62 lines
2.0 KiB
R
62 lines
2.0 KiB
R
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##
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## Data pull and export for Forskermaskinen
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##
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## Exports are made in REDCap instead
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##
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## Data set is made here, not in REDCap, as data here is better organised.
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##
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dta<-read.csv("/Volumes/Data/exercise/source/background.csv",colClasses = "character", na.strings = c("NA","","unknown"))
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export<-dta[,c("pase_0",
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"age",
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"sex",
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"civil",
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"smoker",
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"rtreat",
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"alc",
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"afli",
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"hypertension",
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"diabetes",
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"mrs_0",
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"nihss_c",
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"thrombolysis",
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"pad",
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"thrombechtomy",
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"ami",
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"tci",
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"rdate",
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"cpr",
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"rnumb",
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"height",
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"weight",
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"weight_est",
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"inc_time",
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"compliant",
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"mrs_1",
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"mrs_6",
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"pase_6",
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"visit_1",
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"visit_6")]
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export$diabetes[is.na(export$diabetes)]<-"no"
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export$diabetes[is.na(export$hypertension)]<-"no"
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export$thrombolysis[is.na(export$thrombolysis)]<-"no"
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export$thrombechtomy[is.na(export$thrombechtomy)]<-"no"
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export$pad[is.na(export$pad)]<-"no"
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export$ami[is.na(export$ami)]<-"no"
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export$inc_time[export$inc_time<0]<-0
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export$compliant<-as.numeric(factor(export$compliant))
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export$rdate<-as.Date(export$rdate)
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# export$mrs_0[export$mrs_0==3]<-NA
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export <- export|>
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mutate(any_rep=factor(ifelse(thrombolysis=="yes"|thrombechtomy=="yes","yes","no")), # If not noted, no therapy was received
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weight=ifelse(is.na(weight),weight_est,weight))|>
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select(-c(weight_est))
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write.csv(export|>select(c(rnumb,rtreat)),"/Volumes/Data/SDS upload/study_treatment.csv",row.names = FALSE)
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write.csv(export,"/Volumes/Data/SDS upload/data_all.csv",row.names = FALSE)
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write.csv(export|>select(-c(rtreat)),"/Volumes/Data/SDS upload/background.csv",row.names = FALSE)
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