Minimizing bleeding events

Clarivate has released the 2019 Impact Factor scores. European Heart Journal – Cardiovascular Pharmacotherapy received a score of 6.7, which ranks the journal number 16 in the world in the Cardiac & CV Systems category. The journal remains the number one journal dedicated to cardiovascular pharmacology in the world. We are very grateful to all of our authors, reviewers, editors, and the EHJ CVP family. Thank you! In this issue of the journal, we introduce a new section entitled ‘Pharmapulse’ which will report on interesting events and people within the cardiovascular pharmacology world. Dual antiplatelet treatment (DAPT) is a balance between reduced ischaemic events and increased bleeding risk in patients undergoing percutaneous coronary intervention (PCI).1–4 Witberg and co-workers from Israel have performed a meta-analysis on the external validity of the DAPT score. The authors included 77 274 patients from seven studies and suggest that the DAPT score is useful both for stratifying post-PCI patients into risk strata for future ischaemic and bleeding events and for acting as an aid in choosing the optimal DAPT duration for the individual patient. Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used analgesics. When co-prescribed with warfarin, NSAIDs have been associated with increased risk of bleeding, even with short-term use.5 By using nationwide administrative registries, Dr Schjerning Olsen and co-workers from Denmark have examined the risk of gastrointestinal bleeding (GIB) among anticoagulant-naïve patients with atrial fibrillation (AF) taking oral anticoagulants (OACs) and an NSAID. The authors reported that concomitant NSAID therapy increased the short-term absolute risk of GIB. NOACs alone were associated with lower GIB risks than vitamin K antagonists (VKAs) but concomitant NSAIDs abolished this advantage. In chronic diseases such as AF, risk stratification using prediction models is useful for clinical decision-making.6–8 Most clinical risk stratification models are based on measurement at a single time point rather than serial measurements. Artificial intelligence (AI) may predict one-dimensional outcomes from multidimensional datasets. Dr Goto and co-workers present a new AI model developed for predicting clinical outcomes in AF patients up to 1 year based on sequential measures of prothrombin time–international normalized ratio (PT-INR) within 30 days of enrolment.9 The model performed better than time in therapeutic range (TTR) at predicting clinical outcomes occurring up to 12 months thereafter. The authors conclude that serial PT-INR values contain important information that can be analysed by computer to help to predict adverse clinical outcomes. Dr Marenzi et al. present a review paper, focusing on the rationale, the existing experimental data, and the emerging clinical experience supporting an early, even preventive, use of levosimendan in severe ventricular dysfunction, beyond its recognized indications. Throughout the present COVID-19 pandemic, many questions have been raised regarding the use of angiotensin-converting enzymes/angiotensin II receptor blockers (ACEIs/ARBs) and their implications for the clinical outcomes in COVID-19 patients with some underlying chronic diseases.10 In a review paper, Dr Pinto-Sietsma and co-workers from the Netherlands present theoretical understanding of the mechanisms of SARS-CoV-2 infection and host responses, with a focus on ACEIs/ARBs. The authors propose to consider using angiotensin type 1 receptor (AT1R) antagonists in the treatment of SARS-CoV-2.