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Temporary Liver Support Using Artificial Lung Technologies: Ammonia Removal via Peritoneal Dialysis for Acute Liver Failure with PFC and PDMS at Vacuum Pressure DATA ANALYSIS

report
posted on 2023-12-01, 15:46 authored by Lukas DiBenedittoLukas DiBeneditto

This document details the preparation and statistical analysis of the multi-device recorded data for the master’s thesis research project titled “Temporary Liver Support Using Artificial Lung Technologies: Ammonia Removal via Peritoneal Dialysis for Acute Liver Failure with PFC and PDMS at Vacuum Pressure”. (DiBeneditto, 2023) Central to the analysis is a MATLAB program, “main.m”, comprising 3313 lines of code. This program produced the figures, tables, and results presented in this document. The resulting files are stored in the program working directory, “_trials” and “device-calibration” folders, and represent 355 files across 114 folders, totaling 144 MB. The following sections provide in-depth insights into the methodologies employed, findings obtained, and their implications in the broader context of Acute Liver Failure management. The core objective of our study was to evaluate the efficiency and feasibility of a system incorporating a PDMS filter (representative of artificial liver technology) in tandem with perfluorocarbon (PFC, representative of artificial lung technology) to remove ammonia from a liquid solution in a simulated peritoneal environment. To investigate the potential application for acute liver failure (ALF) patients and attempt to answer two central questions: Can the PDMS filter effectively facilitate the diffusion of ammonia from the liquid to the gas phase, thereby removing it? Does the presence of PFC enhance or influence this ammonia removal process? Our data provides substantial evidence regarding the efficacy of the PDMS filter in facilitating ammonia removal. However, the role of PFC in this process remains unclear and requires further investigation. The complexity of the experiment and the variations observed in trials with similar parameters suggest we need additional studies to understand the variables we are exploring fully.

History

Date

2023-10-31