This thesis conducts an observational study into whether diuretics should be administered to ICU patients with sepsis when length of stay in the ICU and 30-day post-hospital mortality are considered. The central contribution of the thesis is a stepwise, reusable software-based approach for examining the outcome of treatment vs no-treatment decisions with observational data. The thesis implements, demonstrates and draws findings via three steps: Step 1. Form a study group and prepare modeling variables. Step 2. Model the propensity of the study group with respect to the administration of diuretics with a propensity score function and create groups of patients balanced in this propensity. Step 3. Statistically model each outcome with study variables to decide whether the administration of diuretics has a significant impact. Additionally, the thesis presents a preliminary machine learning based method using Genetic Programming to predict mortality and length of stay in ICU outcomes for the study group. The thesis finds, for its study group, in three of five propensity balanced quintiles, a statistically significant longer length of stay when diuretics are administered. For a less sick subset of patients (SAPS ICU admission score < 17) the administration of diuretics has a significant negative effect on mortality.
(2012). An Observational Study: The Effect of Diuretics Administration on Outcomes of Mortality and Mean Duration of I.C.U. Stay. (Tesi di specializzazione, Università degli Studi di Milano-Bicocca, 2012).
An Observational Study: The Effect of Diuretics Administration on Outcomes of Mortality and Mean Duration of I.C.U. Stay
RAMAZZOTTI, DANIELE
2012
Abstract
This thesis conducts an observational study into whether diuretics should be administered to ICU patients with sepsis when length of stay in the ICU and 30-day post-hospital mortality are considered. The central contribution of the thesis is a stepwise, reusable software-based approach for examining the outcome of treatment vs no-treatment decisions with observational data. The thesis implements, demonstrates and draws findings via three steps: Step 1. Form a study group and prepare modeling variables. Step 2. Model the propensity of the study group with respect to the administration of diuretics with a propensity score function and create groups of patients balanced in this propensity. Step 3. Statistically model each outcome with study variables to decide whether the administration of diuretics has a significant impact. Additionally, the thesis presents a preliminary machine learning based method using Genetic Programming to predict mortality and length of stay in ICU outcomes for the study group. The thesis finds, for its study group, in three of five propensity balanced quintiles, a statistically significant longer length of stay when diuretics are administered. For a less sick subset of patients (SAPS ICU admission score < 17) the administration of diuretics has a significant negative effect on mortality.File | Dimensione | Formato | |
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