README.md
In maciejrosolowski/progressdatenbankderivate: Extract and Process Data from the Database of the PROGESS Study
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")$out[
, .(PATSTUID, EVENT, psi)]
)
psi_d0
#> PATSTUID EVENT psi
#> 1: 5635 3 1
#> 2: 5656 3 3
#> 3: 5663 3 NA
#> 4: 5674 3 4
#> 5: 5681 3 NA
#> ---
#> 2209: 238909 3 NA
#> 2210: 240062 3 NA
#> 2211: 242021 3 NA
#> 2212: 244008 3 NA
#> 2213: 9435 3 NA
SIRS
suppressWarnings(
sirs_d0 <- sirs.fct(DID_PROBAND, FRM_BAS, FRM_BEF, FRM_B24, FRM_DIL_LABORWERTE,
DID_CLIN, FRM_RR, FRM_KAT, zp_fabian = "d0")$out[
, .(PATSTUID, EVENT, sirs = infec.septic.servsept,
schock = septischer.schock)]
)
sirs_d0
#> PATSTUID EVENT sirs schock
#> 1: 5635 3 2 FALSE
#> 2: 5656 3 2 FALSE
#> 3: 5663 3 NA NA
#> 4: 5674 3 1 FALSE
#> 5: 5681 3 NA NA
#> ---
#> 2209: 238909 3 NA NA
#> 2210: 240062 3 NA NA
#> 2211: 242021 3 NA NA
#> 2212: 244008 3 NA NA
#> 2213: 9435 3 NA NA
quickSOFA
suppressWarnings(
qsofa <- quickSOFA(FRM_RR, FRM_B24, FRM_BEF, DID_CLIN,
zp_fabian = "auf_in_d0")$out
)
qsofa[, .(PATSTUID, EVENT, qSOFA)]
#> PATSTUID EVENT qSOFA
#> 1: 1564 31 1
#> 2: 1591 31 0
#> 3: 1680 31 1
#> 4: 1740 31 2
#> 5: 1790 31 0
#> ---
#> 2209: 88954 31 NA
#> 2210: 184339 31 NA
#> 2211: 231590 31 NA
#> 2212: 231626 31 NA
#> 2213: 242021 31 NA
Halm
suppressWarnings(
halm <- HalmScore(FRM_B24, FRM_BEF, FRM_RR, FRM_O2A, FRM_O2P, FRM_BEAT,
DID_CLIN, zp_fabian = "auf_in_d-1_in_d0")$out[
, .(PATSTUID, EVENT, halm)
]
)
halm
#> PATSTUID EVENT halm
#> 1: 1564 321 1
#> 2: 1586 321 NA
#> 3: 1591 321 1
#> 4: 1680 321 3
#> 5: 1740 321 2
#> ---
#> 2209: 243434 321 3
#> 2210: 243708 321 3
#> 2211: 243719 321 4
#> 2212: 244008 321 NA
#> 2213: 9435 321 NA
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")$out[, .(PATSTUID, EVENT, SCAP)]
)
scap
#> PATSTUID EVENT SCAP
#> 1: 1564 321 0
#> 2: 1586 321 NA
#> 3: 1591 321 0
#> 4: 1680 321 5
#> 5: 1740 321 21
#> ---
#> 2209: 243434 321 6
#> 2210: 243708 321 11
#> 2211: 243719 321 11
#> 2212: 244008 321 NA
#> 2213: 9435 321 NA
smartCOP
suppressWarnings(
smart_cop <- smartCOP(FRM_RR, FRM_BEF, FRM_VIS, FRM_DIL_LABORWERTE, FRM_B24,
DID_PROBAND, DID_CLIN, DID_OXYGENIND_SINGLE,
FRM_O2A, zp_fabian = "auf_in_d-1_in_d0")$out[
, .(PATSTUID, EVENT, smartCOP)]
)
smart_cop
#> PATSTUID EVENT smartCOP
#> 1: 1564 321 0
#> 2: 1591 321 2
#> 3: 1680 321 1
#> 4: 1740 321 3
#> 5: 1790 321 2
#> ---
#> 2209: 88954 321 NA
#> 2210: 184339 321 NA
#> 2211: 231590 321 NA
#> 2212: 231626 321 NA
#> 2213: 242021 321 NA
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
#> PATSTUID EVENT crb crb65 curb curb65
#> 1: 5635 3 0 0 0 0
#> 2: 5656 3 0 1 0 1
#> 3: 5663 3 NA NA NA NA
#> 4: 5674 3 1 2 2 3
#> 5: 5681 3 NA NA NA NA
#> ---
#> 2209: 238909 3 NA NA NA NA
#> 2210: 240062 3 NA NA NA NA
#> 2211: 242021 3 NA NA NA NA
#> 2212: 244008 3 NA NA NA NA
#> 2213: 9435 3 NA NA NA NA
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
#> [1] 5
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
#> [1] 5 4
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
#> $infec.septic.servsept
#> [1] 3
#>
#> $shock
#> [1] FALSE
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
#> [1] 3
maciejrosolowski/progressdatenbankderivate documentation built on Nov. 29, 2024, 3:39 a.m.
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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
#> PATSTUID EVENT psi
#> 1: 5635 3 1
#> 2: 5656 3 3
#> 3: 5663 3 NA
#> 4: 5674 3 4
#> 5: 5681 3 NA
#> ---
#> 2209: 238909 3 NA
#> 2210: 240062 3 NA
#> 2211: 242021 3 NA
#> 2212: 244008 3 NA
#> 2213: 9435 3 NA
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")$out[
, .(PATSTUID, EVENT, sirs = infec.septic.servsept,
schock = septischer.schock)]
)
sirs_d0
#> PATSTUID EVENT sirs schock
#> 1: 5635 3 2 FALSE
#> 2: 5656 3 2 FALSE
#> 3: 5663 3 NA NA
#> 4: 5674 3 1 FALSE
#> 5: 5681 3 NA NA
#> ---
#> 2209: 238909 3 NA NA
#> 2210: 240062 3 NA NA
#> 2211: 242021 3 NA NA
#> 2212: 244008 3 NA NA
#> 2213: 9435 3 NA NA
quickSOFA
suppressWarnings(
qsofa <- quickSOFA(FRM_RR, FRM_B24, FRM_BEF, DID_CLIN,
zp_fabian = "auf_in_d0")$out
)
qsofa[, .(PATSTUID, EVENT, qSOFA)]
#> PATSTUID EVENT qSOFA
#> 1: 1564 31 1
#> 2: 1591 31 0
#> 3: 1680 31 1
#> 4: 1740 31 2
#> 5: 1790 31 0
#> ---
#> 2209: 88954 31 NA
#> 2210: 184339 31 NA
#> 2211: 231590 31 NA
#> 2212: 231626 31 NA
#> 2213: 242021 31 NA
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")$out[
, .(PATSTUID, EVENT, halm)
]
)
halm
#> PATSTUID EVENT halm
#> 1: 1564 321 1
#> 2: 1586 321 NA
#> 3: 1591 321 1
#> 4: 1680 321 3
#> 5: 1740 321 2
#> ---
#> 2209: 243434 321 3
#> 2210: 243708 321 3
#> 2211: 243719 321 4
#> 2212: 244008 321 NA
#> 2213: 9435 321 NA
SCAP
suppressWarnings(
scap <- SCAP(FRM_B24, FRM_O2A, FRM_RR, FRM_BEF, FRM_DIL_LABORWERTE, DID_CLIN,
DID_PROBAND, FRM_VIS, DID_OXYGENIND_SINGLE,
zp_fabian = "auf_in_d-1_in_d0")$out[, .(PATSTUID, EVENT, SCAP)]
)
scap
#> PATSTUID EVENT SCAP
#> 1: 1564 321 0
#> 2: 1586 321 NA
#> 3: 1591 321 0
#> 4: 1680 321 5
#> 5: 1740 321 21
#> ---
#> 2209: 243434 321 6
#> 2210: 243708 321 11
#> 2211: 243719 321 11
#> 2212: 244008 321 NA
#> 2213: 9435 321 NA
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")$out[
, .(PATSTUID, EVENT, smartCOP)]
)
smart_cop
#> PATSTUID EVENT smartCOP
#> 1: 1564 321 0
#> 2: 1591 321 2
#> 3: 1680 321 1
#> 4: 1740 321 3
#> 5: 1790 321 2
#> ---
#> 2209: 88954 321 NA
#> 2210: 184339 321 NA
#> 2211: 231590 321 NA
#> 2212: 231626 321 NA
#> 2213: 242021 321 NA
CRB, CRB65, CURB, CURB65
suppressWarnings(
curb65 <- curb65.fct(DID_PROBAND, FRM_BEF, FRM_B24, FRM_DIL_LABORWERTE,
FRM_RR, FRM_BEAT = NULL, zp_fabian = "d0")$out[,
.(PATSTUID, EVENT, crb, crb65, curb, curb65)]
)
curb65
#> PATSTUID EVENT crb crb65 curb curb65
#> 1: 5635 3 0 0 0 0
#> 2: 5656 3 0 1 0 1
#> 3: 5663 3 NA NA NA NA
#> 4: 5674 3 1 2 2 3
#> 5: 5681 3 NA NA NA NA
#> ---
#> 2209: 238909 3 NA NA NA NA
#> 2210: 240062 3 NA NA NA NA
#> 2211: 242021 3 NA NA NA NA
#> 2212: 244008 3 NA NA NA NA
#> 2213: 9435 3 NA NA NA NA
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
#> [1] 5
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
#> [1] 5 4
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
#> $infec.septic.servsept
#> [1] 3
#>
#> $shock
#> [1] FALSE
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
#> [1] 3
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