Bert Vandenberk1,2, Eline Vandael3, Tomas Robyns1,2, Joris Vandenberghe4, Christophe Garweg1,2, Veerle Foulon3, Joris Ector1,2, Rik Willems1,2. 1. Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium. 2. Department of Cardiology, University Hospitals Leuven, Leuven, Belgium. 3. Department of Pharmaceutical and Pharmacological Sciences, University of Leuven, Leuven, Belgium. 4. Department of Neurosciences, University of Leuven, Leuven, Belgium.
Abstract
BACKGROUND: Incorporation of QTc in clinical decision support systems requires accurate QT-interval correction, also during common electrocardiogram abnormalities as ventricular conduction defects (VCD). We compared the performance and predictive value of QT correction formulas to design a patient-specific QT correction algorithm (QTcA). METHODS: The first ECG in adult patients with sinus rhythm (SR), atrial fibrillation (AF), and ventricular pacing (VP) was collected retrospectively. QT correction was performed with Bazett (QTcB), Fridericia (QTcFri), Framingham, Hodges, and Rautaharju (QTcR) formulas. Correction formulas were compared using QTc/RR linear regression. Adjusted Cox regression was performed to predict 1-year all-cause mortality. RESULTS: A total of 49,737 patients were included (70.0% SR, 24.1% AF, 5.9% VP, 11.1% VCD). Overall 1-year all-cause mortality rate was 11.8%. In patients without VCD or VP, QTcFri showed significantly better heart rate correction, both overall (P < 0.001) and in subgroups by heart rate (bradycardia P ≤ 0.001, normal P ≤ 0.050, tachycardia P ≤ 0.010). Furthermore, QTcFri improved mortality prediction significantly when compared to QTcB (P < 0.001). Patients with VCD or VP QTcR, including correction for QRS duration, had a significant better heart rate correction than QTcB (P ≤ 0.010) and improved mortality prediction significantly compared to all other formulas (P < 0.001). Implementing QTcA, designed based on QTcFri and QTcR depending on the presence of VCD or VP, reduced the patients considered to be at risk by 61.1% when compared to QTcB. CONCLUSIONS: A patient-specific QT correction algorithm would combine accurate heart rate correction, improved predictive value of mortality, and a reduction of patients considered to be at risk.
BACKGROUND: Incorporation of QTc in clinical decision support systems requires accurate QT-interval correction, also during common electrocardiogram abnormalities as ventricular conduction defects (VCD). We compared the performance and predictive value of QT correction formulas to design a patient-specific QT correction algorithm (QTcA). METHODS: The first ECG in adult patients with sinus rhythm (SR), atrial fibrillation (AF), and ventricular pacing (VP) was collected retrospectively. QT correction was performed with Bazett (QTcB), Fridericia (QTcFri), Framingham, Hodges, and Rautaharju (QTcR) formulas. Correction formulas were compared using QTc/RR linear regression. Adjusted Cox regression was performed to predict 1-year all-cause mortality. RESULTS: A total of 49,737 patients were included (70.0% SR, 24.1% AF, 5.9% VP, 11.1% VCD). Overall 1-year all-cause mortality rate was 11.8%. In patients without VCD or VP, QTcFri showed significantly better heart rate correction, both overall (P < 0.001) and in subgroups by heart rate (bradycardia P ≤ 0.001, normal P ≤ 0.050, tachycardia P ≤ 0.010). Furthermore, QTcFri improved mortality prediction significantly when compared to QTcB (P < 0.001). Patients with VCD or VP QTcR, including correction for QRS duration, had a significant better heart rate correction than QTcB (P ≤ 0.010) and improved mortality prediction significantly compared to all other formulas (P < 0.001). Implementing QTcA, designed based on QTcFri and QTcR depending on the presence of VCD or VP, reduced the patients considered to be at risk by 61.1% when compared to QTcB. CONCLUSIONS: A patient-specific QT correction algorithm would combine accurate heart rate correction, improved predictive value of mortality, and a reduction of patients considered to be at risk.
Authors: Christos Charalambous; James C Moon; Jeff M P Holly; Nishi Chaturvedi; Alun D Hughes; Gabriella Captur Journal: Front Cardiovasc Med Date: 2022-04-22
Authors: Bert Vandenberk; Matthias M Engelen; Greet Van De Sijpe; Jonas Vermeulen; Stefan Janssens; Thomas Vanassche; Peter Verhamme; Paul De Munter; Natalie Lorent; Rik Willems Journal: Int J Cardiol Heart Vasc Date: 2021-11-03
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