Predictive model for assessing the prognosis of rhabdomyolysis patients in the intensive care unit.

ABSTRACT:

Background

Rhabdomyolysis (RM) frequently gives rise to diverse complications, ultimately leading to an unfavorable prognosis for patients. Consequently, there is a pressing need for early prediction of survival rates among RM patients, yet reliable and effective predictive models are currently scarce.

Methods

All data utilized in this study were sourced from the MIMIC-IV database. A multivariable Cox regression analysis was conducted on the data, and the performance of the new model was evaluated based on the Harrell's concordance index (C-index) and the area under the receiver operating characteristic curve (AUC). Furthermore, the clinical utility of the predictive model was assessed through decision curve analysis (DCA).

Results

A total of 725 RM patients admitted

SUBMITTER: Xiong Y 

PROVIDER: S-EPMC11759279 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature