The British Journal of Cardiology

Risk stratification for sudden cardiac death (SCD) and the selection of patients for prophylactic implantable cardiac defibrillator (ICD) in hypertrophic cardiomyopathy (HCM) are still evolving and far from ideal. I present a historical case of HCM that did not have recognised SCD risk factors. This case highlights the deficiency of the present risk-stratification strategy for HCM and European Society of Cardiology (ESC) risk-scoring system.

Infective endocarditis (IE) is a rare, life-threatening infection of the cardiac endocardium caused by bacterial seeding. On the other hand, atopic dermatitis (AD) is a common inflammatory skin condition that disrupts the epidermal barrier, increasing susceptibility to Staphylococcus aureus colonisation and recurrent bacteraemia. This provides a biologically plausible bridge to IE, which we explore in this current literature review.

Dear Sirs, Hypertension case-finding is a priority for the National Health Service (NHS) in England.1 Opportunistic testing of patients at community pharmacies, dentists and opticians is being implemented. These interventions may lack digital integration with primary care and fail to proactively reach those who do not routinely use healthcare or who are at greatest risk of cardiovascular disease.

Designed to provide healthcare professionals with a clear foundation of knowledge on cardiac amyloidosis. This module introduces the clinical presentation and pathophysiology of amyloidosis, highlights “red flag” features, and outlines contemporary non-invasive diagnostic approaches, emphasising the importance of early and accurate diagnosis.

Designed to provide healthcare professionals with a clear foundation in systemic amyloidosis, with a particular focus on AL and transthyretin (ATTR) amyloidosis affecting the heart. In this module, we introduce the definition, classification, pathophysiology and epidemiology of amyloidosis, and explore the key clinical features and prognosis of common subtypes, highlighting why early recognition is critical.

It is with great sadness that we mark the recent death of our friend and editorial board member, Professor Adrian Brady, aged 64. Professor Adrian Brady Adrian was Honorary Professor, University of Glasgow, Consultant Cardiologist, Glasgow Royal Infirmary and Visiting Professor of Cardiology, Mayo Clinic and Cleveland Clinic, USA.

Dear Sirs, We thank Walker and colleagues for their interesting report of a 75-year-old man with platypnoea-orthodeoxia syndrome (POS) related to a large patent foramen ovale (PFO) with preferential shunting. The patient was under surveillance for aortic root dilatation (sinus of Valsalva 41 mm on presentation).1 We would like to further elaborate on, and highlight, the strong relationship between interatrial shunt-associated POS and aortic root pathology. In 2005, Eicher et al.

We evaluated the usability of a novel 2-in-1 blood pressure (BP) and electrocardiogram (ECG) monitor (developed to facilitate earlier detection of hypertension and atrial fibrillation). Arrhythmia clinic patients and public volunteers were recruited. Key themes were generated from semi-structured interviews. Patients (n=12) found the experience of measuring ECG and BP equally positive. Public volunteers (n=11) found BP measurement a more positive experience compared with ECG recording.

Immune checkpoint inhibitors (ICIs) have revolutionised cancer care, but can cause serious cardiac immune-related adverse events (irAEs), particularly myocarditis, which carries up to 50% mortality. This study explores patient pathways to improve early recognition and management of ICI myocarditis in acute settings. This was a retrospective, single-centre case series from a UK tertiary hospital with a specialist cardio-oncology multi-disciplinary team (MDT).

Cardiovascular medicine is undergoing transformation driven by machine learning (ML) technologies.1 Algorithms now assist in imaging interpretation, electrocardiogram (ECG) analysis, and outcome prediction, with increasing sophistication.1,2 The adoption of ML-powered diagnostic tools in cardiology is growing, yet training programmes remain largely unchanged, creating a disconnect between skills taught and those required in contemporary practice.1–4 Despite rigorous clinical preparation, many...