Stopped: logistical issues
Atrial Fibrillation (AF) is the commonest arrhythmia worldwide, affects 5% of people over the age of 65 and increases the risk of stroke and heart failure. The investigators aim to detect clinical and subclinical episodes of atrial fibrillation lasting \>30 seconds to develop risk prediction models to identify patients at high risk for ischaemic stroke.
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To determine the incidence of clinical and subclinical episodes of AF in acutely unwell patients and to generate data for the development and validation of virtual twins and clinical decision support tools.
Timeframe: 48 months
To determine the incidence of clinical and subclinical episodes of AF in acutely unwell patients and to generate data for the development and validation of virtual twins and clinical decision support tools.
Timeframe: 48 months