A Machine Learning Model for Predicting Mortality within 90 Days of Dialysis Initiation.

ABSTRACT:

Background

The first 90 days after dialysis initiation are associated with high morbidity and mortality in end-stage kidney disease (ESKD) patients. A machine learning-based tool for predicting mortality could inform patient-clinician shared decision making on whether to initiate dialysis or pursue medical management. We used the eXtreme Gradient Boosting (XGBoost) algorithm to predict mortality in the first 90 days after dialysis initiation in a nationally representative population from the United States Renal Data System.

Methods

A cohort of adults initiating dialysis between 2008-2017 were studied for outcome of death within 90 days of dialysis initiation. The study dataset included 188 candidate predictors prognostic of early mortality that were known on or before the fi

SUBMITTER: Rankin S 

PROVIDER: S-EPMC9528387 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature