二元分析
自回归模型
因果关系(物理学)
呼吸
可预测性
计量经济学
格兰杰因果关系
呼吸
心率变异性
数学
统计
内科学
心率
麻醉
医学
物理
血压
量子力学
解剖
作者
Alberto Porta,Tito Bassani,Vlasta Bari,Gian Domenico Pinna,Roberto Maestri,Stefano Guzzetti
出处
期刊:IEEE Transactions on Biomedical Engineering
[Institute of Electrical and Electronics Engineers]
日期:2012-03-01
卷期号:59 (3): 832-841
被引量:106
标识
DOI:10.1109/tbme.2011.2180379
摘要
This study was designed to demonstrate the need of accounting for respiration (R) when causality between heart period (HP) and systolic arterial pressure (SAP) is under scrutiny. Simulations generated according to a bivariate autoregressive closed-loop model were utilized to assess how causality changes as a function of the model parameters. An exogenous (X) signal was added to the bivariate autoregressive closed-loop model to evaluate the bias on causality induced when the X source was disregarded. Causality was assessed in the time domain according to a predictability improvement approach (i.e., Granger causality). HP and SAP variability series were recorded with R in 19 healthy subjects during spontaneous and controlled breathing at 10, 15, and 20 breaths/min. Simulations proved the importance of accounting for X signals. During spontaneous breathing, assessing causality without taking into consideration R leads to a significantly larger percentage of closed-loop interactions and a smaller fraction of unidirectional causality from HP to SAP. This finding was confirmed during paced breathing and it was independent of the breathing rate. These results suggest that the role of baroreflex cannot be correctly assessed without accounting for R.
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