Group_19_project: A study of early predictors (Comorbidities and Etiology) of patient's outcome after cirrhosis hospitalization

Project Contributors

• Pauline Charpentier - @Linepocharpe - s231663
• Eva Frossard - @EvaFrossard - s231701
• Noy Tabul - @NoyTii - s232743
• Fabian Ziegler - @fabianhz1 - s231932

Dataset

Our project is based on the study of the following dataset: Mukthinuthlalapati, VV Pavan Kedar et al. (2019). Data from: Early predictors of outcomes of hospitalization for cirrhosis and assessment of the impact of race and ethnicity at safety-net hospitals [Dataset]. Dryad. https://doi.org/10.5061/dryad.6gt88dv We discarded the the race and ethnicity variable since they were considered non-significant variable to determine patient's outcome. We, therefore, chose to focus ouor study on Comorbidities and Etiology, and their according numerical value: Child Pugh Score (CPS) and Charlson Comorbidity Index.

To load the dataset onto the project

1. Create a /data folder in the project
2. Creat a subfolder /_raw
3. Go to the website where the dataset can be found (https://doi.org/10.5061/dryad.6gt88dv) and download the .csv file
4. Upload it in the /data/raw folder

To run the project

To run the project, run the 00_all.qmd

Packages to install

Before running the files that can be found in the "R" folder, a few packages should be installed and the following command lines should be run in your console:

• install.packages('tidyverse')
• install.packages('ggplot2')
• install.packages('ggpubr')
• install.packages('forcats')
• install.packages('quarto')

Structure of the project

• 00_all.qmd: run-all file of the project. Used to render all of the subfiles.
• 01_load.qmd:loading of the files.
• 02_clean.qmd: tidying of the dataset. Joining was performed here (despite not needing it for uor data set)
• 03_augment.qmd: augmentation of the dataset, creation of new variables.
• 04_describe.qmd: creation of introduction graphs giving general statistic information about the dataset.
• 05_analysis_mortality.qmd: analysis of the patients' mortality and the different variables affecting it.
• 06_analysis_comorbidities_etiologies.qmd: investigating the relation between comorbidities/etiologies and the patient's liver disease.
• 07_analysis_CPS.qmd:linear regression model between the CPS and etiologies
• 08_analysis_liver_disease.qmd: linear regression model to see how the different liver diseases affect mortality -> DEAD END
• 09_logistic_analysis.qmd: logistic regression between mortality and CPS
• 10_otherfunctions.qmd: a few other plots that were not relevant in the other files