Predicting Postoperative Delirium in Older Patients Before Elective Surgery: Multicenter Retrospective Cohort Study.

ABSTRACT:

Background

Elective surgeries for older adults are increasing. Machine learning could enhance risk assessment, influencing surgical planning and postoperative care. Preoperative cognitive assessment may facilitate early detection and management of postoperative delirium (POD).

Objective

This study aims to assess machine learning models' predictive ability for POD, focusing on the added predictive value of the neuropsychological assessments before elective surgery.

Methods

This retrospective cohort study analyzed data from the multicenter PAWEL (Patient safety, Efficiency and Life quality in elective surgery) and PAWEL-R (risk) studies, encompassing older patients (≥70 y) undergoing elective surgeries from July 2017 to April 2019. A total of 1624 patients (52.3% male,

SUBMITTER: Wu SJ 

PROVIDER: S-EPMC12364014 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature