README.md

In ohdsi-studies/TkrPredictSimple: Add the title of the package here

Predicting 90-day mortality following total knee replacement

• Analytics use case(s): Patient-Level Prediction
• Study type: Clinical Application
• Tags: Study-a-thon, COVID-19
• Study lead: Jenna Reps, Ross Williams
• Study lead forums tag: jreps, RossW,
• Study start date: Dec 16, 2018
• Study end date: -
• Protocol: Link
• Publications: -
• Results explorer: Link

The objective of this study is to develop and validate various patient-level prediction models for total knee replacement patients.

Introduction

This repo contains the simple models needed for validation of the Oxford Ehden study-athon simple models to predict mortality following a total knee replacement

Features

• Validates the full models developed in Thin and OptumDod as well as a user designed simple and a data driven simple developed in optumDod

• Included in the package are 4 models they are:

  • Analysis_1: the full mdoel developed in optumDod
  • Analysis_1001: the simple model using user defined inputs
  • Analysis_1002: the simple model using data driven development methods (high penalisation)
  • Analysis_2: the full model developed on THIN

Technology

oxfordKneeValidation is an R package.

System Requirements

Requires R (version 3.3.0 or higher).

Dependencies

• PatientLevelPrediction

Getting Started

1. In R, use the following commands to run the study:

```r library(oxfordKneeValidation)

USER INPUTS

=======================

Specify where the temporary files (used by the ff package) will be created:

options(andromedatempdir = "S://temp//tempandromeda")

The folder where the study intermediate and result files will be written:

outputFolder <- "./tkrSimpleResults"

dbms <- user <- pw <- server <- port <-

connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = dbms, server = server, user = user, password = pw, port = port)

Add the database containing the OMOP CDM data

cdmDatabaseSchema <- ''

Add the name of database containing the OMOP CDM data

cdmDatabaseName <- ''

Add a database with read/write access as this is where the cohorts will be generated

cohortDatabaseSchema <- '' oracleTempSchema <- NULL

table name where the cohorts will be generated

cohortTable <- 'tkrSimpleTest'

============== Pick Study Parts To Run: ===========

createCohorts = FALSE predictTkrSimple = TRUE runValidation = TRUE

packageResults = TRUE

minCellCount <- 5 sampleSize <- NULL

============== Pick T and O cohorts ===========

[option 1] use default cohorts

usePackageCohorts <- TRUE newTargetCohortId <- NULL newOutcomeCohortId <- NULL newCohortDatabaseSchema <- NULL newCohortTable <- NULL

=======================

TAR settings - recommended to not edit

=======================

riskWindowStart <- 0 startAnchor <- 'cohort start' riskWindowEnd <- 90 endAnchor <- 'cohort start' firstExposureOnly <- F removeSubjectsWithPriorOutcome <- F priorOutcomeLookback <- 99999 requireTimeAtRisk <- F minTimeAtRisk <- 1 includeAllOutcomes <- T

execute(connectionDetails = connectionDetails, usePackageCohorts = usePackageCohorts, newTargetCohortId = newTargetCohortId, newOutcomeCohortId = newOutcomeCohortId, newCohortDatabaseSchema = newCohortDatabaseSchema, newCohortTable = newCohortTable, cdmDatabaseSchema = cdmDatabaseSchema, cdmDatabaseName = cdmDatabaseName, cohortDatabaseSchema = cohortDatabaseSchema, cohortTable = cohortTable, sampleSize = sampleSize, riskWindowStart = riskWindowStart, startAnchor = startAnchor, riskWindowEnd = riskWindowEnd, endAnchor = endAnchor, firstExposureOnly = firstExposureOnly, removeSubjectsWithPriorOutcome = removeSubjectsWithPriorOutcome, priorOutcomeLookback = priorOutcomeLookback, requireTimeAtRisk = requireTimeAtRisk, minTimeAtRisk = minTimeAtRisk, includeAllOutcomes = includeAllOutcomes, outputFolder = outputFolder, createCohorts = createCohorts, predictTkrSimple = predictTkrSimple, runValidation = runValidation, packageResults = packageResults, minCellCount = minCellCount, verbosity = "INFO", cdmVersion = 5)

```

License

oxfordKneeValidation is licensed under Apache License 2.0

Development

oxfordKneeValidation is being developed in R Studio.

ohdsi-studies/TkrPredictSimple documentation built on Sept. 10, 2020, 8:17 p.m.