Final Project

Author

Rachel Chan

Introduction

This study was aimed to determine if interruptions in breathing during sleep, caused by OSA which is obstructive sleep apnea, could lead to lower average blood pressure during surgery.

Increased sympathetic activity is believed to be the main reason for ongoing platelet activation in patients with obstructive sleep apnea (OSA). Frequent interruptions during sleep coincide with repetitive increases in sympathetic neural activity and the release of vasoconstrictive hormones, which directly activate platelets. The effectiveness of CPAP therapy in reducing platelet activation supports this connection.

Inflammation and pro-atherogenic cytokines, found at higher levels in OSA patients, can directly and indirectly activate platelets. Obesity, closely linked with airway collapse and inflammation, was previously thought to be the main factor for increased platelet activation in OSA patients. However, recent studies suggest that the level of oxygen deprivation in the blood, rather than obesity, correlates with platelet hyperactivity. CPAP therapy reduces platelet activity, indicating a direct link between oxygen deprivation and platelet activity.

Hypoxia itself damages the lining of blood vessels, leading to endothelial dysfunction. Oxygen deprivation triggers a pathway in endothelial cells that results in cell death. Damaged endothelium activates circulating platelets. So, both OSA and obesity are independent but usually coexisting risk factors for ongoing platelet activity.

This study was a retrospective cohort study, meaning that the data collected were from records that occurred in the past. Due to the collecting of data from records there is a possibility that there was points of data that was not added to the data set as it was mentioned that it was cleaned and has missing data points.

Will the type of surgeries affect the the MAP (mean arterial pressure) during the surgery? Does BMI play a major role in cause sleep related hxpoxia?

Load library

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.0     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.0
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(openintro)

Loading required package: airports
Loading required package: cherryblossom
Loading required package: usdata

library(ggfortify)

Load data

library(readxl)
hypoxia <- read_excel("C:/Users/rache/OneDrive/Desktop/math217/hypoxia.xlsx")
View(hypoxia)
hypoxia <- as.data.frame(hypoxia)

Mean and median of BMI

BMI<- hypoxia$BMI
mean(BMI)

[1] 46.74875

median(BMI)

[1] 46

sd(BMI)

[1] 7.77417

IQR(BMI)

[1] 10.2

Box plot of BMI

boxplot(BMI, col = "lightblue", horizontal = TRUE)

Histogram of Minimum nocturnal Sao2

Sao2<- hypoxia$`Min Sao2`
hist(Sao2, col = "lightblue")

Scatterplot of TWA MAP and duration of surgery

ggplot(hypoxia, aes(x=hypoxia$`Duration of Surg`, y=hypoxia$`TWA MAP`))+
geom_point() +
geom_smooth(method = "lm") +
theme_bw()+
labs(x="Duration of Surgery",
y="TWA of MAP During Surgery",
title = "Comparing duration of surgery and TWA of MAP",)

Warning: Use of `` hypoxia$`Duration of Surg` `` is discouraged.
ℹ Use `Duration of Surg` instead.

Warning: Use of `` hypoxia$`TWA MAP` `` is discouraged.
ℹ Use `TWA MAP` instead.

Warning: Use of `` hypoxia$`Duration of Surg` `` is discouraged.
ℹ Use `Duration of Surg` instead.

Warning: Use of `` hypoxia$`TWA MAP` `` is discouraged.
ℹ Use `TWA MAP` instead.

`geom_smooth()` using formula = 'y ~ x'

Duration of the surgery is in hours.TWA MAP is time-weighted average and mean arterial pressure

scatter plot

ggplot(hypoxia, aes(x=BMI, y=Sao2))+
geom_point() +
geom_smooth(method = "lm") +
theme_bw()+
labs(x="BMI",
y="Minimum nocturnal Sao2",
title = "BMI and nocturnal Sao2",)

`geom_smooth()` using formula = 'y ~ x'

Linear Model

fit1 <- lm(data = hypoxia, hypoxia$AHI ~ BMI)
summary(fit1)


Call:
lm(formula = hypoxia$AHI ~ BMI, data = hypoxia)

Residuals:
    Min      1Q  Median      3Q     Max 
-2.2119 -0.8433  0.1494  1.0552  1.3864 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.962842   0.390419   5.028 8.95e-07 ***
BMI         0.019425   0.008242   2.357   0.0191 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 1.072 on 276 degrees of freedom
  (3 observations deleted due to missingness)
Multiple R-squared:  0.01973,   Adjusted R-squared:  0.01618 
F-statistic: 5.555 on 1 and 276 DF,  p-value: 0.01912

Logistis Regression

Gabryelska, A., Łukasik, Z. M., Makowska, J. S., & Białasiewicz, P. (2018). Obstructive Sleep Apnea: From Intermittent Hypoxia to Cardiovascular Complications via Blood Platelets. Frontiers in neurology, 9, 635. https://doi.org/10.3389/fneur.2018.00635