Perfil de lípidos

Análisis exploratorio de Datos en R

#required packages 
library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
## ✔ ggplot2 3.3.6     ✔ purrr   0.3.4
## ✔ tibble  3.1.7     ✔ dplyr   1.0.9
## ✔ tidyr   1.2.0     ✔ stringr 1.4.0
## ✔ readr   2.1.2     ✔ forcats 0.5.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
library(ggplot2)
library(Rcpp)
library(dlookr)
## 
## Attaching package: 'dlookr'
## The following object is masked from 'package:tidyr':
## 
##     extract
## The following object is masked from 'package:base':
## 
##     transform
library(ggpubr)
library(gt)


library(readxl)
covilipidos_survival_analysis <- read_excel("C:/Users/fidel/OneDrive - CINVESTAV/Covid19 y lípidos en Sinaloa/PAPER/Lastround/covilipidos survival analysis.xlsx")
View(covilipidos_survival_analysis)

covilipids <- covilipidos_survival_analysis


str(covilipids)
## tibble [102 × 18] (S3: tbl_df/tbl/data.frame)
##  $ days          : num [1:102] 7 7 2 16 9 10 30 11 1 13 ...
##  $ outcome       : num [1:102] 0 0 1 0 0 0 0 1 1 1 ...
##  $ Clinic        : num [1:102] 0 0 1 0 0 0 0 1 0 0 ...
##  $ Cholesterol   : chr [1:102] ">82" ">82" ">82" ">82" ...
##  $ LDL           : chr [1:102] "<44" ">44" ">44" ">44" ...
##  $ HDL           : chr [1:102] ">24" ">24" NA "<24" ...
##  $ Triglycerides : chr [1:102] "<185" ">185" NA "<185" ...
##  $ Age           : num [1:102] 71 39 66 53 54 25 56 60 76 66 ...
##  $ Sex           : chr [1:102] "M" "F" "M" "F" ...
##  $ Diabetes      : chr [1:102] "SI" "NO" "SI" "SI" ...
##  $ Hypertension  : chr [1:102] "SI" "NO" "SI" "SI" ...
##  $ Obesity       : chr [1:102] "NO" "NO" "NO" "NO" ...
##  $ EDADCUTOFFMORT: chr [1:102] ">59" "<59" ">59" "<59" ...
##  $ Chol          : num [1:102] 97 156 117 133 96 91 121 161 72 191 ...
##  $ Tryg          : num [1:102] 135 248 NA 136 64 103 116 167 NA 90 ...
##  $ LDLc          : num [1:102] 39 95 76 81 42 45 57 91 NA 102 ...
##  $ VLDLc         : num [1:102] 27 49.6 NA 27.2 12.8 20.6 23.2 33.4 NA 18 ...
##  $ HDLc          : num [1:102] 36 29 NA 23 38 33 41 31 NA 51 ...
#create a data frame only with outcome

covilipids <- data.frame(covilipids$outcome, covilipids$Chol, covilipids$Tryg,
                         covilipids$LDLc, covilipids$HDLc)


str(covilipids)
## 'data.frame':    102 obs. of  5 variables:
##  $ covilipids.outcome: num  0 0 1 0 0 0 0 1 1 1 ...
##  $ covilipids.Chol   : num  97 156 117 133 96 91 121 161 72 191 ...
##  $ covilipids.Tryg   : num  135 248 NA 136 64 103 116 167 NA 90 ...
##  $ covilipids.LDLc   : num  39 95 76 81 42 45 57 91 NA 102 ...
##  $ covilipids.HDLc   : num  36 29 NA 23 38 33 41 31 NA 51 ...
#cambiar los nombres con Rbase, de las columnas del data.frame
colnames(covilipids) <- c('outcome', 'Chol', 'Tryg', 'LDLc', 
                          'HDLc') 



covilipids<-covilipids %>% mutate(outcome=recode(outcome,`0` = "Survivor",
                                     `1` = "Non-Survivor"))

str(covilipids)
## 'data.frame':    102 obs. of  5 variables:
##  $ outcome: chr  "Survivor" "Survivor" "Non-Survivor" "Survivor" ...
##  $ Chol   : num  97 156 117 133 96 91 121 161 72 191 ...
##  $ Tryg   : num  135 248 NA 136 64 103 116 167 NA 90 ...
##  $ LDLc   : num  39 95 76 81 42 45 57 91 NA 102 ...
##  $ HDLc   : num  36 29 NA 23 38 33 41 31 NA 51 ...
head(covilipids)
##        outcome Chol Tryg LDLc HDLc
## 1     Survivor   97  135   39   36
## 2     Survivor  156  248   95   29
## 3 Non-Survivor  117   NA   76   NA
## 4     Survivor  133  136   81   23
## 5     Survivor   96   64   42   38
## 6     Survivor   91  103   45   33
covlip1 <- gather(data= covilipids, Lipids, level, -outcome, na.rm = TRUE) 

head(covlip1)
##        outcome Lipids level
## 1     Survivor   Chol    97
## 2     Survivor   Chol   156
## 3 Non-Survivor   Chol   117
## 4     Survivor   Chol   133
## 5     Survivor   Chol    96
## 6     Survivor   Chol    91
#EDA outcome 
#outcome variable, that is defining as survival and non-survival covid-19 patients

#dplyr package and
#dlookr package

#dplyr:

covlip1 %>%  group_by(Lipids,outcome) %>% 
  summarise(
    count = n(),
    mean = mean(level, na.rm = TRUE),
    sd = sd(level, na.rm = TRUE),
    median = median(level, na.rm = TRUE),
    IQR = IQR(level, na.rm = TRUE)
  )
## `summarise()` has grouped output by 'Lipids'. You can override using the
## `.groups` argument.
## # A tibble: 8 × 7
## # Groups:   Lipids [4]
##   Lipids outcome      count  mean    sd median   IQR
##   <chr>  <chr>        <int> <dbl> <dbl>  <dbl> <dbl>
## 1 Chol   Non-Survivor    37 128.   45.0  125    65  
## 2 Chol   Survivor        65 128.   38.9  121    50  
## 3 HDLc   Non-Survivor    34  28.8  13.8   26.5  18  
## 4 HDLc   Survivor        59  30.6  11.2   30    13  
## 5 LDLc   Non-Survivor    35  63.6  36.3   57    55.5
## 6 LDLc   Survivor        59  73    33.8   68    41.5
## 7 Tryg   Non-Survivor    35 182.   89.3  160   100. 
## 8 Tryg   Survivor        63 141.   56.8  136    80
#dlookr:
stats1 <- covlip1 %>%  group_by(Lipids, outcome) %>% describe(level)

stats1 %>% gt()
described_variables Lipids outcome n na mean sd se_mean IQR skewness kurtosis p00 p01 p05 p10 p20 p25 p30 p40 p50 p60 p70 p75 p80 p90 p95 p99 p100
level Chol Non-Survivor 37 0 128.21622 45.01798 7.400910 65.0 0.495378288 -0.25285794 50 56.12 71.0 76.6 90.6 95.00 96.8 108.2 125.0 137.2 158.2 160.00 161.0 184.4 200.40 233.04 237
level Chol Survivor 65 0 127.76923 38.92773 4.828390 50.0 0.230722002 0.43999527 14 38.96 83.6 91.0 97.8 102.00 104.2 111.0 121.0 132.0 139.0 152.00 158.0 186.6 201.40 209.36 210
level HDLc Non-Survivor 34 0 28.76471 13.79297 2.365475 18.0 0.483926327 -0.42627607 6 6.99 9.0 13.3 17.2 19.25 20.0 23.2 26.5 31.0 32.3 37.25 41.2 50.0 50.35 57.70 61
level HDLc Survivor 59 0 30.55932 11.23000 1.462021 13.0 -0.007546554 0.07509718 7 8.16 10.9 13.0 23.0 25.00 26.0 27.0 30.0 34.8 36.0 38.00 39.4 41.8 50.00 55.36 60
level LDLc Non-Survivor 35 0 63.60000 36.32549 6.140128 55.5 0.529724399 -0.58354235 3 6.74 20.3 24.4 32.0 36.00 37.4 43.6 57.0 71.4 76.0 91.50 102.4 110.8 124.60 142.24 147
level LDLc Survivor 59 0 73.00000 33.84855 4.406705 41.5 0.906111917 0.71096777 14 22.12 31.6 37.8 43.8 47.00 49.8 60.2 68.0 76.6 85.0 88.50 95.4 120.4 134.70 164.40 176
level Tryg Non-Survivor 35 0 182.02857 89.25162 15.086278 100.5 0.973763502 0.20671808 60 64.08 80.4 90.8 111.0 115.50 123.8 142.2 160.0 187.8 204.8 216.00 240.2 326.2 378.30 381.64 383
level Tryg Survivor 63 0 140.65079 56.83994 7.161160 80.0 0.357930231 -0.75825679 41 48.44 63.1 73.4 85.4 97.50 103.0 116.0 136.0 154.2 166.4 177.50 195.8 217.4 244.00 254.04 259

Tabla 1 perfil de lípidos entre survivors y non-survivors

library(gtsummary)
## #BlackLivesMatter
library(tidyverse)

#defining the outcome variable as Survival and non-survival... 



covilipreg <- covilipidos_survival_analysis

covilipreg <- covilipreg %>% mutate(outcome=recode(outcome,`0` = "Survivor",
                                                `1` = "Non-Survivor"), Clinic=recode(Clinic, `0` = "Non-Critical",
                                                                                     `1` = "Critical"))


covilipreg %>% 
  select(Sex, Age, Clinic, Diabetes, Hypertension, Obesity,Chol,Tryg,LDLc,VLDLc,HDLc,outcome) %>% 
  tbl_summary(by=outcome) %>% add_p() %>% add_overall()
## Warning: The `fmt_missing()` function is deprecated and will soon be removed
## * Use the `sub_missing()` function instead
Characteristic Overall, N = 1021 Non-Survivor, N = 371 Survivor, N = 651 p-value2
Sex 0.9
F 37 (36%) 13 (35%) 24 (37%)
M 65 (64%) 24 (65%) 41 (63%)
Age 57 (46, 64) 62 (52, 72) 53 (41, 62) <0.001
Clinic <0.001
Critical 37 (36%) 28 (76%) 9 (14%)
Non-Critical 65 (64%) 9 (24%) 56 (86%)
Diabetes 0.4
NO 66 (65%) 22 (59%) 44 (68%)
SI 36 (35%) 15 (41%) 21 (32%)
Hypertension 0.002
NO 43 (42%) 8 (22%) 35 (54%)
SI 59 (58%) 29 (78%) 30 (46%)
Obesity 0.5
NO 86 (84%) 30 (81%) 56 (86%)
SI 16 (16%) 7 (19%) 9 (14%)
Chol 122 (98, 157) 125 (95, 160) 121 (102, 152) 0.8
Tryg 144 (103, 202) 160 (116, 216) 136 (98, 178) 0.041
Unknown 4 2 2
LDLc 67 (41, 89) 57 (36, 92) 68 (47, 88) 0.2
Unknown 8 2 6
VLDLc 29 (21, 40) 32 (23, 43) 27 (20, 36) 0.041
Unknown 4 2 2
HDLc 30 (23, 38) 26 (19, 37) 30 (25, 38) 0.3
Unknown 9 3 6
1 n (%); Median (IQR)
2 Pearson's Chi-squared test; Wilcoxon rank sum test

Figura 1 perfil de lípidos entre survivors y non-survivors

your_font_size <- 10

covlip1 %>% mutate(outcome = factor(outcome, levels=c("Survivor", "Non-Survivor"))) %>% 
  ggplot(aes(x=Lipids, y=level, fill=factor(outcome),add = "jitter"), 
         order = c("Chol", "Tryg", "LDLc", "HDLc")) +
  geom_boxplot()+  geom_jitter(shape=16,
                               position=position_jitter(),
                               alpha = .5)+
  stat_compare_means(aes(group = outcome),method = "wilcox.test", label = "p.signif", hide.ns = T, 
                     size = your_font_size)+
  theme(axis.text.x = element_text(angle = 45, hjust = 1))+ theme_classic2()+ scale_fill_grey(start = 0.9, end = .5)+
  labs(y="Level (mg/dL)", fill= "")+ theme(text = element_text(size = 20), axis.text = element_text(size = 20),
                                     legend.text = element_text(size = 20))

#Estadistica
#prueba de wilcoxon (no parametrica par comparar medias)

#con ggpurb
lipstats<-compare_means(level ~ outcome, data = covlip1, method = "wilcox",
              group.by = "Lipids", paired = FALSE)

lipstats %>% gt()
Lipids .y. group1 group2 p p.adj p.format p.signif method
Chol level Survivor Non-Survivor 0.7780091 0.78 0.778 ns Wilcoxon
Tryg level Survivor Non-Survivor 0.0414503 0.17 0.041 * Wilcoxon
LDLc level Survivor Non-Survivor 0.1734928 0.52 0.173 ns Wilcoxon
HDLc level Survivor Non-Survivor 0.2993499 0.60 0.299 ns Wilcoxon

Análisis Predictivo basado en curvas ROC

Curvas ROC y calculo de AUCs con su IC 95%

#ROC CURVES

#packages
library(pROC)
## Type 'citation("pROC")' for a citation.
## 
## Attaching package: 'pROC'
## The following objects are masked from 'package:stats':
## 
##     cov, smooth, var
library(dplyr)
library(ggplot2)
covilipreg<-covilipreg %>% mutate(outcomeroc = ifelse(outcome == "Non-Survivor", 
                                               '1', '0'))

rocs <- roc(outcomeroc ~ Chol + Tryg + LDLc+ HDLc  , data = covilipreg,
            ci=TRUE, plot=TRUE)
## Setting levels: control = 0, case = 1
## Setting direction: controls < cases
## Setting levels: control = 0, case = 1
## Setting direction: controls < cases

## Setting levels: control = 0, case = 1
## Setting direction: controls > cases

## Setting levels: control = 0, case = 1
## Setting direction: controls > cases

rocs
## $Chol
## 
## Call:
## roc.formula(formula = outcomeroc ~ Chol, data = covilipreg, ci = TRUE,     plot = TRUE)
## 
## Data: Chol in 65 controls (outcomeroc 0) < 37 cases (outcomeroc 1).
## Area under the curve: 0.483
## 95% CI: 0.3581-0.6078 (DeLong)
## 
## $Tryg
## 
## Call:
## roc.formula(formula = outcomeroc ~ Tryg, data = covilipreg, ci = TRUE,     plot = TRUE)
## 
## Data: Tryg in 63 controls (outcomeroc 0) < 35 cases (outcomeroc 1).
## Area under the curve: 0.6249
## 95% CI: 0.5075-0.7424 (DeLong)
## 
## $LDLc
## 
## Call:
## roc.formula(formula = outcomeroc ~ LDLc, data = covilipreg, ci = TRUE,     plot = TRUE)
## 
## Data: LDLc in 59 controls (outcomeroc 0) > 35 cases (outcomeroc 1).
## Area under the curve: 0.5845
## 95% CI: 0.4572-0.7118 (DeLong)
## 
## $HDLc
## 
## Call:
## roc.formula(formula = outcomeroc ~ HDLc, data = covilipreg, ci = TRUE,     plot = TRUE)
## 
## Data: HDLc in 59 controls (outcomeroc 0) > 34 cases (outcomeroc 1).
## Area under the curve: 0.5651
## 95% CI: 0.4359-0.6942 (DeLong)

Multiples curvas en una sola gráfica

liproc<-ggroc(rocs,linetype = 1, size = 1) + theme_bw()+  
  theme(legend.title = element_blank(),text = element_text(size = 12)) +
  theme(legend.text = element_text(size = 12, color = "black", face = "bold"))

liproc

TABLA CON VALORES DE AUC y LOS PUNTOS DE CORTE

Lipids cutoff AUC pvalue
Cholesterol ≤82 0.51 0.7890
Triglycerides >185 0.62 0.0371
LDL ≤44 0.55 0.4552
HDL ≤24 0.58 0.1932

Análisis de Sobrevidad

Basandonos en los puntos de corte para las curvas ROC

#SURVIVAL
#https://www.emilyzabor.com/tutorials/survival_analysis_in_r_tutorial.html
#https://www.datacamp.com/community/tutorials/survival-analysis-R

#install.packages("survminer")

#Load required packages
library("ggplot2")
library("ggpubr")
library("survival")
library("survminer")
## 
## Attaching package: 'survminer'
## The following object is masked from 'package:survival':
## 
##     myeloma
library(readxl)
LIPIDOSCOVIDR <- read_excel("C:/Users/fidel/OneDrive - CINVESTAV/Covid19 y lípidos en Sinaloa/PAPER/Lastround/LIPIDOSCOVIDR.xlsx")

#Compute survival curves of patients stratified by treatment assignments (rx)

chol <- survfit(Surv(days, outcome) ~ CHOLCUTOFMORT, data = LIPIDOSCOVIDR)
tryg <- survfit(Surv(days, outcome) ~ TRIGCUTOFFMORT, data = LIPIDOSCOVIDR)
HDL <- survfit(Surv(days, outcome) ~ HDLCUTOFFMORT , data = LIPIDOSCOVIDR)
LDL <- survfit(Surv(days, outcome) ~ LDLCUTOFFMORT, data = LIPIDOSCOVIDR)

#SHOWME MORE THAN 1 GRAPH IN A FIGURE

require("survminer")

splots <- list()

#ajustes a la gr?fica de sobrevida y tabla:
#https://cran.r-project.org/web/packages/survminer/vignettes/Playing_with_fonts_and_texts.html
# Arrange multiple ggsurvplots and print the output
#http://rpkgs.datanovia.com/survminer/reference/arrange_ggsurvplots.html

splots[[1]] <- ggsurvplot(chol, data = LIPIDOSCOVIDR, pval = TRUE)
splots[[2]] <- ggsurvplot(tryg, data = LIPIDOSCOVIDR, pval = TRUE)
splots[[3]] <-ggsurvplot(LDL, data = LIPIDOSCOVIDR, pval = TRUE)
splots[[4]] <- ggsurvplot(HDL, data = LIPIDOSCOVIDR, pval = TRUE)



# Arrange multiple ggsurvplots and print the output


survi<-arrange_ggsurvplots(splots, print = T,
                           ncol = 2, nrow =2 , risk.table.height = 0.4)
survi

HR model

library(forestmodel)

library(readxl)
LIPIDOSCOVIDRexcluded <- read_excel("C:/Users/fidel/OneDrive - CINVESTAV/Covid19 y lípidos en Sinaloa/PAPER/Lastround/LIPIDOSCOVIDRexcluded.xlsx")


print(forest_model(coxph(Surv(days, outcome) ~ DM + HAS + Obesity  + CHOLCUTOFMORT + TRIGCUTOFFMORT + HDLCUTOFFMORT + LDLCUTOFFMORT, 
                         data=LIPIDOSCOVIDRexcluded)))
## Warning in recalculate_width_panels(panel_positions, mapped_text =
## mapped_text, : Unable to resize forest panel to be smaller than its heading;
## consider a smaller text size

#Hazard Ratios and Fotest plot
#install.packages("usethis")
#install.packages("devtools")
library(usethis)
library(devtools)
#install_github('therneau/survival',dependencies=TRUE)
library(survival)
library(tidyverse)
library(knitr)
library(survminer)
library(survival)
library(ggpubr)


names(LIPIDOSCOVIDR)
##  [1] "days"           "outcome"        "CHOL"           "CHOLCUTOFMORT" 
##  [5] "LDL"            "LDLCUTOFFMORT"  "HDL"            "HDLCUTOFFMORT" 
##  [9] "TRIGLICER"      "TRIGCUTOFFMORT" "edad"           "sexo"          
## [13] "DM"             "HAS"            "Obesity"        "EDADCUTOFFMORT"
survdiff(Surv(days, outcome) ~ DM + HAS + Obesity  + 
           CHOLCUTOFMORT + TRIGCUTOFFMORT + HDLCUTOFFMORT + LDLCUTOFFMORT, 
         data=LIPIDOSCOVIDR)
## Call:
## survdiff(formula = Surv(days, outcome) ~ DM + HAS + Obesity + 
##     CHOLCUTOFMORT + TRIGCUTOFFMORT + HDLCUTOFFMORT + LDLCUTOFFMORT, 
##     data = LIPIDOSCOVIDR)
## 
## n=92, 10 observations deleted due to missingness.
## 
##                                                                                                          N
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  1
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  2
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  2
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44 10
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  2
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  4
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  3
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  4
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  3
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  8
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  3
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  1
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  1
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  1
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  1
## DM=SI, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  1
## DM=SI, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  1
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  2
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  2
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44 12
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  3
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  4
## DM=SI, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1
## DM=SI, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  2
##                                                                                                         Observed
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44        0
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44        0
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        0
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44        0
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44        0
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        0
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44        1
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44        2
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        0
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44        0
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44        1
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44        1
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        0
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44        0
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44        1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44        1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44        1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44        2
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        2
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44        4
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44        1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44        1
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44        1
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44        1
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        0
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44        0
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44        1
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44        0
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        0
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44        0
## DM=SI, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44        0
## DM=SI, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44        1
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        1
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44        1
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        1
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44        3
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44        1
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        1
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44        2
## DM=SI, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44        1
## DM=SI, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44        0
##                                                                                                         Expected
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.0802
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.9186
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.7508
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.0930
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.3288
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.3112
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   1.8414
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.3025
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.1065
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   2.6079
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.1556
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.0217
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.1556
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   1.4368
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   1.2043
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.7508
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.4253
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.1378
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.6143
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.8872
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   3.1820
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.4669
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   1.4543
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   0.4844
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.2223
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.0930
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   1.2043
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.9186
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.4253
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.3868
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.3868
## DM=SI, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.2986
## DM=SI, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   1.9543
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   1.2043
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.5349
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.9342
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   3.2289
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.7414
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.0930
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   2.0242
## DM=SI, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.1065
## DM=SI, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   0.5246
##                                                                                                         (O-E)^2/E
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  8.02e-02
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  9.19e-01
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  7.51e-01
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  9.30e-02
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  3.29e-01
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  3.11e-01
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  3.84e-01
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  9.53e+00
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1.07e-01
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  2.61e+00
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  4.58e+00
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  4.40e+01
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1.56e-01
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  1.44e+00
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  3.47e-02
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  8.27e-02
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  7.77e-01
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  5.40e+00
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  3.13e+00
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  1.40e+00
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  2.10e-01
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  6.09e-01
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  1.42e-01
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  5.49e-01
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  2.72e+00
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  9.30e-02
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  1.20e+00
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  7.21e-03
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  4.25e-01
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  3.87e-01
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  3.87e-01
## DM=SI, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  2.99e-01
## DM=SI, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  4.66e-01
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  3.47e-02
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  4.04e-01
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  4.63e-03
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  1.62e-02
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44  9.02e-02
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  8.85e+00
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  2.88e-04
## DM=SI, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44  7.49e+00
## DM=SI, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44  5.25e-01
##                                                                                                         (O-E)^2/V
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.08220
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.98921
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.80593
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.09518
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.34221
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.32300
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   0.42998
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   9.91488
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.10888
## DM=NO, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   3.25560
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   4.69021
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44  45.00000
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.15932
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   1.56055
## DM=NO, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.03949
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.08883
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.81621
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   5.52853
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   3.30089
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   1.48919
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   0.24209
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.63910
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.16583
## DM=NO, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   0.57620
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   2.82322
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.09518
## DM=NO, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   1.37201
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.00777
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=<44   0.44689
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.40689
## DM=SI, HAS=NO, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.40689
## DM=SI, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.31033
## DM=SI, HAS=NO, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   0.60933
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=<82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.03949
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.42472
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   0.00497
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   0.01896
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=<24, LDLCUTOFFMORT=>44   0.09558
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   9.05295
## DM=SI, HAS=SI, Obesity=NO, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=>185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   0.00032
## DM=SI, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=<44   7.66127
## DM=SI, HAS=SI, Obesity=SI, CHOLCUTOFMORT=>82, TRIGCUTOFFMORT=<185, HDLCUTOFFMORT=>24, LDLCUTOFFMORT=>44   0.55177
## 
##  Chisq= 109  on 41 degrees of freedom, p= 4e-08
model.citok <- coxph(Surv(days, outcome) ~ DM + HAS + Obesity  + 
                       CHOLCUTOFMORT + TRIGCUTOFFMORT + HDLCUTOFFMORT + LDLCUTOFFMORT,
                     data=LIPIDOSCOVIDR)

summary(model.citok)
## Call:
## coxph(formula = Surv(days, outcome) ~ DM + HAS + Obesity + CHOLCUTOFMORT + 
##     TRIGCUTOFFMORT + HDLCUTOFFMORT + LDLCUTOFFMORT, data = LIPIDOSCOVIDR)
## 
##   n= 92, number of events= 34 
##    (10 observations deleted due to missingness)
## 
##                        coef exp(coef) se(coef)      z Pr(>|z|)  
## DMSI               -0.09072   0.91327  0.37007 -0.245   0.8063  
## HASSI               1.18051   3.25604  0.46452  2.541   0.0110 *
## ObesitySI           0.03655   1.03723  0.51787  0.071   0.9437  
## CHOLCUTOFMORT>82    0.35030   1.41949  0.55782  0.628   0.5300  
## TRIGCUTOFFMORT>185  0.11456   1.12138  0.42835  0.267   0.7891  
## HDLCUTOFFMORT>24   -0.64315   0.52563  0.42227 -1.523   0.1277  
## LDLCUTOFFMORT>44   -0.81914   0.44081  0.41286 -1.984   0.0472 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                    exp(coef) exp(-coef) lower .95 upper .95
## DMSI                  0.9133     1.0950    0.4422    1.8863
## HASSI                 3.2560     0.3071    1.3101    8.0926
## ObesitySI             1.0372     0.9641    0.3759    2.8621
## CHOLCUTOFMORT>82      1.4195     0.7045    0.4757    4.2360
## TRIGCUTOFFMORT>185    1.1214     0.8918    0.4843    2.5964
## HDLCUTOFFMORT>24      0.5256     1.9025    0.2297    1.2026
## LDLCUTOFFMORT>44      0.4408     2.2686    0.1963    0.9901
## 
## Concordance= 0.658  (se = 0.058 )
## Likelihood ratio test= 15.06  on 7 df,   p=0.04
## Wald test            = 14.01  on 7 df,   p=0.05
## Score (logrank) test = 15.06  on 7 df,   p=0.04
# Call the model to inspect it's contents
model.citok
## Call:
## coxph(formula = Surv(days, outcome) ~ DM + HAS + Obesity + CHOLCUTOFMORT + 
##     TRIGCUTOFFMORT + HDLCUTOFFMORT + LDLCUTOFFMORT, data = LIPIDOSCOVIDR)
## 
##                        coef exp(coef) se(coef)      z      p
## DMSI               -0.09072   0.91327  0.37007 -0.245 0.8063
## HASSI               1.18051   3.25604  0.46452  2.541 0.0110
## ObesitySI           0.03655   1.03723  0.51787  0.071 0.9437
## CHOLCUTOFMORT>82    0.35030   1.41949  0.55782  0.628 0.5300
## TRIGCUTOFFMORT>185  0.11456   1.12138  0.42835  0.267 0.7891
## HDLCUTOFFMORT>24   -0.64315   0.52563  0.42227 -1.523 0.1277
## LDLCUTOFFMORT>44   -0.81914   0.44081  0.41286 -1.984 0.0472
## 
## Likelihood ratio test=15.06  on 7 df, p=0.03528
## n= 92, number of events= 34 
##    (10 observations deleted due to missingness)