Predictive modeling of perioperative patient deterioration: combining unanticipated ICU admissions and mortality for improved risk prediction.

ABSTRACT:

Objective

This paper presents a comprehensive analysis of perioperative patient deterioration by developing predictive models that evaluate unanticipated ICU admissions and in-hospital mortality both as distinct and combined outcomes.

Materials and methods

With less than 1% of cases resulting in at least one of these outcomes, we investigated 98 features to identify their role in predicting patient deterioration, using univariate analyses. Additionally, multivariate analyses were performed by employing logistic regression (LR) with LASSO regularization. We also assessed classification models, including non-linear classifiers like Support Vector Machines, Random Forest, and XGBoost.

Results

During evaluation, careful attention was paid to the data imbalance therefore m

SUBMITTER: Bakkes THGF 

PROVIDER: S-EPMC11220961 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature