双相情感障碍患者精神与躯体共病特征及相关因素的回顾性分析-现代医学

双相情感障碍患者精神与躯体共病特征及相关因素的回顾性分析

单位：南京医科大学附属脑科医院精神二科620病区, 江苏南京 210029

分类号：R749.4

出版年·卷·期（页码）：2026·54·第七期（1080-1089）

摘要：

目的：探讨双相情感障碍(BD)患者的精神及躯体共病特征，分析其相关因素，并评估不同BD亚型及性别间共病谱的差异。方法：回顾性纳入2022年1月至2024年12月于南京医科大学附属脑科医院就诊的BD患者318例，其中BD Ⅰ型205例(64.47%)，BD Ⅱ型113例(35.53%)。收集人口学特征、临床资料及药物治疗信息。采用单因素分析及多因素Logistic回归筛选共病的独立相关因素，构建风险识别模型并以受试者工作特征(ROC)曲线评估区分能力，Bootstrap法(1 000次重抽样)进行内部验证。结果：318例患者中共病196例(61.64%)，共病谱系前3位为焦虑障碍(27.04%)、代谢综合征(23.90%)、物质使用障碍(13.84%)。多因素Logistic回归显示，发病年龄<20岁(OR=3.108，95%CI：1.712~5.642)、病程>5年(OR=2.655，95%CI：1.534~4.596)、年发作频率≥4次(OR=2.367，95%CI：1.321~4.239)、联合使用≥2种非典型抗精神病药(OR=2.103，95%CI：1.164~3.801)为共病的独立相关因素(均P<0.05)。风险识别模型ROC曲线下面积(AUC)为0.812(95%CI：0.768~0.856)，Bootstrap校正后AUC为0.795，最佳截断值对应灵敏度为74.8%、特异度为72.5%。进一步分析显示，以BD Ⅱ型为参照组，BD Ⅰ型患者总体共病风险更高(aOR=1.65，95%CI：1.02~2.67)；以男性为参照组，女性焦虑障碍共病风险更高(aOR=2.52，95%CI：1.45~4.36)，而物质使用障碍共病风险更低(aOR=0.41，95%CI：0.21~0.78)。结论：BD患者共病率较高，基于常规临床指标的风险识别模型可辅助识别合并共病的高风险患者。BD亚型及性别与共病谱存在不同关联模式，临床应结合患者特征实施个体化管理策略。

Objective: To investigate the psychiatric and somatic comorbidity patterns in patients with bipolar disorder(BD), analyze associated factors and evaluate differences in comorbidity spectra across BD subtypes and sexes. Methods: A total of 318 patients with BD treated at the Affiliated Brain Hospital of Nanjing Medical University from January 2022 to December 2024 were retrospectively enrolled, including 205 cases(64.47%) of BD type Ⅰ and 113 cases(35.53%) of BD type Ⅱ. Demographic characteristics, clinical data and medication information were collected. Univariate analysis and multivariate Logistic regression were used to identify independent factors associated with comorbidities, and a risk prediction model was constructed. Discriminative ability was assessed using the receiver operating characteristic(ROC) curve, and internal validation was performed using the Bootstrap method with 1000 resampling iterations. Results: Among the 318 patients, 196(61.64%) presented with comorbidities. The top three comorbidities were anxiety disorders(27.04%), metabolic syndrome(23.90%) and substance use disorders(13.84%). Multivariate Logistic regression revealed that age at onset <20 years(OR=3.108, 95%CI:1.712-5.642), disease duration>5 years(OR=2.655, 95%CI:1.534-4.596), annual episode frequency≥4(OR=2.367, 95%CI:1.321-4.239) and concomitant use of≥2 atypical antipsychotics(OR=2.103, 95%CI:1.164-3.801) were independent factors associated with comorbidities(all P＜0.05). The area under the ROC curve(AUC) of the risk prediction model was 0.812(95%CI:0.768-0.856) and the Bootstrap-corrected AUC was 0.795. At the optimal cutoff value, the sensitivity was 74.8% and the specificity was 72.5%. Further analyses showed that, using BD type Ⅱ as the reference group, patients with BD type Ⅰ had a higher overall comorbidity risk(aOR=1.65, 95%CI:1.02-2.67); using males as the reference group, females had a higher risk of comorbid anxiety disorders(aOR=2.52, 95%CI:1.45-4.36) but a lower risk of comorbid substance use disorders(aOR=0.41, 95%CI:0.21-0.78). Conclusion: Patients with BD have a high comorbidity rate. The risk prediction model based on routine clinical indicators may assist in identifying patients at high risk for comorbidities. BD subtypes and sex show different association patterns with comorbidity spectra, suggesting that individualized management strategies should be implemented according to patient characteristics in clinical practice.

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