João Pedro Ferreira1, Nicolas Girerd2, John Gregson3, Ichraq Latar2, Abhinav Sharma4, Marc A Pfeffer5, John J V McMurray6, Azmil H Abdul-Rahim7, Bertram Pitt8, Kenneth Dickstein9, Patrick Rossignol2, Faiez Zannad10. 1. National Institute of Health and Medical Research (INSERM), Center for Clinical Multidisciplinary Research 1433, INSERM U1116, University of Lorraine, Regional University Hospital of Nancy, French Clinical Research Infrastructure Network (F-CRIN) Investigation Network Initiative-Cardiovascular and Renal Clinical Trialists, Nancy, France; Department of Physiology and Cardiothoracic Surgery, Cardiovascular Research and Development Unit, Faculty of Medicine, University of Porto, Porto, Portugal. 2. National Institute of Health and Medical Research (INSERM), Center for Clinical Multidisciplinary Research 1433, INSERM U1116, University of Lorraine, Regional University Hospital of Nancy, French Clinical Research Infrastructure Network (F-CRIN) Investigation Network Initiative-Cardiovascular and Renal Clinical Trialists, Nancy, France. 3. Department of Biostatistics, London School of Hygiene & Tropical Medicine, London, United Kingdom. 4. Duke Clinical Research Institute, Duke University, Durham, North Carolina; Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, Alberta, Canada. 5. Division of Cardiovascular Medicine, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts. 6. BHF Cardiovascular Research Centre, University of Glasgow, Glasgow, Scotland, United Kingdom. 7. Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, Scotland, United Kingdom. 8. Department of Medicine, University of Michigan School of Medicine, Ann Arbor, Michigan. 9. Department of Cardiology, University of Bergan, Stavanger University Hospital, Stavanger, Norway. 10. National Institute of Health and Medical Research (INSERM), Center for Clinical Multidisciplinary Research 1433, INSERM U1116, University of Lorraine, Regional University Hospital of Nancy, French Clinical Research Infrastructure Network (F-CRIN) Investigation Network Initiative-Cardiovascular and Renal Clinical Trialists, Nancy, France. Electronic address: f.zannad@chru-nancy.fr.
Abstract
BACKGROUND: Stroke can occur after myocardial infarction (MI) in the absence of atrial fibrillation (AF). OBJECTIVES: This study sought to identify risk factors (excluding AF) for the occurrence of stroke and to develop a calibrated and validated stroke risk score in patients with MI and heart failure (HF) and/or systolic dysfunction. METHODS: The datasets included in this pooling initiative were derived from 4 trials: CAPRICORN (Effect of Carvedilol on Outcome After Myocardial Infarction in Patients With Left Ventricular Dysfunction), OPTIMAAL (Optimal Trial in Myocardial Infarction With Angiotensin II Antagonist Losartan), VALIANT (Valsartan in Acute Myocardial Infarction Trial), and EPHESUS (Eplerenone Post-Acute Myocardial Infarction Heart Failure Efficacy and Survival Study); EPHESUS was used for external validation. A total of 22,904 patients without AF or oral anticoagulation were included in this analysis. The primary outcome was stroke, and death was treated as a "competing risk." RESULTS: During a median follow-up of 1.9 years (interquartile range: 1.3 to 2.7 years), 660 (2.9%) patients had a stroke. These patients were older, more often female, smokers, and hypertensive; they had a higher Killip class; a lower estimated glomerular filtration rate; and a higher proportion of MI, HF, diabetes, and stroke histories. The final stroke risk model retained older age, Killip class 3 or 4, estimated glomerular filtration rate ≤45 ml/min/1.73 m2, hypertension history, and previous stroke. The models were well calibrated and showed moderate to good discrimination (C-index = 0.67). The observed 3-year event rates increased steeply for each sextile of the stroke risk score (1.8%, 2.9%, 4.1%, 5.6%, 8.3%, and 10.9%, respectively) and were in agreement with the expected event rates. CONCLUSIONS: Readily accessible risk factors associated with the occurrence of stroke were identified and incorporated in an easy-to-use risk score. This score may help in the identification of patients with MI and HF and a high risk for stroke despite their not presenting with AF.
RCT Entities:
BACKGROUND:Stroke can occur after myocardial infarction (MI) in the absence of atrial fibrillation (AF). OBJECTIVES: This study sought to identify risk factors (excluding AF) for the occurrence of stroke and to develop a calibrated and validated stroke risk score in patients with MI and heart failure (HF) and/or systolic dysfunction. METHODS: The datasets included in this pooling initiative were derived from 4 trials: CAPRICORN (Effect of Carvedilol on Outcome After Myocardial Infarction in Patients With Left Ventricular Dysfunction), OPTIMAAL (Optimal Trial in Myocardial Infarction With Angiotensin II Antagonist Losartan), VALIANT (Valsartan in Acute Myocardial Infarction Trial), and EPHESUS (Eplerenone Post-Acute Myocardial Infarction Heart Failure Efficacy and Survival Study); EPHESUS was used for external validation. A total of 22,904 patients without AF or oral anticoagulation were included in this analysis. The primary outcome was stroke, and death was treated as a "competing risk." RESULTS: During a median follow-up of 1.9 years (interquartile range: 1.3 to 2.7 years), 660 (2.9%) patients had a stroke. These patients were older, more often female, smokers, and hypertensive; they had a higher Killip class; a lower estimated glomerular filtration rate; and a higher proportion of MI, HF, diabetes, and stroke histories. The final stroke risk model retained older age, Killip class 3 or 4, estimated glomerular filtration rate ≤45 ml/min/1.73 m2, hypertension history, and previous stroke. The models were well calibrated and showed moderate to good discrimination (C-index = 0.67). The observed 3-year event rates increased steeply for each sextile of the stroke risk score (1.8%, 2.9%, 4.1%, 5.6%, 8.3%, and 10.9%, respectively) and were in agreement with the expected event rates. CONCLUSIONS: Readily accessible risk factors associated with the occurrence of stroke were identified and incorporated in an easy-to-use risk score. This score may help in the identification of patients with MI and HF and a high risk for stroke despite their not presenting with AF.
Authors: Jin Man Jung; Yong Hyun Kim; Sungwook Yu; Kyungmi O; Chi Kyung Kim; Tae Jin Song; Yong Jae Kim; Bum Joon Kim; Sung Hyuk Heo; Kwang Yeol Park; Jeong Min Kim; Jong Ho Park; Jay Chol Choi; Man Seok Park; Joon Tae Kim; Kang Ho Choi; Yang Ha Hwang; Jong Won Chung; Oh Young Bang; Gyeong Moon Kim; Woo Keun Seo Journal: J Clin Neurol Date: 2019-10 Impact factor: 3.077
Authors: Mandeep R Mehra; Muthiah Vaduganathan; Min Fu; João Pedro Ferreira; Stefan D Anker; John G F Cleland; Carolyn S P Lam; Dirk J van Veldhuisen; William M Byra; Theodore E Spiro; Hsiaowei Deng; Faiez Zannad; Barry Greenberg Journal: Eur Heart J Date: 2019-11-21 Impact factor: 29.983
Authors: Wenxian Sun; Luyang Zhang; Weishi Liu; Mengke Tian; Xin Wang; Jing Liang; Yuying Wang; Lan Ding; Lulu Pei; Jie Lu; Yuming Xu; Bo Song Journal: Int J Gen Med Date: 2021-12-09