Last updated: 2018-11-15

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Introduction

The goal of this analysis is to look at the weight changes relative to discharge.

# Open libraries
library(ggplot2)
Warning: package 'ggplot2' was built under R version 3.4.4
library(VennDiagram)
Warning: package 'VennDiagram' was built under R version 3.4.4
Loading required package: grid
Loading required package: futile.logger
# Open weight change data
weight_change <- read.csv("../data/weight_relapse_weight_info.csv", stringsAsFactors = FALSE)

Weight change over time, part 1

T1 to T2

# Plot weight change over time

boxplot(weight_change$Weight_diff_T1T2, xlab = "T1 to T2", ylab = "Weight change (lbs)")

# Number of individuals that lost weight

weight_subset <- weight_change[which(weight_change$Weight_diff_T1T2 < 0),]
nrow(weight_subset)
[1] 2
mean(weight_subset$Weight_diff_T1T2)
[1] -2.85
weight_subset <- weight_change[which(weight_change$Weight_diff_T1T2 > 0),]
nrow(weight_subset)
[1] 53
mean(weight_subset$Weight_diff_T1T2)
[1] 12.68283

T2 to T3

# Plot weight change over time

boxplot(weight_change$Weight_diff_T3T2, xlab = "T2 to T3", ylab = "Weight change (lbs)")

# Number of individuals that lost weight

weight_subset <- weight_change[which(weight_change$Weight_diff_T3T2 < -5),]
nrow(weight_subset)
[1] 2
weight_subset <- weight_change[which(weight_change$Weight_diff_T3T2 < 0),]
nrow(weight_subset)
[1] 7
mean(weight_subset$Weight_diff_T3T2)
[1] -6.364286
summary(weight_subset$Weight_diff_T3T2)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-14.500  -7.750  -4.600  -6.364  -3.950  -2.050 
weight_subset <- weight_change[which(weight_change$Weight_diff_T3T2 > 5),]
nrow(weight_subset)
[1] 24
weight_subset <- weight_change[which(weight_change$Weight_diff_T3T2 > 0),]
nrow(weight_subset)
[1] 34
mean(weight_subset$Weight_diff_T3T2)
[1] 10.70588
summary(weight_subset$Weight_diff_T3T2)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   0.30    4.30    8.00   10.71   13.28   45.20

T2 to T4

# Plot weight change over time

boxplot(weight_change$Weight_diff_T4T2, xlab = "T2 to T4", ylab = "Weight change (lbs)")

# Number of individuals that lost weight

weight_subset <- weight_change[which(weight_change$Weight_diff_T4T2 < -5),]
nrow(weight_subset)
[1] 7
weight_subset <- weight_change[which(weight_change$Weight_diff_T4T2 < 0),]
nrow(weight_subset)
[1] 8
mean(weight_subset$Weight_diff_T4T2)
[1] -9.6125
summary(weight_subset$Weight_diff_T4T2)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-16.000 -14.625  -9.000  -9.613  -6.725  -0.300 
weight_subset <- weight_change[which(weight_change$Weight_diff_T4T2 > 5),]
nrow(weight_subset)
[1] 19
weight_subset <- weight_change[which(weight_change$Weight_diff_T4T2 > 0),]
nrow(weight_subset)
[1] 30
mean(weight_subset$Weight_diff_T4T2)
[1] 11.035
summary(weight_subset$Weight_diff_T4T2)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  0.300   3.925   8.300  11.035  12.975  40.600

T2 to T5

# Plot weight change over time

boxplot(weight_change$Weight_diff_T5T2, xlab = "T2 to T5", ylab = "Weight change (lbs)")

# Number of individuals that lost weight

weight_subset <- weight_change[which(weight_change$Weight_diff_T5T2 < -5),]
nrow(weight_subset)
[1] 5
weight_subset <- weight_change[which(weight_change$Weight_diff_T5T2 < 0),]
nrow(weight_subset)
[1] 8
mean(weight_subset$Weight_diff_T5T2)
[1] -10.7875
summary(weight_subset$Weight_diff_T5T2)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 -19.50  -16.65  -11.95  -10.79   -4.30   -0.50 
weight_subset <- weight_change[which(weight_change$Weight_diff_T5T2 > 5),]
nrow(weight_subset)
[1] 22
weight_subset <- weight_change[which(weight_change$Weight_diff_T5T2 > 0),]
nrow(weight_subset)
[1] 24
mean(weight_subset$Weight_diff_T5T2)
[1] 14.00208
summary(weight_subset$Weight_diff_T5T2)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  1.250   6.275  11.400  14.002  21.225  31.600

Are the same individuals losing weight at each time period?

# Losing 0 pounds

weight_subset3 <- weight_change[which(weight_change$Weight_diff_T3T2 < 0),]
nrow(weight_subset3)
[1] 7
weight_subset4 <- weight_change[which(weight_change$Weight_diff_T4T2 < 0),]
nrow(weight_subset4)
[1] 8
weight_subset5 <- weight_change[which(weight_change$Weight_diff_T5T2 < 0),]
nrow(weight_subset5)
[1] 8
mylist <- list()
mylist[["T2 to T3"]] <- weight_subset3$ID
mylist[["T2 to T4"]] <- weight_subset4$ID
mylist[["T2 to T5"]] <- weight_subset5$ID

intersect(mylist$`T2 to T3`, mylist$`T2 to T4`)
[1] 2218 2234 2242 2270
intersect(mylist$`T2 to T3`, mylist$`T2 to T5`)
[1] 2234 2270
intersect(mylist$`T2 to T4`, mylist$`T2 to T5`)
[1] 2232 2234 2270
intersect(intersect(mylist$`T2 to T3`, mylist$`T2 to T4`), mylist$`T2 to T5`)
[1] 2234 2270
# Make as pdf 
Four_comp <- venn.diagram(mylist, filename= NULL, main=NULL, cex=1.5 , fill = NULL, lty=1, height=2000, width=2000, scaled = FALSE)

grid.draw(Four_comp)

dev.off()
null device 
          1 
pdf(file = "~/Dropbox/Figures/Negative_weight_loss.pdf")
  grid.draw(Four_comp)
dev.off()
null device 
          1 
# Losing 5 pounds

weight_subset3 <- weight_change[which(weight_change$Weight_diff_T3T2 < -5),]
nrow(weight_subset3)
[1] 2
weight_subset4 <- weight_change[which(weight_change$Weight_diff_T4T2 < -5),]
nrow(weight_subset4)
[1] 7
weight_subset5 <- weight_change[which(weight_change$Weight_diff_T5T2 < -5),]
nrow(weight_subset5)
[1] 5
mylist <- list()
mylist[["T2 to T3"]] <- weight_subset3$ID
mylist[["T2 to T4"]] <- weight_subset4$ID
mylist[["T2 to T5"]] <- weight_subset5$ID

intersect(mylist$`T2 to T3`, mylist$`T2 to T4`)
[1] 2234
intersect(mylist$`T2 to T3`, mylist$`T2 to T5`)
[1] 2234
intersect(mylist$`T2 to T4`, mylist$`T2 to T5`)
[1] 2232 2234 2270
intersect(intersect(mylist$`T2 to T3`, mylist$`T2 to T4`), mylist$`T2 to T5`)
[1] 2234
# Make as pdf 
Four_comp <- venn.diagram(mylist, filename= NULL, main=NULL, cex=1.5 , fill = NULL, lty=1, height=2000, width=2000, scaled = FALSE)

grid.draw(Four_comp)
dev.off()
null device 
          1 
pdf(file = "~/Dropbox/Figures/5_pound_weight_loss.pdf")
  grid.draw(Four_comp)
dev.off()
null device 
          1

Weight change over time, part 2

T2 to RRED T4

# Plot weight change over time

boxplot(weight_change$Weight_diff_REDT4T2, xlab = "T2 to RRED T4", ylab = "Weight change (lbs)")

# Number of individuals that lost weight

weight_subset <- weight_change[which(weight_change$Weight_diff_REDT4T2 < -5),]
nrow(weight_subset)
[1] 0
weight_subset <- weight_change[which(weight_change$Weight_diff_REDT4T2 < 0),]
nrow(weight_subset)
[1] 1
mean(weight_subset$Weight_diff_REDT4T2)
[1] -3.08
summary(weight_subset$Weight_diff_REDT4T2)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  -3.08   -3.08   -3.08   -3.08   -3.08   -3.08 
weight_subset <- weight_change[which(weight_change$Weight_diff_REDT4T2 > 5),]
nrow(weight_subset)
[1] 2
weight_subset <- weight_change[which(weight_change$Weight_diff_REDT4T2 > 0),]
nrow(weight_subset)
[1] 5
mean(weight_subset$Weight_diff_REDT4T2)
[1] 7.166
summary(weight_subset$Weight_diff_REDT4T2)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  0.200   3.500   4.630   7.166  12.000  15.500

T2 to RRED T5

# Plot weight change over time

boxplot(weight_change$Weight_diff_REDT5T2, xlab = "T2 to RRED T5", ylab = "Weight change (lbs)")

# Number of individuals that lost weight

weight_subset <- weight_change[which(weight_change$Weight_diff_REDT5T2 < -5),]
nrow(weight_subset)
[1] 1
weight_subset <- weight_change[which(weight_change$Weight_diff_REDT5T2 < 0),]
nrow(weight_subset)
[1] 3
mean(weight_subset$Weight_diff_REDT5T2)
[1] -5.01
summary(weight_subset$Weight_diff_REDT5T2)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 -6.440  -5.535  -4.630  -5.010  -4.295  -3.960 
weight_subset <- weight_change[which(weight_change$Weight_diff_REDT5T2 > 5),]
nrow(weight_subset)
[1] 3
weight_subset <- weight_change[which(weight_change$Weight_diff_REDT5T2 > 0),]
nrow(weight_subset)
[1] 3
mean(weight_subset$Weight_diff_REDT5T2)
[1] 11.72667
summary(weight_subset$Weight_diff_REDT5T2)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   9.31   10.21   11.10   11.73   12.94   14.77

How many individuals lost weight relative to admission weight?

# T1 to T3
weight_subset <- weight_change[which(weight_change$Weight_diff_T3T1 < 0),]
nrow(weight_subset)
[1] 1
# T1 to T4
weight_subset <- weight_change[which(weight_change$Weight_diff_T4T1 < 0),]
nrow(weight_subset)
[1] 2
# T1 to T5
weight_subset <- weight_change[which(weight_change$Weight_diff_T5T1 < 0),]
nrow(weight_subset)
[1] 2

Session information

sessionInfo()
R version 3.4.3 (2017-11-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: OS X El Capitan 10.11.6

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
[1] VennDiagram_1.6.20  futile.logger_1.4.3 ggplot2_3.0.0      

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.18         formatR_1.5          compiler_3.4.3      
 [4] pillar_1.3.0         git2r_0.23.0         plyr_1.8.4          
 [7] workflowr_1.1.1      bindr_0.1.1          futile.options_1.0.1
[10] R.methodsS3_1.7.1    R.utils_2.7.0        tools_3.4.3         
[13] digest_0.6.16        evaluate_0.11        tibble_1.4.2        
[16] gtable_0.2.0         pkgconfig_2.0.2      rlang_0.2.2         
[19] yaml_2.2.0           bindrcpp_0.2.2       withr_2.1.2         
[22] stringr_1.3.1        dplyr_0.7.6          knitr_1.20          
[25] rprojroot_1.3-2      tidyselect_0.2.4     glue_1.3.0          
[28] R6_2.2.2             rmarkdown_1.10       lambda.r_1.2.3      
[31] purrr_0.2.5          magrittr_1.5         whisker_0.3-2       
[34] backports_1.1.2      scales_1.0.0         htmltools_0.3.6     
[37] assertthat_0.2.0     colorspace_1.3-2     stringi_1.2.4       
[40] lazyeval_0.2.1       munsell_0.5.0        crayon_1.3.4        
[43] R.oo_1.22.0

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