In maciejrosolowski/progressdatenbankderivate: Extract and Process Data from the Database of the PROGESS Study

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

progressdatenbankderivate

The goal of progressdatenbankderivate is to extract data from an excel file containing an export from the database of the PROGRESS project and to compute several pneumonia scores based on this data.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("maciejrosolowski/progressdatenbankderivate")

Example

Read the data exported from the database of the PROGRESS project.

library(readxl)
library(data.table)
library(progressdatenbankderivate)
excel_fn <- paste0("/net/ifs2/san_projekte/projekte/", 
                   "PROGRESS/Datenmanagement/Data_freezes/", 
                   "20190320/PROGRESS-freeze_201903_01.xlsx")
DID_PROBAND <- readxl::read_excel(excel_fn, 'DID_PROBAND')
FRM_BAS <- readxl::read_excel(excel_fn, 'FRM_BAS')
FRM_BEF <- readxl::read_excel(excel_fn, 'FRM_BEF')
FRM_B24 <- readxl::read_excel(excel_fn, 'FRM_B24')
FRM_RR <- readxl::read_excel(excel_fn, 'FRM_RR', guess_max = 10e5)
FRM_O2A <- readxl::read_excel(excel_fn, 'FRM_O2A')
FRM_DIL_LABORWERTE <- readxl::read_excel(excel_fn, "FRM_DIL_LABORWERTE")
FRM_VIS <- readxl::read_excel(excel_fn, 'FRM_VIS')
DID_CLIN <- readxl::read_excel(excel_fn, 'DID_CLIN')
FRM_KAT <- readxl::read_excel(excel_fn, 'FRM_KAT')
FRM_O2P <- readxl::read_excel(excel_fn, 'FRM_O2P')
FRM_BEAT <- readxl::read_excel(excel_fn, 'FRM_BEAT', guess_max = 10e5)
DID_OXYGENIND_SINGLE <- readxl::read_excel(excel_fn, 'DID_OXYGENIND_SINGLE')
data.table::setDT(DID_PROBAND)
data.table::setDT(FRM_BAS)
data.table::setDT(FRM_BEF)
data.table::setDT(FRM_B24)
data.table::setDT(FRM_RR)
data.table::setDT(FRM_O2A)
data.table::setDT(FRM_DIL_LABORWERTE)
data.table::setDT(FRM_VIS)
data.table::setDT(DID_CLIN)
data.table::setDT(FRM_KAT)
data.table::setDT(FRM_O2P)
data.table::setDT(FRM_BEAT)
data.table::setDT(DID_OXYGENIND_SINGLE)

PSI

This is an example which shows how to compute the Pneumonia Severity Index (PSI):

# suppress warnings about no non-missing values while computing min or max
# by PATSTUID and EVENT.
suppressWarnings(
  psi_d0 <- psi.fct(DID_PROBAND, FRM_BAS, FRM_BEF, FRM_B24, FRM_RR, FRM_O2A, 
                    FRM_DIL_LABORWERTE,FRM_VIS, zp_fabian = "d0")$out[
                      , .(PATSTUID, EVENT, psi)]
)
psi_d0

SIRS

suppressWarnings(
  sirs_d0 <- sirs.fct(DID_PROBAND, FRM_BAS, FRM_BEF, FRM_B24, FRM_DIL_LABORWERTE,
                      DID_CLIN, FRM_RR, FRM_KAT, zp_fabian = "d0")$out[
                        , .(PATSTUID, EVENT, sirs = infec.septic.servsept,
                   schock = septischer.schock)]
)
sirs_d0

quickSOFA

suppressWarnings(
  qsofa <- quickSOFA(FRM_RR, FRM_B24, FRM_BEF, DID_CLIN,
                     zp_fabian = "auf_in_d0")$out
)
qsofa[, .(PATSTUID, EVENT, qSOFA)]

Halm

suppressWarnings(
  halm <- HalmScore(FRM_B24, FRM_BEF, FRM_RR, FRM_O2A, FRM_O2P, FRM_BEAT,
                    DID_CLIN, zp_fabian = "auf_in_d-1_in_d0")$out[
                      , .(PATSTUID, EVENT, halm)
                    ]
)
halm

SCAP

suppressWarnings(
  scap <- SCAP(FRM_B24, FRM_O2A, FRM_RR, FRM_BEF, FRM_DIL_LABORWERTE, DID_CLIN,
               DID_PROBAND, FRM_VIS, DID_OXYGENIND_SINGLE,
               zp_fabian = "auf_in_d-1_in_d0")$out[, .(PATSTUID, EVENT, SCAP)]
)
scap

smartCOP

suppressWarnings(
  smart_cop <- smartCOP(FRM_RR, FRM_BEF, FRM_VIS, FRM_DIL_LABORWERTE, FRM_B24,
                        DID_PROBAND, DID_CLIN, DID_OXYGENIND_SINGLE,
                        FRM_O2A, zp_fabian = "auf_in_d-1_in_d0")$out[
                          , .(PATSTUID, EVENT, smartCOP)]
)
smart_cop

CRB, CRB65, CURB, CURB65

suppressWarnings(
  curb65 <- curb65.fct(DID_PROBAND, FRM_BEF, FRM_B24, FRM_DIL_LABORWERTE, 
                       FRM_RR, FRM_BEAT = NULL, zp_fabian = "d0")$out[,
                         .(PATSTUID, EVENT, crb, crb65, curb, curb65)]
)
curb65

How to compute the scores based on values of the input parameters

PSI

psi <- psi_simple(
  age = 68,
  verwirrt = 1,
  hfrq.max = 130,
  afrq.max = 35,
  sysbp.min = 80,
  temp.min = 34,
  temp.max = 35,
  tumor = 1,
  herz = 1,
  cerebro = 1,
  renal = 1,
  liver = 1,
  gender = 1,
  nurse.home = 1,
  art.ph.min = 7.2,
  bun = 10,
  snat = 120,
  gluk = 16,
  haemkrt = 0.2,
  apo2.min = 50,
  pleu_erg = 1)
psi

An example with vectors as arguments in the function call

psi <- psi_simple(
  age = c(68, 61),
  verwirrt = c(1, 0),
  hfrq.max = c(130, 125),
  afrq.max = c(35, 26),
  sysbp.min = c(80, 98),
  temp.min = c(34, 36),
  temp.max = c(35, 37),
  tumor = c(1, 0),
  herz = c(1, 0),
  cerebro = c(1, 0),
  renal = c(1, 0),
  liver = c(1, 0),
  gender = c(1, 0),
  nurse.home = c(1, 0),
  art.ph.min = c(7.2, 7.5),
  bun = c(10, 11),
  snat = c(120, 134),
  gluk = c(16, 9),
  haemkrt = c(0.2, 0.25),
  apo2.min = c(50, 52),
  pleu_erg = c(1, 0))
psi

SIRS

sirs <- sirs_simple(
  temp.min = 34,
  temp.max = 35,
  hfrq.max = 104,
  afrq.max = 20,
  pco2 = 4.1,
  leuko_min = 7800,
  leuko_max = 7900,
  stkern.neutro = 395,
  smkern.neutro = 4424,
  verwirrt = 1,
  thrombo_min = 216000,
  thrombo.daybefore = 205000,
  oxi.ind = 43.81,
  chr.lunge = 1,
  diur = 3120,
  gewicht = 70,
  bemin = 3.4,
  sysbp.min = 95,
  map = 10.44,
  kate = FALSE)
sirs

Halm

halm <- HalmScore_simple(
  hfrq.max = 104,
  sysbp.min = 95,
  afrq.max = 19,
  o2p.min = 90,
  apo2.min = 50,
  bea = 1,
  sauerst = 0,
  temp.max = 38,
  verwirrt = 0,
  gcs = 15)
halm