Predicting Prolonged Length of Hospital Stay for Peritoneal Dialysis-Treated Patients Using Stacked Generalization: Model Development and Validation Study.

ABSTRACT:

Background

The increasing number of patients treated with peritoneal dialysis (PD) and their consistently high rate of hospital admissions have placed a large burden on the health care system. Early clinical interventions and optimal management of patients at a high risk of prolonged length of stay (pLOS) may help improve the medical efficiency and prognosis of PD-treated patients. If timely clinical interventions are not provided, patients at a high risk of pLOS may face a poor prognosis and high medical expenses, which will also be a burden on hospitals. Therefore, physicians need an effective pLOS prediction model for PD-treated patients.

Objective

This study aimed to develop an optimal data-driven model for predicting the pLOS risk of PD-treated patients using basic admi

SUBMITTER: Kong G 

PROVIDER: S-EPMC8173398 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature