Multidimensional rhythm disturbances as a precursor of sustained ventricular tachyarrhythmias

Cardiac cycle dynamics reflect underlying physiological changes that could predict imminent arrhythmias but are obscured by high complexity, nonstatio narity, and large interindividual differences. To overcome these problems, we developed an adaptive technique, referred to as the modified Karhunen-Lo eve transform (MKLT), that identifies an individual characteristic ("core") pattern of cardiac cycles and then tracks the changes in the pattern by pr ojecting the signal onto characteristic eigenvectors. We hypothesized that disturbances in the core pattern, indicating progressive destabilization of cardiac rhythm, would predict the onset of spontaneous sustained ventricul ar tachyarrhythmias (VTAs) better than previously reported methods. We anal yzed serial ambulatory ECGs recorded in 57 patients at the time of VTA and non-VTA 24-hour periods. The disturbances in the pattern were found in 82% of the recordings before the onset of impending VTA, and their dimensionali ty, defined as the number of unstable orthogonal projections, increased gra dually several hours before the onset. MKLT provided greater sensitivity an d specificity (70% and 93%) compared with the best traditional method (68% and 67%, respectively). We present a theoretical analysis of MKLT and descr ibe the effects of ectopy and slow changes in cardiac cycles on the disturb ances in the pattern. We conclude that MKLT provides greater predictive acc uracy than previously reported methods. The improvement is due to the use o f individual patterns as a reference for tracking the changes. Because this approach is independent of the group reference values or the underlying cl inical context, it should have substantial potential for predicting other f orms of arrhythmic events in other populations.