Holzgrefe Henry H, Cavero Icilio, Gleason Carol R, Warner William A, Buchanan Lewis V, Gill Michael W, Burkett Dennis E, Durham Stephen K
Pharmaceutical Research Institute, Bristol-Myers Squibb Co., Syracuse, NY 13221, USA.
J Pharmacol Toxicol Methods. 2007 Mar-Apr;55(2):159-75. doi: 10.1016/j.vascn.2006.05.007. Epub 2006 May 27.
QT intervals are not regulated on a beat-to-beat cadence, but are strongly influenced by the preceding heart rate history (hysteresis). ECG sampling, when performed over sufficiently long periods, results in the detection of ranges of different QT values for each discrete RR interval. Given the potential impact of QT hysteresis in QT interval rate-correction procedures, we hypothesized that, physiologically, the QT interval exists as a probabilistic variable where the exact value corresponding to any RR interval is precisely estimated from the associated QT population.
Digital ECGs were collected for 18-21 h in telemetered dogs (n=7) and cynomolgus monkeys (n=7) employing epicardial ECG leads for accurate T(end) detection, and analyzed by computerized algorithms. Descriptive statistics were calculated for raw QT values in 10 ms RR increments. Individual rate-corrected QT (QTc) formulae were derived from the slopes of log-transformed QT-RR data where each QT point was the mean of >250 beats/RR increment. The aptness of this QTc model was assessed by residual analysis.
Beat-to-beat ECG analysis demonstrated that for all discrete cycle lengths, the associated raw QT intervals were normally distributed populations, spanning approximately 30-40 and 45-100 ms in the dog and cynomolgus monkey, respectively. In both species, QTc was stable (< or =5 ms variation) over all physiological RR intervals.
The probabilistic treatment of raw QT interval populations natively associated to any RR interval provides hysteresis-free raw QT estimates which can be accurately modeled, allowing the derivation of a precise QTc value. Previous unawareness of the probabilistic nature of the QT interval explains the historical failure of numerous QT rate-correction formulae to correctly solve this scientific issue. Importantly, QT distribution analysis has the potential to provide, for the first time, a universal and sensitive method for QT heart rate-correction, providing a robust method for nonclinical and clinical cardiac safety investigations of repolarization delay.
QT间期并非逐搏调节,而是受先前心率历史(滞后现象)的强烈影响。当进行足够长时间的心电图采样时,会检测到每个离散RR间期对应的不同QT值范围。鉴于QT滞后现象对QT间期心率校正程序的潜在影响,我们推测,从生理学角度来看,QT间期作为一个概率变量存在,其中与任何RR间期对应的精确值可从相关QT总体中精确估计。
使用心外膜心电图导联以准确检测T波终点,对遥测犬(n = 7)和食蟹猴(n = 7)进行18 - 21小时的数字心电图采集,并通过计算机算法进行分析。以10毫秒RR增量计算原始QT值的描述性统计量。个体心率校正QT(QTc)公式由对数转换后的QT - RR数据斜率得出,其中每个QT点是>250次心跳/ RR增量的平均值。通过残差分析评估该QTc模型的适用性。
逐搏心电图分析表明,对于所有离散周期长度,相关的原始QT间期均为正态分布总体,在犬和食蟹猴中分别跨越约30 - 40毫秒和45 - 100毫秒。在两个物种中,QTc在所有生理RR间期内均稳定(变化≤5毫秒)。
对与任何RR间期天然相关的原始QT间期总体进行概率处理可提供无滞后的原始QT估计值,这些估计值可精确建模,从而得出精确的QTc值。先前对QT间期概率性质的忽视解释了众多QT心率校正公式在历史上未能正确解决这一科学问题的原因。重要的是,QT分布分析有可能首次提供一种通用且灵敏的QT心率校正方法,为复极延迟的非临床和临床心脏安全性研究提供一种可靠方法。