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心率分形性破坏作为健康人群阈下抑郁症状的一个印记

Heart Rate Fractality Disruption as a Footprint of Subthreshold Depressive Symptoms in a Healthy Population.

作者信息

Mandarano Piergiorgio, Ossola Paolo, Castiglioni Paolo, Faini Andrea, Marazzi Pierluca, Carsillo Maria, Rozzi Stefano, Lazzeroni Davide

机构信息

Department of Medicine and Surgery, University of Parma, Parma, Italy.

School of Child and Adolescent Neuropsychiatry, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.

出版信息

Clin Neuropsychiatry. 2022 Jun;19(3):163-173. doi: 10.36131/cnfioritieditore20220305.

Abstract

OBJECTIVE

Psychopathology (and depression in particular) is a cardiovascular risk factor independent from any co-occurring pathology. This link is traced back to the mind-heart-body connection, whose underlying mechanisms are still not completely known. To study psychopathology in relation to the heart, it is necessary to observe the autonomic nervous system, which mediates among the parts of that connection. Its gold standard of evaluation is the study of heart rate variability (HRV). To investigate whether any association exists between the HRV parameters and sub-threshold depressive symptoms in a sample of healthy subjects.

METHOD

In this cross-sectional study, two short-term HRV recordings (5 min - supine and sitting) have been analyzed in 77 healthy subjects. Here we adopted a three-fold approach to evaluate HRV: a set of scores belonging to the time domain; to the frequency domain (high, low, and very low frequencies) and a set of 'nonlinear' parameters. The PHQ-9 (Patient Health Questionnaire-9) scale was used to detect depressive symptoms.

RESULTS

Depressive symptoms were associated only with a parameter from the non-linear approach and specifically the long-term fluctuations of fractal dimensions (DFA-α2). This association remained significant even after controlling for age, gender, BMI (Body-Mass-Index), arterial hypertension, anti-hypertensive drugs, dyslipidemia, and smoking habits. Moreover, the DFA-α2 was not affected by the baroreflex (postural change), unlike other autonomic markers.

CONCLUSIONS

Fractal analysis of HRV (DFA-α2) allows then to predict depressive symptoms below the diagnostic threshold in healthy subjects regardless of their health status. DFA-α2 may be considered as an imprint of subclinical depression on the heart rhythm.

摘要

目的

精神病理学(尤其是抑郁症)是一种独立于任何并发疾病的心血管危险因素。这种联系可追溯到心-身-体的关联,其潜在机制仍未完全明确。为了研究与心脏相关的精神病理学,有必要观察自主神经系统,它在这种关联的各部分之间起介导作用。其评估的金标准是心率变异性(HRV)研究。旨在调查健康受试者样本中HRV参数与阈下抑郁症状之间是否存在关联。

方法

在这项横断面研究中,对77名健康受试者的两次短期HRV记录(5分钟——仰卧位和坐位)进行了分析。在此我们采用了三种方法来评估HRV:一组属于时域的分数;频域(高频、低频和极低频)的分数以及一组“非线性”参数。使用患者健康问卷-9(PHQ-9)量表来检测抑郁症状。

结果

抑郁症状仅与非线性方法中的一个参数相关,具体而言是分形维数(DFA-α2)的长期波动。即使在控制了年龄、性别、体重指数(BMI)、动脉高血压、抗高血压药物、血脂异常和吸烟习惯之后,这种关联仍然显著。此外,与其他自主神经标志物不同,DFA-α2不受压力反射(体位改变)的影响。

结论

HRV的分形分析(DFA-α2)能够在不考虑健康受试者健康状况的情况下预测低于诊断阈值的抑郁症状。DFA-α2可被视为亚临床抑郁症在心律上的一种印记。

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