Background

Although heart rate variability (HRV) is widely used to assess cardiac autonomic function, few studies have specifically investigated nocturnal HRV.

Objective

The purpose of this study was to assess the association between nocturnal HRV and cardiovascular disease (CVD) incidence over 4 years in a population-based sample.

Methods

A total of 1784 participants (48.2% men; 58 ± 11 years) from the HypnoLaus population-based cohort free of CVD at baseline were included. Polysomnography-based electrocardiograms were exported to analyze time- and frequency-domain HRV, Poincaré plots indices, detrended fluctuation analysis, acceleration capacity (AC) and deceleration capacity (DC), entropy, heart rate fragmentation (HRF), and heart rate turbulence. Multivariable-adjusted Cox regression analysis was used to assess the association between HRV indices and incident CVD events.

Results

Sixty-seven participants (3.8%) developed CVD over mean follow-up of 4.1 ± 1.1 years. In a fully adjusted model, AC (hazard ratio per 1-SD increase; 95% confidence interval: 1.59; 1.17–2.16; P = .004), DC (0.63; 0.47–0.84; P = .002), and HRF (1.41; 1.11–1.78; P = .005) were the only HRV metrics significantly associated with incident CVD events after controlling for false discovery rate.

Conclusion

Nocturnal novel HRV parameters such as AC, DC, and HRF are better predictors of CVD events than time and frequency traditional HRV parameters. These findings suggest a form of dysautonomia and fragmented rhythms, but further experimental studies are needed to delineate the underlying physiological mechanisms of these novel HRV parameters.

中文翻译：

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夜间心率变异性与心血管疾病事件之间的关联：HypnoLaus 基于人群的研究

背景

尽管心率变异性 (HRV) 被广泛用于评估心脏自主神经功能，但很少有研究专门研究夜间 HRV。

客观的

本研究的目的是在基于人群的样本中评估 4 年内夜间 HRV 与心血管疾病 (CVD) 发病率之间的关联。

方法

共有 1784 名参与者（48.2% 男性；58 ± 11 岁）来自 HypnoLaus 人群，基线时无 CVD。导出基于多导睡眠图的心电图以分析时域和频域 HRV、庞加莱图指数、去趋势波动分析、加速能力 (AC) 和减速能力 (DC)、熵、心率碎片 (HRF) 和心率湍流。多变量调整的 Cox 回归分析用于评估 HRV 指数与 CVD 事件之间的关联。

结果

67 名参与者 (3.8%) 在平均 4.1 ± 1.1 年的随访中发展为 CVD。在完全调整的模型中，AC（每增加 1-SD 的风险比；95% 置信区间：1.59；1.17–2.16；P = .004）、DC（0.63；0.47–0.84；P = .002）和 HRF（ 1.41；1.11–1.78；P = .005）是在控制错误发现率后与 CVD 事件显着相关的唯一 HRV 指标。

结论

夜间新的 HRV 参数，如 AC、DC 和 HRF，比时间和频率的传统 HRV 参数更能预测 CVD 事件。这些发现表明了一种形式的自主神经功能障碍和节律碎片，但需要进一步的实验研究来描述这些新的 HRV 参数的潜在生理机制。