Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2010
Use of a novel transfer function to reduce repolarization interval hysteresis.
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Halámek Josef, Jurák Pavel, Bunch T Jared, Lipoldová Jolana, Novák Miroslav, Vondra Vlastimil, Leinveber Pavel, Plachy Martin, Kara Tomas, Villa Marco, Frána Petr, Soucek Miroslav, Somers Virend K, Asirvatham Samuel J
Аннотация
BACKGROUND: Cardiac repolarization is assessed by the QT interval on the surface electrocardiogram and varies with the heart rate. Standard QT corrections (QTc) do not account for the lag in QT change following a change in heart rate (QT hysteresis). Our group has developed and tested a transfer function (TRF) model to assess the effectiveness of a dynamic model of QT/RR coupling in eliminating hysteresis.
METHODS: We studied three groups: group I, healthy volunteers (n = 23, 41 ± 17 years); group II, hypertensive patients (n = 25, 45 ± 11 years); and group III, patients in a predominately paced rhythm (n = 5, 75 ± 6 years). To vary the heart rate, either exercise bicycling in the supine position (groups I and II) or manipulation of the pacemaker parameters (group III) was done. We then compared a dynamic TRF model with a model based on weighted averages of previous RR intervals. Two parameters were tested: root mean square (RMS) of the error signal between measured and computed QT and the elimination of hysteretic loops.
RESULTS: TRF-based measurements eliminated hysteresis in 22/23 (95%) group I patients, 21/25 (84%) group II patients, and 4/5 (80%) group III patients. When hysteresis elimination was not complete, the QT drift that followed RR intervals was different before and after bicycling (100 ms). In these patients, the corresponding QT interval did not significantly change during this period. The TRF model was found superior to the other tested models with respect to both analyzed parameters (RMS and hysteresis elimination).
CONCLUSION: The TRF model limited QT hysteresis in healthy, hypertensive, and pacemaker-dependent patients. In addition, an important finding of QT drift in patients with hypertension was identified. With further study in these and other diseased states, the TRF model may improve our ability to measure accurately cardiac repolarization and to determine arrhythmia risk.
METHODS: We studied three groups: group I, healthy volunteers (n = 23, 41 ± 17 years); group II, hypertensive patients (n = 25, 45 ± 11 years); and group III, patients in a predominately paced rhythm (n = 5, 75 ± 6 years). To vary the heart rate, either exercise bicycling in the supine position (groups I and II) or manipulation of the pacemaker parameters (group III) was done. We then compared a dynamic TRF model with a model based on weighted averages of previous RR intervals. Two parameters were tested: root mean square (RMS) of the error signal between measured and computed QT and the elimination of hysteretic loops.
RESULTS: TRF-based measurements eliminated hysteresis in 22/23 (95%) group I patients, 21/25 (84%) group II patients, and 4/5 (80%) group III patients. When hysteresis elimination was not complete, the QT drift that followed RR intervals was different before and after bicycling (100 ms). In these patients, the corresponding QT interval did not significantly change during this period. The TRF model was found superior to the other tested models with respect to both analyzed parameters (RMS and hysteresis elimination).
CONCLUSION: The TRF model limited QT hysteresis in healthy, hypertensive, and pacemaker-dependent patients. In addition, an important finding of QT drift in patients with hypertension was identified. With further study in these and other diseased states, the TRF model may improve our ability to measure accurately cardiac repolarization and to determine arrhythmia risk.
Предметные рубрики MeSH
AdolescentAdultAgedAged, 80 and overCardiac Pacing, ArtificialCohort StudiesElectrocardiographyFemaleFollow-Up StudiesHeart Conduction SystemHeart RateHumansHypertensionLong QT SyndromeMaleMiddle AgedModels, CardiovascularPacemaker, ArtificialReference ValuesRisk AssessmentTreatment OutcomeYoung Adult