摘要
目的:研究癫痫疾病对心率变异性复杂度的影响,探索癫痫疾病的病理生理机制。方法:基于多尺度熵方法回顾性分析212例癫痫患者和212例健康对照清醒状态下相同时间段内4 h的RR间期序列,并量化SampEn(样本熵)、Slope_(1-5)(1~5连续5个尺度下SampEn值线性拟合的斜率)、Area_(1-5)(5个SampEn值的总和)、Area_(6-15)(6~15连续10个尺度下SampEn值的总和)、Area_(6-20)(6~20连续15个尺度下SampEn值的总和)以及SampEn_(5)(尺度5下的熵值)等特征参数以表征心率变异性复杂度。基于ROC曲线及其AUC值评估心率变异性复杂度指标区分癫痫患者和健康对照的能力。结果:癫痫患者的心率变异性复杂度指标Slope_(1-5)、SampEn_(5)、Area_(1-5)、Area_(6-15)、Area_(6-20)均显著低于健康对照(P<0.001),且与癫痫病程及发作频率无显著相关性。Slope_(1-5)区分癫痫患者和健康对照的性能最佳,AUC值为0.764,灵敏度和特异度分别为75.0%和68.9%。结论:基于多尺度熵方法量化的心率变异性复杂度指标为癫痫病理生理机制的探索提供了新的视角,在癫痫疾病的辅助诊断、治疗、预后及风险预测领域具有潜在的临床应用价值。
Objective To investigate the effects of epilepsy on heart rate variability(HRV)complexity and to explore the pathophysiological mechanism of epilepsy.Methods 4-hour heartbeat interval time series from 212 epileptic patients and 212 healthy control subjects under awake state were retrospectively analyzed using multiscale entropy methods.The HRV complexity indices including SampEn(sample entropy),Slope_(1-5)(slope of the linear fit of SampEn values at 5 consecutive scales from 1 to 5),Area_(1-5)(sum of 5 SampEn values),Area_(6-15)(sum of SampEn values at 10 consecutive scales from 6 to 15),Area_(6-20)(sum of SampEn values at 15 consecutive scales from 6 to 20)and SampEn_(5)(entropy value at scale 5),were to characterize the complexity of heart rate variability.The ability of the heart rate variability complexity to differentiate between epileptic patients and healthy controls was assessed based on ROC curves and their AUC values.Results The heart rate variability complexity indexes Slope_(1-5),SampEn_(5),Area_(1-5),Area_(6-15)and Area_(6-20)were significantly lower in epileptic patients than in healthy controls(P<0.001)and did not correlate significantly with the duration of epilepsy or seizure frequency.Slope_(1-5)had the best performances in differentiating epileptic patients from healthy controls,with an AUC value of 0.764 and the sensitivity and specificity of 75.0%and 68.9%,respectively.Conclusion The heart rate variability complexity indies quantified based on multiscale entropy method provides a new perspective for the exploration of the pathophysiological mechanism of epilepsy and has potential clinical application in the field of adjunctive diagnosis,treatment,prognosis and risk prediction of epilepsy.
作者
刘洪运
杨曌
湛萍
孟凡刚
王卫东
LIU Hong-yun;YANG Zhao;ZHAN Ping;MENG Fan-gang;WANG Wei-dong(Research Center for Biomedical Engineering,Medical Innovation&Research Division,Chinese PLA General Hospital,Beijing 100853,China;National Engineering Laboratory for Neuromodulation,School of Aerospace Engineering,Tsinghua University,Beijing 100084,China;Beijing Neurosurgical Institute,Beijing 100070,China;Departmentt of Neurosurgery,Beijing Tiantan Hospital,Capital Medical University,Beijing 100070,China)
出处
《医疗卫生装备》
CAS
2022年第1期11-16,26,共7页
Chinese Medical Equipment Journal
关键词
癫痫
心率变异性
多尺度熵
样本熵
自主神经功能
癫痫病理生理机制
epilepsy
heart rate variability
multiscale entropy
sample entropy
autonomic nerve function
pathophysiological mechanism of epilepsy
