BMC Geriatrics · Jul 2, 2025

Development and validation of a prediction model for postoperative delirium in older patients undergoing major noncardiac surgery: protocol for a prospective multi-centre cohort study

By Wang YN, Hu JH, Chen Y et al.

BACKGROUND: Postoperative delirium (POD) is a common complication in older patients after surgery, leading to a series of adverse outcomes. This study aims to develop and validate a prediction model for POD in older patients following major noncardiac surgery. METHODS: In this prospective, multi-centre, cohort study, a total of 972 older patients undergoing major noncardiac surgery will be enrolled from three hospitals in Jiangsu, China (n = 680 for model development and n = 292 for external validation). Candidate predictors have been selected according to existing literature and clinical expertise. The primary outcome is POD within 7 days postoperatively or before discharge, assessed by the 3-minute Confusion Assessment Method or Confusion Assessment Method for Intensive Care Unit. The secondary outcomes include postoperative pain intensity, quality of recovery, and quality of sleep. The model will be derived using the univariate and multivariable logistic regression analyses. The internal validation will be conducted using the bootstrapping method. Based on data from different study sites, the external validation will be performed using the area under the receiver operating characteristic curve, Hosmer-Lemeshow goodness-of-fit statistic, and max-rescaled Brier score. DISCUSSION: The results of this multi-centre cohort study will be presented as the model formula and a web-based risk calculator for clinical application, contributing to early prediction of POD and improvement of decision-making in older patients undergoing major noncardiac surgery. TRIAL REGISTRATION: Chinese Clinical Trial Register (ID: ChiCTR2300072164, https://www.chictr.org.cn/showprojEN.html?proj=197451 . ), prospectively registered on 5 June 2023.

doi.org/10.1186/s12877-025-06153-8 Open access PubMed 40604623 Biomarkers