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process_1.R
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process_1.R
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# # # # # # # # # # # # # # # # # # # # #
# This script: #
# define case cohort #
# # # # # # # # # # # # # # # # # # # # #
## Import libraries---
library("tidyverse")
library('plyr')
library('dplyr')
library('lubridate')
library('stringr')
library("data.table")
library("ggpubr")
library("finalfit")
# import data
col_spec_1 <-cols_only(patient_index_date = col_date(format = ""),
age = col_number(),
sex = col_character(),
stp = col_character(),
region = col_character(),
has_outcome_1yr = col_number(),
uti_record = col_number(),
lrti_record = col_number(),
urti_record = col_number(),
sinusitis_record = col_number(),
ot_externa_record = col_number(),
ot_media_record = col_number(),
pneumonia_record = col_number(),
cancer_comor = col_integer(),
cardiovascular_comor = col_integer(),
chronic_obstructive_pulmonary_comor = col_integer(),
heart_failure_comor = col_integer(),
connective_tissue_comor = col_integer(),
dementia_comor = col_integer(),
diabetes_comor = col_integer(),
diabetes_complications_comor = col_integer(),
hemiplegia_comor = col_integer(),
hiv_comor = col_integer(),
metastatic_cancer_comor = col_integer(),
mild_liver_comor = col_integer(),
mod_severe_liver_comor = col_integer(),
mod_severe_renal_comor = col_integer(),
mi_comor = col_integer(),
peptic_ulcer_comor = col_integer(),
peripheral_vascular_comor = col_integer(),
patient_id = col_number()
)
col_spec_2 <-cols_only(patient_index_date = col_date(format = ""),
age = col_number(),
sex = col_character(),
stp = col_character(),
region = col_character(),
has_outcome_1yr = col_number(),
has_outcome_6weekafter = col_number(),
uti_record = col_number(),
lrti_record = col_number(),
urti_record = col_number(),
sinusitis_record = col_number(),
ot_externa_record = col_number(),
ot_media_record = col_number(),
pneumonia_record = col_number(),
cancer_comor = col_integer(),
cardiovascular_comor = col_integer(),
chronic_obstructive_pulmonary_comor = col_integer(),
heart_failure_comor = col_integer(),
connective_tissue_comor = col_integer(),
dementia_comor = col_integer(),
diabetes_comor = col_integer(),
diabetes_complications_comor = col_integer(),
hemiplegia_comor = col_integer(),
hiv_comor = col_integer(),
metastatic_cancer_comor = col_integer(),
mild_liver_comor = col_integer(),
mod_severe_liver_comor = col_integer(),
mod_severe_renal_comor = col_integer(),
mi_comor = col_integer(),
peptic_ulcer_comor = col_integer(),
peripheral_vascular_comor = col_integer(),
patient_id = col_number()
)
df <- read_csv(here::here("output", "input_case.csv"),
col_types = col_spec_1)
df_match <- read_csv(here::here("output", "input_control.csv"),
col_types = col_spec_2)
# filter cohort (defalut)
df = df %>% filter(!is.na(patient_index_date))
# check cohort_case
dttable <- select(df,age,sex,stp,region,has_outcome_1yr,uti_record,lrti_record,urti_record,sinusitis_record,ot_externa_record,
ot_media_record,pneumonia_record)
colsfortab <- colnames(dttable)
dttable %>% summary_factorlist(explanatory = colsfortab) -> t
write_csv(t, here::here("output", "table_case_0.csv"))
df_1 <- df %>% filter(has_outcome_1yr == "0")
dttable_1 <- select(df_1,age,sex,stp,region,uti_record,lrti_record,urti_record,sinusitis_record,ot_externa_record,
ot_media_record,pneumonia_record)
colsfortab_1 <- colnames(dttable_1)
dttable_1 %>% summary_factorlist(explanatory = colsfortab_1) -> t1
write_csv(t1, here::here("output", "table_case_1.csv"))
# filter cohort (defalut)
df_match = df_match %>% filter(!is.na(patient_index_date))
# check cohort_control
dt <- select(df_match,age,sex,stp,region,has_outcome_1yr,has_outcome_6weekafter,uti_record,lrti_record,urti_record,sinusitis_record,ot_externa_record,
ot_media_record,pneumonia_record)
coldt <- colnames(dt)
dt %>% summary_factorlist(explanatory = coldt) -> t2
write_csv(t2, here::here("output", "table_control_0.csv"))
df_match_1 <- df_match %>% filter(has_outcome_6weekafter == "0")
df_match_1 <- df_match_1 %>% filter(has_outcome_1yr == "0")
dt_1 <- select(df_match_1,age,sex,stp,region,uti_record,lrti_record,urti_record,sinusitis_record,ot_externa_record,
ot_media_record,pneumonia_record)
coldt_1 <- colnames(dt_1)
dt_1 %>% summary_factorlist(explanatory = coldt_1) -> t3
write_csv(t3, here::here("output", "table_control_1.csv"))
## select urti for matching ##
case_csv <- df_1 %>% filter (urti_record == "1")
match_csv <- df_match_1 %>% filter (urti_record == "1")
## create charlson index
case_csv$cancer_comor<- ifelse(case_csv$cancer_comor == 1L, 2L, 0L)
case_csv$cardiovascular_comor <- ifelse(case_csv$cardiovascular_comor == 1L, 1L, 0L)
case_csv$chronic_obstructive_pulmonary_comor <- ifelse(case_csv$chronic_obstructive_pulmonary_comor == 1L, 1L, 0)
case_csv$heart_failure_comor <- ifelse(case_csv$heart_failure_comor == 1L, 1L, 0L)
case_csv$connective_tissue_comor <- ifelse(case_csv$connective_tissue_comor == 1L, 1L, 0L)
case_csv$dementia_comor <- ifelse(case_csv$dementia_comor == 1L, 1L, 0L)
case_csv$diabetes_comor <- ifelse(case_csv$diabetes_comor == 1L, 1L, 0L)
case_csv$diabetes_complications_comor <- ifelse(case_csv$diabetes_complications_comor == 1L, 2L, 0L)
case_csv$hemiplegia_comor <- ifelse(case_csv$hemiplegia_comor == 1L, 2L, 0L)
case_csv$hiv_comor <- ifelse(case_csv$hiv_comor == 1L, 6L, 0L)
case_csv$metastatic_cancer_comor <- ifelse(case_csv$metastatic_cancer_comor == 1L, 6L, 0L)
case_csv$mild_liver_comor <- ifelse(case_csv$mild_liver_comor == 1L, 1L, 0L)
case_csv$mod_severe_liver_comor <- ifelse(case_csv$mod_severe_liver_comor == 1L, 3L, 0L)
case_csv$mod_severe_renal_comor <- ifelse(case_csv$mod_severe_renal_comor == 1L, 2L, 0L)
case_csv$mi_comor <- ifelse(case_csv$mi_comor == 1L, 1L, 0L)
case_csv$peptic_ulcer_comor <- ifelse(case_csv$peptic_ulcer_comor == 1L, 1L, 0L)
case_csv$peripheral_vascular_comor <- ifelse(case_csv$peripheral_vascular_comor == 1L, 1L, 0L)
## total charlson for each patient
charlson=c("cancer_comor","cardiovascular_comor","chronic_obstructive_pulmonary_comor",
"heart_failure_comor","connective_tissue_comor", "dementia_comor",
"diabetes_comor","diabetes_complications_comor","hemiplegia_comor",
"hiv_comor","metastatic_cancer_comor" ,"mild_liver_comor",
"mod_severe_liver_comor", "mod_severe_renal_comor", "mi_comor",
"peptic_ulcer_comor" , "peripheral_vascular_comor" )
case_csv$charlson_score=rowSums(case_csv[charlson])
## Charlson - as a catergorical group variable
case_csv <- case_csv %>%
mutate(charlsonGrp = case_when(charlson_score >0 & charlson_score <=2 ~ 2,
charlson_score >2 & charlson_score <=4 ~ 3,
charlson_score >4 & charlson_score <=6 ~ 4,
charlson_score >=7 ~ 5,
charlson_score == 0 ~ 1))
case_csv$charlsonGrp <- as.factor(case_csv$charlsonGrp)
case_csv$charlsonGrp <- factor(case_csv$charlsonGrp,
labels = c("zero", "low", "medium", "high", "very high"))
case_csv <- select(case_csv,-all_of(charlson))
write_csv(case_csv, here::here("output", "case_csv.csv"))
## create charlson index
match_csv$cancer_comor<- ifelse(match_csv$cancer_comor == 1L, 2L, 0L)
match_csv$cardiovascular_comor <- ifelse(match_csv$cardiovascular_comor == 1L, 1L, 0L)
match_csv$chronic_obstructive_pulmonary_comor <- ifelse(match_csv$chronic_obstructive_pulmonary_comor == 1L, 1L, 0)
match_csv$heart_failure_comor <- ifelse(match_csv$heart_failure_comor == 1L, 1L, 0L)
match_csv$connective_tissue_comor <- ifelse(match_csv$connective_tissue_comor == 1L, 1L, 0L)
match_csv$dementia_comor <- ifelse(match_csv$dementia_comor == 1L, 1L, 0L)
match_csv$diabetes_comor <- ifelse(match_csv$diabetes_comor == 1L, 1L, 0L)
match_csv$diabetes_complications_comor <- ifelse(match_csv$diabetes_complications_comor == 1L, 2L, 0L)
match_csv$hemiplegia_comor <- ifelse(match_csv$hemiplegia_comor == 1L, 2L, 0L)
match_csv$hiv_comor <- ifelse(match_csv$hiv_comor == 1L, 6L, 0L)
match_csv$metastatic_cancer_comor <- ifelse(match_csv$metastatic_cancer_comor == 1L, 6L, 0L)
match_csv$mild_liver_comor <- ifelse(match_csv$mild_liver_comor == 1L, 1L, 0L)
match_csv$mod_severe_liver_comor <- ifelse(match_csv$mod_severe_liver_comor == 1L, 3L, 0L)
match_csv$mod_severe_renal_comor <- ifelse(match_csv$mod_severe_renal_comor == 1L, 2L, 0L)
match_csv$mi_comor <- ifelse(match_csv$mi_comor == 1L, 1L, 0L)
match_csv$peptic_ulcer_comor <- ifelse(match_csv$peptic_ulcer_comor == 1L, 1L, 0L)
match_csv$peripheral_vascular_comor <- ifelse(match_csv$peripheral_vascular_comor == 1L, 1L, 0L)
match_csv$charlson_score=rowSums(match_csv[charlson])
## Charlson - as a catergorical group variable
match_csv <- match_csv %>%
mutate(charlsonGrp = case_when(charlson_score >0 & charlson_score <=2 ~ 2,
charlson_score >2 & charlson_score <=4 ~ 3,
charlson_score >4 & charlson_score <=6 ~ 4,
charlson_score >=7 ~ 5,
charlson_score == 0 ~ 1))
match_csv$charlsonGrp <- as.factor(match_csv$charlsonGrp)
match_csv$charlsonGrp <- factor(match_csv$charlsonGrp,
labels = c("zero", "low", "medium", "high", "very high"))
match_csv <- select(match_csv,-all_of(charlson))
write_csv(match_csv, here::here("output", "match_csv.csv"))