TY - JOUR
T1 - Predicting risk of cardiovascular events 1 to 3 years post-myocardial infarction using a global registry
AU - for the TIGRIS Study Investigators
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
N1 - Funding Information:
The TIGRIS study and this work were supported by AstraZeneca. The authors would like to thank the patients, their families, and all investigators involved in this study. Assistance with project management, site management, data management, and regulatory affairs was provided by Worldwide Clinical Trials Evidence Group, Nottingham, United Kingdom. Medical writing support was provided by Paragon, Knutsford, UK, in accordance with Good Publication Practice guidelines.
Publisher Copyright:
© 2019 The Authors. Clinical Cardiology published by Wiley Periodicals, Inc.
PY - 2020/1/1
Y1 - 2020/1/1
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 - cardiac risk factors and prevention
KW - coronary artery disease
KW - myocardial infarction
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U2 - 10.1002/clc.23283
DO - 10.1002/clc.23283
M3 - Article
C2 - 31713893
AN - SCOPUS:85075200117
SN - 0160-9289
VL - 43
SP - 24
EP - 32
JO - Clinical Cardiology
JF - Clinical Cardiology
IS - 1
ER -
