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n2006.Rmd
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n2006.Rmd
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---
title: "bita_nis06"
output: word_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
BITA / LITA , NIS: 2006
```{r}
library(haven);library(tidyverse);library(MASS);library(survey)
```
```{r read the raw df into the document}
df <- read_csv("/Volumes/SVD2/cabg_pci/n2006mod.csv")
```
Now, prior to further analysis, remove the variables that are not needed in this study.
Also:
1. Keep only primary surgery; remove patients with prior CABG
2. Remove patients with concomitant valve surgery
```{r}
n06 <- df
pricabg <- as.character(c("V4581")) # prior MI
a <- pricabg
n06$pricabg <- with(n06, ifelse((DX1 %in% a | DX2 %in% a | DX3 %in% a | DX4 %in% a | DX4 %in% a | DX5 %in% a | DX6 %in% a | DX7 %in% a | DX8 %in% a | DX10 %in% a | DX11 %in% a | DX12 %in% a | DX13 %in% a | DX14 %in% a | DX15 %in% a ), "yes","no"))
n06 %>% count(pricabg)
```
Remove patients with prior CABG:
```{r remove prior CABG patients}
df2 <- n06 %>% filter(pricabg == "no")
dim(df2) # df2 contains only patients with primary CABG surgery and no prior CABG surgery.
```
```{r remove patients undergoing concomitant valve surgery}
# valve replacement/ valve repair
valve <- as.character(c('3511','3512','3513','3514','3521','3522','3523','3524','3526','3525','3527',
'3528'))
a <- valve
df2$valve <- with(df2, ifelse((PR1 %in% a | PR2 %in% a | PR3 %in% a | PR4 %in% a | PR4 %in% a | PR5 %in% a | PR6 %in% a | PR7 %in% a | PR8 %in% a | PR10 %in% a | PR11 %in% a | PR12 %in% a | PR13 %in% a | PR14 %in% a | PR15 %in% a), "yes","no"))
df2 %>% count(valve)
```
```{r remove valve patients too}
df3 <- df2 %>% filter(valve == "no")
dim(df3)
```
1. Keep only patients who underwent CABG; remove patients with underwent PCI:
```{r remove PCI patients}
df4 <- df3 %>% filter(cabg == "yes")
```
```{r change name of df to get more variables}
n06 <- df4
```
```{r prior conditions}
priormi <- as.character(c("412")) # prior MI
a <- priormi
n06$priormi <- with(n06, ifelse((DX1 %in% a | DX2 %in% a | DX3 %in% a | DX4 %in% a | DX4 %in% a | DX5 %in% a | DX6 %in% a | DX7 %in% a | DX8 %in% a | DX10 %in% a | DX11 %in% a | DX12 %in% a | DX13 %in% a | DX14 %in% a | DX15 %in% a ), "yes","no"))
table(n06$priormi)
```
```{r}
priorpci <- as.character(c("V4582")) # prior PCI
a <- priorpci
n06$priorpci <- with(n06, ifelse((DX1 %in% a | DX2 %in% a | DX3 %in% a | DX4 %in% a | DX4 %in% a | DX5 %in% a | DX6 %in% a | DX7 %in% a | DX8 %in% a | DX10 %in% a | DX11 %in% a | DX12 %in% a | DX13 %in% a | DX14 %in% a | DX15 %in% a), "yes","no"))
table(n06$priorpci)
```
```{r}
chf <- as.character('4280','4281','4282','4283','4284','4285','4286','4287','4288') # ICD9 codes for CHF
a <- chf
n06$chf <- with(n06, ifelse((DX1 %in% a | DX2 %in% a | DX3 %in% a | DX4 %in% a | DX4 %in% a | DX5 %in% a | DX6 %in% a | DX7 %in% a | DX8 %in% a | DX10 %in% a | DX11 %in% a | DX12 %in% a | DX13 %in% a | DX14 %in% a | DX15 %in% a), "yes","no"))
table(n06$chf)
```
```{r}
shock <- as.character(c("78551")) # prior CABG
a <- shock
n06$shock <- with(n06, ifelse((DX1 %in% a | DX2 %in% a | DX3 %in% a | DX4 %in% a | DX4 %in% a | DX5 %in% a | DX6 %in% a | DX7 %in% a | DX8 %in% a | DX10 %in% a | DX11 %in% a | DX12 %in% a | DX13 %in% a | DX14 %in% a | DX15 %in% a ), "yes","no"))
table(n06$shock)
```
```{r}
stemi <- as.character(c("41071")) # prior CABG
a <- stemi
n06$stemi <- with(n06, ifelse((DX1 %in% a | DX2 %in% a | DX3 %in% a | DX4 %in% a | DX4 %in% a | DX5 %in% a | DX6 %in% a | DX7 %in% a | DX8 %in% a | DX10 %in% a | DX11 %in% a | DX12 %in% a | DX13 %in% a | DX14 %in% a | DX15 %in% a ), "yes","no"))
n06 %>% count(stemi)
```
```{r change df name to get more variables }
df <- n06
```
```{r carotid disease}
carotid.d <- as.character(c("43310")) # carotid artery disease
a <- carotid.d
df$carotid <- with(df, ifelse((DX1 %in% a | DX2 %in% a | DX3 %in% a | DX4 %in% a | DX4 %in% a | DX5 %in% a | DX6 %in% a | DX7 %in% a | DX8 %in% a | DX10 %in% a | DX11 %in% a | DX12 %in% a | DX13 %in% a | DX14 %in% a | DX15 %in% a), "yes","no"))
table(df$carotid)
```
```{r}
pristroke <- as.character(c("V1254","4380")) # prior stroke
a <- pristroke
df$pristroke <- with(df, ifelse((DX1 %in% a | DX2 %in% a | DX3 %in% a | DX4 %in% a | DX4 %in% a | DX5 %in% a | DX6 %in% a | DX7 %in% a | DX8 %in% a | DX10 %in% a | DX11 %in% a | DX12 %in% a | DX13 %in% a | DX14 %in% a | DX15 %in% a ), "yes","no"))
table(df$pristroke)
```
```{r}
priicd <- as.character(c("V4502")) # prior ICD implant
a <- priicd
df$priicd <- with(df, ifelse((DX1 %in% a | DX2 %in% a | DX3 %in% a | DX4 %in% a | DX4 %in% a | DX5 %in% a | DX6 %in% a | DX7 %in% a | DX8 %in% a | DX10 %in% a | DX11 %in% a | DX12 %in% a | DX13 %in% a | DX14 %in% a | DX15 %in% a ), "yes","no"))
table(df$priicd)
```
```{r}
dementia <- as.character(c("2900","2941","2942","2948","3310","3311","3312","33182")) # dementia
a <- dementia
df$dementia <- with(df, ifelse((DX1 %in% a | DX2 %in% a | DX3 %in% a | DX4 %in% a | DX4 %in% a | DX5 %in% a | DX6 %in% a | DX7 %in% a | DX8 %in% a | DX10 %in% a | DX11 %in% a | DX12 %in% a | DX13 %in% a | DX14 %in% a | DX15 %in% a ), "yes","no"))
table(df$dementia)
```
```{r get var for n06 and convert them to lower case}
names(n06)
names(n06) <- tolower(names(n06))
names(n06)
```
1. Now we need to add the cm_variables from the core dataframe:
```{r}
sev <- read_csv("/Volumes/SVD2/cabg_pci/annals_rev_cabg_pci/nis2006sev.csv")
names(sev) <- tolower(names(sev))
names(sev)
sev2 <- sev %>% dplyr::select(hospid, key, cm_aids:cm_wghtl)
names(sev2)
```
Now combine the two df with key:
```{r combine }
df2 <- left_join(n06, sev2, by = "key")
names(df2)
```