**OSF_LongCOVID.Rdata** contains the data for the 6-month incidence and co-occurrence of long-COVID features. Loading the Rdata object in R results in one variable called `res` that contains the results for the comparison of long-COVID features between cohorts. `res` is an array of 12 lists and each list corresponds to the results for the comparison between two specific cohorts (after propensity score matching unless otherwise stated). Specifically: - `res[[1]]`: results for the comparison between COVID-19 and influenza (from 1 day to 6 months) - `res[[2]]`: results for the comparison between COVID-19 and influenza (from 3 months to 6 months) - `res[[3]]`: results for the comparison between males and females - `res[[4]]`: results for the comparison between patients over the age of 45 and patients between 10 and 44 years-old - `res[[5]]`: results for the comparison between patients from 22 to 44 years-old and patients between 10 and 21 years-old - `res[[6]]`: results for the comparison between patients above the age of 65 and patients between 45 and 64 years-old - `res[[7]]`: results for the comparison between non-white and white patients - `res[[8]]`: results for the comparison between hospitalized and non-hospitalized patients - `res[[9]]`: results for the comparison between patients with vs. without leukocytosis - `res[[10]]`: results for the comparison between patients requiring vs not requiring ICU admission - `res[[11]]`: results for the unmatched comparison between COVID-19 and influenza (from 1 day to 6 months) - `res[[12]]`: results for the unmatched comparison between COVID-19 and influenza (from 3 months to 6 months) Each element of the array contains information about cohorts being compared, the outcomes being compared, and the results of the comparison. Specifically they contain: - `cohort1`: the name of the first cohort - `cohort2`: the name of the second cohort - `outcomeNames`: the name of the outcomes - `outcomes`: an array with the results for each outcome The results of the Kaplan-Meier analysis for the *i*th outcome are stored in `outcomes[[i]]$KM` which contains the following elements: - `endSurvivals`: the survival (1-event probability) probability at the end of the follow-up period for the two cohorts - `HR`: the hazard ratio for the comparison - `HR_ci`: the 95% CI for the hazard ratio - `p`: the corresponding p-value - `survival$time`: a vector of time in days corresponding to the x-axis of all KM figures - `survival$values1`: the survival (1-event probability) for the first cohort - `survival$values2`: the survival (1-event probability) for the second cohort - `survival$CI1`: the 95% confidence interval for the survival for the first cohort - `survival$CI2`: the 95% confidence interval for the survival for the second cohort As an illustration the following few lines of code would plot, for the comparison between COVID-19 and influenza over the 3-6 month period (`res[[2]]`), the probability of co-occurrence of abnormal Breathing and fatigue (`outcomes[[26]]`) for the COVID-19 cohort (i.e. first cohort of the comparison so using `values1`): `load('OSF_LongCOVID.Rdata')` `kmResults=res[[2]]$outcomes[[26]]$KM$survival` `plot(kmResults$time,1-kmResults$values1,type='l')`