ARE SERIAL HOLTER QT, LATE POTENTIAL, AND WAVELET MEASUREMENT CLINICALLY USEFUL

Clinical centers are increasingly using new techniques such as Holter QT, late potential, and wavelet measurements. However, we lack validat ed databases for the assessment of the performance of the signal-proce ssing methods and their reproducibility. Failure of the QT interval to adapt to changes in the heart rate is considered to be a more meaning ful parameter than QT prolongation itself. Ln this study, different fa ctors that may affect the reproducibility of QT and QTm (onset of the QRS to the maximum of T) measurement are analyzed: the incidence of sy mpathetic tone and parasympathetic activity on low- and high-frequency QT variability, the very low frequency dependency of the QT interval to changes in the R-R interval, changes in the heart's position, and m easurement errors. Typical root-mean-square values of the beat-to-beat measurement errors in upright-position Holter recordings are only 1.5 ms for QT versus 3.4 ms for QTm. Although the dependence of the QT in terval on the heart rate is well established, the method for rate corr ection of the QT interval remains controversial. None of the formulas for heart rate adjustment of the QT previously proposed provide comple te correction for all of the rate influences involved due to ''memory phenomenon''; that is, there is a time delay ranging up to 3-4 minutes , between a change in heart rate and the subsequent change in the QT i nterval. This problem has been solved by developing patient-specific n eural networks that are trained to ''identify'' the dynamic behavior o f the QT interval (or QTm) as a function of the R-R interval in order to predict the heat-to-beat changes of the QT interval as a function o f the measured beat-to-beat changes of the R-R interval. Computing the differences between the predicted and the measured QT interval will a llow for the detection of any significant deviations, both in the stea dy-state and transient conditions. Recent developments in the analysis of the high-resolution electrocardiogram (HRECG) in the time domain a nd frequency domain, with emphasis on the assessment of the reproducib ility of late potential and wavelet measurements, are also reported in this study. The two main causes of variability in HRECG analysis are physiology and, for time-domain analysis, intermanufacturer variabilit y. Physiologic changes can be overcome by standardizing the clinical p rotocols and repeating the recordings. The most important technical re quirement for the proper use of late potentials is to standardize the algorithm for the detection of QRS offset among different late potenti al analyzing machines so that clinical data can be exchanged. The rece ntly introduced wavelet transform provides a fruitful alternative to t he more classical time-domain methods. Preliminary results show an 8 t o 15% performance improvement over conventional time-domain analysis f or the stratification of the HRECG after myocardial infarction. Reprod ucibility is excellent, up to 100%, but needs to be assessed on larger populations matched for age, sex, and pathology.