Quantifying the Response of QT Variability to Heart Rate Variability Based on Linear Parametric Model and Information Decomposition Method
Li Chenxi#, Pan Yue, Wang Zhigang, Zhang Zhengguo, Peng Yi#*
Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing 100005, China
摘要自主神经系统(ANS)的平衡对于规避与心脏相关的疾病风险具有重要意义。本课题运用频域的线性参数模型和非线性信息分解方法,分析QT变异性(QTV)对于心率变异性(HRV)的响应,揭示心脏自主神经的调节状态。使用来自THEW数据库的Holter数据,选用其中的正常组(Normal,n=186)和高心律失常和心源性猝死风险组(ESRD,n=41)进行对比。提取昼夜安静态各5 min RR间期(RRI)和相对应的QT间期(QTI)序列,计算频域参数QTV与HRV相关的百分占比(LR)和信息分解的RRI对于QTI的可预测性(PI),并结合RRI序列的时域、频域和符号动力学分析,探讨QTV对于HRV的响应在两组人群中可能的差异和发生机制。对于LR和PI,Normal组均表现出显著的昼夜差异,而ESRD组则均不存在,反映出ESRD组ANS交互作用的缺失。两组间同时段同指标对比时,低频段LR无显著差异,而在高频段,Normal组的LR值均显著小于同时段ESRD组的LR值(白天:18.36%±17.38% vs 39.37%±23.80%, P<0.05;夜晚: 28.63%±18.77% vs 42.31%±21.97%, P<0.05);Normal组夜晚的PI显著大于ESRD组夜晚的PI(0.310±0.155 vs 0.236±0.131, P<0.05),而在白天无显著差异。研究表明,线性参数模型和基于信息分解的非线性预测对自主神经活动的敏感性不同;高心律失常和心源性猝死风险人群中HRV对QTV的调控呈复杂度降低的特点。
Abstract：The balance of autonomic nerve system (ANS) plays an important role in avoiding the risk of heart-related diseases. To reveal the regulation of ANS, the response of QT variability (QTV) to heart rate variability (HRV) was analyzed by using linear parametric model in frequency domain and nonlinear information decomposition method. The Holter data were provided by THEW, database Normal was selected as normal controls (Normal, n=186) and database ESRD as typical subjects of ANS dysfunction with high risk for cardiac arrhythmias and sudden cardiac death (ESRD, n=41). 5 min RR interval (RRI) and the corresponding QT interval (QTI) at rest were extracted both in daytime and on night. The QTV fraction related to HRV (LR) in the frequency domain and the predictive information (PI) from RRI to QTI based on the information theory were calculated, combined with time-domain indexes, frequency domain indexes and symbolic dynamic analysis (SDA) of RRI, to explore the possible difference of QTV response to HRV in the two groups and its potential mechanism. There were significant diurnal differences both for LR and PI in Normal, but no significant diurnal variation of that was observed in ESRD, reflecting the loss of ANS reciprocal interaction in ESRD. When comparing the same indexes between Normal group and ESRD group in the same time period, there were no significant differences in LR values in low frequency band between two groups, while LR values in high frequency band in Normal were significant smaller than that in ESRD (Day: 18.36%±17.38% vs 39.37%±23.80%, P<0.05; Night: 28.63%±18.77% vs 42.31%±21.97%, P <0.05); PI on night was significantly higher in Normal compared with that in ESRD (0.310±0.155 vs 0.236±0.131, P <0.05), but no significant difference in PI was found between two groups in daytime. The results demonstrated that linear parametric model and nonlinear prediction based on information decomposition have different sensitivity to ANS activity; The complexity of HRV in regulating QTV in population with high risk for cardiac arrhythmias and sudden cardiac death is reduced.
基金资助:国家自然科学基金(81071225,81471746);中国医学科学院医学与健康科技创新工程项目(2016-I2M-3-018) #中国生物医学工程学会会员(Member, Chinese Society of Biomedical Engineering)
通讯作者:
E-mail:pengyi@pumc.edu.cn
引用本文:
李晨曦,潘越,王志刚,张正国,彭屹. 以线性参数模型和信息分解方法评价QT变异性对心率变异性的响应[J]. 中国生物医学工程学报, 2018, 37(3): 305-312.
Li Chenxi, Pan Yue, Wang Zhigang, Zhang Zhengguo, Peng Yi. Quantifying the Response of QT Variability to Heart Rate Variability Based on Linear Parametric Model and Information Decomposition Method. Chinese Journal of Biomedical Engineering, 2018, 37(3): 305-312.
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