Predictive modeling of COVID-19 mortality risk in chronic kidney disease patients using multiple machine learning algorithms.

ABSTRACT: The coronavirus disease 2019 (COVID-19) has a significant impact on the global population, particularly on individuals with chronic kidney disease (CKD). COVID-19 patients with CKD will face a considerably higher risk of mortality than the general population. This study developed a predictive model for assessing mortality in COVID-19-affected CKD patients, providing personalized risk prediction to optimize clinical management and reduce mortality rates. We developed machine learning algorithms to analyze 219 patients' clinical laboratory test data retrospectively. The performance of each model was assessed using a calibration curve, decision curve analysis, and receiver operating characteristic (ROC) curve. It was found that the LightGBM model showed the most satisfied performance, with an

SUBMITTER: Luo L 

PROVIDER: S-EPMC11541900 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature