Shiny app (OHDSI Analysis Viewer) errors out after clicking "View Diagnostics

Open kzollove opened this issue 2 years ago • 0 comments

Describe the bug diagnosisPlp.txt viewPlpError.txt plpError.txt

I am running through a very typical single PLP model workflow. When I get to the end of the workflow, I run viewPlp, which starts normally. Within the Shiny app, when I navigate to prediction, and then click the "View Diagnostics" button, the shiny app closes with an error:

Set up (please run in R "sessionInfo()" and copy the output here): copy the system set up details including the R version and operating system details...

sessionInfo() R version 4.2.1 (2022-06-23 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 19042)

Matrix products: default

locale: [1] LC_COLLATE=English_United States.utf8 [2] LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8 [4] LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8

attached base packages: [1] stats graphics grDevices utils datasets methods
[7] base

other attached packages: [1] shiny_1.7.2 magrittr_2.0.3
[3] PatientLevelPrediction_6.3.2 CohortDiagnostics_3.2.2
[5] FeatureExtraction_3.2.0 Andromeda_0.6.3
[7] dplyr_1.1.1 DatabaseConnector_6.2.0

loaded via a namespace (and not attached): [1] reactable_0.3.0 fontawesome_0.3.0
[3] bit64_4.0.5 httr_1.4.3
[5] PRROC_1.3.1 tippy_0.1.0
[7] tools_4.2.1 backports_1.4.1
[9] bslib_0.4.0 DT_0.26
[11] utf8_1.2.3 R6_2.5.1
[13] lazyeval_0.2.2 colorspace_2.0-3
[15] DBI_1.1.3 withr_2.5.0
[17] tidyselect_1.2.0 bit_4.0.5
[19] compiler_4.2.1 Cyclops_3.3.1
[21] cli_3.6.1 plotly_4.10.1
[23] triebeard_0.4.1 sass_0.4.2
[25] scales_1.2.0 checkmate_2.1.0
[27] readr_2.1.4 commonmark_1.8.0
[29] digest_0.6.31 pkgconfig_2.0.3
[31] htmltools_0.5.3 dbplyr_2.3.2
[33] fastmap_1.1.0 htmlwidgets_1.5.4
[35] rlang_1.1.0 keyring_1.3.1
[37] rstudioapi_0.13 RSQLite_2.3.1
[39] jquerylib_0.1.4 generics_0.1.3
[41] jsonlite_1.8.4 crosstalk_1.2.0
[43] zip_2.3.0 CohortGenerator_0.8.0
[45] Matrix_1.4-1 Rcpp_1.0.10
[47] munsell_0.5.0 fansi_1.0.4
[49] shinycssloaders_1.0.0 reticulate_1.28
[51] lifecycle_1.0.3 pROC_1.18.0
[53] yaml_2.3.5 plyr_1.8.8
[55] grid_4.2.1 blob_1.2.4
[57] promises_1.2.0.1 crayon_1.5.2
[59] shinydashboard_0.7.2 ROhdsiWebApi_1.3.1
[61] lattice_0.20-45 splines_4.2.1
[63] hms_1.1.3 pillar_1.9.0
[65] ParallelLogger_3.1.0 markdown_1.3
[67] glue_1.6.2 data.table_1.14.8
[69] pool_1.0.1 remotes_2.4.2
[71] memuse_4.2-3 png_0.1-7
[73] vctrs_0.6.1 tzdb_0.3.0
[75] ShinyAppBuilder_1.1.2 httpuv_1.6.5
[77] urltools_1.7.3 gtable_0.3.0
[79] purrr_1.0.1 tidyr_1.3.0
[81] reactR_0.4.4 assertthat_0.2.1
[83] cachem_1.0.6 ggplot2_3.3.6
[85] xfun_0.32 mime_0.12
[87] OhdsiShinyModules_1.1.0 xtable_1.8-4
[89] later_1.3.0 viridisLite_0.4.0
[91] ResultModelManager_0.4.0 survival_3.3-1
[93] tibble_3.2.1 rJava_1.0-6
[95] SqlRender_1.15.0 memoise_2.0.1
[97] ellipsis_0.3.2

To Reproduce Enter the code you tried to run here (with sensitive information such as passwords removed)

connectionDetails <- createConnectionDetails( dbms = 'spark', connectionString = keyring::key_get("databricks-connection-string"), pathToDriver = "C:\R\" )

cdmDatabaseSchema <- "ctsi_production_legacy_red" cohortDatabaseSchema <- resultsDatabaseSchema <- "trdwResults" cdmVersion <- "5.4" cohortTable <- "cohort"

targetCohortId <- 3 outcomeCohortId <- 4

databaseDetails <- createDatabaseDetails( connectionDetails = connectionDetails, cdmDatabaseSchema = cdmDatabaseSchema, cohortDatabaseSchema = cohortDatabaseSchema, cohortTable = cohortTable, targetId = targetCohortId, outcomeDatabaseSchema = cohortDatabaseSchema, outcomeTable = cohortTable, outcomeIds = outcomeCohortId )

-# Ever in History ---------------------------------------------------------

covariateConceptIdsEverInHistory <- c( 8507, 8532, # Male -gender # Female -gender 1368671, 1337720, # milrinone (Inotropes) -drug # dobutamine (Inotropes) -drug 443454, 4077982, # Prior stroke -condition # HO cerebrovascular accident -obs 255573, 4151705, # chronic obstructive lung disease -condition # chronic obstructive airway disease HO -obs 46271022, # chronic kidney disease -condition 193782, # ESRD -cond 42539502, 38001396, 4322471, # Kidney transplant -cond -obs -proc 4064161, 196463, 3171064, # cirrhosis -cond -cond -obs 4273629, # TODO active chemotherapy # should this have a time window? -proc 4182210, # dementia -cond 433163, # protein-calorie malnutrition -cond 4043039, 4042889, 4143732, # illicit drug use -cond 4234597, 436954, 4279309, # illicit drug use -cond 4239381, # psychoactive substance abuse -condition 40765289, 4005823, # tobacco use -meas# tobacco user -obs 4298794, 4275495, 4310250, # current smoker, tobacco smoking behavior, Ex-smoker -obs 36714559, # disorder caused by alcohol -cond 201820, 4058709, # Diabetes mellitus -condition # Diabetes mellitus H/O -obs non standard 313217, 4194288, # Atrial fib - cond # Atrial fib HO -obs 314665, 4323077, # Atrial flutter - cond # Atrial flutter HO -obs 443392, 4144289, # malignant neoplastic disease -cond # malignant neoplasm HO -obs 440383, 441542, # Depressive Disorder -cond # Anxiety -cond 21604709, 21604565, # SSRIs -drug # benzos -drug 317576, 3168727, # coronary artery disease -cond -obs 316139, 4059317, # History of heart failure before index admission 37109664, 4338594, # Left ventricular assist device -obs -proc 42538117, 4058860, 4137127, # Transplanted heart -cond -obs -proc 4140455 # Home oxygen -proc )

excludedConcepts <- c( 4155297, 4179242 # malignant neoplasm of skin -cond # HO malignant neoplasm of skin -obs )

covariateSettingsEverInHistory <- createCovariateSettings(useDemographicsGender = TRUE, useDemographicsAge = TRUE, useDrugExposureAnyTimePrior = TRUE, useConditionOccurrenceAnyTimePrior = TRUE, useMeasurementAnyTimePrior = TRUE, useObservationAnyTimePrior = TRUE, useProcedureOccurrenceAnyTimePrior = TRUE, includedCovariateConceptIds = covariateConceptIdsEverInHistory, excludedCovariateConceptIds = excludedConcepts, addDescendantsToInclude = TRUE, addDescendantsToExclude = TRUE)

#Month before ----------------------------------

covariateConceptIdsOneMonth <- c( 4146536, 4059475 # Renal Dialysis -proc -obs )

covariateSettingsOneMonth <- createCovariateSettings(useProcedureOccurrenceShortTerm = TRUE, shortTermStartDays = -30, includedCovariateConceptIds = covariateConceptIdsOneMonth, addDescendantsToInclude = TRUE)

#Year before ------------------------------------

covariateConceptIdsLastYear <- c( 9203, 9201, # Emergency Room Visit, Inpatient Visit 4163872 # Chest X ray -proc )

covariateSettingsLastYear <- createCovariateSettings(useVisitConceptCountShortTerm = TRUE, useProcedureOccurrenceShortTerm = TRUE, shortTermStartDays = -365, includedCovariateConceptIds = covariateConceptIdsLastYear, addDescendantsToInclude = TRUE)

covariateSettings <- list( covariateSettingsEverInHistory, covariateSettingsOneMonth, covariateSettingsLastYear #covariateSettingsAtAdmission, #covariateSettingsDuringHospitalization, #covariateSettingsAdmissionMedRec )

restrictPlpDataSettings <- createRestrictPlpDataSettings(sampleSize = 10000)

plpData <- getPlpData( databaseDetails = databaseDetails, covariateSettings = covariateSettings, restrictPlpDataSettings = restrictPlpDataSettings )

savePlpData(plpData, "lhs_chf_1")

populationSettings <- createStudyPopulationSettings( washoutPeriod = 0, firstExposureOnly = FALSE, removeSubjectsWithPriorOutcome = FALSE, priorOutcomeLookback = 1, riskWindowStart = 1, riskWindowEnd = 365, startAnchor = 'cohort start', endAnchor = 'cohort start', minTimeAtRisk = 364, requireTimeAtRisk = FALSE, includeAllOutcomes = TRUE )

splitSettings <- createDefaultSplitSetting( trainFraction = 0.75, testFraction = 0.25, type = 'stratified', nfold = 2, splitSeed = 1234 )

#Under sample or over sample? sampleSettings <- createSampleSettings()

featureEngineeringSettings <- createFeatureEngineeringSettings()

preprocessSettings <- createPreprocessSettings( minFraction = 0, normalize = T, removeRedundancy = F )

lrModel <- setLassoLogisticRegression()

diagnosis <- diagnosePlp( plpData = plpData, outcomeId = outcomeCohortId, analysisId = 'singleDemo', populationSettings = populationSettings, splitSettings = splitSettings, sampleSettings = sampleSettings, featureEngineeringSettings = featureEngineeringSettings, preprocessSettings = preprocessSettings, modelSettings = lrModel, logSettings = createLogSettings(), saveDirectory = file.path(getwd(), 'singlePlp') )

lrResults <- runPlp( plpData = plpData, outcomeId = outcomeCohortId, analysisId = 'singleDemo', analysisName = 'Demonstration of runPlp for training single PLP models', populationSettings = populationSettings, splitSettings = splitSettings, sampleSettings = sampleSettings, featureEngineeringSettings = featureEngineeringSettings, preprocessSettings = preprocessSettings, modelSettings = lrModel, logSettings = createLogSettings(), executeSettings = createExecuteSettings( runSplitData = T, runSampleData = T, runfeatureEngineering = T, runPreprocessData = T, runModelDevelopment = T, runCovariateSummary = T ), saveDirectory = file.path(getwd(), 'singlePlp') )

viewPlp( runPlp = lrResults, diagnosePlp = diagnosis )

PLP Log File Enter the log file contents here (plplog.txt) 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation outcomeId: 4 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation binary: TRUE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation includeAllOutcomes: TRUE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation firstExposureOnly: FALSE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation washoutPeriod: 0 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation removeSubjectsWithPriorOutcome: FALSE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation priorOutcomeLookback: 1 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation requireTimeAtRisk: FALSE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation minTimeAtRisk: 364 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation restrictTarToCohortEnd: FALSE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation riskWindowStart: 1 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation startAnchor: cohort start 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation riskWindowEnd: 365 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation endAnchor: cohort start 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation restrictTarToCohortEnd: FALSE 2023-06-21 13:18:32 [Main thread] INFO PatientLevelPrediction createStudyPopulation Outcome is 0 or 1 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation outcomeId: 4 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation binary: TRUE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation includeAllOutcomes: TRUE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation firstExposureOnly: FALSE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation washoutPeriod: 0 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation removeSubjectsWithPriorOutcome: FALSE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation priorOutcomeLookback: 1 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation requireTimeAtRisk: FALSE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation minTimeAtRisk: 364 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation restrictTarToCohortEnd: FALSE 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation riskWindowStart: 1 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation startAnchor: cohort start 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation riskWindowEnd: 3650 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation endAnchor: cohort start 2023-06-21 13:18:32 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation restrictTarToCohortEnd: FALSE 2023-06-21 13:18:33 [Main thread] INFO PatientLevelPrediction createStudyPopulation Outcome is 0 or 1 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation outcomeId: 4 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation binary: TRUE 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation includeAllOutcomes: TRUE 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation firstExposureOnly: FALSE 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation washoutPeriod: 0 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation removeSubjectsWithPriorOutcome: FALSE 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation priorOutcomeLookback: 1 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation requireTimeAtRisk: FALSE 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation minTimeAtRisk: 364 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation restrictTarToCohortEnd: FALSE 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation riskWindowStart: 1 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation startAnchor: cohort start 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation riskWindowEnd: 365 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation endAnchor: cohort start 2023-06-21 13:18:39 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation restrictTarToCohortEnd: FALSE 2023-06-21 13:18:40 [Main thread] INFO PatientLevelPrediction createStudyPopulation Outcome is 0 or 1 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation outcomeId: 4 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation binary: TRUE 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation includeAllOutcomes: FALSE 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation firstExposureOnly: FALSE 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation washoutPeriod: 0 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation removeSubjectsWithPriorOutcome: FALSE 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation priorOutcomeLookback: 0 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation requireTimeAtRisk: FALSE 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation minTimeAtRisk: 0 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation restrictTarToCohortEnd: FALSE 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation riskWindowStart: 1 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation startAnchor: cohort start 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation riskWindowEnd: 365 2023-06-21 13:18:40 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation endAnchor: cohort start 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation restrictTarToCohortEnd: FALSE 2023-06-21 13:18:41 [Main thread] INFO PatientLevelPrediction createStudyPopulation Outcome is 0 or 1 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation outcomeId: 4 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation binary: TRUE 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation includeAllOutcomes: TRUE 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation firstExposureOnly: FALSE 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation washoutPeriod: 0 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation removeSubjectsWithPriorOutcome: FALSE 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation priorOutcomeLookback: 1 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation requireTimeAtRisk: FALSE 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation minTimeAtRisk: 364 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation restrictTarToCohortEnd: FALSE 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation riskWindowStart: 1 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation startAnchor: cohort start 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation riskWindowEnd: 365 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation endAnchor: cohort start 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction createStudyPopulation restrictTarToCohortEnd: FALSE 2023-06-21 13:18:41 [Main thread] INFO PatientLevelPrediction createStudyPopulation Outcome is 0 or 1 2023-06-21 13:18:41 [Main thread] INFO PatientLevelPrediction diagnosePlp Saving diagnosePlp to C:/Users/kzollovenecek/Documents/git_repos/LHS-CHF-Readmission/singlePlp/singleDemo/diagnosePlp.rds 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction checkInputs binary : TRUEincludeAllOutcomes : TRUEfirstExposureOnly : FALSEwashoutPeriod : 0removeSubjectsWithPriorOutcome : FALSEpriorOutcomeLookback : 1requireTimeAtRisk : FALSEminTimeAtRisk : 364riskWindowStart : 1startAnchor : cohort startriskWindowEnd : 365endAnchor : cohort startrestrictTarToCohortEnd : FALSE 2023-06-21 13:18:41 [Main thread] DEBUG PatientLevelPrediction checkInputs test : 0.25train : 0.75seed : 1234nfold : 2 2023-06-21 13:18:42 [Main thread] DEBUG PatientLevelPrediction checkInputs numberOutcomestoNonOutcomes : 1sampleSeed : 1 2023-06-21 13:18:42 [Main thread] DEBUG PatientLevelPrediction checkInputs : 2023-06-21 13:18:42 [Main thread] DEBUG PatientLevelPrediction checkInputs minFraction : 0normalize : TRUEremoveRedundancy : FALSE 2023-06-21 13:18:42 [Main thread] DEBUG PatientLevelPrediction checkInputs fitFunction : fitCyclopsModelparam : laplace-FALSE-0.01-0-20-0.01 2023-06-21 13:18:42 [Main thread] DEBUG PatientLevelPrediction checkInputs runSplitData : TRUErunSampleData : TRUErunfeatureEngineering : TRUErunPreprocessData : TRUErunModelDevelopment : TRUErunCovariateSummary : TRUE 2023-06-21 13:18:42 [Main thread] INFO PatientLevelPrediction printHeader Patient-Level Prediction Package version 6.3.2 2023-06-21 13:18:42 [Main thread] INFO PatientLevelPrediction printHeader Study started at: 2023-06-21 13:18:42 2023-06-21 13:18:42 [Main thread] INFO PatientLevelPrediction printHeader AnalysisID: singleDemo 2023-06-21 13:18:42 [Main thread] INFO PatientLevelPrediction printHeader AnalysisName: Demonstration of runPlp for training single PLP models 2023-06-21 13:18:42 [Main thread] INFO PatientLevelPrediction printHeader TargetID: 3 2023-06-21 13:18:42 [Main thread] INFO PatientLevelPrediction printHeader OutcomeID: 4 2023-06-21 13:18:42 [Main thread] INFO PatientLevelPrediction printHeader Cohort size: 3768 2023-06-21 13:18:43 [Main thread] INFO PatientLevelPrediction printHeader Covariates: 821 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction outcomeId: 4 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction binary: TRUE 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction includeAllOutcomes: TRUE 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction firstExposureOnly: FALSE 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction washoutPeriod: 0 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction removeSubjectsWithPriorOutcome: FALSE 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction priorOutcomeLookback: 1 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction requireTimeAtRisk: FALSE 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction minTimeAtRisk: 364 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction restrictTarToCohortEnd: FALSE 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction riskWindowStart: 1 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction startAnchor: cohort start 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction riskWindowEnd: 365 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction endAnchor: cohort start 2023-06-21 13:18:43 [Main thread] DEBUG PatientLevelPrediction restrictTarToCohortEnd: FALSE 2023-06-21 13:18:44 [Main thread] INFO PatientLevelPrediction Outcome is 0 or 1 2023-06-21 13:18:44 [Main thread] DEBUG PatientLevelPrediction checkInputsSplit test: 0.25 2023-06-21 13:18:44 [Main thread] DEBUG PatientLevelPrediction checkInputsSplit train: 0.75 2023-06-21 13:18:44 [Main thread] DEBUG PatientLevelPrediction checkInputsSplit nfold: 2 2023-06-21 13:18:44 [Main thread] INFO PatientLevelPrediction checkInputsSplit seed: 1234 2023-06-21 13:18:44 [Main thread] INFO PatientLevelPrediction Creating a 25% test and 75% train (into 2 folds) random stratified split by class 2023-06-21 13:18:44 [Main thread] INFO PatientLevelPrediction Data split into 941 test cases and 2827 train cases (1414, 1413) 2023-06-21 13:18:45 [Main thread] INFO PatientLevelPrediction dataSummary Train Set: 2023-06-21 13:18:45 [Main thread] INFO PatientLevelPrediction dataSummary Fold 1 1414 patients with 351 outcomes - Fold 2 1413 patients with 350 outcomes 2023-06-21 13:18:47 [Main thread] INFO PatientLevelPrediction dataSummary 753 covariates in train data 2023-06-21 13:18:47 [Main thread] INFO PatientLevelPrediction dataSummary Test Set: 2023-06-21 13:18:47 [Main thread] INFO PatientLevelPrediction dataSummary 941 patients with 233 outcomes 2023-06-21 13:18:47 [Main thread] INFO PatientLevelPrediction sampleData Starting data sampling 2023-06-21 13:18:47 [Main thread] INFO PatientLevelPrediction sampleData Applying sameData 2023-06-21 13:18:47 [Main thread] INFO PatientLevelPrediction No sampling - returning same data 2023-06-21 13:18:47 [Main thread] INFO PatientLevelPrediction sampleData Finished data sampling 2023-06-21 13:18:47 [Main thread] INFO PatientLevelPrediction dataSummary Train Set: 2023-06-21 13:18:47 [Main thread] INFO PatientLevelPrediction dataSummary Fold 1 1414 patients with 351 outcomes - Fold 2 1413 patients with 350 outcomes 2023-06-21 13:18:49 [Main thread] INFO PatientLevelPrediction dataSummary 753 covariates in train data 2023-06-21 13:18:49 [Main thread] INFO PatientLevelPrediction dataSummary Test Set: 2023-06-21 13:18:49 [Main thread] INFO PatientLevelPrediction dataSummary 941 patients with 233 outcomes 2023-06-21 13:18:49 [Main thread] INFO PatientLevelPrediction featureEngineer Starting Feature Engineering 2023-06-21 13:18:49 [Main thread] INFO PatientLevelPrediction featureEngineer Applying sameData 2023-06-21 13:18:49 [Main thread] INFO PatientLevelPrediction No sampling - returning same data 2023-06-21 13:18:49 [Main thread] INFO PatientLevelPrediction featureEngineer Done Feature Engineering 2023-06-21 13:18:49 [Main thread] INFO PatientLevelPrediction dataSummary Train Set: 2023-06-21 13:18:49 [Main thread] INFO PatientLevelPrediction dataSummary Fold 1 1414 patients with 351 outcomes - Fold 2 1413 patients with 350 outcomes 2023-06-21 13:18:51 [Main thread] INFO PatientLevelPrediction dataSummary 753 covariates in train data 2023-06-21 13:18:51 [Main thread] INFO PatientLevelPrediction dataSummary Test Set: 2023-06-21 13:18:51 [Main thread] INFO PatientLevelPrediction dataSummary 941 patients with 233 outcomes 2023-06-21 13:18:51 [Main thread] DEBUG PatientLevelPrediction preprocessData minFraction: 0 2023-06-21 13:18:51 [Main thread] DEBUG PatientLevelPrediction preprocessData normalize: TRUE 2023-06-21 13:18:51 [Main thread] DEBUG PatientLevelPrediction preprocessData removeRedundancy: FALSE 2023-06-21 13:18:55 [Main thread] INFO FeatureExtraction Normalizing covariates 2023-06-21 13:18:56 [Main thread] INFO FeatureExtraction Tidying covariates took 4.63 secs 2023-06-21 13:18:56 [Main thread] INFO PatientLevelPrediction dataSummary Train Set: 2023-06-21 13:18:56 [Main thread] INFO PatientLevelPrediction dataSummary Fold 1 1414 patients with 351 outcomes - Fold 2 1413 patients with 350 outcomes 2023-06-21 13:18:58 [Main thread] INFO PatientLevelPrediction dataSummary 753 covariates in train data 2023-06-21 13:18:58 [Main thread] INFO PatientLevelPrediction dataSummary Test Set: 2023-06-21 13:18:58 [Main thread] INFO PatientLevelPrediction dataSummary 941 patients with 233 outcomes 2023-06-21 13:18:58 [Main thread] INFO PatientLevelPrediction runPlp 2023-06-21 13:18:59 [Main thread] INFO PatientLevelPrediction Running Cyclops 2023-06-21 13:19:02 [Main thread] INFO PatientLevelPrediction Done. 2023-06-21 13:19:02 [Main thread] INFO PatientLevelPrediction createCyclopsModel GLM fit status: OK 2023-06-21 13:19:03 [Main thread] INFO PatientLevelPrediction getVariableImportance Creating variable importance data frame 2023-06-21 13:19:05 [Main thread] INFO PatientLevelPrediction predictCyclops Prediction took 2.36 secs 2023-06-21 13:19:05 [Main thread] INFO PatientLevelPrediction No sampling - returning same data 2023-06-21 13:19:06 [Main thread] INFO PatientLevelPrediction Removing infrequent and redundant covariates and normalizing 2023-06-21 13:19:08 [Main thread] INFO PatientLevelPrediction Prediction took 1.69 secs 2023-06-21 13:19:08 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Calculating Performance for Test 2023-06-21 13:19:08 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary ============= 2023-06-21 13:19:08 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary AUC 70.32 2023-06-21 13:19:08 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary 95% lower AUC: 66.41 2023-06-21 13:19:08 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary 95% upper AUC: 74.24 2023-06-21 13:19:08 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary AUPRC: 45.66 2023-06-21 13:19:08 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Brier: 0.17 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Eavg: 0.02 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Calibration in large- Mean predicted risk 0.2548 : observed risk 0.2476 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Calibration in large- Intercept -0.0435 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Weak calibration intercept: -0.1453 - gradient:0.891 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Hosmer-Lemeshow calibration gradient: 0.88 intercept: 0.02 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Average Precision: 0.46 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Calculating Performance for Train 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary ============= 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary AUC 75.33 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary 95% lower AUC: 73.27 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary 95% upper AUC: 77.39 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary AUPRC: 51.39 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Brier: 0.16 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Eavg: 0.02 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Calibration in large- Mean predicted risk 0.2478 : observed risk 0.248 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Calibration in large- Intercept 0.0011 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Weak calibration intercept: 0.1642 - gradient:1.172 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Hosmer-Lemeshow calibration gradient: 1.15 intercept: -0.04 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Average Precision: 0.52 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Calculating Performance for CV 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary ============= 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary AUC 70.73 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary 95% lower AUC: 68.57 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary 95% upper AUC: 72.89 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary AUPRC: 43.38 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Brier: 0.17 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Eavg: 0.01 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Calibration in large- Mean predicted risk 0.2499 : observed risk 0.248 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Calibration in large- Intercept -0.0114 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Weak calibration intercept: -0.0669 - gradient:0.9428 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Hosmer-Lemeshow calibration gradient: 0.95 intercept: 0.01 2023-06-21 13:19:09 [Main thread] INFO PatientLevelPrediction getEvaluationStatistics_binary Average Precision: 0.43 2023-06-21 13:19:10 [Main thread] INFO PatientLevelPrediction Calculating covariate summary @ 2023-06-21 13:19:10 2023-06-21 13:19:10 [Main thread] INFO PatientLevelPrediction This can take a while... 2023-06-21 13:19:10 [Main thread] INFO PatientLevelPrediction createCovariateSubsets Creating binary labels 2023-06-21 13:19:10 [Main thread] INFO PatientLevelPrediction createCovariateSubsets Joining with strata 2023-06-21 13:19:10 [Main thread] INFO PatientLevelPrediction createCovariateSubsets calculating subset of strata 1 2023-06-21 13:19:10 [Main thread] INFO PatientLevelPrediction createCovariateSubsets calculating subset of strata 2 2023-06-21 13:19:10 [Main thread] INFO PatientLevelPrediction createCovariateSubsets calculating subset of strata 3 2023-06-21 13:19:10 [Main thread] INFO PatientLevelPrediction createCovariateSubsets calculating subset of strata 4 2023-06-21 13:19:10 [Main thread] INFO PatientLevelPrediction Restricting to subgroup 2023-06-21 13:19:11 [Main thread] INFO PatientLevelPrediction Calculating summary for subgroup TestWithNoOutcome 2023-06-21 13:19:15 [Main thread] INFO PatientLevelPrediction Restricting to subgroup 2023-06-21 13:19:16 [Main thread] INFO PatientLevelPrediction Calculating summary for subgroup TrainWithOutcome 2023-06-21 13:19:19 [Main thread] INFO PatientLevelPrediction Restricting to subgroup 2023-06-21 13:19:20 [Main thread] INFO PatientLevelPrediction Calculating summary for subgroup TrainWithNoOutcome 2023-06-21 13:19:23 [Main thread] INFO PatientLevelPrediction Restricting to subgroup 2023-06-21 13:19:24 [Main thread] INFO PatientLevelPrediction Calculating summary for subgroup TestWithOutcome 2023-06-21 13:19:28 [Main thread] INFO PatientLevelPrediction aggregateCovariateSummaries Aggregating with labels and strata 2023-06-21 13:19:30 [Main thread] INFO PatientLevelPrediction Finished covariate summary @ 2023-06-21 13:19:30 2023-06-21 13:19:30 [Main thread] INFO PatientLevelPrediction runPlp Run finished successfully. 2023-06-21 13:19:30 [Main thread] INFO PatientLevelPrediction runPlp Saving PlpResult 2023-06-21 13:19:30 [Main thread] INFO PatientLevelPrediction savePlpModel Creating directory to save model 2023-06-21 13:19:30 [Main thread] INFO PatientLevelPrediction runPlp plpResult saved to ..\C:/Users/kzollovenecek/Documents/git_repos/LHS-CHF-Readmission/singlePlp/singleDemo\plpResult

Additional context Add any other context about the problem here. viewPlp(

runPlp = lrResults,
diagnosePlp = diagnosis
) Connecting using SQLite driver All or some PLP result tables do not exist, tables being recreated Deleting existing tables Creating PLP results tables |===========================================================| 100% Executing SQL took 0.131 secs PLP result migrration being applied Migrating data set Migrator using SQL files in PatientLevelPrediction Connecting using SQLite driver Creating migrations table |===========================================================| 100% Executing SQL took 0.0307 secs Migrations table created Executing migration: Migration_1-store_version.sql |===========================================================| 100% Executing SQL took 0.00614 secs Saving migration: Migration_1-store_version.sql |===========================================================| 100% Executing SQL took 0.00824 secs Migration complete Migration_1-store_version.sql Updating version number Connecting using SQLite driver |===========================================================| 100% Executing SQL took 0.0123 secs Connecting using SQLite driver Adding TAR |===========================================================| 100% Executing SQL took 0.00666 secs tarId: 1 Adding cohort Cohort: 3 Inserting data took 0.0166 secs Adding cohort Cohort: 3 Inserting data took 0.0136 secs tId: 1 Adding cohort Cohort: 4 Inserting data took 0.0131 secs Adding cohort Cohort: 4 Inserting data took 0.0216 secs oId: 2 Adding new population settings Inserting data took 0.00867 secs popSetId: 1 Adding new covariate settings Inserting data took 0.0126 secs covSetId: 1 Adding new model settings Inserting data took 0.0136 secs modSetId: 1 Adding new plp data settings Inserting data took 0.0109 secs plpDataSetId: 1 Adding new feature_engineering settings Inserting data took 0.0107 secs FESetId: 1 Adding new sample settings Inserting data took 0.0119 secs sampleSetId: 1 Adding new tidy covariates settings Inserting data took 0.0125 secs tidySetId: 1 Adding new split settings Inserting data took 0.0116 secs splitId: 1 |===========================================================| 100% Executing SQL took 0.00488 secs modelDesignId: 1 |===========================================================| 100% Executing SQL took 0.0086 secs |===========================================================| 100% Executing SQL took 0.00834 secs Database meta data already exists Database1 already exists |===========================================================| 100% Executing SQL took 0.00557 secs modelId: 1 inserted for modelDesignId 1and databaseId 1 TAR exists json in jsons:TRUE Cohort Cohort: 3 exists in cohort_definition with cohort id3 Cohort Cohort: 3 exists in cohorts with cohort id1 json in jsons:TRUE Cohort Cohort: 4 exists in cohort_definition with cohort id4 Cohort Cohort: 4 exists in cohorts with cohort id2 Population settings exists Split setting exists Inserting performance... |===========================================================| 100% Executing SQL took 0.0215 secs performanceId: 1 Inserting attrition for performance 1 Inserting data took 0.0125 secs Adding PredictionDistribution Inserting predictionDistribution for performance 1 Inserting data took 0.0294 secs Adding ThresholdSummary Inserting thresholdSummary for performance 1 Inserting data took 0.0236 secs Adding EvaluationStatistics Inserting evaluationSummary for performance 1 Inserting data took 0.0102 secs Adding CalibrationSummary Inserting calibrationSummary for performance 1 Inserting data took 0.0186 secs Adding DemographicSummary Inserting demographicSummary for performance 1 Inserting data took 0.0135 secs Restricting to covariates included in model Inserting covariateSummary for result 1 Inserting data took 0.0161 secs Connecting using SQLite driver TAR exists tarId: 1 json in jsons:TRUE Cohort Cohort: 3 exists in cohort_definition with cohort id3 Cohort Cohort: 3 exists in cohorts with cohort id1 tId: 1 json in jsons:TRUE Cohort Cohort: 4 exists in cohort_definition with cohort id4 Cohort Cohort: 4 exists in cohorts with cohort id2 oId: 2 Population settings exists popSetId: 1 Covariate setting exists covSetId: 1 Model setting exists modSetId: 1 Split setting exists plpDataSetId: 1 feature engineering setting exists FESetId: 1 sample setting exists sampleSetId: 1 tidy covariates setting exists tidySetId: 1 Split setting exists splitId: 1 modelDesignId: 1 Database meta data already exists Database1 already exists |===========================================================| 100% Executing SQL took 0.0329 secs diagnosticId: 1 Adding DiagnosticSummary Inserting data took 0.00931 secs Adding DiagnosticParticipants Adding DiagnosticPredictors Inserting data took 0.0117 secs Adding DiagnosticOutcomes Inserting data took 0.0095 secs Adding DiagnosticDesigns Connecting using SQLite driver Loading required package: shiny

Listening on http://127.0.0.1:3129 [1] "model design: 1" Warning: Error in dplyr::relocate: Can't subset columns that don't exist. ✖ Column 1.2 doesn't exist. 79: <Anonymous> 78: signalCondition 77: signal_abort 76: cnd_signal 75: handlers[[1L]] 74: <Anonymous> 73: signalCondition 72: signal_abort 71: abort 70: stop_subscript 69: stop_subscript_oob 68: <Anonymous> 67: vctrs::vec_as_location 66: chr_as_locations 65: as_indices_impl 64: as_indices_sel_impl 63: walk_data_tree 62: reduce_sels 61: eval_c 60: walk_data_tree 59: vars_select_eval 55: eval_select_impl 54: tidyselect::eval_select 53: eval_relocate 52: relocate.data.frame 51: dplyr::relocate 50: %>% 49: getDiagnostics 48: :: shiny observe 47: 4: shiny::runApp 3: ShinyAppBuilder::viewShiny 2: viewPlps 1: viewPlp

Jun 21 '23 17:06 kzollove