Andrea Mazzanti1,2,3, Alessandro Trancuccio1,2,3, Deni Kukavica1,2,3, Eleonora Pagan4, Meng Wang5, Muhammad Mohsin1, Derick Peterson5, Vincenzo Bagnardi4, Wojciech Zareba6, Silvia G Priori1,2,3. 1. Molecular Cardiology, Istituti Clinici Scientifici Maugeri, IRCCS, Via Maugeri 10, 27100 Pavia, Italy. 2. Department of Molecular Medicine, University of Pavia, Pavia, Italy. 3. Molecular Cardiology, Fundación Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain. 4. Department of Statistics and Quantitative Methods, University of Milan-Bicocca, Milan, Italy. 5. Department of Computational Biology and Biostatistics, University of Rochester, Rochester, NY, USA. 6. Cardiology Unit of the Department of Medicine, University of Rochester Medical Center, 265 Crittenden Blvd., CU 420653, Rochester, NY 14642, USA.
Abstract
AIMS: Risk stratification of patients with long QT syndrome (LQTS) represents a difficult task. In 2018, we proposed a granular estimate of the baseline 5-year risk of life-threatening arrhythmias (LAE) for patients with LQTS, based on the genotype (long QT syndrome Type 1, long QT syndrome Type 2, and long QT syndrome Type 3) and the duration of the QTc interval. We sought to externally validate a novel risk score model (1-2-3-LQTS-Risk model) in a geographically diverse cohort from the USA and to evaluate its performance and assess potential clinical implication of this novel model. METHODS AND RESULTS: The prognostic model (1-2-3-LQTS-Risk model) was derived using data from a prospective, single-centre longitudinal cohort study published in 2018 (discovery cohort) and was validated using an independent cohort of 1689 patients enrolled in the International LQTS Registry (Rochester NY, USA). The validation study revealed a C-index of 0.69 [95% confidence interval (CI): 0.61-0.77] in the validation cohort, when compared with C-index of 0.79 (95% CI: 0.70-0.88) in the discovery cohort. Adopting a 5-year risk ≥5%, as suggested by the ROC curve analysis as the most balanced threshold for implantable cardioverter-defibrillator (ICD) implantation, would result in a number needed to treat (NNT) of nine (NNT = 9; 95% CI: 6.3-13.6). CONCLUSION: The 1-2-3-LQTS-Risk model, the first validated 5-year risk score model for patients with LQTS, can be used to aid clinicians to identify patients at the highest risk of LAE who could benefit most from an ICD implant and avoid unnecessary implants. Published on behalf of the European Society of Cardiology. All rights reserved.
AIMS: Risk stratification of patients with long QT syndrome (LQTS) represents a difficult task. In 2018, we proposed a granular estimate of the baseline 5-year risk of life-threatening arrhythmias (LAE) for patients with LQTS, based on the genotype (long QT syndrome Type 1, long QT syndrome Type 2, and long QT syndrome Type 3) and the duration of the QTc interval. We sought to externally validate a novel risk score model (1-2-3-LQTS-Risk model) in a geographically diverse cohort from the USA and to evaluate its performance and assess potential clinical implication of this novel model. METHODS AND RESULTS: The prognostic model (1-2-3-LQTS-Risk model) was derived using data from a prospective, single-centre longitudinal cohort study published in 2018 (discovery cohort) and was validated using an independent cohort of 1689 patients enrolled in the International LQTS Registry (Rochester NY, USA). The validation study revealed a C-index of 0.69 [95% confidence interval (CI): 0.61-0.77] in the validation cohort, when compared with C-index of 0.79 (95% CI: 0.70-0.88) in the discovery cohort. Adopting a 5-year risk ≥5%, as suggested by the ROC curve analysis as the most balanced threshold for implantable cardioverter-defibrillator (ICD) implantation, would result in a number needed to treat (NNT) of nine (NNT = 9; 95% CI: 6.3-13.6). CONCLUSION: The 1-2-3-LQTS-Risk model, the first validated 5-year risk score model for patients with LQTS, can be used to aid clinicians to identify patients at the highest risk of LAE who could benefit most from an ICD implant and avoid unnecessary implants. Published on behalf of the European Society of Cardiology. All rights reserved.
Authors: Katja E Odening; Henk J van der Linde; Michael J Ackerman; Paul G A Volders; Rachel M A Ter Bekke Journal: Eur Heart J Date: 2022-08-21 Impact factor: 35.855