A nomogram and risk stratification for predicting subsyndromal delirium in elderly patients in a post-anaesthesia...

Subsyndromal delirium, as a transitional state of postoperative delirium, does not meet the diagnostic threshold for delirium but independently contributes to adverse outcomes in elderly patients. Early identification and intervention can effectively prevent disease progression.

This study focuses on the post-anesthesia care unit, a critical window period for postoperative recovery, aiming to develop a reliable risk prediction model.

A prospective cohort study.

Subsyndromal delirium was assessed with the Confusion Assessment Method at 30 min post-extubation and pre-transfer. The least absolute shrinkage and selection operator and multivariate logistic regression were applied to screen independent predictors and construct a nomogram. The performance of the model was evaluated by discrimination, calibration and clinical utility. Patients were subsequently divided into low-risk and high-risk subgroups.

The overall incidence of subsyndromal delirium in 2636 elderly patients in the post-anesthesia care unit was 18.6 %. Age, latest neutrophil to lymphocyte ratio, nighttime surgery, intraoperative hypothermia, patient-controlled analgesia usage, and duration of mechanical ventilation in the post-anesthesia care unit were identified as independent risk factors for predicting subsyndromal delirium. The areas under the ROC curve of the model were 0.904 (95 % CI: 0.878-0.931) and 0.850 (95 % CI: 0.814-0.886) in the training and validation cohorts, respectively. The calibration curves and decision curve analysis demonstrated good consistency and clinical value. Significant differences in subsyndromal delirium rates were observed between the low-risk and high-risk groups (P < 0.001).

The developed nomogram model incorporating six clinical variables demonstrated excellent discrimination and calibration, with its risk stratification effectively identifying high-risk subsyndromal delirium patients.