Development and validation of prediction model using nursing notes on sentiment scores for prognosis of patients with severe acute kidney injury receiving continuous renal replacement therapy based on computational intelligence algorithms.

ABSTRACT:

Background

Currently, the prediction values of models for the prognosis of acute kidney injury (AKI) receiving continuous renal replacement therapy (CRRT) were ordinary and establishing a better prediction model is necessary. Nursing notes are an important predictor of in-hospital mortality in intensive care unit (ICU) patients. This study established prognostic prediction models for AKI patients receiving CRRT especially using nursing notes.

Methods

Totally, 682 AKI patients undergoing CRRT were included. AKI was diagnosed based on Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Four hundred and twelve patients lacking nursing notes data were excluded. Finally, 270 patients were included and randomly divided into a training set (n=189) and a testing set (n=81) a

SUBMITTER: Zha D 

PROVIDER: S-EPMC9652558 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature