Tang S, Xu TD, Liang Y, Ye X, Zhang HJ, Dai R, Yang G, Kong XQ, Sun W. Risk factors and prediction model for depressive disorder in survivors of acute cerebral hemorrhage. World J Psychiatry 2026; 16(4): 113317 [DOI: 10.5498/wjp.v16.i4.113317]
Corresponding Author of This Article
Xiang-Qing Kong, PhD, Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Gulou District, Nanjing 210000, Jiangsu Province, China. 15905218148@163.com
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Cardiac & Cardiovascular Systems
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Retrospective Study
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Apr 19, 2026 (publication date) through Mar 30, 2026
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World Journal of Psychiatry
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2220-3206
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Tang S, Xu TD, Liang Y, Ye X, Zhang HJ, Dai R, Yang G, Kong XQ, Sun W. Risk factors and prediction model for depressive disorder in survivors of acute cerebral hemorrhage. World J Psychiatry 2026; 16(4): 113317 [DOI: 10.5498/wjp.v16.i4.113317]
World J Psychiatry. Apr 19, 2026; 16(4): 113317 Published online Apr 19, 2026. doi: 10.5498/wjp.v16.i4.113317
Risk factors and prediction model for depressive disorder in survivors of acute cerebral hemorrhage
Shi Tang, Tong-Da Xu, Yi Liang, Xing Ye, Hong-Ju Zhang, Rui Dai, Ge Yang, Xiang-Qing Kong, Wei Sun
Shi Tang, Yi Liang, Xing Ye, Hong-Ju Zhang, Rui Dai, Ge Yang, Department of Cardiology, Xuzhou Municipal Hospital Affiliated to Xuzhou Medical University, Xuzhou 221000, Jiangsu Province, China
Tong-Da Xu, Department of Cardiology, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, Jiangsu Province, China
Xiang-Qing Kong, Wei Sun, Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210000, Jiangsu Province, China
Co-first authors: Shi Tang and Tong-Da Xu.
Co-corresponding authors: Xiang-Qing Kong and Wei Sun.
Author contributions: Tang S and Xu TD contributed equally as co-first authors; Tang S, Xu TD, Liang Y, Ye X, Zhang HJ, Dai R, Yang G, and Sun W contributed to data collection and paper writing; Kong XQ was responsible for funding application, reviewing and editing, communication coordination, ethical review, copyright and licensing, and follow-up; Kong XQ and Sun W contributed equally as co-corresponding authors; all authors did research design and data analysis and approved the final version to publish.
Institutional review board statement: The research was reviewed and approved by the Xuzhou Municipal Hospital Affiliated to Xuzhou Medical University, No. xyyll[2025]105.
Informed consent statement: All research participants or their legal guardians provided written informed consent prior to study registration.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement:
No other data available.
Corresponding author: Xiang-Qing Kong, PhD, Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Gulou District, Nanjing 210000, Jiangsu Province, China. 15905218148@163.com
Received: September 23, 2025 Revised: October 23, 2025 Accepted: December 17, 2025 Published online: April 19, 2026 Processing time: 187 Days and 20.9 Hours
Abstract
BACKGROUND
Post-intracerebral hemorrhage (ICH) depression is a prevalent and debilitating complication, adversely affecting recovery and survival. While identifying at-risk patients early is crucial, a comprehensive understanding of the specific risk factors in the acute phase remains limited. This study hypothesizes that a combination of clinical, imaging, and laboratory factors can effectively predict the onset of acute post-ICH depressive disorders. We hypothesized that advanced age, deep hematoma location, midline shift, low serum albumin, and high modified Rankin Scale (mRS) scores are independent risk factors, and a model combining these would demonstrate high predictive accuracy for acute post-ICH depression.
AIM
To investigate the risk factors and construct a prediction model for depressive disorder after acute ICH.
METHODS
This retrospective study analyzed 199 acute ICH survivors. Depression was assessed via Hamilton Depression Rating Scale 17-item version and confirmed by psychiatrists to rule out mimicking conditions/other psychiatric disorders. Univariate/multivariate logistic regression identified independent risk factors; a prediction model was built and evaluated via receiver operating characteristic (area under the curve for discriminatory power). Sample size (199) met the 180-190 minimum, estimated from 40%-60% assumed depression prevalence.
RESULTS
The depressive disorder group had older age, longer hospital stays, larger hematoma volumes, higher proportions of deep hematomas and brain midline shift, more severe brain atrophy, lower serum albumin, and worse neurological deficits (P < 0.05). Multivariate analysis identified older age, deep hematomas, brain midline shifts, low albumin, and increased mRS scores as independent risk factors (P < 0.05). The combined prediction model had an area under the curve of 0.885 (95% confidence interval: 0.832-0.926), 93.3% sensitivity, 67.0% specificity, and better predictive efficiency than single indicators.
CONCLUSION
A model incorporating age, deep hematoma, midline shift, albumin, and mRS score effectively predicts depression risk in acute ICH survivors, though external validation is required.
Core Tip: This study identified five independent risk factors (advanced age, deep hematoma, midline shift, low albumin, high modified Rankin Scale score) for post-intracerebral hemorrhage depression in the acute phase. A predictive model combining these factors demonstrated high discriminatory power (area under the curve = 0.885). This model aids in the early clinical screening of high-risk individuals, facilitating timely intervention to improve long-term prognosis. Key findings emphasize the roles of structural brain injury, systemic inflammation/malnutrition (reflected by albumin), and functional dependence in depression pathogenesis after acute intracerebral hemorrhage.
