住院老年精神分裂症患者暴力行为调查及相关因素的Logistic回归分析-东南大学学报医学版

住院老年精神分裂症患者暴力行为调查及相关因素的Logistic回归分析

单位：南京医科大学附属脑科医院老年精神科, 江苏南京 210000

分类号：R473.5

出版年·卷·期（页码）：2025·44·第二期（220-228）

摘要：

目的:探讨住院老年精神分裂症患者暴力行为的现状以及危险因素,据此构建预测模型。方法:回顾性分析2021年3月至2024年3月于本院住院治疗的314例老年精神分裂症患者的临床资料,根据是否出现暴力行为分为暴力行为组(n=109)和非暴力行为组(n=205)。比较两组临床风险因素,明确住院老年精神分裂症患者出现暴力行为的风险因素,根据结果构建预测模型,绘制ROC曲线分析模型的预测价值。结果:314例老年精神分裂症住院患者暴力行为发生率为34.71%(109/314)。多因素Logistic回归分析显示,既往精神疾病未治疗(OR=1.879,95%CI 1.175~7.103)、药物依从性差(OR=2.215,95%CI 1.216~7.854)、暴力行为史(OR=3.746,95%CI 1.385~12.745)、非自愿住院(OR=2.014,95%CI 1.209~7.367)、被害妄想(OR=1.186,95%CI 1.098~6.289)、PANSS阳性症状量表评分＞28分(OR=3.013,95%CI 1.308~9.364)、PANSS阴性症状量表评分＞25分(OR=2.785,95%CI 1.264~8.964)以及父母有家暴行为(OR=1.396,95%CI 1.146~6.786)是住院老年精神分裂症患者暴力行为的独立风险因素。根据风险因素构建列线图风险预测模型,该模型ROC曲线下面积为0.815(95% CI 0.711~0.919),敏感度和特异度分别为0.82和0.80。模型校准曲线结果显示,预测曲线与标准曲线拟优度良好。结论:住院老年精神分裂症患者的暴力行为与多个独立风险因素密切相关,基于这些独立风险因素构建的预测模型表现出良好的预测能力,可为临床护理干预提供一定的预测价值,有助于识别暴力行为的高风险患者,进而为采取有效的预防和干预措施。

Objective: To investigate the prevalence and risk factors of violent behavior in hospitalized elderly patients with schizophrenia and to construct a predictive model based on these findings. Methods: A retrospective analysis was conducted on the clinical data of 314 elderly patients with schizophrenia hospitalized in our facility from March 2021 to March 2024. Patients were divided into violence group(n=109) and non-violence group(n=205) based on the presence of violent behavior. Clinical risk factors between the two groups were compared to identify risk factors associated with violent behavior in hospitalized elderly schizophrenia patients. Predictive model was constructed based on these findings, and ROC curve was plotted to evaluate the model's predictive value. Results: This study included 314 hospitalized elderly patients with schizophrenia, with a violent behavior incidence of 34.71%(109/314). Multivariate Logistic regression analysis showed that untreated prior psychiatric illness(OR=1.879, 95% CI 1.175-7.103), poor medication adherence(OR=2.215, 95% CI 1.216-7.854), history of violent behavior(OR=3.746, 95% CI 1.385-12.745), involuntary hospitalization(OR=2.014, 95% CI 1.209-7.367), persecutory delusions(OR=1.186, 95% CI 1.098-6.289), PANSS positive symptom score>28(OR=3.013, 95% CI 1.308-9.364), PANSS negative symptom score>25(OR=2.785, 95% CI 1.264-8.964), and parental history of domestic violence(OR=1.396, 95% CI 1.146-6.786) were independent risk factors for violent behavior. Nomogram-based risk prediction model was constructed based on the identified risk factors. The area under the ROC curve(AUC) for this model was 0.815(95% CI 0.711-0.919), with sensitivity of 0.82 and specificity of 0.80. The model's calibration curve showed strong agreement between the predicted and actual probabilities. Conclusion: Violent behavior in hospitalized elderly patients with schizophrenia is closely associated with several independent risk factors. The predictive model builted on these independent factors demonstrates good predictive capability, providing valuable insights for clinical care interventions. This model can help identify high-risk patients for violent behavior, thereby facilitating effective prevention and intervention strategies.

参考文献：

[1] JAVITT D C.Cognitive impairment associated with schizophrenia:from pathophysiology to treatment[J].Annu Rev Pharmacol Toxicol,2023,63:119-141.
[2] FISCHER C E,NAMASIVAYAM A,CRAWFORD H L,et al.Psychotic disorders in the elderly:diagnosis,epidemiology,and treatment[J].Psychiatr Clin North Am,2022,45(4):691-705.
[3] CORNELIS C,DE PICKER L J,COPPENS V,et al.Impaired sensorimotor adaption in schizophrenia in comparison to age-matched and elderly controls[J].Neuropsychobiology,2022,81(2):127-140.
[4] KRAKOWSKI M I,TURAL U,CZOBOR P.Separate pathways to violent behavior in schizophrenia and in the general population[J].J Psychiatr Res,2022,151:235-241.
[5] SONNWEBER M,LAU S,KIRCHEBNER J.Violent and non-violent offending in patients with schizophrenia:exploring influences and differences via machine learning[J].Compr Psychiatry,2021,107:152238.
[6] 李茜,张云淑,严保平,等.注射用利培酮微球(Ⅱ)治疗急性期精神分裂症患者的疗效及安全性研究[J].中国全科医学,2023,26(32):4007-4012.
[7] 陈卿,刘成锋,程娟,等.深圳市宝安区在册精神分裂症患者高风险行为影响因素交互作用分析[J].中华疾病控制杂志,2022,26(6):691-695,739.
[8] 曹子瑶,钱程,谢国华,等.老年精神分裂症住院患者被动自杀意念与促甲状腺激素和催乳素的相关性研究[J].中国全科医学,2023,26(23):2894-2898.
[9] 白雪,崔胜男,冯铭,等.神经系统疾病icd-10与icd-11分类对比研究[J].中国医药导报,2019,16(3):175-178,182.
[10] CHAN A H Y,HORNE R,HANKINS M,et al.The medication adherence report scale:a measurement tool for eliciting patients' reports of nonadherence[J].Br J Clin Pharmacol,2020,86(7):1281-1288.
[11] KAY S R,FISZBEIN A,OPLER L A.The positive and negative syndrome scale(panss)for schizophrenia[J].Schizophr Bull,1987,13(2):261-276.
[12] 张志坚.老年精神分裂症患者社会认知现状及对社会功能的影响[J].中国肿瘤临床,2020,47(17):919.
[13] 郭妹,张景双.精神分裂症患者用药合理性的调查与研究[J].中国医院药学杂志,2019,39(3):306-309.
[14] 张志坚.精神分裂症状患者暴力行为因素分析及管理措施研究[J].介入放射学杂志,2020,29(6):642.
[15] 银燕,余建英,熊智.影响精神分裂症病人攻击行为的相关因素分析[J].护理研究,2019,33(21):3667-3671.
[16] 仪玉伟,闫芳,靳玉宏,等.精神分裂症住院患者危险行为的影响因素分析[J].首都医科大学学报,2021,42(2):323-327.
[17] 魏泸懿,杨先梅,范箬馨,等.精神分裂症患者服药依从性与不同类型危险行为的关联研究[J].四川大学学报(医学版),2023,54(6):1201-1207.
[18] 张伟波,陈春梅,何思源,等.社区精神分裂症患者暴力行为综合风险预测模型的建立[J].中国心理卫生杂志,2022,36(10):844-850.
[19] 代雨岑,郭易,秦小荣,等.中国精神分裂症患者暴力行为影响因素的Meta分析[J].现代预防医学,2020,47(16):2998-3001,3011.
[20] 孔令茵,吴逢春,雷炳业,等.基于多模态MRI精神分裂症脑复杂网络研究进展[J].中国医学影像技术,2020,36(10):1550-1554.
[21] JANAH M,HARGIANA G.Levels of stress and coping strategies in family caregivers who treat schizophrenic patients with risk of violent behavior[J].J Public Health Res,2021,10(s1):jphr.2021.2404.

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