Retrospective Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Psychiatry. Mar 19, 2025; 15(3): 102117
Published online Mar 19, 2025. doi: 10.5498/wjp.v15.i3.102117
Developing a nomogram for postoperative delirium in elderly patients with hip fractures
Liang Li, Wei-Wei Sheng, Li-Juan Song, Shuai Cheng, En-Gang Cui, Yong-Bing Zhang, Xue-Zhong Yu, Yan-Li Liu
Liang Li, Shuai Cheng, Department of Orthopaedics and Traumatology, Dongying People’s Hospital, Dongying 257091, Shandong Province, China
Wei-Wei Sheng, Li-Juan Song, Yan-Li Liu, Department of Health Care, Dongying People’s Hospital, Dongying 257091, Shandong Province, China
En-Gang Cui, Department of Medical Imaging, Dongying People’s Hospital, Dongying 257091, Shandong Province, China
Yong-Bing Zhang, Department of Joint Surgery, Dongying People’s Hospital, Dongying 257091, Shandong Province, China
Xue-Zhong Yu, Department of Spine Surgery, Dongying People’s Hospital, Dongying 257091, Shandong Province, China
Co-first authors: Liang Li and Wei-Wei Sheng.
Author contributions: Li L and Sheng WW contributed equally to this work and are co-first authors; Li L, Sheng WW, and Liu YL designed the study, collected and analyzed data, and wrote the manuscript; Li L, Sheng WW, Song LJ, Cheng S, Cui EG, Zhang YB, Yu XZ, and Liu YL participated in the study’s conception and data collection; and all authors read and approved the final version.
Supported by Wang Zhengguo Foundation for Traumatic Medicine “Sequential Medical Research Special Foundation”, No 2024-XG-M05.
Institutional review board statement: This study was approved by the Ethic Committee of Dongying People’s Hospital.
Informed consent statement: The written informed consent was waived owing to the retrospective and deidentified nature of this study.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: No additional data are available.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yan-Li Liu, Assistant Professor, PhD, Department of Health Care, Dongying People’s Hospital, No. 317 Dongcheng South 1st Road, Dongying 257091, Shandong Province, China. dyliuyanli@163.com
Received: November 21, 2024
Revised: December 30, 2024
Accepted: January 21, 2025
Published online: March 19, 2025
Processing time: 96 Days and 20.1 Hours
Core Tip

Core Tip: This study integrates advanced machine learning techniques, including Lasso regression, support vector machine, and random forest, to determine independent risk factors for postoperative delirium. A nomogram prediction model was developed and demonstrated high accuracy and stability in both training and validation cohorts. The decision curve analysis confirmed its clinical use within a risk threshold range of 8%-35%. This tool provides valuable guidance for the early determination of patients at high-risk and personalized postoperative management to reduce postoperative delirium incidence.