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重度抑郁症中的心脏线索:评估电风险评分作为一种预测性心电图生物标志物

Cardiac Clues in Major Depressive Disorder: Evaluating Electrical Risk Score as a Predictive Electrocardiography Biomarker.

作者信息

Atilan Fedai Ulker, Fedai Halil, Tanriverdi Zulkif

机构信息

Department of Psychiatry, Faculty of Medicine, Harran University, Sanliurfa 63300, Turkey.

Department of Cardiology, Faculty of Medicine, Harran University, Sanliurfa 63300, Turkey.

出版信息

Medicina (Kaunas). 2025 May 31;61(6):1026. doi: 10.3390/medicina61061026.

Abstract

: Major depressive disorder (MDD) is a prevalent psychiatric illness increasingly recognized as a systemic condition with implications for cardiovascular diseases. Growing evidence indicates that individuals with MDD have an elevated risk of cardiovascular mortality, underscoring the need for reliable, non-invasive biomarkers to assess cardiac risk. While underlying mechanisms remain unclear, electrocardiogram (ECG)-based markers offer a promising, non-invasive means of evaluation. Among these, the electrical risk score (ERS), a composite derived from specific ECG parameters, has emerged as a predictor of adverse cardiac outcomes. This study aimed to investigate the association between ERS and MDD, and whether ERS correlates with depression severity and illness duration. : In this retrospective cross-sectional study, 12-lead ECGs were evaluated to calculate the ERS based on six ECG parameters: heart rate, corrected QT interval, Tp-e interval, frontal QRS-T angle, QRS transition zone, and presence of left ventricular hypertrophy according to Sokolow-Lyon criteria. The Hamilton Depression Rating Scale (HAM-D) was utilized. : The study included 102 patients with MDD and 62 healthy controls. No significant differences were observed in baseline or laboratory parameters between the groups. However, heart rate, Tp-e interval, frontal QRS-T angle, and ERS were significantly higher in the depression group. ROC analysis identified ERS as the strongest predictor of depression. ERS was significantly higher in patients with severe depression compared to those with mild symptoms and showed a positive correlation with both disease duration and HAM-D score. : Here, we show that the ECG-derived ERS is significantly elevated in patients with MDD and is associated with increased cardiac risk. ERS outperformed conventional ECG parameters in identifying individuals with depression and demonstrated positive associations with both illness duration and symptom severity. These findings suggest that ERS may serve as a practical, non-invasive biomarker for assessing cardiovascular vulnerability in this population.

摘要

重度抑郁症(MDD)是一种常见的精神疾病,越来越被认为是一种全身性疾病,与心血管疾病相关。越来越多的证据表明,患有MDD的个体心血管死亡风险升高,这凸显了需要可靠的非侵入性生物标志物来评估心脏风险。虽然潜在机制尚不清楚,但基于心电图(ECG)的标志物提供了一种有前景的非侵入性评估方法。其中,电风险评分(ERS),一种从特定ECG参数得出的综合指标,已成为不良心脏结局的预测指标。本研究旨在调查ERS与MDD之间的关联,以及ERS是否与抑郁严重程度和病程相关。

在这项回顾性横断面研究中,对12导联心电图进行评估,根据六个ECG参数计算ERS:心率、校正QT间期、Tp-e间期、额面QRS-T角、QRS过渡区以及根据索科洛夫-里昂标准判断的左心室肥厚情况。使用汉密尔顿抑郁评定量表(HAM-D)。

该研究纳入了102例MDD患者和62例健康对照。两组之间在基线或实验室参数方面未观察到显著差异。然而,抑郁组的心率、Tp-e间期、额面QRS-T角和ERS显著更高。ROC分析确定ERS是抑郁最强的预测指标。与轻度症状患者相比,重度抑郁患者的ERS显著更高,并且与病程和HAM-D评分均呈正相关。

在此,我们表明,MDD患者中基于心电图得出的ERS显著升高,且与心脏风险增加相关。在识别抑郁症患者方面,ERS优于传统的ECG参数,并与病程和症状严重程度均呈正相关。这些发现表明,ERS可能作为一种实用的非侵入性生物标志物,用于评估该人群的心血管易损性。

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