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Predicting risk of cardiovascular events 1 to 3 years post-myocardial infarction using a global registry

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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; TIGRIS Study Investigators.

In: CLIN CARDIOL, Vol. 43, No. 1, 01.2020, p. 24-32.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Pocock, SJ, Brieger, D, Gregson, J, Chen, JY, Cohen, MG, Goodman, SG, Granger, CB, Grieve, R, Nicolau, JC, Simon, T, Westermann, D, Yasuda, S, Hedman, K, Rennie, KL, Sundell, KA & TIGRIS Study Investigators 2020, 'Predicting risk of cardiovascular events 1 to 3 years post-myocardial infarction using a global registry', CLIN CARDIOL, vol. 43, no. 1, pp. 24-32. https://doi.org/10.1002/clc.23283

APA

Pocock, S. J., Brieger, D., Gregson, J., Chen, J. Y., Cohen, M. G., Goodman, S. G., Granger, C. B., Grieve, R., Nicolau, J. C., Simon, T., Westermann, D., Yasuda, S., Hedman, K., Rennie, K. L., Sundell, K. A., & TIGRIS Study Investigators (2020). Predicting risk of cardiovascular events 1 to 3 years post-myocardial infarction using a global registry. CLIN CARDIOL, 43(1), 24-32. https://doi.org/10.1002/clc.23283

Vancouver

Pocock SJ, Brieger D, Gregson J, Chen JY, Cohen MG, Goodman SG et al. Predicting risk of cardiovascular events 1 to 3 years post-myocardial infarction using a global registry. CLIN CARDIOL. 2020 Jan;43(1):24-32. https://doi.org/10.1002/clc.23283

Bibtex

@article{87889894cac34850ba9f6b7bba1d98a7,
title = "Predicting risk of cardiovascular events 1 to 3 years post-myocardial infarction using a global registry",
abstract = "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.",
keywords = "Aged, Aged, 80 and over, Cardiovascular Diseases/diagnosis, Female, Humans, Male, Middle Aged, Models, Cardiovascular, Myocardial Infarction/complications, Prognosis, Prospective Studies, Registries, Risk Assessment, Risk Factors",
author = "Pocock, {Stuart J} and David Brieger and John Gregson and Chen, {Ji Y} and Cohen, {Mauricio G} and Goodman, {Shaun G} and Granger, {Christopher B} and Richard Grieve and Nicolau, {Jose C} and Tabassome Simon and Dirk Westermann and Satoshi Yasuda and Katarina Hedman and Rennie, {Kirsten L} and Sundell, {Karolina Andersson} and {TIGRIS Study Investigators}",
note = "{\textcopyright} 2019 The Authors. Clinical Cardiology published by Wiley Periodicals, Inc.",
year = "2020",
month = jan,
doi = "10.1002/clc.23283",
language = "English",
volume = "43",
pages = "24--32",
journal = "CLIN CARDIOL",
issn = "0160-9289",
publisher = "John Wiley and Sons Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - Predicting risk of cardiovascular events 1 to 3 years post-myocardial infarction using a global registry

AU - Pocock, Stuart J

AU - Brieger, David

AU - Gregson, John

AU - Chen, Ji Y

AU - Cohen, Mauricio G

AU - Goodman, Shaun G

AU - Granger, Christopher B

AU - Grieve, Richard

AU - Nicolau, Jose C

AU - Simon, Tabassome

AU - Westermann, Dirk

AU - Yasuda, Satoshi

AU - Hedman, Katarina

AU - Rennie, Kirsten L

AU - Sundell, Karolina Andersson

AU - TIGRIS Study Investigators

N1 - © 2019 The Authors. Clinical Cardiology published by Wiley Periodicals, Inc.

PY - 2020/1

Y1 - 2020/1

N2 - 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.

AB - 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.

KW - Aged

KW - Aged, 80 and over

KW - Cardiovascular Diseases/diagnosis

KW - Female

KW - Humans

KW - Male

KW - Middle Aged

KW - Models, Cardiovascular

KW - Myocardial Infarction/complications

KW - Prognosis

KW - Prospective Studies

KW - Registries

KW - Risk Assessment

KW - Risk Factors

U2 - 10.1002/clc.23283

DO - 10.1002/clc.23283

M3 - SCORING: Journal article

C2 - 31713893

VL - 43

SP - 24

EP - 32

JO - CLIN CARDIOL

JF - CLIN CARDIOL

SN - 0160-9289

IS - 1

ER -