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Risk Prediction in Women With Congenital Long QT Syndrome

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...

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Autores principales: Goldenberg, Ilan, Bos, J. Martijn, Yoruk, Ayhan, Chen, Anita Y., Lopes, Coeli, Huang, David T., Kutyifa, Valentina, Younis, Arwa, Aktas, Mehmet K., Z. Rosero, Spencer, McNitt, Scott, Sotoodehnia, Nona, Kudenchuk, Peter J., Rea, Thomas D., Arking, Dan E., Scott, Christopher G., Briske, Kaylie A., Sorensen, Katrina, J. Ackerman, Michael, Zareba, Wojciech
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8483453/
https://www.ncbi.nlm.nih.gov/pubmed/34238014
http://dx.doi.org/10.1161/JAHA.121.021088
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author Goldenberg, Ilan
Bos, J. Martijn
Yoruk, Ayhan
Chen, Anita Y.
Lopes, Coeli
Huang, David T.
Kutyifa, Valentina
Younis, Arwa
Aktas, Mehmet K.
Z. Rosero, Spencer
McNitt, Scott
Sotoodehnia, Nona
Kudenchuk, Peter J.
Rea, Thomas D.
Arking, Dan E.
Scott, Christopher G.
Briske, Kaylie A.
Sorensen, Katrina
J. Ackerman, Michael
Zareba, Wojciech
author_facet Goldenberg, Ilan
Bos, J. Martijn
Yoruk, Ayhan
Chen, Anita Y.
Lopes, Coeli
Huang, David T.
Kutyifa, Valentina
Younis, Arwa
Aktas, Mehmet K.
Z. Rosero, Spencer
McNitt, Scott
Sotoodehnia, Nona
Kudenchuk, Peter J.
Rea, Thomas D.
Arking, Dan E.
Scott, Christopher G.
Briske, Kaylie A.
Sorensen, Katrina
J. Ackerman, Michael
Zareba, Wojciech
author_sort Goldenberg, Ilan
collection PubMed
description 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.
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spelling pubmed-84834532021-10-06 Risk Prediction in Women With Congenital Long QT Syndrome Goldenberg, Ilan Bos, J. Martijn Yoruk, Ayhan Chen, Anita Y. Lopes, Coeli Huang, David T. Kutyifa, Valentina Younis, Arwa Aktas, Mehmet K. Z. Rosero, Spencer McNitt, Scott Sotoodehnia, Nona Kudenchuk, Peter J. Rea, Thomas D. Arking, Dan E. Scott, Christopher G. Briske, Kaylie A. Sorensen, Katrina J. Ackerman, Michael Zareba, Wojciech J Am Heart Assoc Original Research 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. John Wiley and Sons Inc. 2021-07-09 /pmc/articles/PMC8483453/ /pubmed/34238014 http://dx.doi.org/10.1161/JAHA.121.021088 Text en © 2021 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Research
Goldenberg, Ilan
Bos, J. Martijn
Yoruk, Ayhan
Chen, Anita Y.
Lopes, Coeli
Huang, David T.
Kutyifa, Valentina
Younis, Arwa
Aktas, Mehmet K.
Z. Rosero, Spencer
McNitt, Scott
Sotoodehnia, Nona
Kudenchuk, Peter J.
Rea, Thomas D.
Arking, Dan E.
Scott, Christopher G.
Briske, Kaylie A.
Sorensen, Katrina
J. Ackerman, Michael
Zareba, Wojciech
Risk Prediction in Women With Congenital Long QT Syndrome
title Risk Prediction in Women With Congenital Long QT Syndrome
title_full Risk Prediction in Women With Congenital Long QT Syndrome
title_fullStr Risk Prediction in Women With Congenital Long QT Syndrome
title_full_unstemmed Risk Prediction in Women With Congenital Long QT Syndrome
title_short Risk Prediction in Women With Congenital Long QT Syndrome
title_sort risk prediction in women with congenital long qt syndrome
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8483453/
https://www.ncbi.nlm.nih.gov/pubmed/34238014
http://dx.doi.org/10.1161/JAHA.121.021088
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