Roy Sriwattanakomen1, Kenneth J Mukamal2, Alexei Shvilkin2. 1. Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts. Electronic address: rsriwat1@gmail.com. 2. Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Abstract
BACKGROUND: QT interval prolongation is a major arrhythmia risk factor. Standard QT interval limits are defined for preserved intrinsic atrioventricular and interventricular conduction. However, ventricular pacing (VP) prolongs the QRS duration, induces electrical remodeling, and therefore obscures the intrinsic QT interval. No consensus exists on QT interval monitoring during VP. OBJECTIVE: The aim of this study was to develop an algorithm to predict the QT interval during intrinsic conduction (IC) from the VP electrocardiogram. METHODS: We measured electrocardiographic intervals QRS, QT, QTpeak, JTpeak, and TpeakTend in 38 participants with cardiac devices and preserved atrioventricular and interventricular conduction. We performed paired measurements in AAI (IC) and DDD (VP) pacing modes at equal heart rates at baseline and after 1 week of VP. We fit linear mixed models to predict IC QT intervals from VP intervals and compared their fit with other proposed methods of IC QT interval estimation. RESULTS: After 1 week of VP, the IC QT interval prolonged while the VP QT interval shortened from their respective baseline values. VP QT interval shortening was due to TpeakTend interval shortening. JTpeak and QTpeak intervals prolonged in both pacing modes at 1 week. A formula using VP QTpeak interval and heart rate closely predicted the IC QT interval (r = 0.94), outperforming other methods, including subtraction of "excess" QRS duration from the actual QT interval (r = 0.64) and subtraction of fixed values from heart rate-corrected QT interval (r = 0.58 and r = 0.69). Validation in 2000 bootstrapped data sets confirmed the model's performance (r = 0.93) compared to others (r = 0.43-0.58). CONCLUSION: In patients with VP, a formula using the QTpeak interval accurately predicts the intrinsic QT interval.
BACKGROUND: QT interval prolongation is a major arrhythmia risk factor. Standard QT interval limits are defined for preserved intrinsic atrioventricular and interventricular conduction. However, ventricular pacing (VP) prolongs the QRS duration, induces electrical remodeling, and therefore obscures the intrinsic QT interval. No consensus exists on QT interval monitoring during VP. OBJECTIVE: The aim of this study was to develop an algorithm to predict the QT interval during intrinsic conduction (IC) from the VP electrocardiogram. METHODS: We measured electrocardiographic intervals QRS, QT, QTpeak, JTpeak, and TpeakTend in 38 participants with cardiac devices and preserved atrioventricular and interventricular conduction. We performed paired measurements in AAI (IC) and DDD (VP) pacing modes at equal heart rates at baseline and after 1 week of VP. We fit linear mixed models to predict IC QT intervals from VP intervals and compared their fit with other proposed methods of IC QT interval estimation. RESULTS: After 1 week of VP, the IC QT interval prolonged while the VP QT interval shortened from their respective baseline values. VP QT interval shortening was due to TpeakTend interval shortening. JTpeak and QTpeak intervals prolonged in both pacing modes at 1 week. A formula using VP QTpeak interval and heart rate closely predicted the IC QT interval (r = 0.94), outperforming other methods, including subtraction of "excess" QRS duration from the actual QT interval (r = 0.64) and subtraction of fixed values from heart rate-corrected QT interval (r = 0.58 and r = 0.69). Validation in 2000 bootstrapped data sets confirmed the model's performance (r = 0.93) compared to others (r = 0.43-0.58). CONCLUSION: In patients with VP, a formula using the QTpeak interval accurately predicts the intrinsic QT interval.
Authors: Santiago Colunga; Remigio Padrón; Daniel García-Iglesias; José Manuel Rubín; Diego Pérez; Raquel Del Valle; Pablo Avanzas; César Morís; David Calvo Journal: J Clin Med Date: 2019-09-09 Impact factor: 4.241