Package 'akiFlagger'

Flag patients for AKI

Description

Add in the AKI column in a patient dataframe according to the KDIGO criterion

Usage

returnAKIpatients(
  dataframe,
  HB_trumping = FALSE,
  eGFR_impute = FALSE,
  window1 = as.difftime(2, units = "days"),
  window2 = as.difftime(7, units = "days"),
  add_min_creat = FALSE,
  add_baseline_creat = FALSE
)

Arguments

dataframe	patient dataset
HB_trumping	boolean on whether to have historical baseline creatinine values trump the local minimum creatinine values
eGFR_impute	boolean on whether to impute missing baseline creatinine values with CKD-EPI equation
window1	rolling window length of the shorter time window; defaults to 48 hours
window2	rolling window length of the longer time window; defaults to 162 hours
add_min_creat	boolean on whether to add the intermediate columns generated during calculation
add_baseline_creat	boolean on whether to add the baseline creatinine values in

Value

patient dataset with AKI column added in

#Imports

Examples

returnAKIpatients(toy)

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Toy dataset

Description

Since real patient data is probably protected health information (PHI), this toy dataset contains all the relevant columns the flagger takes in.

Usage

toy

Format

A data frame (1078 x 6) consisting of relevant AKI measurements for patients

patient_id

int, the patient identifier

enc

int, the encounter identifier

inpatient

boolean, whether or not the creatinine measurement taken was an inpatient measurement

admission

POSIXct, the time the patient was admitted

time

POSIXct, the time at which the creatinine measurement was taken

creatinine

float, the creatinine value of the measurement taken

@source http://akiflagger.readthedocs.io/

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