Implementation and evaluation of specialist heart failure pharmacist prescribing clinics.

Background: Medications form the basis of treatment for heart failure (HF) and adherence is crucial as untreated HF has a mortality of greater than 30%. As such, specialist HF pharmacists with expertise in prescribing and promoting adherence have become an integral part of the wider HF multidisciplinary team (MDT).

Aim: To implement specialist HF pharmacist prescribing clinics and evaluate their impact.

Long-term follow-up of the TRED-HF trial: Implications for therapy in patients with dilated cardiomyopathy and heart failure remission.

Aims: In TRED-HF, 40% of patients with recovered dilated cardiomyopathy (DCM) relapsed in the short term after therapy withdrawal. This follow-up investigates the longer-term effects of therapy withdrawal.

Methods And Results: TRED-HF was a randomized trial investigating heart failure therapy withdrawal in patients with recovered DCM over 6 months.

Implementing a clinical scientist-led screening clinic for hypertrophic and dilated cardiomyopathies.

Background: The burden of screening for inherited cardiac conditions on health services grows ever larger, with each new diagnosis necessitating screening of additional family members. Screening these usually asymptomatic, low-risk individuals is currently performed by consultant cardiologists, consuming vital clinic resources that could otherwise be diverted to sicker patients requiring specialist consultant input. Clinical scientists now constitute a highly skilled and often underutilised group of individuals with training in areas such as clinical evaluation, 12-lead electrocardiography (ECG) interpretation, and echocardiography.

The development of inherited cardiac conditions services: current position and future perspectives.

Background: Over the last two decades, inherited cardiac conditions (ICC) centres have emerged with the aim of improving outcomes for patients and their families, through early diagnosis, genetic testing, risk assessment and specialist treatment.

Sources Of Data: A literature search was performed using PubMed (https://pubmed.ncbi.

Artificial intelligence methods for improved detection of undiagnosed heart failure with preserved ejection fraction.

Aim: Heart failure with preserved ejection fraction (HFpEF) remains under-diagnosed in clinical practice despite accounting for nearly half of all heart failure (HF) cases. Accurate and timely diagnosis of HFpEF is crucial for proper patient management and treatment. In this study, we explored the potential of natural language processing (NLP) to improve the detection and diagnosis of HFpEF according to the European Society of Cardiology (ESC) diagnostic criteria.