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Aims
Despite recent advances in the treatment of chronic heart failure (HF), mortality and hospitalizations still remain high. Additional therapies to improve mortality and morbidity are urgently needed. The efficacy of cardiac glycosides – although regularly used for HF treatment – remains unclear. DIGIT-HF was designed to demonstrate that digitoxin on top of standard of care treatment improves mortality and morbidity in patients with HF and a reduced ejection fraction (HFrEF).
Methods
Patients with chronic HF, New York Heart Association (NYHA) functional class III–IV and left ventricular ejection fraction (LVEF) ≤ 40%, or patients in NYHA functional class II and LVEF ≤ 30% are randomized 1:1 in a double-blind fashion to treatment with digitoxin (target serum concentration 8–18 ng/mL) or matching placebo. Randomization is stratified by centre, sex, NYHA functional class (II, III, or IV), atrial fibrillation, and treatment with cardiac glycosides at baseline. A total of 2190 eligible patients will be included in this clinical trial (1095 per group). All patients receive standard of care treatment recommended by expert guidelines upon discretion of the treating physician. The primary outcome is a composite of all-cause mortality or hospital admission for worsening HF (whatever occurs first). Key secondary endpoints are all-cause mortality, hospital admission for worsening HF, and recurrent hospital admission for worsening HF.
Conclusion
The DIGIT-HF trial will provide important evidence, whether the cardiac glycoside digitoxin reduces the risk for all-cause mortality and/or hospital admission for worsening HF in patients with advanced chronic HFrEF on top of standard of care treatment.
This expert opinion paper on cardiac imaging after acute ischemic stroke or transient ischemic attack (TIA) includes a statement of the "Heart and Brain" consortium of the German Cardiac Society and the German Stroke Society. The Stroke Unit-Commission of the German Stroke Society and the German Atrial Fibrillation NETwork (AFNET) endorsed this paper. Cardiac imaging is a key component of etiological work-up after stroke. Enhanced echocardiographic tools, constantly improving cardiac computer tomography (CT) as well as cardiac magnetic resonance imaging (MRI) offer comprehensive non- or less-invasive cardiac evaluation at the expense of increased costs and/or radiation exposure. Certain imaging findings usually lead to a change in medical secondary stroke prevention or may influence medical treatment. However, there is no proof from a randomized controlled trial (RCT) that the choice of the imaging method influences the prognosis of stroke patients. Summarizing present knowledge, the German Heart and Brain consortium proposes an interdisciplinary, staged standard diagnostic scheme for the detection of risk factors of cardio-embolic stroke. This expert opinion paper aims to give practical advice to physicians who are involved in stroke care. In line with the nature of an expert opinion paper, labeling of classes of recommendations is not provided, since many statements are based on expert opinion, reported case series, and clinical experience.
Risk prediction in patients with heart failure (HF) is essential to improve the tailoring of preventive, diagnostic, and therapeutic strategies for the individual patient, and effectively use health care resources. Risk scores derived from controlled clinical studies can be used to calculate the risk of mortality and HF hospitalizations. However, these scores are poorly implemented into routine care, predominantly because their calculation requires considerable efforts in practice and necessary data often are not available in an interoperable format. In this work, we demonstrate the feasibility of a multi-site solution to derive and calculate two exemplary HF scores from clinical routine data (MAGGIC score with six continuous and eight categorical variables; Barcelona Bio-HF score with five continuous and six categorical variables). Within HiGHmed, a German Medical Informatics Initiative consortium, we implemented an interoperable solution, collecting a harmonized HF-phenotypic core data set (CDS) within the openEHR framework. Our approach minimizes the need for manual data entry by automatically retrieving data from primary systems. We show, across five participating medical centers, that the implemented structures to execute dedicated data queries, followed by harmonized data processing and score calculation, work well in practice. In summary, we demonstrated the feasibility of clinical routine data usage across multiple partner sites to compute HF risk scores. This solution can be extended to a large spectrum of applications in clinical care.