2026 年第 8 期 第 21 卷

植入型心律转复除颤器术后患者创伤后应激障碍风险预测模型的构建及验证

Development and validation of a risk prediction model for post-traumatic stress disorder in patients after implantable cardioverter-defibrillator implantation

作者：胡晓媛1张哲1尚帅2

英文作者：Hu Xiaoyuan1 Zhang Zhe1 Shang Shuai2

单位：1新疆医科大学第一附属医院设备与信息管理部，乌鲁木齐830054；2新疆医科大学第一附属医院心血管病中心，乌鲁木齐830054

英文单位：1Department of Equipment and Information Management the First Affiliated Hospital of Xinjiang Medical University Urumqi 830054 China; 2Cardiovascular Disease Center the First Affiliated Hospital of Xinjiang Medical University Urumqi 830054 China

关键词：植入型心律转复除颤器；创伤后应激障碍；风险预测模型；列线图

英文关键词：Implantablecardioverter-defibrillator;Post-traumaticstressdisorder;Riskpredictionmodel;Nomogram

• 摘要：

• 目的 探讨植入型心律转复除颤器（ICD）患者术后创伤后应激障碍（PTSD）的影响因素，构建风险预测模型。方法 采用回顾性研究设计，选取2022年1月至2024年12月新疆医科大学第一附属医院收治的接受ICD植入手术的542例患者为研究对象。收集患者人口学资料、临床资料及心理相关资料，术后3个月采用临床用创伤后应激障碍诊断量表评估患者PTSD，并依此将患者分为PTSD组（59例）和非PTSD组（483例）。多因素Logistic回归分析确定独立危险因素，基于独立危险因素构建列线图风险预测模型。采用校准曲线、受试者工作特征曲线及决策曲线分析（DCA）验证模型的校准度、区分度及临床净收益。结果 术前精神心理疾病史、ICD电击经历、低社会支持、合并重度心力衰竭、应对方式消极及高医院焦虑抑郁量表评分是ICD患者术后发生PTSD的独立危险因素（均P＜0.05）。基于上述因素构建的列线图预测模型，经验证，校准曲线与理想对角线拟合度高（Hosmer-Lemeshow检验P=0.509），表明模型校准度优异；曲线下面积为0.902（95%置信区间：0.857～0.947），提示模型区分度良好；DCA结果显示，在较广的阈值概率范围内（0.03～0.98），模型临床净收益均高于“全干预”或“不干预”策略，具备良好的临床实用性。结论 术前精神心理疾病史、ICD电击经历等是ICD患者术后PTSD的核心危险因素，基于以上因素构建列线图预测模型具有良好的预测效能与临床应用价值。

• Objective To explore the influencing factors of post-traumatic stress disorder (PTSD) in patients after implantable cardioverter-defibrillator (ICD) implantation and construct a risk prediction model. Methods A retrospective study was conducted. A total of 542 patients who underwent ICD implantation in the First Affiliated Hospital of Xinjiang Medical University from January 2022 to December 2024 were enrolled. Demographic, clinical and psychological data of patients were collected. The clinician-administered PTSD scale was adopted to assess PTSD at 3 months after surgery, and patients were divided into PTSD group (59 cases) and non-PTSD group (483 cases). Multivariate Logistic regression analysis was performed to identify independent risk factors, and a nomogram risk prediction model was established based on these factors. Calibration curve, receiver operating characteristic curve and decision curve analysis (DCA) were used to verify the calibration, discrimination and clinical net benefit of the model. Results Preoperative history of mental illness, ICD shock experience, low social support, complicated severe heart failure, negative coping style and high hospital anxiety and depression scale score were independent risk factors for postoperative PTSD in ICD recipients (all P＜0.05). The nomogram prediction model constructed based on the above factors was verified with high fitting degree between calibration curve and ideal diagonal line (Hosmer-Lemeshow test P=0.509), indicating excellent calibration; the area under the curve was 0.902 (95% confidence interval: 0.857-0.947), suggesting favorable discrimination. DCA results showed that within a wide threshold probability range (0.03-0.98), the clinical net benefit of the model was higher than the treat-all or treat-none strategies, with satisfactory clinical practicability. Conclusion Preoperative mental illness history, ICD shock experience and other indicators are core risk factors for postoperative PTSD in ICD patients. The nomogram prediction model constructed on these factors presents favorable predictive performance and clinical application value.