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日间和夜间心率动态作为抑郁严重程度的数字生物标志物的可用性。

The usability of daytime and night-time heart rate dynamics as digital biomarkers of depression severity.

机构信息

Parc Sanitari Sant Joan de Déu, Fundació Sant Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain.

Aragón Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza, Spain.

出版信息

Psychol Med. 2023 Jun;53(8):3249-3260. doi: 10.1017/S0033291723001034. Epub 2023 May 15.

Abstract

BACKGROUND

Alterations in heart rate (HR) may provide new information about physiological signatures of depression severity. This 2-year study in individuals with a history of recurrent major depressive disorder (MDD) explored the intra-individual variations in HR parameters and their relationship with depression severity.

METHODS

Data from 510 participants (Number of observations of the HR parameters = 6666) were collected from three centres in the Netherlands, Spain, and the UK, as a part of the remote assessment of disease and relapse-MDD study. We analysed the relationship between depression severity, assessed every 2 weeks with the Patient Health Questionnaire-8, with HR parameters in the week before the assessment, such as HR features during all day, resting periods during the day and at night, and activity periods during the day evaluated with a wrist-worn Fitbit device. Linear mixed models were used with random intercepts for participants and countries. Covariates included in the models were age, sex, BMI, smoking and alcohol consumption, antidepressant use and co-morbidities with other medical health conditions.

RESULTS

Decreases in HR variation during resting periods during the day were related with an increased severity of depression both in univariate and multivariate analyses. Mean HR during resting at night was higher in participants with more severe depressive symptoms.

CONCLUSIONS

Our findings demonstrate that alterations in resting HR during all day and night are associated with depression severity. These findings may provide an early warning of worsening depression symptoms which could allow clinicians to take responsive treatment measures promptly.

摘要

背景

心率(HR)的变化可能提供有关抑郁严重程度生理特征的新信息。这项为期 2 年的研究针对有反复发作性重度抑郁症(MDD)病史的个体,探讨了 HR 参数的个体内变化及其与抑郁严重程度的关系。

方法

该研究的数据来自荷兰、西班牙和英国的三个中心,共 510 名参与者(HR 参数的观察次数=6666),这些参与者是远程评估疾病和复发-MDD 研究的一部分。我们分析了抑郁严重程度与 HR 参数之间的关系,抑郁严重程度每两周通过患者健康问卷-8 进行评估,HR 参数包括前一周的全天、白天和夜间休息期间、全天活动期间的 HR 特征,使用腕戴 Fitbit 设备进行评估。线性混合模型采用参与者和国家的随机截距。纳入模型的协变量包括年龄、性别、BMI、吸烟和饮酒、抗抑郁药使用以及与其他医疗健康状况的合并症。

结果

日间休息期间 HR 变化的减少与单变量和多变量分析中的抑郁严重程度增加相关。夜间休息时的平均 HR 在抑郁症状更严重的参与者中较高。

结论

我们的发现表明,全天和夜间休息时的 HR 变化与抑郁严重程度有关。这些发现可能提供抑郁症状恶化的早期预警,从而使临床医生能够及时采取响应性治疗措施。

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