Contrary to the accepted view, myocardial edema during the first week after ischemia/reperfusion follows a bimodal pattern. The initial wave appears abruptly upon reperfusion and dissipates at 24 h. Conversely, the deferred wave of edema appears progressively days after ischemia/reperfusion and is maximal around day 7 after reperfusion.

No abstract

Research on cardioprotection has attracted considerable attention during the past 30 years following the discovery of ischemic preconditioning with great advances being made in the field, particularly in the description of the molecular signalling behind this cardioprotective intervention. In a time when basic research is struggling to translate its findings into therapies in the clinical setting, this viewpoint has the intention of presenting to clinical and basic scientists how the reperfusion injury salvage kinase pathway has been described and dissected, as well as highlighting its relevance in cardioprotection.

30Background: Physicians in the emergency department (ED) need additional tools to stratify patients with acute 31

AimsThe potential of remote ischaemic conditioning (RIC) to ameliorate myocardial ischaemia-reperfusion injury (IRI) remains controversial. We aimed to analyse the pre-clinical evidence base to ascertain the overall effect and variability of RIC in animal in vivo models of myocardial IRI. Furthermore, we aimed to investigate the impact of different study protocols on the protective utility of RIC in animal models and identify gaps in our understanding of this promising therapeutic strategy.Methods and resultsOur primary outcome measure was the difference in mean infarct size between RIC and control groups in in vivo models of myocardial IRI. A systematic review returned 31 reports, from which we made 22 controlled comparisons of remote ischaemic preconditioning (RIPreC) and 21 of remote ischaemic perconditioning and postconditioning (RIPerC/RIPostC) in a pooled random-effects meta-analysis. In total, our analysis includes data from 280 control animals and 373 animals subject to RIC. Overall, RIPreC reduced infarct size as a percentage of area at risk by 22.8% (95% CI 18.8–26.9%), when compared with untreated controls (P < 0.001). Similarly, RIPerC/RIPostC reduced infarct size by 22.2% (95% CI 17.1–25.3%; P < 0.001). Interestingly, we observed significant heterogeneity in effect size (T2 = 92.9% and I2 = 99.4%; P < 0.001) that could not be explained by any of the experimental variables analysed by meta-regression. However, few reports have systematically characterized RIC protocols, and few of the included in vivo studies satisfactorily met study quality requirements, particularly with respect to blinding and randomization.ConclusionsRIC significantly reduces infarct size in in vivo models of myocardial IRI. Heterogeneity between studies could not be explained by the experimental variables tested, but studies are limited in number and lack consistency in quality and study design. There is therefore a clear need for more well-performed in vivo studies with particular emphasis on detailed characterization of RIC protocols and investigating the potential impact of gender. Finally, more studies investigating the potential benefit of RIC in larger species are required before translation to humans.

Among patients with STEMI, there is a wide regional variation in clinical profiles, hospital care and mortality. Substantial room for improvement remains at a global level for increasing reperfusion rates, reducing delays and post-discharge mortality in patients with STEMI.

Introduction and objectives The COVID-19 outbreak has had an unclear impact on the treatment and outcomes of patients with ST-segment elevation myocardial infarction (STEMI). The aim of this study was to assess changes in STEMI management during the COVID-19 outbreak. Methods Using a multicenter, nationwide, retrospective, observational registry of consecutive patients who were managed in 75 specific STEMI care centers in Spain, we compared patient and procedural characteristics and in-hospital outcomes in 2 different cohorts with 30-day follow-up according to whether the patients had been treated before or after COVID-19. Results Suspected STEMI patients treated in STEMI networks decreased by 27.6% and patients with confirmed STEMI fell from 1305 to 1009 (22.7%). There were no differences in reperfusion strategy (> 94% treated with primary percutaneous coronary intervention in both cohorts). Patients treated with primary percutaneous coronary intervention during the COVID-19 outbreak had a longer ischemic time (233 [150-375] vs 200 [140-332] minutes, P < .001) but showed no differences in the time from first medical contact to reperfusion. In-hospital mortality was higher during COVID-19 (7.5% vs 5.1%; unadjusted OR, 1.50; 95%CI, 1.07-2.11; P < .001); this association remained after adjustment for confounders (risk-adjusted OR, 1.88; 95%CI, 1.12-3.14; P = .017). In the 2020 cohort, there was a 6.3% incidence of confirmed SARS-CoV-2 infection during hospitalization. Conclusions The number of STEMI patients treated during the current COVID-19 outbreak fell vs the previous year and there was an increase in the median time from symptom onset to reperfusion and a significant 2-fold increase in the rate of in-hospital mortality. No changes in reperfusion strategy were detected, with primary percutaneous coronary intervention performed for the vast majority of patients. The co-existence of STEMI and SARS-CoV-2 infection was relatively infrequent.

Risk assessment have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of – usually interactive and online available – tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.