Novel probabilistic method for precisely correcting the QT interval for heart rate in telemetered dogs and cynomolgus monkeys

• Published in: Journal of pharmacological and toxicological methods Vol. 55; no. 2; pp. 159 - 175
• Main Authors: Holzgrefe, Henry H., Cavero, Icilio, Gleason, Carol R., Warner, William A., Buchanan, Lewis V., Gill, Michael W., Burkett, Dennis E., Durham, Stephen K.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.03.2007
• Subjects: Algorithms; Animals; Beagle dog; Calibration; Circadian Rhythm; Cynomolgus; Cynomolgus monkey; Data Interpretation, Statistical; Dogs; ECG; Electrocardiography; Epicardial; Female; Heart Rate - physiology; Long QT Syndrome - physiopathology; Macaca fascicularis; Male; Methods; Models, Statistical; Probability; QT prolongation; QT rate-correction; Telemetry; Beagle dog; QT prolongation; QT rate-correction; Cynomolgus monkey; ECG; Probability; Telemetry; Epicardial; Methods
• ISSN: 1056-8719; 1873-488X
• DOI: 10.1016/j.vascn.2006.05.007

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. Methods: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. Results: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 (≤ 5 ms variation) over all physiological RR intervals. Discussion: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.