Setup
1. Packages
2. Working Directory
BIS Datasets
Patient Info Dataset
Data Analysis

Setup

Packages

If error at this stage be sure your RMarkdown is up-to-date and that all installed packages are up to date. Did not include install packages code (install.packages(‘package_of_interest’)), you should be able to add what you don’t have.

library(readr)
library(ggplot2)
library(gridExtra)
library(grid)
library(rmarkdown)
library(dplyr)
library(scales)
library(tidyverse)
library(data.table)
library(patchwork)

Working Directory

This code will set your working directory, aka where your files are located. Save all “XXX.spa” files into one folder and adjust the code below to your personal working directory.

setwd("~/Desktop/Desktop - Amaterasu/School/Medical/Research/Anesthesia Elective/BIS Sugamex")

BIS Data Set

Importing Dataset

You can import either using the import wizard feature underneath the “environment” tab in the upper right corner, or use the following code adjusted to your specific savefile name.

BIS <- read_delim("L07272245.spa", delim = "|", 
                  escape_double = FALSE, col_types = cols(Time = col_datetime(format = "%m/%d/%Y %H:%M:%S")), 
                  trim_ws = TRUE, skip = 1)

BIS2 <- read_delim("L07290213.spa", delim = "|", 
                  escape_double = FALSE, col_types = cols(Time = col_datetime(format = "%m/%d/%Y %H:%M:%S")), 
                  trim_ws = TRUE, skip = 1)

Curating the Database

The data needs to be transformed for analysis. Each paragraph of text needs to be reproduced for your new imported data set (aka. copy paste paragraph and change BIS to your new name (BIS3, BIS4, etc)). Need to also record if patient moved or not, which will be important for data analysis

BIS[BIS==-3276.8] <- NA
BIS[BIS==-327.7] <- NA
BISagg <- aggregate(BIS, list(rep(1:(nrow(BIS) %/% 60 + 1), each = 60, len = nrow(BIS))), mean)[-1];
BISagg$Movement <- 'No Movement'
BISagg$ID <- 'L07272245'
BISagg<- BISagg %>%
    mutate(Time = ymd_hms(Time), 
           dif = Time - ymd_hms('2023-07-28 00:03:13'), #Suggamadex injection time
           rank = dense_rank(dif) - row_number()[dif== 0])
IDRows <- BISagg$rank >= -10 & BISagg$rank <= 5
BISagg <- BISagg[IDRows, ]
BISagg <- BISagg[, c(59, 57, 56, 1:55)]
 
BIS2[BIS2==-3276.8] <- NA
BIS2[BIS2==-327.7] <- NA
BIS2agg <- aggregate(BIS2, list(rep(1:(nrow(BIS2) %/% 60 + 1), each = 60, len = nrow(BIS2))), mean)[-1];
BIS2agg$Movement <- 'Movement'
BIS2agg$ID <- 'L07290213'
BIS2agg<- BIS2agg %>%
    mutate(Time = ymd_hms(Time), 
           dif = Time - ymd_hms('2023-07-29 03:18:36'), #Suggamadex injection time
           rank = dense_rank(dif) - row_number()[dif== 0])
IDRows2 <- BIS2agg$rank >= -10 & BIS2agg$rank <= 5
BIS2agg <- BIS2agg[IDRows2, ] 
BIS2agg <- BIS2agg[, c(59, 57, 56, 1:55)]

Summarizing BIS Databased

Create one dataset of BIS information averaging based on time from Suggamadex injection.

BISav<- rbind(BISagg, BIS2agg)

Patient Information Database

Enter new data on patient information here as collected.

Abbreviations

BIS = Bispectral Index
SEF = Spectral Edge Frequency
PatientID = Case Number
Ht = Height (kg)
Wt = Weight (cm)
ET_Sevo = End-tidal Sevoflurane (%)
ET_CO2_Basline = End-tidal CO2 5 minutes before Sugammadex administration
BP_Baseline = Blood Pressure 5 minutes before sugamex injection
O2_Sat_Baseline = Oxygen Saturation 5 minutes before sugamex injection (%)
Sugammadex_dose = Sugammadex dose (mg)
Time_Sugax_admin = Time Sugammadex was administered (day-month-year hour:minute:second)
ET_CO2_Inj = End-tidal CO2 at time of Sugammadex administration
HR_5minB = HR 5 minutes before Sugammadex admin
HR_5minP = HR 4 minutes after Sugammadex admin
HR_inj = Heart Rate at time of Sugammadex administration (bpm)
BP_inj = Blood Pressure at time of Sugammadex administration
O2_Sat_Inj = Oxygen Saturation at time of Sugammadex administration (%)
Movements = any observed twitching/movement of patient
Comorbidities = relevant comorbidities
HTN = Hypertension
DM = Diabetes Mellitus
ICM = Ischemic Cardiomyopathy

PtDB <- read_csv("BISSugamex Pt Info.csv")

Data Analysis

Future Stats

Patient characteristics will be summarized using means with standard deviations, counts, and percentages as appropriate. Suggamadex dose should be examined for differences between movement groups and BIS. BIS, SEF, EMG, and SPI will be examined using linear effects model with and without EMG as a covariant to examine changes overtime.

#remove_when_prepared_to_run_stats mAge <- mean(PtDB$Age) 
#remove mHt <- mean(PtDB$Ht_m)
#remove mWt <- means(PtDB$Wt_kg)
#remove mBMI <- means(PtDB$BMI)
#remove HTN <- length(grep("HTN", PtDB))
#remove DysL <- length(grep("Dyslipidemia", PtDB))
#remove DM <- length(grep("DM", PtDB))
#remove ICM <- length(grep("ICM", PtDB))
#remove AHTN <- length(grep("Anti-HTN", PtDB))
#remove Statin <- length(grep("Statin", PtDB))
#remove aB <- length(grep("a-Blocker", PtDB))
#remove bB <- length(grep("b-Blocker", PtDB))
#remove aT <- length(grep("Antithrombolytics", PtDB))
#remove aC <- length(grep("Anticoagulants", PtDB))

#Can add other common pathologies/medications seen

#remove Table1 <- data.frame(mAge, mHt, mWt, mBMI, HTN, DysL, DM, ICM, AHTN, Statin, aB, bB, aT, aC)

#remove 

#remove lmBIS <-lm(BISav$DB13U01...12 ~ BISagg$Time)
#remove lmBISEMG <-lm(BISav$DB13U01...12 ~ BISagg$Time + BISagg$EMGLOW01...16)


#remove lmSEF <-lm(BISav$SEF08...9 ~ BISagg$Time)
#remove lmBISSEF <-lm(BISav$SEF08...9 ~ BISagg$Time + BISagg$EMGLOW01...16)

#remove lmEMG <-lm(BISav$EMGLOW01...16 ~ BISagg$Time)

#remove lm <-lm(BISav$DB13U01...12 ~ BISagg$Time)
#remove lmBISEMG <-lm(BISav$DB13U01...12 ~ BISagg$Time + BISagg$EMGLOW01...16)

Plotting BIS and marking Sugamex

The important information for this study is the BIS = “DB13U01…12” and SEF = “SEF08…9”, EMG = “EMGLOW01…16”, and SQI = “SQI10…17” and movement. We want to plot BIS, SEF, EMG, and SQI against time and mark when we gave Sugammadex (a value recorded in the OR) to see any change in activity around that time. We also want to make two separate graph sets for patients that moved and patients that did not for Per protocol, sevoflurane was left at steady concentration and not changed for 5 minutes. Values to manually add: time sugamex given and amount of sugamex admin (mg).

gBIS<- ggplot(data=BISav, aes(x=rank, y=DB13U01...12, group = factor(Movement, level=c('Movement', 'No Movement')), colour= Movement)) + 
    geom_line()+
    geom_point()+
    ggtitle("BIS") +
    theme(plot.title = element_text(hjust = 0.5)) +
    ylab("Bispectral Index") +
    xlab("Time (minutes)") + 
  geom_segment(x=0, y=0, xend=0, yend =100, color= 'black') +
  geom_text(x=-5, y=70, label = "Sugammadex Admin", size=3, color = 'black')

gSEF<- ggplot(data=BISav, aes(x=rank, y=SEF08...9, group = factor(Movement, level=c('Movement', 'No Movement')), colour= Movement)) + 
  geom_line()+
  geom_point()+
  ggtitle("SEF95") +
  theme(plot.title = element_text(hjust = 0.5), legend.position = "none") +
  ylab("Spectral Edge Frequency") +
  xlab("Time (minutes)") + 
  geom_segment(x=0, y=0, xend=0, yend =100, color= 'black') +
  geom_text(x=-5, y=23, label = "Sugammadex Admin", size=3, color = 'black')

gEMG<- ggplot(data=BISav, aes(x=rank, y=EMGLOW01...16, group = factor(Movement, level=c('Movement', 'No Movement')), colour= Movement)) + 
  geom_line()+
  geom_point()+
  ggtitle("EMG") +
  theme(plot.title = element_text(hjust = 0.5), legend.position = "none") +
  ylab("Electromyography (dB)") +
  xlab("Time (minutes)") + 
  geom_segment(x=0, y=0, xend=0, yend =100, color= 'black') +
  geom_text(x=-5, y=43, label = "Sugammadex Admin", size=3, color = 'black')


gSQI<- ggplot(data=BISav, aes(x=rank, y=SQI10...17, group = factor(Movement, level=c('Movement', 'No Movement')), colour= Movement)) + 
  geom_line()+
  geom_point()+
  ggtitle("SQI") +  
  theme(plot.title = element_text(hjust = 0.5), legend.position = "none") +
  ylab("Signal Quality Index") +
  xlab("Time (minutes)") + 
  geom_segment(x=0, y=0, xend=0, yend =100, color= 'black') +
  geom_text(x=-5, y=83, label = "Sugammadex Admin", size=3, color = 'black')


gBISgrob <- ggplotGrob(gBIS)
gSEFgrob <- ggplotGrob(gSEF)
gEMGgrob <- ggplotGrob(gEMG)
gSQIgrob <- ggplotGrob(gSQI)

gBIS + gSEF + gEMG + gSQI +
  plot_layout(ncol = 2, nrow = 2, guides = "collect")

# stat_summary(fun.data = mean_se, geom = "errorbar", width = 0.2)

Supplementary Pt Specifc Plot

This represents a solid example of one patient overtime in case you want supplementary visualization

gBIS2<- ggplot(data=BIS2agg, aes(x=rank, y=DB13U01...12, group =1,)) + 
  geom_line()+
  geom_point()+
  ggtitle("BIS") +
  theme(plot.title = element_text(hjust = 0.5)) +
  ylab("Bispectral Index") +
  xlab("Time (minutes)") + 
  geom_segment(x=0, y=0, xend=0, yend =100) +
  geom_text(x=0, y=80, label = "50mg Sugammadex", size=3)

gSEF2<- ggplot(data=BIS2agg, aes(x=rank, y=SEF08...9, group =1,)) + 
  geom_line()+
  geom_point()+
  ggtitle("SEF95") +
  theme(plot.title = element_text(hjust = 0.5)) +
  ylab("Spectral Edge Frequency") +
  xlab("Time (minutes)") + 
  geom_segment(x=0, y=0, xend=0, yend =100) +
  geom_text(x=0, y=80, label = "50mg Sugammadex", size=3)

gEMG2<- ggplot(data=BIS2agg, aes(x=rank, y=EMGLOW01...16, group =1,)) + 
  geom_line()+
  geom_point()+
  ggtitle("EMG") +
  theme(plot.title = element_text(hjust = 0.5)) +
  ylab("Electromyography (dB)") +
  xlab("Time (minutes)") + 
  geom_segment(x=0, y=0, xend=0, yend =100) +
  geom_text(x=0, y=80, label = "50mg Sugammadex", size=3)

gSQI2<- ggplot(data=BIS2agg, aes(x=rank, y=SQI10...17, group =1,)) + 
  geom_line()+
  geom_point()+
  ggtitle("SQI") +
  theme(plot.title = element_text(hjust = 0.5)) +
  ylab("Signal Quality Index") +
  xlab("Time (minutes)") + 
  geom_segment(x=0, y=0, xend=0, yend =100) +
  geom_text(x=0, y=80, label = "50mg Sugammadex", size=3)

gBIS2grob <- ggplotGrob(gBIS2)
gSEF2grob <- ggplotGrob(gSEF2)
gEMG2grob <- ggplotGrob(gEMG2)
gSQI2grob <- ggplotGrob(gSQI2)
grid.arrange(gBIS2grob, gSEF2grob, gEMG2grob, gSQI2grob, ncol =2, nrow=2, top=textGrob("L07290213", gp=gpar(fontsize=20,font=8)))

BIS Data

Edward Willow

2023-08-08

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