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Publication Name World Journal of Psychiatry
Manuscript ID 121714
DOI 10.5498/wjp.121714
Country China
Category Psychiatry
Manuscript Type Retrospective Study
Article Title Construction of a prediction model for fall risk in older patients with osteoporosis and comorbid with psychiatric disorders
Manuscript Source Unsolicited Manuscript
All Author List Dan Shen, Li Sun, Wei-Ping Cheng, Ting-Ting Wang and Hai-Yan Gu
Funding Agency and Grant Number
Funding Agency Grant Number
Nantong University Special Research Fund for Clinical Medicine No. 2025LY056
Nantong University Special Research Fund for Clinical Medicine No.2023HY002
Corresponding Author Hai-Yan Gu, Chief Physician, Department of Nursing, Affiliated Nantong Clinical College of Nantong University, Nantong First People’s Hospital, No. 666 Shengli Road, Nantong 226001, Jiangsu Province, China. guhaiyan.2009@163.com
Key Words Osteoporosis; Depression; Anxiety; Risk of falling; Prediction model; Aging
Core Tip Older patients with osteoporosis are prone to falls, and this study identified depression, anxiety, poor balance, and low vitamin D levels as key contributing factors. Early screening of high-risk individuals was enabled by a predictive model that combined psychological and physical indicators and showed good performance.
Citation Shen D, Sun L, Cheng WP, Wang TT, Gu HY. Construction of a prediction model for fall risk in older patients with osteoporosis and comorbid with psychiatric disorders. World J Psychiatry 2026; In press
PDF 121714-in-press.pdf
Received
2026-04-28 12:08
Peer-Review Started
2026-04-28 12:08
First Decision by Editorial Office Director
2026-05-20 09:10
Return for Revision
2026-05-20 09:10
Revised
2026-06-05 15:04
Publication Fee Transferred
2026-06-11 03:39
Second Decision by Editor
2026-06-26 02:16
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director
2026-06-26 05:53
Articles in Press
2026-06-26 05:53
Edit the Manuscript by Language Editor
Typeset the Manuscript
ISSN 2220-3206 (online)
Open Access This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
Copyright ©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com