Consumption of coffee, one of the most popular beverages around the world, has been associated with a lower risk of cardiovascular and all-cause mortality in population-based studies. However, little is known about these associations in patient populations. This prospective study aimed to examine the consumption of caffeinated and decaffeinated coffee in relation to cardiovascular disease (CVD) mortality, ischemic heart disease (IHD) mortality, and all-cause mortality in patients with a prior myocardial infarction (MI). We included 4365 Dutch patients from the Alpha Omega Cohort who were aged 60-80 y (21% female) and had experienced an MI <10 y before study enrollment. At baseline (2002-2006), dietary data including coffee consumption over the past month was collected with a 203-item validated food-frequency questionnaire. Causes of death were monitored until 1 January 2013. HRs for mortality in categories of coffee consumption were obtained from multivariable Cox proportional hazard models, adjusting for lifestyle and dietary factors. Most patients (96%) drank coffee, and the median total coffee intake was 375 mL/d (∼3 cups/d). During a median follow-up of 7.1 y, a total of 945 deaths occurred, including 396 CVD-related and 266 IHD-related deaths. Coffee consumption was inversely associated with CVD mortality, with HRs of 0.69 (95% CI: 0.54, 0.89) for >2-4 cups/d and 0.72 (0.55, 0.95) for >4 cups/d, compared with 0-2 cups/d. Corresponding HRs were 0.77 (95% CI: 0.57, 1.05) and 0.68 (95% CI: 0.48, 0.95) for IHD mortality and 0.84 (95% CI: 0.71, 1.00) and 0.82 (95% CI: 0.68, 0.98) for all-cause mortality, respectively. Similar associations were found for decaffeinated coffee and for coffee with additives. Drinking coffee, either caffeinated or decaffeinated, may lower the risk of CVD and IHD mortality in patients with a prior MI. This study was registered at clinicaltrials.gov as NCT03192410.

IntroductionEarly recognition of individuals with increased risk of sudden cardiac arrest (SCA) remains challenging. SCA research so far has used data from cardiologist care, but missed most SCA victims, since they were only in general practitioner (GP) care prior to SCA. Studying individuals with type 2 diabetes (T2D) in GP care may help solve this problem, as they have increased risk for SCA, and rich clinical datasets, since they regularly visit their GP for check-up measurements. This information can be further enriched with extensive genetic and metabolic information.AimTo describe the study protocol of the REcognition of Sudden Cardiac arrest vUlnErability in Diabetes (RESCUED) project, which aims at identifying clinical, genetic and metabolic factors contributing to SCA risk in individuals with T2D, and to develop a prognostic model for the risk of SCA.MethodsThe RESCUED project combines data from dedicated SCA and T2D cohorts, and GP data, from the same region in the Netherlands. Clinical data, genetic data (common and rare variant analysis) and metabolic data (metabolomics) will be analysed (using classical analysis techniques and machine learning methods) and combined into a prognostic model for risk of SCA.ConclusionThe RESCUED project is designed to increase our ability at early recognition of elevated SCA risk through an innovative strategy of focusing on GP data and a multidimensional methodology including clinical, genetic and metabolic analyses.

Introduction: In cardiac arrest, ventricular fibrillation (VF) waveform characteristics such as amplitude spectrum area (AMSA) are studied to identify an underlying myocardial infarction (MI). Observational studies report lower AMSA-values in patients with than without underlying MI. Moreover, experimental studies with 12-lead ECG-recordings show lowest VF-characteristics when the MI-localisation matches the ECG-recording direction. However, out-of-hospital cardiac arrest (OHCA)-studies with defibrillator-derived VF-recordings are lacking. Methods: Multi-centre (Amsterdam/Nijmegen, the Netherlands) cohort-study on the association between AMSA, ST-elevation MI (STEMI) and its localisation. AMSA was calculated from defibrillator pad-ECG recordings (proxy for lead II, inferior vantage point); STEMI-localisation was determined using ECG/angiography/autopsy findings. Results: We studied AMSA-values in 754 OHCA-patients. There were statistically significant differences between no STEMI, anterior STEMI and inferior STEMI (Nijmegen: no

Aims This study aimed to establish whether higher levels of glycated haemoglobin (HbA1c) are associated with increased sudden cardiac arrest (SCA) risk in non-diabetic individuals. Methods and results Case–control study in non-diabetic individuals (HbA1c &lt; 6.5%) in the Netherlands. Cases were SCA patients with electrocardiogram (ECG)-documented ventricular fibrillation (VF, the predominant cause of SCA) and HbA1c measurements immediately after VF, prospectively included in September 2009–December 2012. Controls (up to 10 per case) were age/sex-matched non-SCA individuals, included in July 2006–November 2007. We studied 306 cases (56.4 ± 6.8 years, 79.1% male) and 1722 controls (54.0 ± 6.8 years, 64.8% male). HbA1c levels were higher in cases than in controls (5.8 ± 0.3% vs. 5.4 ± 0.3%, P &lt; 0.001). The proportion of increased HbA1c (≥5.7%) was 63.1% in cases and 19.3% in controls (P &lt; 0.001). Multivariate regression models indicated that increased HbA1c was associated with a &gt; six-fold increased VF risk [adjusted odds ratio (ORadj) 6.74 (5.00–9.09)] and that 0.1% increase in HbA1c level was associated with 1.4-fold increase in VF risk, independent of concomitant cardiovascular risk factors. Increased VF risk at higher HbA1c is associated with acute myocardial infarction (MI) as cause of VF [OR 1.14 (1.04–1.24)], but the association between HbA1c and VF was similar in non-MI patients [OR 1.32 (1.21–1.44)] and MI patients [OR 1.47 (1.37–1.58)]. Conclusion Among non-diabetic individuals, risk of VF increased with rising HbA1c levels, independent of concomitant cardiovascular disease. Future studies should establish whether HbA1c level may be used as biomarker to recognize individuals at risk for VF.