Department of Neurology, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, Anhui, China.
Center for Xin'An Medicine and Modernization of Traditional Chinese Medicine, Institute of Health and Medicine, Hefei Comprehensive National Science Center, Hefei, Anhui, China.
Br J Hosp Med (Lond). 2024 Sep 30;85(9):1-12. doi: 10.12968/hmed.2024.0208. Epub 2024 Sep 19.
To investigate the application value of a machine learning model in predicting mild depression associated with migraine without aura (MwoA). 178 patients with MwoA admitted to the Department of Neurology of the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine from March 2022 to March 2024 were selected as subjects. According to their inpatient medical records, 38 patients were selected as the validation group by random number method, and the remaining 140 patients were included in the modelling group. According to the diagnosis results, the patients in the modelling group and validation group were further divided into a MwoA with mild depression group and a MwoA without mild depression group. The results of univariate analysis and Multivariate logistic regression analysis showed that gender, course of disease, attack frequency, headache duration, Migraine Disability Assessment Questionnaire (MIDAS), and Headache Impact Test-6 (HIT-6) score were independent influencing factors for mild depression in MwoA patients ( < 0.05). The receiver operating characteristic (ROC) analysis results showed that the area under the curve of the established prediction model for MwoA patients with mild depression in the modelling group and the validation group was 0.982 and 0.901, respectively, the sensitivity was 0.978 and 0.857, respectively, and the specificity was 0.892 and 0.929, respectively. Gender, course of disease, seizure frequency, headache duration, MIDAS score, and HIT-6 score are independent influencing factors for mild depression in patients with MwoA. The model displays good performance for the prediction of mild depression in patients with MwoA.
为了探究机器学习模型在预测无先兆偏头痛伴轻度抑郁（MwoA）中的应用价值。选取 2022 年 3 月至 2024 年 3 月安徽中医药大学第一附属医院神经内科收治的 MwoA 患者 178 例为研究对象。根据患者住院病历，采用随机数字法抽取 38 例患者作为验证组，剩余 140 例患者纳入建模组。根据诊断结果，建模组和验证组患者进一步分为 MwoA 伴轻度抑郁组和 MwoA 不伴轻度抑郁组。单因素分析和多因素 logistic 回归分析结果显示，性别、病程、发作频率、头痛持续时间、偏头痛残疾评估问卷（MIDAS）和头痛影响测试-6（HIT-6）评分是 MwoA 患者伴发轻度抑郁的独立影响因素（<0.05）。受试者工作特征（ROC）分析结果显示，建模组和验证组 MwoA 伴发轻度抑郁患者预测模型的曲线下面积分别为 0.982、0.901，敏感度分别为 0.978、0.857，特异度分别为 0.892、0.929。性别、病程、发作频率、头痛持续时间、MIDAS 评分、HIT-6 评分是 MwoA 患者伴发轻度抑郁的独立影响因素。该模型对 MwoA 患者伴发轻度抑郁的预测效果良好。
