Nothing
## ----setup, include=FALSE-----------------------------------------------------
suppressWarnings({
suppressPackageStartupMessages({
loadNamespace("knitr") # for opts_chunk only
library("icd")
library("magrittr")
})
})
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----uranium-long-------------------------------------------------------------
uranium_pathology[1:10, ]
## ----explain10----------------------------------------------------------------
explain_code("R55")
## ----uranium-wide-------------------------------------------------------------
head(uranium_pathology)
## ----comorbidities------------------------------------------------------------
quan_comorbidities <- comorbid(uranium_pathology, icd10_map_quan_elix)
# see the first few rows and columns:
quan_comorbidities[1:6, c(1, 3:10)]
## ----tidy---------------------------------------------------------------------
comorbid_charlson(uranium_pathology, return_df = TRUE)[1:5, 1:5]
## ----big----------------------------------------------------------------------
# shuffle the rows:
set.seed(1441)
u <- uranium_pathology[sample(seq_len(nrow(uranium_pathology))), ]
head(u)
quan_comorbidities <- comorbid(u,
icd10_map_quan_elix,
return_df = TRUE,
return_binary = TRUE,
restore_id_order = FALSE)
# see the first few rows and columns:
quan_comorbidities[1:6, c(1, 3:9)]
## ----cholera------------------------------------------------------------------
# create trivial comorbidity map:
cholera_typhoid_map <- list(cholera = "A00", typhoid = "A01")
patients <- data.frame(patient = c("0001", "0001", "0002"),
code = c("A001234567", "A01", "A019"))
comorbid(patients , map = cholera_typhoid_map)
## ----htncx--------------------------------------------------------------------
icd10_map_quan_elix$HTNcx
## ----setuppcs, echo = FALSE---------------------------------------------------
n <- 10
nm <- "code"
set.seed(1441)
pcs_sample <- sample(unname(unlist(icd10_map_ahrq_pcs)), n)
pts <- data.frame(id = sample(LETTERS, n),
pc = pcs_sample)
res <- icd10_comorbid(pts,
map = icd10_map_ahrq_pcs,
icd_name = "pc",
return_binary = TRUE)
print(res)
colSums(res)
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