Tiberiu A Pana1, Adrian D Wood1, Mamas A Mamas2, Allan B Clark3, Joao H Bettencourt-Silva4,5, David J McLernon6, John F Potter5,7, Phyo K Myint1,3,7,8. 1. Ageing Clinical and Experimental Research Team, Institute of Applied Health Sciences, School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, UK. 2. Keele Cardiovascular Research Group, Centre for Prognosis Research, Institute for Primary Care and Health Sciences, Keele University, Stoke-on-Trent, UK. 3. Norwich Medical School, University of East Anglia, Norwich, UK. 4. Department of Medicine, Clinical Informatics, University of Cambridge, Cambridge, UK. 5. Norfolk and Norwich University Hospital, Norwich, UK. 6. Medical Statistics Team, Institute of Applied Health Sciences, School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, UK. 7. Norwich Cardiovascular Research Group, Norwich Medical School, University of East Anglia, Norwich, UK. 8. Aberdeen Royal Infirmary, NHS Grampian, Aberdeen, UK.
Abstract
OBJECTIVES: To determine the risk factor profiles associated with post-acute ischaemic stroke (AIS) myocardial infarction (MI) over long-term follow-up. METHODS: This observational study includes prospectively identified AIS patients (n = 9840) admitted to a UK regional centre between January 2003 and December 2016 (median follow-up: 4.72 years). Predictors of post-stroke MI during follow-up were examined using logistic and Cox regression models for in-hospital and post-discharge events, respectively. MI incidence was determined using a competing risk non-parametric estimator. The influence of post-stroke MI on mortality was examined using Cox regressions. RESULTS: Mean age (SD) of study participants was 77.3 (12.2) years (48% males). Factors associated with in-hospital MI (OR [95% CI]) were increasing blood glucose (1.80 [1.17-2.77] per 10 mmol/L), total leucocyte count (1.25 [1.01-1.54] per 10 × 109 /L) and CRP (1.05 [1.02-1.08] per 10 mg/L increase). Age (HR [95% CI] = 1.03 [1.01-1.06]), coronary heart disease (1.59 [1.01-2.50]), chronic kidney disease (2.58 [1.44-4.63]) and cancers (1.76 [1.08-2.89]) were associated with incident MI between discharge and one-year follow-up. Age (1.02 [1.00-1.03]), diabetes (1.96 [1.38-2.65]), congestive heart failure (2.07 [1.44-2.99]), coronary heart disease (1.81 [1.31-2.50]), hypertension [1.86 (1.24-2.79)] and peripheral vascular disease (2.25 [1.40-3.63]) were associated with incident MI between 1 and 5 years after discharge. Diabetes (2.01 [1.09-3.72]), hypertension (3.69 [1.44-9.45]) and peripheral vascular disease (2.46 [1.02-5.98]) were associated with incident MI between 5 and 10 years after discharge. Cumulative MI incidence over 10 years was 5.4%. MI during all follow-up periods (discharge-1, 1-5, 5-10 years) was associated with increased risk of death (respective HR [95% CI] = 3.26 [2.51-4.15], 1.96 [1.58-2.42] and 1.92 [1.26-2.93]). CONCLUSIONS: In conclusion, prognosis is poor in post-stroke MI. We highlight a range of potential areas to focus preventative efforts.
OBJECTIVES: To determine the risk factor profiles associated with post-acute ischaemic stroke (AIS) myocardial infarction (MI) over long-term follow-up. METHODS: This observational study includes prospectively identified AISpatients (n = 9840) admitted to a UK regional centre between January 2003 and December 2016 (median follow-up: 4.72 years). Predictors of post-stroke MI during follow-up were examined using logistic and Cox regression models for in-hospital and post-discharge events, respectively. MI incidence was determined using a competing risk non-parametric estimator. The influence of post-stroke MI on mortality was examined using Cox regressions. RESULTS: Mean age (SD) of study participants was 77.3 (12.2) years (48% males). Factors associated with in-hospital MI (OR [95% CI]) were increasing blood glucose (1.80 [1.17-2.77] per 10 mmol/L), total leucocyte count (1.25 [1.01-1.54] per 10 × 109 /L) and CRP (1.05 [1.02-1.08] per 10 mg/L increase). Age (HR [95% CI] = 1.03 [1.01-1.06]), coronary heart disease (1.59 [1.01-2.50]), chronic kidney disease (2.58 [1.44-4.63]) and cancers (1.76 [1.08-2.89]) were associated with incident MI between discharge and one-year follow-up. Age (1.02 [1.00-1.03]), diabetes (1.96 [1.38-2.65]), congestive heart failure (2.07 [1.44-2.99]), coronary heart disease (1.81 [1.31-2.50]), hypertension [1.86 (1.24-2.79)] and peripheral vascular disease (2.25 [1.40-3.63]) were associated with incident MI between 1 and 5 years after discharge. Diabetes (2.01 [1.09-3.72]), hypertension (3.69 [1.44-9.45]) and peripheral vascular disease (2.46 [1.02-5.98]) were associated with incident MI between 5 and 10 years after discharge. Cumulative MI incidence over 10 years was 5.4%. MI during all follow-up periods (discharge-1, 1-5, 5-10 years) was associated with increased risk of death (respective HR [95% CI] = 3.26 [2.51-4.15], 1.96 [1.58-2.42] and 1.92 [1.26-2.93]). CONCLUSIONS: In conclusion, prognosis is poor in post-stroke MI. We highlight a range of potential areas to focus preventative efforts.
Authors: Lan Gao; Andrew Bivard; Mark Parsons; Neil J Spratt; Christopher Levi; Kenneth Butcher; Timothy Kleinig; Bernard Yan; Qiang Dong; Xin Cheng; Min Lou; Congguo Yin; Chushuang Chen; Peng Wang; Longting Lin; Philip Choi; Ferdinand Miteff; Marj Moodie Journal: Front Neurol Date: 2021-12-14 Impact factor: 4.003