Panerai R B, Haunton V J, Hanby M F, Salinet A S M, Robinson T G
Department of Cardiovascular Sciences, University of Leicester, Leicester, UK. NIHR Biomedical Research Unit for Cardiovascular Sciences, Glenfield Hospital, Leicester, UK.
Physiol Meas. 2016 May;37(5):661-72. doi: 10.1088/0967-3334/37/5/661. Epub 2016 Apr 19.
The autoregulation index (ARI) can reflect the effectiveness of cerebral blood flow (CBF) control in response to dynamic changes in arterial blood pressure (BP), but objective criteria for its validation have not been proposed. Monte Carlo simulations were performed by generating 5 min long random input/output signals that mimic the properties of mean beat-to-beat BP and CBF velocity (CBFV) as usually obtained by non-invasive measurements in the finger (Finometer) and middle cerebral artery (transcranial Doppler ultrasound), respectively. Transfer function analysis (TFA) was used to estimate values of ARI by optimal fitting of template curves to the output (or CBFV) response to a step change in input (or BP). Two-step criteria were adopted to accept estimates of ARI as valid. The 95% confidence limit of the mean coherence function (0.15-0.25 Hz) ([Formula: see text]) was estimated from 15 000 runs, resulting in [Formula: see text] = 0.190 when using five segments of data, each with 102.4 s (512 samples) duration (Welch's method). This threshold for acceptance was dependent on the TFA settings and increased when using segments with shorter duration (51.2 s). For signals with mean coherence above the critical value, the 5% confidence limit of the normalised mean square error (NMSEcrit) for fitting the step response to Tieck's model, was found to be approximately 0.30 and independent of the TFA settings. Application of these criteria to physiological and clinical sets of data showed their ability to identify conditions where ARI estimates should be rejected, for example due to CBFV step responses lacking physiological plausibility. A larger number of recordings were rejected from acute ischaemic stroke patients than for healthy volunteers. More work is needed to validate this procedure with different physiological conditions and/or patient groups. The influence of non-stationarity in BP and CBFV signals should also be investigated.
自动调节指数(ARI)能够反映脑血流量(CBF)在应对动脉血压(BP)动态变化时的控制效果,但尚未提出其验证的客观标准。通过生成5分钟长的随机输入/输出信号进行蒙特卡洛模拟,这些信号分别模拟了通常通过手指(Finometer)和大脑中动脉(经颅多普勒超声)的非侵入性测量获得的逐搏平均血压和脑血流速度(CBFV)的特性。传递函数分析(TFA)用于通过将模板曲线最佳拟合到输入(或BP)阶跃变化的输出(或CBFV)响应来估计ARI值。采用两步标准来接受ARI估计值为有效。从15000次运行中估计平均相干函数(0.15 - 0.25 Hz)([公式:见正文])的95%置信限,当使用五段数据时,每段数据持续时间为102.4秒(512个样本)(韦尔奇方法),结果为[公式:见正文] = 0.190。该接受阈值取决于TFA设置,并且在使用持续时间较短(51.2秒)的段时会增加。对于平均相干高于临界值的信号,发现将阶跃响应拟合到蒂克模型的归一化均方误差(NMSEcrit)的5%置信限约为0.30,且与TFA设置无关。将这些标准应用于生理和临床数据集表明,它们能够识别应拒绝ARI估计值的情况,例如由于CBFV阶跃响应缺乏生理合理性。与健康志愿者相比,急性缺血性中风患者被拒绝的记录数量更多。需要开展更多工作以在不同生理条件和/或患者群体中验证该程序。还应研究BP和CBFV信号中的非平稳性影响。