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Re‐CHARGE‐AF: Recalibration of the CHARGE‐AF Model for Atrial Fibrillation Risk Prediction in Patients With Acute Stroke
BACKGROUND: Performance of existing atrial fibrillation (AF) risk prediction models in poststroke populations is unclear. We evaluated predictive utility of an AF risk model in patients with acute stroke and assessed performance of a fully refitted model. METHODS AND RESULTS: Within an academic hosp...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751842/ https://www.ncbi.nlm.nih.gov/pubmed/34666503 http://dx.doi.org/10.1161/JAHA.121.022363 |
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author | Ashburner, Jeffrey M. Wang, Xin Li, Xinye Khurshid, Shaan Ko, Darae Trisini Lipsanopoulos, Ana Lee, Priscilla R. Carmichael, Taylor Turner, Ashby C. Jackson, Corban Ellinor, Patrick T. Benjamin, Emelia J. Atlas, Steven J. Singer, Daniel E. Trinquart, Ludovic Lubitz, Steven A. Anderson, Christopher D. |
author_facet | Ashburner, Jeffrey M. Wang, Xin Li, Xinye Khurshid, Shaan Ko, Darae Trisini Lipsanopoulos, Ana Lee, Priscilla R. Carmichael, Taylor Turner, Ashby C. Jackson, Corban Ellinor, Patrick T. Benjamin, Emelia J. Atlas, Steven J. Singer, Daniel E. Trinquart, Ludovic Lubitz, Steven A. Anderson, Christopher D. |
author_sort | Ashburner, Jeffrey M. |
collection | PubMed |
description | BACKGROUND: Performance of existing atrial fibrillation (AF) risk prediction models in poststroke populations is unclear. We evaluated predictive utility of an AF risk model in patients with acute stroke and assessed performance of a fully refitted model. METHODS AND RESULTS: Within an academic hospital, we included patients aged 46 to 94 years discharged for acute ischemic stroke between 2003 and 2018. We estimated 5‐year predicted probabilities of AF using the Cohorts for Heart and Aging Research in Genomic Epidemiology for Atrial Fibrillation (CHARGE‐AF) model, by recalibrating CHARGE‐AF to the baseline risk of the sample, and by fully refitting a Cox proportional hazards model to the stroke sample (Re‐CHARGE‐AF) model. We compared discrimination and calibration between models and used 200 bootstrap samples for optimism‐adjusted measures. Among 551 patients with acute stroke, there were 70 incident AF events over 5 years (cumulative incidence, 15.2%; 95% CI, 10.6%–19.5%). Median predicted 5‐year risk from CHARGE‐AF was 4.8% (quartile 1–quartile 3, 2.0–12.6) and from Re‐CHARGE‐AF was 16.1% (quartile 1–quartile 3, 8.0–26.2). For CHARGE‐AF, discrimination was moderate (C statistic, 0.64; 95% CI, 0.57–0.70) and calibration was poor, underestimating AF risk (Greenwood‐Nam D’Agostino chi‐square, P<0.001). Calibration with recalibrated baseline risk was also poor (Greenwood‐Nam D’Agostino chi‐square, P<0.001). Re‐CHARGE‐AF improved discrimination (P=0.001) compared with CHARGE‐AF (C statistic, 0.74 [95% CI, 0.68–0.79]; optimism‐adjusted, 0.70 [95% CI, 0.65–0.75]) and was well calibrated (Greenwood‐Nam D’Agostino chi‐square, P=0.97). CONCLUSIONS: Covariates from an established AF risk model enable accurate estimation of AF risk in a poststroke population after recalibration. A fully refitted model was required to account for varying baseline AF hazard and strength of associations between covariates and incident AF. |
format | Online Article Text |
id | pubmed-8751842 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87518422022-01-14 Re‐CHARGE‐AF: Recalibration of the CHARGE‐AF Model for Atrial Fibrillation Risk Prediction in Patients With Acute Stroke Ashburner, Jeffrey M. Wang, Xin Li, Xinye Khurshid, Shaan Ko, Darae Trisini Lipsanopoulos, Ana Lee, Priscilla R. Carmichael, Taylor Turner, Ashby C. Jackson, Corban Ellinor, Patrick T. Benjamin, Emelia J. Atlas, Steven J. Singer, Daniel E. Trinquart, Ludovic Lubitz, Steven A. Anderson, Christopher D. J Am Heart Assoc Original Research BACKGROUND: Performance of existing atrial fibrillation (AF) risk prediction models in poststroke populations is unclear. We evaluated predictive utility of an AF risk model in patients with acute stroke and assessed performance of a fully refitted model. METHODS AND RESULTS: Within an academic hospital, we included patients aged 46 to 94 years discharged for acute ischemic stroke between 2003 and 2018. We estimated 5‐year predicted probabilities of AF using the Cohorts for Heart and Aging Research in Genomic Epidemiology for Atrial Fibrillation (CHARGE‐AF) model, by recalibrating CHARGE‐AF to the baseline risk of the sample, and by fully refitting a Cox proportional hazards model to the stroke sample (Re‐CHARGE‐AF) model. We compared discrimination and calibration between models and used 200 bootstrap samples for optimism‐adjusted measures. Among 551 patients with acute stroke, there were 70 incident AF events over 5 years (cumulative incidence, 15.2%; 95% CI, 10.6%–19.5%). Median predicted 5‐year risk from CHARGE‐AF was 4.8% (quartile 1–quartile 3, 2.0–12.6) and from Re‐CHARGE‐AF was 16.1% (quartile 1–quartile 3, 8.0–26.2). For CHARGE‐AF, discrimination was moderate (C statistic, 0.64; 95% CI, 0.57–0.70) and calibration was poor, underestimating AF risk (Greenwood‐Nam D’Agostino chi‐square, P<0.001). Calibration with recalibrated baseline risk was also poor (Greenwood‐Nam D’Agostino chi‐square, P<0.001). Re‐CHARGE‐AF improved discrimination (P=0.001) compared with CHARGE‐AF (C statistic, 0.74 [95% CI, 0.68–0.79]; optimism‐adjusted, 0.70 [95% CI, 0.65–0.75]) and was well calibrated (Greenwood‐Nam D’Agostino chi‐square, P=0.97). CONCLUSIONS: Covariates from an established AF risk model enable accurate estimation of AF risk in a poststroke population after recalibration. A fully refitted model was required to account for varying baseline AF hazard and strength of associations between covariates and incident AF. John Wiley and Sons Inc. 2021-10-20 /pmc/articles/PMC8751842/ /pubmed/34666503 http://dx.doi.org/10.1161/JAHA.121.022363 Text en © 2021 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Original Research Ashburner, Jeffrey M. Wang, Xin Li, Xinye Khurshid, Shaan Ko, Darae Trisini Lipsanopoulos, Ana Lee, Priscilla R. Carmichael, Taylor Turner, Ashby C. Jackson, Corban Ellinor, Patrick T. Benjamin, Emelia J. Atlas, Steven J. Singer, Daniel E. Trinquart, Ludovic Lubitz, Steven A. Anderson, Christopher D. Re‐CHARGE‐AF: Recalibration of the CHARGE‐AF Model for Atrial Fibrillation Risk Prediction in Patients With Acute Stroke |
title | Re‐CHARGE‐AF: Recalibration of the CHARGE‐AF Model for Atrial Fibrillation Risk Prediction in Patients With Acute Stroke |
title_full | Re‐CHARGE‐AF: Recalibration of the CHARGE‐AF Model for Atrial Fibrillation Risk Prediction in Patients With Acute Stroke |
title_fullStr | Re‐CHARGE‐AF: Recalibration of the CHARGE‐AF Model for Atrial Fibrillation Risk Prediction in Patients With Acute Stroke |
title_full_unstemmed | Re‐CHARGE‐AF: Recalibration of the CHARGE‐AF Model for Atrial Fibrillation Risk Prediction in Patients With Acute Stroke |
title_short | Re‐CHARGE‐AF: Recalibration of the CHARGE‐AF Model for Atrial Fibrillation Risk Prediction in Patients With Acute Stroke |
title_sort | re‐charge‐af: recalibration of the charge‐af model for atrial fibrillation risk prediction in patients with acute stroke |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751842/ https://www.ncbi.nlm.nih.gov/pubmed/34666503 http://dx.doi.org/10.1161/JAHA.121.022363 |
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