Development and validation of a nomogram for predicting subsyndromal delirium in critically ill patients in the emergency department

This study aimed to develop and validate a nomogram for predicting subsyndromal delirium (SSD) risk in critically ill patients in the emergency department (ED). A retrospective cohort study was conducted on 712 patients admitted to the ED resuscitation room of Peking Union Medical College Hospital from January 2025 to August 2025. Patients were randomly divided into training (n = 525) and validation (n = 187) sets. Multivariate logistic regression analyses were performed to identify independent risk factors for SSD. A nomogram prediction model was constructed based on these factors and evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Multivariate analysis identified six independent predictors of SSD: marital status (divorced: OR = 12.210, 95%CI 1.334-111.750), physical restraint (OR = 10.386, 95%CI 2.932-36.786), RASS score (OR = 4.090, 95%CI 2.029-8.243), APACHE II score (OR = 1.092, 95%CI 1.011-1.180), Barthel index (OR = 0.968, 95%CI 0.951-0.984), and PSQI score (OR = 1.239, 95%CI 1.123-1.368). The nomogram demonstrated excellent discrimination, with an AUC of 0.898. The calibration curve showed good agreement between predicted and actual probabilities. DCA indicated that the nomogram had significant clinical net benefit across a wide range of threshold probabilities. This study developed a novel nomogram that incorporates six readily available clinical variables. This tool effectively predicts the individual risk of SSD in ED critically ill patients, facilitating early identification and targeted preventive interventions to improve patient outcomes.

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Publication Details

Journal
Internal and Emergency Medicine
Published
2026-07-25
DOI
https://doi.org/10.1007/s11739-026-04448-1
Primary Topic
Intensive Care Unit Cognitive Disorders
Type
article
Field-Weighted Citation Impact
0.00

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article

Development and validation of a nomogram for predicting subsyndromal delirium in critically ill patients in the emergency department

Pengxia Sun, Changyun Wei, Yunyi Le, Fan Li et al.
Internal and Emergency Medicine
Intensive Care Unit Cognitive Disorders
article

Development and validation of a nomogram for predicting subsyndromal delirium in critically ill patients in the emergency department

Pengxia Sun, Changyun Wei, Yunyi Le, Fan Li, Jian Gao, Tengyun Shang, Qin Zhu, Hui Wang, Meng Su, Tianmei Feng
article en

Abstract

This study aimed to develop and validate a nomogram for predicting subsyndromal delirium (SSD) risk in critically ill patients in the emergency department (ED). A retrospective cohort study was conducted on 712 patients admitted to the ED resuscitation room of Peking Union Medical College Hospital from January 2025 to August 2025. Patients were randomly divided into training (n = 525) and validation (n = 187) sets. Multivariate logistic regression analyses were performed to identify independent risk factors for SSD. A nomogram prediction model was constructed based on these factors and evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Multivariate analysis identified six independent predictors of SSD: marital status (divorced: OR = 12.210, 95%CI 1.334-111.750), physical restraint (OR = 10.386, 95%CI 2.932-36.786), RASS score (OR = 4.090, 95%CI 2.029-8.243), APACHE II score (OR = 1.092, 95%CI 1.011-1.180), Barthel index (OR = 0.968, 95%CI 0.951-0.984), and PSQI score (OR = 1.239, 95%CI 1.123-1.368). The nomogram demonstrated excellent discrimination, with an AUC of 0.898. The calibration curve showed good agreement between predicted and actual probabilities. DCA indicated that the nomogram had significant clinical net benefit across a wide range of threshold probabilities. This study developed a novel nomogram that incorporates six readily available clinical variables. This tool effectively predicts the individual risk of SSD in ED critically ill patients, facilitating early identification and targeted preventive interventions to improve patient outcomes.

Internal and Emergency Medicine
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Peking University (CN), Peking Union Medical College Hospital (CN), Peking University Third Hospital (CN)
National Natural Science Foundation of China, Peking Union Medical College Hospital, Peking Union Medical College
Reduced inequalities, Peace, Justice and strong institutions
Openalex Percentile: Top 7%
Intensive Care Unit Cognitive Disorders
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