Association between instantaneous heart rate sequence during the awake period and cardiovascular events: a study based on Sleep Heart Health Study.

Abstract

Background: Heart rate variability (HRV) has been reported to be associated with cardiovascular diseases (CVD), while few studies focused on the instantaneous heart rate (IHR). This study aimed to establish models to predict the occurrence of cardiovascular events based on the IHR sequence.

Methods: A total of 2977 participants with useful electrocardiogram (ECG) data and free of CVD events at baseline from the Sleep Heart Health Study (SHHS) database were included in this retrospective cohort study. All IHR indicators were measured during the awake period before sleep. The logistic regression, random forest, and XGBoost methods were used to develop the predictive models. The model performance was quantified by calculating the area under the curve (AUC).

Results: Of theses 2977 participants, 1460 (49.04%) participants had CVD events during the 15-year follow-up. Higher standard deviation of IHR (SDHR) (OR=0.906; 95% CI, 0.832-0.986), coefficient of variation of IHR (CVHR) (OR=0.910; 95% CI, 0.835-0.990), power in low frequency (LF) (OR=0.896; 95% CI, 0.822-0.975), power in high frequency (HF) (OR=0.872; 95% CI, 0.796-0.955), and total power (TP) (OR=0.887; 95% CI, 0.813-0.967) were associated with the lower risk of CVD events, while ratio of semi-minor axis and semi-major axis in Poincare plot (SDratio) (OR=1.105; 95% CI, 1.012-1.206) was related to the higher risk of CVD events. The AUCs of the logistic regression, random forest, and the XGBoost models were 0.734 (95% CI, 0.701-0.767), 0.794 (95% CI, 0.764-0.823) and 0.828 (95% CI, 0.801-0.855) in the testing set, respectively.

Conclusions: IHR sequences were important predictors of cardiovascular events. The IHR indicators should be paid more attention to in future clinical researches on CVD.