Automated identification of patient subgroups: A case-study on mortality of COVID-19 patients admitted to the ICU.

ABSTRACT:

Background

- Subgroup discovery (SGD) is the automated splitting of the data into complex subgroups. Various SGD methods have been applied to the medical domain, but none have been extensively evaluated. We assess the numerical and clinical quality of SGD methods.

Method

- We applied the improved Subgroup Set Discovery (SSD++), Patient Rule Induction Method (PRIM) and APRIORI - Subgroup Discovery (APRIORI-SD) algorithms to obtain patient subgroups on observational data of 14,548 COVID-19 patients admitted to 73 Dutch intensive care units. Hospital mortality was the clinical outcome. Numerical significance of the subgroups was assessed with information-theoretic measures. Clinical significance of the subgroups was assessed by comparing variable importance on population and su

SUBMITTER: Vagliano I 

PROVIDER: S-EPMC10266884 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature