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Aims Left ventricular ejection fraction (EF) is required to categorize heart failure (HF) [i.e. HF with preserved (HFpEF), mid-range (HFmrEF), and reduced (HFrEF) EF] but is often not captured in population-based cohorts or non-HF registries. The aim was to create an algorithm that identifies EF subphenotypes for research purposes. Methods and results We included 42 061 HF patients from the Swedish Heart Failure Registry. As primary analysis, we performed two logistic regression models including 22 variables to predict (i) EF >= vs. = vs. = 50% and 0.76 (95% CI 0.75-0.76) for EF >= 40%. Similar results were achieved for HFrEF and HFpEF in the multinomial model, but the C-statistic for HFmrEF was lower: 0.63 (95% CI 0.63-0.64). The external validation showed similar discriminative ability to the development cohort. Conclusions Routine clinical characteristics could potentially be used to identify different EF subphenotypes in databases where EF is not readily available. Accuracy was good for the prediction of HFpEF and HFrEF but lower for HFmrEF. The proposed algorithm enables more effective research on HF in the big data setting. ; Funding Agencies|Swedish National Board of Health and Welfare; Swedish Association of Local Authorities and Regions; Swedish Society of Cardiology; Swedish Heart-Lung FoundationSwedish Heart-Lung Foundation; Servier, the NetherlandsNetherlands Government; EU/EFPIA Innovative Medicines Initiative 2 Joint Undertaking BigData@Heart [116074]; Swedish Research CouncilSwedish Research Council [2013-23897-104604-23, 523-2014-2336]; Swedish Heart Lung FoundationSwedish Heart-Lung Foundation [20150557, 20170841]; Stockholm County CouncilStockholm County Council [20140220, 20170112]; UCL Hospitals NIHR Biomedical Research Centre; Dutch Heart Foundation, a part of Facts and Figures

Heart failure (HF) is responsible for substantial morbidity and mortality and is increasing in prevalence. Although there has been remarkable progress in the treatment of HF with reduced ejection fraction (HFrEF), morbidity and mortality are still substantial. Cardiac contractility modulation (CCM) signals, consisting of biphasic high‐voltage bipolar signals delivered to the right ventricular septum during the absolute refractory period, have been shown to improve symptoms, exercise tolerance and quality of life and reduce the rate of HF hospitalizations in patients with ejection fractions (EF) between 25% and 45%. CCM therapy is currently approved in the European Union, China, India, Australia and Brazil for use in symptomatic HFrEF patients with normal or slightly prolonged QRS duration. CCM is particularly beneficial in patients with baseline EF between 35% and 45%, which includes half the range of HF patients with mid‐range EFs (HFmrEF). At the cellular level, CCM has been shown in HFrEF patients to improve calcium handling, to reverse the foetal myocyte gene programme associated with HF, and to facilitate reverse remodelling. This review highlights the preclinical and clinical literature related to CCM in HFrEF and HFmrEF and outlines the potential of CCM for HF with preserved EF, concluding that CCM may fill an important unmet need in the therapeutic approach to HF across the range of EFs.

Background: Heart failure (HF) is associated with type 2 diabetes mellitus (T2DM). Antihyperglycemic drugs have interaction with heart failure among diabetic patients. To date, the data on real world use of diabetic medication in Malaysian heart failure patients with T2DM has not been elucidated. Objective: This study aims to identify the prescribing pattern of antihyperglycemic regimens in HF patients with T2DM, and to investigate the association between glycemic control and other factors such as demographic and clinical characteristics with left ventricular ejection fraction (LVEF) in these patients. Methods: This retrospective observational study involved patients diagnosed to have HF and T2DM who were seen in the outpatient clinic in a government tertiary hospital in Malaysia. Patients receiving at least one oral antidiabetic agent and/or insulin for at least 3 months prior were included. The differences and association between study outcomes were examined and analyzed using Pearson's Chi-square test, One-Way ANOVA, Binary Logistic Regression and multiple Multinomial Logistic Regression models. Results: From July to December 2019, 194 patients were included in this study. The majority (52.1%) of the patients had HF with preserved ejection fraction (HFpEF), 20.6% had HF with mid-range EF (HFmrEF), and 27.3% had HF with reduced EF (HFrEF). Overall, metformin (59.8%) was the commonest antihyperglycemic agent prescribed, followed by insulins (54.0%), and sulphonylureas (44.9%). The most prescribed agents for HFpEF, HFmrEF, and HFrEF patients were metformin (65.3%), insulins (62.5%), and sulphonylureas (60.4%), respectively. The prescribing trend of sulphonylureas was found to be significantly associated with patients' LVEF status (p = 0.033). The odds for sulphonylurea prescription among the HFrEF patients were 2.42 times higher compared to the HFpEF patients [95% confidence interval [CI], 1.23–4.79]. There was no association found between glycemic control with patients' LVEF. Conclusion: Our findings reported ...

Funding: This study was endorsed by the ESICM. Free support for running the electronic database was granted from the Department of Epidemiology, Aarhus University, Denmark. The support of the study in France by a grant from 'Fondation Assistance Publique-Hôpitaux de Paris pour la recherche' is greatly appreciated. In Norway, the study was supported by a grant from the Health Region West. In addition, the study was supported by a grant from the European Open Science Cloud (EOSC). EOSCsecretariat.eu has received funding from the European Union's Horizon 2020 Framework Programme called H2020-INFRAEOSC-05-2018-2019, Grant Agreement Number 831644. This work was supported by the Forschungskommission of the Medical Faculty of the Heinrich Heine University Düsseldorf, No. 2018-32 to G.W. and No. 2020-21 to R.R.B. for a Clinician Scientist Track. Open access funding was enabled and organized by Projekt DEAL. No (industry) sponsorship has been received for this investigator-initiated study. ; AIMS: Chronic heart failure (CHF) is a major risk factor for mortality in coronavirus disease 2019 (COVID-19). This prospective international multicentre study investigates the role of pre-existing CHF on clinical outcomes of critically ill old (≥70 years) intensive care patients with COVID-19. METHODS AND RESULTS: Patients with pre-existing CHF were subclassified as having ischaemic or non-ischaemic cardiac disease; patients with a documented ejection fraction (EF) were subclassified according to heart failure EF: reduced (HFrEF, n = 132), mild (HFmrEF, n = 91), or preserved (HFpEF, n = 103). Associations of heart failure characteristics with the 30 day mortality were analysed in univariate and multivariate logistic regression analyses. Pre-existing CHF was reported in 566 of 3917 patients (14%). Patients with CHF were older, frailer, and had significantly higher SOFA scores on admission. CHF patients showed significantly higher crude 30 day mortality [60% vs. 48%, P < 0.001; odds ratio 1.87, 95% confidence interval (CI) 1.5-2.3] and 3 month mortality (69% vs. 56%, P < 0.001). After multivariate adjustment for confounders (SOFA, age, sex, and frailty), no independent association of CHF with mortality remained [adjusted odds ratio (aOR) 1.2, 95% CI 0.5-1.5; P = 0.137]. More patients suffered from pre-existing ischaemic than from non-ischaemic disease [233 vs. 328 patients (n = 5 unknown aetiology)]. There were no differences in baseline characteristics between ischaemic and non-ischaemic disease or between HFrEF, HFmrEF, and HFpEF. Crude 30 day mortality was significantly higher in HFrEF compared with HFpEF (64% vs. 48%, P = 0.042). EF as a continuous variable was not independently associated with 30 day mortality (aOR 0.98, 95% CI 0.9-1.0; P = 0.128). CONCLUSIONS: In critically ill older COVID-19 patients, pre-existing CHF was not independently associated with 30 day mortality. TRIAL REGISTRATION NUMBER: NCT04321265. ; publishersversion ; epub_ahead_of_print