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Predicting risk of cardiovascular events 1 to 3 years post‐myocardial infarction using a global registry
BACKGROUND: Risk prediction tools are lacking for patients with stable disease some years after myocardial infarction (MI). HYPOTHESIS: A practical long‐term cardiovascular risk index can be developed. METHODS: The long‐Term rIsk, Clinical manaGement and healthcare Resource utilization of stable cor...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wiley Periodicals, Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954378/ https://www.ncbi.nlm.nih.gov/pubmed/31713893 http://dx.doi.org/10.1002/clc.23283 |
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author | Pocock, Stuart J. Brieger, David Gregson, John Chen, Ji Y. Cohen, Mauricio G. Goodman, Shaun G. Granger, Christopher B. Grieve, Richard Nicolau, Jose C. Simon, Tabassome Westermann, Dirk Yasuda, Satoshi Hedman, Katarina Rennie, Kirsten L. Sundell, Karolina Andersson |
author_facet | Pocock, Stuart J. Brieger, David Gregson, John Chen, Ji Y. Cohen, Mauricio G. Goodman, Shaun G. Granger, Christopher B. Grieve, Richard Nicolau, Jose C. Simon, Tabassome Westermann, Dirk Yasuda, Satoshi Hedman, Katarina Rennie, Kirsten L. Sundell, Karolina Andersson |
author_sort | Pocock, Stuart J. |
collection | PubMed |
description | BACKGROUND: Risk prediction tools are lacking for patients with stable disease some years after myocardial infarction (MI). HYPOTHESIS: A practical long‐term cardiovascular risk index can be developed. METHODS: The long‐Term rIsk, Clinical manaGement and healthcare Resource utilization of stable coronary artery dISease in post‐myocardial infarction patients prospective global registry enrolled patients 1 to 3 years post‐MI (369 centers; 25 countries), all with ≥1 risk factor (age ≥65 years, diabetes mellitus requiring medication, second prior MI, multivessel coronary artery disease, or chronic non‐end‐stage kidney disease [CKD]). Self‐reported health was assessed with EuroQoL‐5 dimensions. Multivariable Poisson regression models were used to determine key predictors of the primary composite outcome (MI, unstable angina with urgent revascularization [UA], stroke, or all‐cause death) over 2 years. RESULTS: The primary outcome occurred in 621 (6.9%) of 9027 eligible patients: death 295 (3.3%), MI 195 (2.2%), UA 103 (1.1%), and stroke 58 (0.6%). All events accrued linearly. In a multivariable model, 11 significant predictors of primary outcome (age ≥65 years, diabetes, second prior MI, CKD, history of major bleed, peripheral arterial disease, heart failure, cardiovascular hospitalization (prior 6 months), medical management (index MI), on diuretic, and poor self‐reported health) were identified and combined into a user‐friendly risk index. Compared with lowest‐risk patients, those in the top 16% had a rate ratio of 6.9 for the primary composite, and 18.7 for all‐cause death (overall c‐statistic; 0.686, and 0.768, respectively). External validation was performed using the Australian Cooperative National Registry of Acute Coronary Care, Guideline Adherence and Clinical Events registry (c‐statistic; 0.748, and 0.849, respectively). CONCLUSIONS: In patients >1‐year post‐MI, recurrent cardiovascular events and deaths accrue linearly. A simple risk index can stratify patients, potentially helping to guide management. |
format | Online Article Text |
id | pubmed-6954378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Wiley Periodicals, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-69543782020-01-14 Predicting risk of cardiovascular events 1 to 3 years post‐myocardial infarction using a global registry Pocock, Stuart J. Brieger, David Gregson, John Chen, Ji Y. Cohen, Mauricio G. Goodman, Shaun G. Granger, Christopher B. Grieve, Richard Nicolau, Jose C. Simon, Tabassome Westermann, Dirk Yasuda, Satoshi Hedman, Katarina Rennie, Kirsten L. Sundell, Karolina Andersson Clin Cardiol Clinical Investigations BACKGROUND: Risk prediction tools are lacking for patients with stable disease some years after myocardial infarction (MI). HYPOTHESIS: A practical long‐term cardiovascular risk index can be developed. METHODS: The long‐Term rIsk, Clinical manaGement and healthcare Resource utilization of stable coronary artery dISease in post‐myocardial infarction patients prospective global registry enrolled patients 1 to 3 years post‐MI (369 centers; 25 countries), all with ≥1 risk factor (age ≥65 years, diabetes mellitus requiring medication, second prior MI, multivessel coronary artery disease, or chronic non‐end‐stage kidney disease [CKD]). Self‐reported health was assessed with EuroQoL‐5 dimensions. Multivariable Poisson regression models were used to determine key predictors of the primary composite outcome (MI, unstable angina with urgent revascularization [UA], stroke, or all‐cause death) over 2 years. RESULTS: The primary outcome occurred in 621 (6.9%) of 9027 eligible patients: death 295 (3.3%), MI 195 (2.2%), UA 103 (1.1%), and stroke 58 (0.6%). All events accrued linearly. In a multivariable model, 11 significant predictors of primary outcome (age ≥65 years, diabetes, second prior MI, CKD, history of major bleed, peripheral arterial disease, heart failure, cardiovascular hospitalization (prior 6 months), medical management (index MI), on diuretic, and poor self‐reported health) were identified and combined into a user‐friendly risk index. Compared with lowest‐risk patients, those in the top 16% had a rate ratio of 6.9 for the primary composite, and 18.7 for all‐cause death (overall c‐statistic; 0.686, and 0.768, respectively). External validation was performed using the Australian Cooperative National Registry of Acute Coronary Care, Guideline Adherence and Clinical Events registry (c‐statistic; 0.748, and 0.849, respectively). CONCLUSIONS: In patients >1‐year post‐MI, recurrent cardiovascular events and deaths accrue linearly. A simple risk index can stratify patients, potentially helping to guide management. Wiley Periodicals, Inc. 2019-11-12 /pmc/articles/PMC6954378/ /pubmed/31713893 http://dx.doi.org/10.1002/clc.23283 Text en © 2019 The Authors. Clinical Cardiology published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Clinical Investigations Pocock, Stuart J. Brieger, David Gregson, John Chen, Ji Y. Cohen, Mauricio G. Goodman, Shaun G. Granger, Christopher B. Grieve, Richard Nicolau, Jose C. Simon, Tabassome Westermann, Dirk Yasuda, Satoshi Hedman, Katarina Rennie, Kirsten L. Sundell, Karolina Andersson Predicting risk of cardiovascular events 1 to 3 years post‐myocardial infarction using a global registry |
title | Predicting risk of cardiovascular events 1 to 3 years post‐myocardial infarction using a global registry |
title_full | Predicting risk of cardiovascular events 1 to 3 years post‐myocardial infarction using a global registry |
title_fullStr | Predicting risk of cardiovascular events 1 to 3 years post‐myocardial infarction using a global registry |
title_full_unstemmed | Predicting risk of cardiovascular events 1 to 3 years post‐myocardial infarction using a global registry |
title_short | Predicting risk of cardiovascular events 1 to 3 years post‐myocardial infarction using a global registry |
title_sort | predicting risk of cardiovascular events 1 to 3 years post‐myocardial infarction using a global registry |
topic | Clinical Investigations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954378/ https://www.ncbi.nlm.nih.gov/pubmed/31713893 http://dx.doi.org/10.1002/clc.23283 |
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