Abstract
Ischaemic heart disease persists as the leading global cause of death. Myocardial infarction (MI) accounts for a large proportion of death due to cardiovascular disease. Between 2007 and 2016, age-sex standardised mortality for MI in Scotland has fallen by 42.5% from 129 to 74 per 100,000 population – a trend also apparent in other countries. Despite improvements in survival, considerable disparities exist according to sexin terms of delivery of guideline-recommended treatments and outcomes following MI suggesting women may be disadvantaged. Use of high-sensitivity troponin assays with sex-specific thresholds increases the detection of MI in women. However, women are less likely to undergo percutaneous coronary revascularisation (PCI) and are more often subject to underutilisation of evidence-based secondary preventative pharmacotherapy. Differences in adoption of invasive management may, in part, be explained by a perception held by clinicians and patients that outcomes are worse for women receiving PCI, as well as differences in symptoms and baseline risk profile which may impact clinical decision-making. Adverse events post-MI, including cardiogenic shock, heart failure and death, remain more common in women than in men, most notably in those with ST-elevation myocardial infarction (STEMI). Whether sex remains an independent predictor of adverse events despite adjustments for the higher risk-profile of women, notably age, is less clear. We hypothesised that sex-related differences in demographics and comorbidity underpin disparities in management and outcomes of women and men hospitalised with MI or angina. We investigated this hypothesis by analysis of a contemporary secondary care electronic registry (e-Registry) using electronic patient records (EPRs) for patients admitted to a complex regional healthcare network.
Original language | English |
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Journal | European Heart Journal - Quality of Care and Clinical Outcomes |
Early online date | 25 Jul 2019 |
DOIs | |
Publication status | E-pub ahead of print - 25 Jul 2019 |
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Colin McCowan
- School of Medicine - Professor in Health Data Science
- Sir James Mackenzie Institute for Early Diagnosis
- Population and Behavioural Science Division
Person: Academic