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Wiley Open Access, Journal of the American Heart Association, 14(10), 2021

DOI: 10.1161/jaha.121.021088

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Risk Prediction in Women With Congenital Long QT Syndrome

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Background We aimed to provide personalized risk estimates for cardiac events (CEs) and life‐threatening events in women with either type 1 or type 2 long QT. Methods and Results The prognostic model was derived from the Rochester Long QT Syndrome Registry, comprising 767 women with type 1 long QT (n=404) and type 2 long QT (n=363) from age 15 through 60 years. The risk prediction model included the following variables: genotype/mutation location, QTc‐specific thresholds, history of syncope, and β‐blocker therapy. A model was developed with the end point of CEs (syncope, aborted cardiac arrest, or long QT syndrome–related sudden cardiac death), and was applied with the end point of life‐threatening events (aborted cardiac arrest, sudden cardiac death, or appropriate defibrillator shocks). External validation was performed with data from the Mayo Clinic Genetic Heart Rhythm Clinic (N=467; type 1 long QT [n=286] and type 2 long QT [n=181]). The cumulative follow‐up duration among the 767 enrolled women was 22 243 patient‐years, during which 323 patients (42%) experienced ≥1 CE. Based on genotype‐phenotype data, we identified 3 risk groups with 10‐year projected rates of CEs ranging from 15%, 29%, to 51%. The corresponding 10‐year projected rates of life‐threatening events were 2%, 5%, and 14%. C statistics for the prediction model for the 2 respective end points were 0.68 (95% CI 0.65–0.71) and 0.71 (95% CI 0.66–0.76). Corresponding C statistics for the model in the external validation Mayo Clinic cohort were 0.65 (95% CI 0.60–0.70) and 0.77 (95% CI 0.70–0.84). Conclusions This is the first risk prediction model that provides absolute risk estimates for CEs and life‐threatening events in women with type 1 or type 2 long QT based on personalized genotype‐phenotype data. The projected risk estimates can be used to guide female‐specific management in long QT syndrome.