We are delighted to welcome two new editorial board members to The British Journal of Cardiology: Drs C Michael Gibson and Amar Puttanna
For UK healthcare professionals only
Mike is a Professor of Medicine at Harvard Medical School, and an interventional cardiologist at the Beth Israel Deaconess in Boston, USA. He is the founder and director of the academic research organization PERFUSE and has been principal investigator or has led core services for over 120 clinical trials, the results of which have been published in leading journals. Mike is also an active user of Twitter (@CMichaelGibson).
Amar is a Consultant in Diabetes and Endocrinology at the Good Hope Hospital, Sutton Coldfield, West Midlands. A regular contributor to the journal, Amar has previously been very active in the Young Diabetologists and Endocrinologists Forum. He has a keen eye for tracking and interpreting the many clinical trials with agents old and new in the management of diabetes. See Updates from the American Diabetes Association 2019 meeting report
NICE draft guidance for rivaroxaban in CAD and PAD
The National Institute for Health and Care Excellence (NICE) has published a positive draft final appraisal determination (FAD) recommending the use of rivaroxaban (Xarelto®, Bayer), 2.5 mg twice daily combined with aspirin (75-100 mg once daily), as an option for preventing atherothrombotic events in adult patients with coronary artery disease (CAD) or symptomatic peripheral artery disease (PAD), who are at risk of ischaemic events.
The draft guidance is based on results from the COMPASS study. Dr Derek Connolly (Birmingham City Hospital), who was one of the study investigators said: “There have been few recent major new advances in the medical management of patients with CAD and PAD to protect them against strokes and heart attacks.
“The COMPASS trial showed that adding rivaroxaban vascular dose to low-dose aspirin significantly reduced vascular events. The large reduction in events outweighed the increase in major bleeding events seen.”
It is estimated that 170,000 deaths a year in the UK – a quarter of all deaths – are due to cardiovascular disease, including CAD and PAD.
Polypill shown to reduce CVD by a third
The first large randomised trial with a polypill has been shown to reduce the risk of major cardiovascular events by a third in five years compared to lifestyle advice alone.
Carried out on 6,838 individuals in Iran, aged between 40 to 75 years including those with and without a history of cardiovascular disease, the PolyIran study compared a four-component polypill, containing aspirin, atorvastatin, hydrochlorothiazide and either enalapril or valsartan, with lifestyle advice (e.g. healthy diet with low salt, sugar, and fat content, exercise, weight control, and abstinence from smoking and opium).
The study showed the once-daily polypill reduced the risk of major cardiovascular events (including hospitalisation for acute coronary syndrome, fatal myocardial infarction, sudden death, heart failure, coronary artery revascularisation procedures, and non-fatal and fatal stroke) by 34% overall and by around 40% in individuals without a history of CVD over five years, and by approximately 20% in those with previous CVD.
The effects were similar in both men and women and the old and young. After adjusting for participants taking other cardiovascular drugs, the overall protective effect of the polypill was reduced to 22% (from 34%) but remained statistically significant. Systolic and diastolic blood pressure did not differ significantly between the groups, but low-density lipoprotein cholesterol was significantly lower in polypill arm. Adherence was high.
The study was published in The Lancet (Lancet 2019;394:672–83).
AI may identify AF from an electrocardiogram
An artificial intelligence (AI) model has been found to identify patients with intermittent atrial fibrillation (AF). The model can be used during normal rhythm and is a quick and non-invasive 10-second test.
The study, published in The Lancet (doi: 10.1016/S0140-6736(19)31721-0) showed that researchers could train an AI model to detect AF from 10-second electrocardiograms (ECGs). Carried out on over 640,000 ECGs from over 180,000 patients, the model had an accuracy of 83%. It is thought it can find signals in the ECG that might be invisible to the human eye.