--- a
+++ b/overview/cohort-tables-full.R
@@ -0,0 +1,117 @@
+data.filename <- '../../data/cohort-sanitised.csv'
+require(data.table)
+COHORT <- fread(data.filename)
+
+percentMissing <- function(x, sf = 3) {
+  round(sum(is.na(x))/length(x), digits = sf)*100
+}
+
+# Remove the patients we shouldn't include
+COHORT <-
+  COHORT[
+    # remove negative times to death
+    COHORT$time_death > 0 &
+      # remove patients who should be excluded
+      !COHORT$exclude
+    ,
+    ]
+
+# Age, 5, 50, 95, %missing
+print(quantile(COHORT$age, c(0.5, 0.025, 0.975)))
+
+# Gender
+print(table(COHORT$gender))
+print(table(COHORT$gender)/nrow(COHORT)*100)
+
+# Deprivation, 5, 50, 95, %missing
+print(quantile(COHORT$imd_score, c(0.5, 0.025, 0.975), na.rm = TRUE))
+print(percentMissing(COHORT$imd_score))
+
+# SCAD subtype
+print(table(COHORT$diagnosis)/nrow(COHORT)*100)
+
+# PCI
+print(sum(COHORT$pci_6mo)/nrow(COHORT)*100)
+
+# CABG
+print(sum(COHORT$cabg_6mo)/nrow(COHORT)*100)
+
+# previous/recurrent MI
+print(sum(COHORT$hx_mi)/nrow(COHORT)*100)
+
+# nitrates (listed as 1 and NA not T and F)
+print(sum(COHORT$long_nitrate, na.rm = TRUE)/nrow(COHORT)*100)
+
+# Smoking, by category, %missing
+print(table(COHORT$smokstatus)/nrow(COHORT)*100)
+print(percentMissing(COHORT$smokstatus))
+
+# Hypertension
+print(sum(COHORT$hypertension)/nrow(COHORT)*100)
+
+# Diabetes, yes/no
+print(
+  (sum(COHORT$diabetes == 'Diabetes unspecified type') +
+    sum(COHORT$diabetes == 'Type 1 diabetes') +
+    sum(COHORT$diabetes == 'Type 2 diabetes')) /nrow(COHORT)*100
+)
+
+# Total cholesterol
+print(quantile(COHORT$total_chol_6mo, c(0.5, 0.025, 0.975), na.rm = TRUE))
+print(percentMissing(COHORT$total_chol_6mo))
+
+# HDL
+print(quantile(COHORT$hdl_6mo, c(0.5, 0.025, 0.975), na.rm = TRUE))
+print(percentMissing(COHORT$hdl_6mo))
+
+# Heart failure
+print(sum(COHORT$heart_failure)/nrow(COHORT)*100)
+
+# Peripheral arterial disease
+print(sum(COHORT$pad)/nrow(COHORT)*100)
+
+# Atrial fibrillation
+print(sum(COHORT$hx_af)/nrow(COHORT)*100)
+
+# Stroke
+print(sum(COHORT$hx_stroke)/nrow(COHORT)*100)
+
+# Chronic kidney disease
+print(sum(COHORT$hx_renal)/nrow(COHORT)*100)
+
+# COPD
+print(sum(COHORT$hx_copd)/nrow(COHORT)*100)
+
+# Cancer
+print(sum(COHORT$hx_cancer)/nrow(COHORT)*100)
+
+# Chronic liver disease
+print(sum(COHORT$hx_liver)/nrow(COHORT)*100)
+
+# Depression
+print(sum(COHORT$hx_depression)/nrow(COHORT)*100)
+
+# Anxiety
+print(sum(COHORT$hx_anxiety)/nrow(COHORT)*100)
+
+# Heart rate
+print(quantile(COHORT$pulse_6mo, c(0.5, 0.025, 0.975), na.rm = TRUE))
+print(percentMissing(COHORT$pulse_6mo))
+
+# Creatinine
+print(quantile(COHORT$crea_6mo, c(0.5, 0.025, 0.975), na.rm = TRUE))
+print(percentMissing(COHORT$crea_6mo))
+
+# WCC
+print(quantile(COHORT$total_wbc_6mo, c(0.5, 0.025, 0.975), na.rm = TRUE))
+print(percentMissing(COHORT$total_wbc_6mo))
+
+# Haemoglobin
+print(quantile(COHORT$haemoglobin_6mo, c(0.5, 0.025, 0.975), na.rm = TRUE))
+print(percentMissing(COHORT$haemoglobin_6mo))
+
+# Follow-up, 5, 50, 95
+print(quantile(COHORT$endpoint_death_date, c(0.5, 0.025, 0.975)))/365.25
+
+# Death vs censored, %
+print(table(COHORT$endpoint_death)) /nrow(COHORT)*100