| 曹琼,何菊芳,王于蓝,等.慢性失眠病人焦虑的影响因素及其预测模型的建立[J].安徽医药,2025,29(6):1170-1174. |
| 慢性失眠病人焦虑的影响因素及其预测模型的建立 |
| Factors affecting anxiety in patients with chronic insomnia and the development of a prediction model |
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| DOI：10.3969/j.issn.1009-6469.2025.06.021 |
| 中文关键词: 入睡和睡眠障碍 焦虑 多因素分析 列线图模型 LASSO回归 |
| 英文关键词: Sleep initiation and maintenance disorders Anxiety Multifactorial analysis Columnar graphical modelling LASSO regression |
| 基金项目:四川省中医药管理局中医药科研专项课题( 2023MS513) |
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| 中文摘要: |
| 目的分析慢性失眠病人焦虑影响因素，建立预测模型并进行验证。方法选择 2021年 7月至 2023年 9月四川省南充精神卫生中心接诊的慢性失眠病人 533例进行研究。病人以 7∶3比例用 R4.1.3软件分为模型组 387例，验证组 146例，根据有无焦虑将模型组病人分为焦虑组与无焦虑组，比较焦虑组与无焦虑组病人基本情况及失眠临床特征，以 LASSO回归筛选出潜在影响因素后行多因素 logistic回归，建立列线图模型并进行验证。结果模型组 387例慢性失眠病人中出现 83例( 21.45%)焦虑。在 LASSO回归基础上行多因素 logistic回归分析，结果显示:性别、婚姻状况、家庭月收入、作息习惯、亲属失眠状况、均总睡眠时间为慢性失眠病人焦虑状况的独立影响因素( P<0.05)。以多因素 logistic回归所获得的独立影响因素构建预测模日型，用列线图形式展示。模型验证结果显示，区分度:模型组受试者操作特征曲线( ROC曲线)曲线下面积为 0.74，95%CI为(0.68，0.80)；验证组 ROC曲线下面积为 0.72，95%CI为( 0.66，0.78)。准确度:模型组与验证组模型曲线与理想模型基本拟合成对角线， Hosmer-Lemeshow拟合优度检验显示 P>0.05。临床有效性分析结果显示当预测概率阈值为 0.15~0.82时使用该研究模型预测慢性失眠病人焦虑的净获益最高。结论慢性失眠焦虑的发生与性别、婚姻状况、家庭月收入、作息习惯、亲属失眠状况、日均总睡眠时间有关，该研究建立的列线图模型用于预测慢性失眠病人焦虑具有较高的准确度与区分度。 |
| 英文摘要: |
| Objective To analyze the influencing factors of anxiety in patients with chronic insomnia and to develop a validated pre-diction model. Methods A total of 533 patients with chronic insomnia treated in Nanchong Mental Health Center from July 2021 toSeptember 2023 were included in the study. The patients were assigned into a model group (n=387) and a validation group (n=146) us-ing R 4.1.3 software at a 7∶3 ratio. Based on the presence or absence of anxiety, the model group was further categorized into an anxi-ety subgroup and a non-anxiety subgroup. The baseline characteristics and clinical features of insomnia were compared between the anxiety and non-anxiety subgroups. Potential influencing factors were screened using LASSO regression, followed by multivariate logis-tic regression analysis. A nomogram model was subsequently developed and validated.Results Anxiety was present in 83 (21.45%) of387 patients with chronic insomnia in the model group.The results of multivariate logistic regression analysis on the basis of LASSO re-gression showed that gender, marital status, monthly family income, daily routines, insomnia status of family members, and average totaldaily sleep duration were the independent influences on the anxiety status of patients with chronic insomnia (P<0.05). A predictivemodel was constructed with the independent influences obtained from multivariate logistic regression and presented in the form of a no-mogram. The results of model validation showed the following: As for differentiation, the area under the ROC curve of the model groupwas 0.74, with a 95% CI of (0.68, 0.80), while the area under the ROC curve of the validation group was 0.72, with a 95% CI of (0.66,0.78); The model curves of the model group and the verification group were basically fitted to the diagonal line with the ideal model,and the Hosmer-Lemeshow goodness of fit test showed that P>0.05. The results of clinical validity analyses showed that the study mod-el achieved the highest net benefit at prediction probability thresholds ranging from 0.15 to 0.82. Conclusions The occurrence of chronic insomnia and anxiety is associated with factors including gender, marital status, monthly household income, daily routines, fam-ily history of insomnia, and average total daily sleep duration. The nomogram model established in this study demonstrates high accura-cy and discriminative ability in predicting anxiety among patients with chronic insomnia. |
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