癫痫共患抑郁、焦虑的危险因素分析及模型构建-东南大学学报医学版

癫痫共患抑郁、焦虑的危险因素分析及模型构建

单位：南京医科大学附属脑科医院功能神经外科, 江苏南京 210029

分类号：R473.6

出版年·卷·期（页码）：2025·44·第二期（313-321）

摘要：

目的:探讨癫痫患者共患抑郁、焦虑的现状以及危险因素,并构建预测模型。方法: 回顾性分析2022年2月至2024年5月于本院住院治疗的328例癫痫患者的临床资料,单因素分析筛选癫痫患者共患焦虑、抑郁的危险因素,多因素Logistic回归分析进一步筛选独立风险因素,根据结果构建癫痫共患抑郁、焦虑的预测模型,采用受试者工作特征(ROC)曲线及Homer-Lemeshow检验评估模型的预测价值。结果:328例癫痫患者中63例(19.21%)共患焦虑,81例(24.70%)共患抑郁,50例(15.24%)共患抑郁和焦虑。多因素 Logistic 回归分析结果显示,家庭收入(OR=2.802,95%CI 1.575~8.075)、工作状态(OR=2.315,95%CI 1.409~7.926)、癫痫病程(OR=3.287,95%CI 1.831~9.337)、无发作状态持续时间(OR=1.797,95%CI 1.275~4.827)以及合并其他慢病(OR=1.948,95%CI 1.360~6.653)是癫痫患者共患抑郁的独立影响因素;癫痫发作频率(OR=1.629,95%CI 1.258~6.746)、癫痫病程(OR=3.604,95%CI 1.726~8.835)、服药依从性(OR=1.872,95%CI 1.384~7.083)以及无发作状态持续时间(OR=2.247,95%CI 1.685~7.740)是癫痫患者共患焦虑的独立影响因素。癫痫共患抑郁预测模型ROC曲线下面积(AUC)为0.807(95%CI 0.724~0.890),Homer-Lemeshow检验P＞0.05,模型的诊断性能及准确度较高;癫痫共患焦虑预测模型AUC为0.799(95%CI 0.701~0.897),Homer-Lemeshow检验P＞0.05,模型的诊断性能及准确度较高。结论:本研究确定了癫痫共患抑郁、焦虑的危险因素并初步建立了的预测模型,该模型的预测效能较好,有助于在护理实践中早期识别并干预具有抑郁和焦虑共患风险的患者。

Objective: To investigate the prevalence and risk factors of comorbid depression and anxiety in patients with epilepsy and to construct a predictive model. Methods: A retrospective analysis was conducted on the clinical data of 328 epilepsy inpatients treated at our hospital between February 2022 and May 2024. Univariate analysis was used to identify potential risk factors for comorbid depression and anxiety in epilepsy patients, followed by multivariate Logistic regression to determine independent risk factors. The predictive model for comorbid depression and anxiety in epilepsy was constructed based on these results, and its predictive value was evaluated using receiver operating characteristic(ROC) curve analysis and the Hosmer-Lemeshow test. Results: A total of 328 epilepsy patients were included in the study, with 19.21%(63/328) experiencing comorbid anxiety, 24.70%(81/328) with comorbid depression, and 15.24%(50/328) with both depression and anxiety. Multivariate Logistic regression analysis identified that family income(OR=2.802, 95% CI 1.575-8.075), employment status(OR=2.315, 95% CI 1.409-7.926), epilepsy duration(OR=3.287, 95% CI 1.831-9.337), duration of seizure-free state(OR=1.797, 95% CI 1.275-4.827), and presence of other chronic diseases(OR=1.948, 95% CI 1.360-6.653) were independent risk factors for comorbid depression. For comorbid anxiety, independent risk factors included seizure frequency(OR=1.629, 95% CI 1.258-6.746), epilepsy duration(OR=3.604, 95% CI 1.726-8.835), medication adherence(OR=1.872, 95% CI 1.384-7.083), and duration of seizure-free state(OR=2.247, 95% CI 1.685-7.740). The area under the ROC curve(AUC) for the model predicting comorbid depression was 0.807(95% CI 0.724-0.890), with a Hosmer-Lemeshow test result of P>0.05, indicating high diagnostic performance and accuracy. For the comorbid anxiety prediction model, the AUC was 0.799(95% CI 0.701-0.897), with a Hosmer-Lemeshow test result of P>0.05, also indicating high diagnostic performance and accuracy. Conclusion: This study identified risk factors for comorbid depression and anxiety in epilepsy patients and developed a preliminary predictive model with strong predictive efficiency. This model may aid in early identification and intervention for patients at risk of comorbid depression and anxiety in clinical practice.

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