Identifying prognostic factors for survival in intensive care unit patients with SIRS or sepsis by machine learning analysis on electronic health records.

ABSTRACT:

Background

Systemic inflammatory response syndrome (SIRS) and sepsis are the most common causes of in-hospital death. However, the characteristics associated with the improvement in the patient conditions during the ICU stay were not fully elucidated for each population as well as the possible differences between the two.

Goal

The aim of this study is to highlight the differences between the prognostic clinical features for the survival of patients diagnosed with SIRS and those of patients diagnosed with sepsis by using a multi-variable predictive modeling approach with a reduced set of easily available measurements collected at the admission to the intensive care unit (ICU).

Methods

Data were collected from 1,257 patients (816 non-sepsis SIRS and 441 sepsis) admitted

SUBMITTER: Mollura M 

PROVIDER: S-EPMC10942078 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature