Wang DY, Fu CH, Ma MM, Men LC, Huang B, Han Y. Risk factors for anxiety and depression in elderly frail patients based on bedside ultrasound multimodal assessment. World J Psychiatry 2026; 16(10): 118743 [DOI: 10.5498/wjp.118743]
Corresponding Author of This Article
Lian-Chao Men, Department of Emergency Medicine, Hejian Branch of Cangzhou Central Hospital, No. 32 Jingkai South Street, Cangzhou 061000, Hebei Province, China. 17733726859@163.com
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Psychiatry
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research-article
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Wang DY, Fu CH, Ma MM, Men LC, Huang B, Han Y. Risk factors for anxiety and depression in elderly frail patients based on bedside ultrasound multimodal assessment. World J Psychiatry 2026; 16(10): 118743 [DOI: 10.5498/wjp.118743]
World J Psychiatry. Oct 19, 2026; 16(10): 118743 Published online Oct 19, 2026. doi: 10.5498/wjp.118743
Risk factors for anxiety and depression in elderly frail patients based on bedside ultrasound multimodal assessment
Dan-Yang Wang, Chen-Hui Fu, Meng-Mei Ma, Lian-Chao Men, Bin Huang, Yu Han
Dan-Yang Wang, Department of Ultrasound, Hejian Branch of Cangzhou Central Hospital, Cangzhou 061000, Hebei Province, China
Chen-Hui Fu, Ultrasound Medical Center, Cangzhou Central Hospital, Cangzhou 061000, Hebei Province, China
Meng-Mei Ma, Yu Han, Department of Critical Care Medicine, Hejian Branch of Cangzhou Central Hospital, Cangzhou 061000, Hebei Province, China
Lian-Chao Men, Department of Emergency Medicine, Hejian Branch of Cangzhou Central Hospital, Cangzhou 061000, Hebei Province, China
Bin Huang, Party Committee, Hejian Branch of Cangzhou Central Hospital, Cangzhou 061000, Hebei Province, China
Author contributions: Wang DY was responsible for study design, data analysis, and manuscript writing; Fu CH conducted ultrasound examinations and provided technical guidance; Ma MM and Men LC participated in clinical data collection and organization; Huang B coordinated the project; Han Y supervised the study and approved the final manuscript; all authors have read and approved the final version of the manuscript.
AI contribution statement: The authors confirm that Kimi 2.6 (developed by Moonshot AI) was used solely for language polishing to improve the clarity and readability of the answering-reviewers document. No AI tool was used to generate any portion of the main text, nor was it involved in the design of the study, interpretation of results, or the creation of any images in the manuscript. All scientific content, data analysis, and conclusions presented herein remain solely the work of the authors.
Supported by the Hebei Provincial Medical Scientific Research Program, No. 20251578.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of Cangzhou Central Hospital (No. 2024-315-02). The study was conducted in accordance with the principles of the Declaration of Helsinki.
Informed consent statement: Due to the retrospective design of the study and the use of anonymized clinical data, the requirement for written informed consent was waived by the Ethics Committee of Cangzhou Central Hospital (No. 2024-315-02).
Conflict-of-interest statement: The authors declare no conflict of interest in publishing the manuscript.
Data sharing statement: The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.
Corresponding author: Lian-Chao Men, Department of Emergency Medicine, Hejian Branch of Cangzhou Central Hospital, No. 32 Jingkai South Street, Cangzhou 061000, Hebei Province, China. 17733726859@163.com
Received: February 3, 2026 Revised: March 10, 2026 Accepted: August 25, 2026 Published online: October 19, 2026 Processing time: 249 Days and 0.5 Hours
Abstract
BACKGROUND
Anxiety and depression represent frequent complications among elderly frail patients that substantially impact functional recovery and quality of life. While bedside ultrasound multimodal assessment might serve as a valuable tool for identifying high-risk patients, the specific parameters underlying its predictive value remain incompletely understood.
AIM
To examine how bedside ultrasound multimodal parameters affect anxiety and depression development in elderly frail patients.
METHODS
This retrospective study enrolled 125 elderly frail patients admitted to our hospital’s geriatrics department between January 2022 and December 2024. Based on bedside ultrasound multimodal assessment severity, participants were categorized into a: (1) Low-risk cohort (mild abnormality, n = 56); and (2) High-risk cohort (moderate-severe abnormality, n = 69). The evaluated ultrasound parameters included diaphragm thickness fraction, rectus femoris cross-sectional area, inferior vena cava collapsibility index, cardiac output, and lung ultrasound score. Anxiety and depression assessment was performed using the Hospital Anxiety and Depression Scale 3 months after admission.
RESULTS
The study cohort included 125 elderly frail patients (average age 76.8 ± 8.5 years, 52.8% males). Anxiety developed in 42 patients (33.6%) and depression in 48 patients (38.4%). Three independent risk factors were identified: (1) Low diaphragm thickness fraction (< 20%) [odds ratio (OR) = 3.68, 95% confidence interval (CI): 1.58-8.57, P = 0.002]; (2) Reduced rectus femoris cross-sectional area (< 4.0 cm²) (OR = 2.95, 95% CI: 1.42-6.13, P = 0.004); and (3) Elevated lung ultrasound score (≥ 12 points) (OR = 2.67, 95% CI: 1.28-5.56, P = 0.009). A clear dose-response relationship was observed (Spearman r = 0.452, P < 0.001).
CONCLUSION
Bedside ultrasound multimodal assessment abnormalities constitute independent predictors of anxiety and depression in elderly frail patients. Early ultrasound-based risk stratification may facilitate targeted psychological screening and timely preventive interventions in this vulnerable population.
Core Tip: Bedside ultrasound provides fast, non-invasive evaluation for multisystem dysfunction in elderly frail patients. The study shows that diaphragm dysfunction and sarcopenia are independently predictive of anxiety and depression, with a demonstrated dose-response relationship that extends to pulmonary abnormalities diagnosed at the bedside by multimodal ultrasound. The use of early ultrasound-based risk stratification may allow for earlier psychosocial screening and targeted interventions in this high-risk population.
