)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortIds = c(1),
rowIdField = "row_id",
cohortTableIsTemp = FALSE,
covariateSettings = settings,
aggregated = TRUE)
saveCovariateData(covs, "c:/temp/covsTable1")
covariateData1 <- loadCovariateData("c:/temp/covsTable1")
tables <- createTable1(covariateData1, output = "one column", showCounts = T, showPercent = F)
tables <- createTable1(covariateData1, output = "two columns", showCounts = T, showPercent = F)
tables <- createTable1(covariateData1, covariateData1, output = "one column", showCounts = F, showPercent = T)
tables <- createTable1(covariateData1, covariateData1, output = "two columns", showCounts = T, showPercent = F)
write.csv(tables$part1, "c:/temp/table1Part1.csv", row.names = FALSE)
write.csv(tables$part2, "c:/temp/table1Part2.csv", row.names = FALSE)
print(tables$part1)
covariateData1 <- covariateData
covariateData2 <- covariateData
# Eunomia ------------------------------------------------------
library(FeatureExtraction)
library(Eunomia)
options(andromedaTempFolder = "c:/andromedaTemp")
connectionDetails <- getEunomiaConnectionDetails()
createCohorts(connectionDetails)
settings <- createCovariateSettings(useDemographicsGender = TRUE,
useDemographicsAge = FALSE,
useDemographicsAgeGroup = FALSE,
useDemographicsRace = FALSE,
useDemographicsEthnicity = FALSE,
useDemographicsIndexYear = FALSE,
useDemographicsIndexMonth = FALSE,
useDemographicsPriorObservationTime = FALSE,
useDemographicsPostObservationTime = FALSE,
useDemographicsTimeInCohort = FALSE,
useConditionOccurrenceAnyTimePrior = FALSE,
useConditionOccurrenceLongTerm = FALSE,
useConditionOccurrenceMediumTerm = FALSE,
useConditionOccurrenceShortTerm = FALSE,
useConditionEraAnyTimePrior = FALSE,
useConditionEraLongTerm = FALSE,
useConditionEraMediumTerm = FALSE,
useConditionEraShortTerm = FALSE,
useConditionEraOverlapping = FALSE,
useConditionEraStartLongTerm = FALSE,
useConditionEraStartMediumTerm = FALSE,
useConditionEraStartShortTerm = FALSE,
useConditionGroupEraAnyTimePrior = FALSE,
useConditionGroupEraLongTerm = FALSE,
useConditionGroupEraMediumTerm = FALSE,
useConditionGroupEraShortTerm = FALSE,
useConditionGroupEraOverlapping = FALSE,
useConditionGroupEraStartLongTerm = FALSE,
useConditionGroupEraStartMediumTerm = FALSE,
useConditionGroupEraStartShortTerm = FALSE,
useConditionOccurrencePrimaryInpatientLongTerm = FALSE,
useDrugExposureAnyTimePrior = FALSE,
useDrugExposureLongTerm = FALSE,
useDrugExposureMediumTerm = FALSE,
useDrugExposureShortTerm = FALSE,
useDrugEraAnyTimePrior = FALSE,
useDrugEraLongTerm = FALSE,
useDrugEraMediumTerm = FALSE,
useDrugEraShortTerm = FALSE,
useDrugEraOverlapping = FALSE,
useDrugEraStartLongTerm = FALSE,
useDrugEraStartMediumTerm = FALSE,
useDrugEraStartShortTerm = FALSE,
useDrugGroupEraAnyTimePrior = FALSE,
useDrugGroupEraLongTerm = FALSE,
useDrugGroupEraMediumTerm = FALSE,
useDrugGroupEraShortTerm = FALSE,
useDrugGroupEraOverlapping = FALSE,
useDrugGroupEraStartLongTerm = FALSE,
useDrugGroupEraStartMediumTerm = FALSE,
useDrugGroupEraStartShortTerm = FALSE,
useProcedureOccurrenceAnyTimePrior = FALSE,
useProcedureOccurrenceLongTerm = FALSE,
useProcedureOccurrenceMediumTerm = FALSE,
useProcedureOccurrenceShortTerm = FALSE,
useDeviceExposureAnyTimePrior = FALSE,
useDeviceExposureLongTerm = FALSE,
useDeviceExposureMediumTerm = FALSE,
useDeviceExposureShortTerm = FALSE,
useMeasurementAnyTimePrior = FALSE,
useMeasurementLongTerm = FALSE,
useMeasurementMediumTerm = FALSE,
useMeasurementShortTerm = FALSE,
useMeasurementValueAnyTimePrior = FALSE,
useMeasurementValueLongTerm = FALSE,
useMeasurementValueMediumTerm = FALSE,
useMeasurementValueShortTerm = FALSE,
useMeasurementRangeGroupAnyTimePrior = FALSE,
useMeasurementRangeGroupLongTerm = FALSE,
useMeasurementRangeGroupMediumTerm = FALSE,
useMeasurementRangeGroupShortTerm = FALSE,
useObservationAnyTimePrior = FALSE,
useObservationLongTerm = FALSE,
useObservationMediumTerm = FALSE,
useObservationShortTerm = FALSE,
useCharlsonIndex = FALSE,
useDcsi = FALSE,
useChads2 = FALSE,
useChads2Vasc = FALSE,
useDistinctConditionCountLongTerm = FALSE,
useDistinctConditionCountMediumTerm = FALSE,
useDistinctConditionCountShortTerm = FALSE,
useDistinctIngredientCountLongTerm = FALSE,
useDistinctIngredientCountMediumTerm = FALSE,
useDistinctIngredientCountShortTerm = FALSE,
useDistinctProcedureCountLongTerm = FALSE,
useDistinctProcedureCountMediumTerm = FALSE,
useDistinctProcedureCountShortTerm = FALSE,
useDistinctMeasurementCountLongTerm = FALSE,
useDistinctMeasurementCountMediumTerm = FALSE,
useDistinctMeasurementCountShortTerm = FALSE,
useVisitCountLongTerm = FALSE,
useVisitCountMediumTerm = FALSE,
useVisitCountShortTerm = FALSE,
longTermStartDays = -365,
mediumTermStartDays = -180,
shortTermStartDays = -30,
endDays = 0,
includedCovariateConceptIds = c(),
addDescendantsToInclude = FALSE,
excludedCovariateConceptIds = c(),
addDescendantsToExclude = FALSE,
includedCovariateIds = c())
covs <- getDbCovariateData(connectionDetails = connectionDetails,
cdmDatabaseSchema = "main",
cohortDatabaseSchema = "main",
cohortTable = "cohort",
cohortIds = c(2^34),
covariateSettings = settings,
aggregated = TRUE)
collect(covs$covariatesContinuous)
collect(covs$covariates)
collect(covs$covariateRef) %>% filter(covariateId %% 1000 == 3)
x <- collect(covs$covariateRef)
View(x)
settings <- createTemporalCovariateSettings(useDemographicsGender = TRUE,
useDemographicsAge = TRUE,
useDemographicsAgeGroup = TRUE,
useDemographicsRace = TRUE,
useDemographicsEthnicity = TRUE,
useDemographicsIndexYear = TRUE,
useDemographicsIndexMonth = TRUE,
useDemographicsPriorObservationTime = TRUE,
useDemographicsPostObservationTime = TRUE,
useDemographicsTimeInCohort = TRUE,
useDemographicsIndexYearMonth = TRUE,
useConditionOccurrence = TRUE,
useConditionOccurrencePrimaryInpatient = TRUE,
useConditionEraStart = TRUE,
useConditionEraOverlap = TRUE,
useConditionEraGroupStart = TRUE,
useConditionEraGroupOverlap = TRUE,
useDrugExposure = TRUE,
useDrugEraStart = TRUE,
useDrugEraOverlap = TRUE,
useDrugEraGroupStart = TRUE,
useDrugEraGroupOverlap = TRUE,
useProcedureOccurrence = TRUE,
useDeviceExposure = TRUE,
useMeasurement = TRUE,
useMeasurementValue = TRUE,
useMeasurementRangeGroup = TRUE,
useObservation = TRUE,
useCharlsonIndex = TRUE,
useDcsi = TRUE,
useChads2 = TRUE,
useChads2Vasc = TRUE,
useHfrs = TRUE,
useDistinctConditionCount = TRUE,
useDistinctIngredientCount = TRUE,
useDistinctProcedureCount = TRUE,
useDistinctMeasurementCount = TRUE,
useDistinctObservationCount = TRUE,
useVisitCount = TRUE,
useVisitConceptCount = TRUE)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
cdmDatabaseSchema = "main",
cohortDatabaseSchema = "main",
cohortTable = "cohort",
cohortIds = c(1,2),
covariateSettings = settings,
aggregated = TRUE)
connection <- connect(connectionDetails)
querySql(connection, "SELECT * FROM main.cohort LIMIT 100")
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