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情绪调节能力对评估抑郁症患者认知改善的预测效用。

Predictive utility of emotional regulation abilities for assessing cognitive improvement in depression.

机构信息

Department of Neurology, Shanghai Tongji Hospital, School of Medicine, Tongji University, Shanghai 200092, China; Department of Neurology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, 2800 Gongwei Road, Pudong, Shanghai, 201399, China.

Department of Clinical Medicine, The Second School of Clinical Medicine, Guangdong Medical University, Dongguan, Guangdong 523808, China.

出版信息

J Psychiatr Res. 2024 Nov;179:46-55. doi: 10.1016/j.jpsychires.2024.08.036. Epub 2024 Aug 27.

Abstract

OBJECTIVE

To construct a predictive model for the improvement of cognitive function in patients with depressive disorder treated with SNRIs, based on emotional regulation abilities, and to provide personalized treatment for depressed patients.

METHODS

Clinical data from 170 patients with depressive disorder treated with SNRIs at Tongji Hospital, Shanghai, from December 2017 to May 2023 were collected. Based on whether the MoCA-B total score at 3-6 months post-treatment was at least 2 points higher than at baseline, patients were divided into the cognitive function improved group (n = 80) and the cognitive function not improved group (n = 90). Stepwise logistic regression and LASSO regression were used to select predictive factors, and logistic regression analysis was applied to construct predictive models solely based on emotional regulation abilities, combined with executive functions and HAMD scores. The models were further validated through Bootstrap internal validation, calibration curve plotting, and C-index calculation, and a comparison between the two models was performed.

RESULTS

An ER model with an area under the ROC curve of 0.817was established using four emotional regulation ability indicators: the valence of reappraised images, the arousal of negative images, the arousal of neutral images, and the success of reappraisal (arousal). Internal validation using Bootstrap showed a C index of 0.817, and clinical decision curves indicated that this model has a significant net benefit with a probability of improved cognitive function ranging from about 20 to 85%. Additionally, an EREH model including emotional regulation ability, executive function, and HAMD score as predictors was constructed using Lasso and logistic regression methods. This model reached an area under the ROC curve of 0.859and clinical decision curves showed high net benefits with probabilities of improved cognitive function ranging from 10 to 100%. The calibration curves of both models coincided well with the actual curves, with the latter having a higher AUC and significant statistical differences between the two models.

CONCLUSION

This study suggests that emotional regulation ability may serve as a predictor for the improvement of cognitive functions in patients with depression depressive disorder treated with SNRIs. However, it is important to note that there may be other factors not covered or included in this study.The predictive model that includes executive functions and HAMD scores offers better differentiation and consistency and is more feasible in clinical practice.

摘要

目的

基于情绪调节能力,构建预测 SNRIs 治疗抑郁障碍患者认知功能改善的模型,为抑郁患者提供个体化治疗。

方法

收集 2017 年 12 月至 2023 年 5 月在上海同济大学附属同济医院接受 SNRIs 治疗的 170 例抑郁障碍患者的临床资料。根据治疗后 3-6 个月 MoCA-B 总分是否至少比基线提高 2 分,将患者分为认知功能改善组(n=80)和认知功能未改善组(n=90)。采用逐步逻辑回归和 LASSO 回归筛选预测因素,基于情绪调节能力、执行功能和 HAMD 评分构建预测模型。采用 Bootstrap 内部验证、校准曲线绘制和 C 指数计算对模型进行进一步验证,并比较两种模型。

结果

建立了一个基于四个情绪调节能力指标(再评价图像的效价、负性图像的唤醒度、中性图像的唤醒度和再评价的成功度)的 ROC 曲线下面积为 0.817 的 ER 模型。使用 Bootstrap 进行内部验证时,C 指数为 0.817,临床决策曲线表明,该模型具有显著的净效益,认知功能改善的概率约为 20%至 85%。此外,还使用 Lasso 和逻辑回归方法构建了一个包含情绪调节能力、执行功能和 HAMD 评分作为预测因子的 EREH 模型。该模型的 ROC 曲线下面积达到 0.859,临床决策曲线显示,认知功能改善的概率为 10%至 100%时,具有较高的净效益。两个模型的校准曲线与实际曲线吻合良好,后者的 AUC 更高,且两个模型之间存在显著的统计学差异。

结论

本研究表明,情绪调节能力可能是预测 SNRIs 治疗抑郁障碍患者认知功能改善的一个指标。然而,需要注意的是,本研究可能还存在其他未涵盖或未纳入的因素。包含执行功能和 HAMD 评分的预测模型具有更好的区分度和一致性,在临床实践中更具可行性。

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