Alkhodari Mohanad, Jelinek Herbert F, Werghi Naoufel, Hadjileontiadis Leontios J, Khandoker Ahsan H
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:714-717. doi: 10.1109/EMBC44109.2020.9175830.
Early and noninvasive identification of heart failure progression is an important adjunct to successful and timely intervention. Severity of heart failure (HF) was assessed by Left Ventricular Ejection Fraction (LVEF). In this paper, we explore the circadian (24-hour) heart rate variability (HRV) features from ''normal" (EF >50%), "at-risk" (EF <40%), and "border-line" (40% ≤ EF ≤ 50%) patient data to determine whether HRV features can predict the stage of heart failure. All coronary artery disease (CAD) 24-hour circadian heart rate data were fitted by a cosinor analysis algorithm. Hourly HRV features from time- and frequency-domains were then extracted from all 24-hour patient data. A one-way ANOVA test was performed followed by a Tukey post-hoc multiple comparison test to investigate the differences among the three groups. The results showed a statistically significant difference between the three groups when using the normalized high frequency (HF Norm), low frequency peak (LF Peak), and the normalized very-low frequency (VLF Norm) for the 05:00-06:00 and 18:00-19:00 time periods. These results highlight a possible link between the circadian variation of sympathetic and parasympathetic nervous system activity and LVEF for CAD patients. The results could be useful in differentiating the various degrees of LVEF by using only noninvasive HRV features derived over a 24-hour period.Clinical relevance- The proposed method could be clinically useful to estimate the extent of LVEF associated with the severity of heart failure by recording the circadian variation of the heart rate in CAD patients. However, further clinical trials on a larger cohort of patients and controls are required.
早期且无创地识别心力衰竭进展是成功及时干预的重要辅助手段。通过左心室射血分数（LVEF）评估心力衰竭（HF）的严重程度。在本文中，我们从“正常”（EF>50%）、“高危”（EF<40%）和“临界”（40%≤EF≤50%）患者数据中探索昼夜（24小时）心率变异性（HRV）特征，以确定HRV特征是否能预测心力衰竭阶段。所有冠状动脉疾病（CAD）患者的24小时昼夜心率数据均采用余弦分析算法进行拟合。然后从所有24小时患者数据中提取时域和频域的每小时HRV特征。进行单因素方差分析，随后进行Tukey事后多重比较检验，以研究三组之间的差异。结果显示，在05:00 - 06:00和18:00 - 19:00时间段使用归一化高频（HF Norm）、低频峰值（LF Peak）和归一化极低频（VLF Norm）时，三组之间存在统计学显著差异。这些结果突出了CAD患者交感神经和副交感神经系统活动的昼夜变化与LVEF之间可能存在的联系。仅通过使用24小时内得出的无创HRV特征来区分不同程度的LVEF，这些结果可能会有所帮助。临床相关性——所提出的方法通过记录CAD患者心率的昼夜变化，在临床上可能有助于估计与心力衰竭严重程度相关的LVEF程度。然而，需要对更大规模的患者和对照组进行进一步的临床试验。
