AIMS:Anaemia is common in patients with chronic heart failure (CHF), worsening functional status and prognosis. The role of erythropoiesis-stimulating agents (ESAs) to reduce hospitalization remains unclear. METHODS AND RESULTS:A pre-registered systematic search was performed of randomized controlled trials in adults with CHF and anaemia, comparing any ESA at any dose versus placebo or no treatment.Fourteen trials were included with 3128 participants, with moderate quality of evidence for most outcomes and variable risk of bias. Meta-analysis during 5604 person-years of follow-up demonstrated no significant difference in first CHF hospitalization comparing ESAs with control: Peto odds ratio (OR) 0.93, 95% CI 0.78-1.10, P = .37; trial heterogeneity I2 = 36%. ESAs significantly reduced total CHF hospitalization with 622 events/2698 person-years, compared with 761/2914 person-years for control: incidence rate ratio 0.81, 95% CI 0.73 to 0.90, P < .001; no heterogeneity between trials, I2 = 0%. There were no significant differences between treatment groups for all-cause mortality (OR 1.01, 95% CI 0.86-1.18, P = .88; I2 = 35%) or incident adverse events. Patients randomized to ESAs increased their haemoglobin level [mean difference (MD) 1.6 g/dL compared with control, 95% CI 1.6-1.7, P < .001] and exercise tolerance (MD 69 metres, 95% CI 17-122, P = .009), with lower NYHA class on follow-up (MD -0.73 class, 95% CI -1.11 to -0.36, P < .001). CONCLUSION:ESA treatment in patients with CHF and mild anaemia can reduce recurrent CHF hospitalization and improve functional capacity, without any impact on adverse events. Including ESAs in CHF management could be considered in patients with anaemia at high risk of recurrent hospital admissions.

Artificial intelligence (AI) has increasingly become a transformative tool in cardiology, particularly in diagnosing and managing atrial fibrillation (AF), the most prevalent cardiac arrhythmia. This review aims to critically assess and synthesize current AI methodologies and their clinical relevance in AF diagnosis, risk prediction, and therapeutic guidance. It systematically evaluates recent advancements in AI methodologies, including machine learning, deep learning, and natural language processing, for AF detection, risk stratification, and therapeutic decision-making. AI-driven tools have demonstrated superior accuracy and efficiency in interpreting electrocardiograms (ECGs), continuous monitoring via wearable devices, and predicting AF onset and progression compared to traditional clinical approaches. Deep learning algorithms, notably convolutional neural networks (CNNs) and recurrent neural networks (RNNs), have revolutionized ECG analysis, identifying subtle waveform features predictive of AF development. Additionally, AI models significantly enhance clinical decision-making by personalizing anticoagulation therapy, optimizing rhythm versus rate-control strategies, and predicting procedural outcomes for catheter ablation. Despite considerable potential, practical adoption of AI in clinical practice is constrained by challenges including data privacy, explainability, and integration into clinical workflows. Addressing these challenges through robust validation studies, transparent algorithm development, and interdisciplinary collaborations will be crucial. In conclusion, AI represents a paradigm shift in AF management, promising improvements in diagnostic precision, personalized care, and patient outcomes. This review highlights the growing clinical importance of AI in AF care and provides a consolidated perspective on current applications, limitations, and future directions.

Background: Anemia is a common comorbidity in heart failure (HF) and has been associated with adverse clinical consequences. This retrospective, descriptive cohort study examined phenotype-specific differences in anemia severity, clinical presentation, comorbid burden, and in-hospital management across HF subtypes classified by left ventricular ejection fraction (LVEF). Methods: We retrospectively analyzed 443 adult patients hospitalized with concurrent HF and anemia from January 2022 to December 2024. Patients were stratified by LVEF into HFrEF (<40%), HFmrEF (40–49%), and HFpEF (≥50%). All patients included met WHO criteria for anemia. Demographic, clinical, paraclinical, and therapeutic data were extracted, and descriptive statistical methods were used to evaluate intergroup differences. No formal time-to-event analyses (e.g., Kaplan–Meier curves) were performed; instead, exploratory cumulative readmission analyses using fixed follow-up windows were conducted. In-hospital mortality was recorded and stratified by HF phenotype. Results: The cohort comprised 213 (48.0%) HFrEF, 118 (26.6%) HFmrEF, and 112 (25.3%) HFpEF patients. The distribution of anemia severity, management strategies, and comorbidity profiles varied significantly across phenotypes. Severe anemia predominated in the HFmrEF cohort (54.2%), whereas mild anemia was most common in HFpEF (52.1%) and HFrEF (52.1%). Mean hemoglobin concentrations were 8.39 ± 1.79 g/dL (HFmrEF), 9.07 ± 2.47 g/dL (HFpEF), and 8.62 ± 1.94 g/dL (HFrEF). Rates of atrial fibrillation (48.2% in HFpEF), hypertensive ECG changes (63.4% in HFpEF), and ischemic-lesion patterns (>50% in HFrEF) differed by cohort. Echocardiographically, grade III mitral regurgitation and severe pulmonary hypertension each affected 25.4% of HFmrEF patients, whereas HFpEF patients most often exhibited grade II mitral regurgitation (42.9%) and moderate pulmonary hypertension (42.9%). HFrEF patients had severe pulmonary hypertension. Intravenous (IV) iron was the primary treatment modality, with highest utilization in HFmrEF. IV iron use ranged from 69.9% (HFrEF) to 84.8% (HFmrEF), with transfusion rates of 5.6% (HFrEF)–16.1% (HFpEF). Comorbid burdens differed by phenotype: HFrEF was associated with structural heart disease, HFmrEF with vascular and hepatic pathology, and HFpEF with metabolic and degenerative comorbidities. Discharge pharmacotherapy reflected phenotype-specific treatment patterns. Conclusions: This real-world descriptive analysis highlights substantial variation in anemia burden and management across the HF spectrum. While limited to descriptive findings, our analysis highlights the heterogeneity of anemia in HF and describes observed associations across phenotypes, without implying causality. These findings should be interpreted as hypothesis-generating. These findings are observational, exploratory, and cannot establish a causal relationship between intravenous iron use and survival.

More than 64 million people worldwide have heart failure (HF), and these numbers are expected to rise. Acute HF (AHF) is the leading cause of hospitalization in patients over 65 years old and is linked to high mortality and readmission rates. AHF may also be a frequent complication in patients hospitalized for other medical reasons as well as after cardiac or non-cardiac surgery. These three entities are summarized as secondary AHF. As secondary AHF has been largely overlooked by medical research and education, little is known about its pathophysiology, phenotypes, diagnosis, management, and prognosis. Secondary AHF occurring after non-cardiac surgery warrants particular attention due to its very high mortality rates of up to 44% within 1 year and is therefore the focus of this review. The scope of this document is to summarize the available evidence regarding the pathophysiology, prevention, diagnosis, treatment, and prognosis of AHF after non-cardiac surgery. Key to prevention is understanding and addressing the pathophysiology of AHF after non-cardiac surgery, which involves close monitoring of fluid status to avoid volume overload and/or hypovolemia, avoiding hypo- and/or hypertension, treating pain and anaemia to prevent tachycardia, and avoiding electrolyte disturbances to prevent arrhythmias. Cardiac biomarkers, such as cardiac troponins and natriuretic peptides, serve as important diagnostic tools and enhance risk stratification in the perioperative setting. A low threshold to perform echocardiography in this population is suggested. Vigilant post-operative care is essential for the early recognition and treatment of AHF after non-cardiac surgery, which could help improve outcomes for patients.

The importance of atrial cardiomyopathy (AtCM) as a specific clinical entity is increasingly recognized. Past definitions have varied, and the lack of consistent cut-offs for imaging parameters and biomarkers have limited clinical utility to diagnose and track AtCM progression. While research has mainly focused on AtCM in the context of atrial fibrillation, emerging evidence underscores its relevance in remodelling and development of heart failure. The aim of this consensus document was to provide a contemporary framework for AtCM, evolve the definitions of AtCM and atrial failure for more widespread clinical use, and help to direct emerging research and future clinical trials. Supporting the work of early career researchers, this consensus document evaluates diagnostic markers and summarizes the underpinning mechanisms, clinical characteristics and prognostic impact of AtCM. Our objective was to bring together new translational scientific progress, catalyse future research and enable clinical application to facilitate better management, for example in patient groups where aggressive control of risk factors or comorbidities could prevent AtCM progression. We redefined AtCM as a graded disorder that includes electrical dysfunction of the atria along with evidence of either mechanical atrial dysfunction, atrial enlargement and/or atrial fibrosis. Atrial failure is the end-stage manifestation of AtCM, characterized by progressive structural, electrophysiological and functional changes. Earlier identification, risk stratification and ongoing research into therapeutic options have the potential to prevent the clinical consequences of AtCM and atrial failure, including adverse patient outcomes and poor quality of life associated with atrial fibrillation and heart failure.

Acute heart failure (AHF) affects millions of people each year and vasodilators have been a central part of treatment for over 25 years. The haemodynamic effects of vasodilators vary considerably among individual agents. Some vasodilators, such as nitrates, primarily act on the venous system by redistributing the circulating blood volume away from the heart towards the venous capacitance system. Other vasodilators, such as nesiritide, lead to balanced vasodilatation in the arteries and veins, decreasing left ventricular afterload and preload. Considering mechanisms of action, intravenous vasodilators are thought to be effective in patients with AHF, particularly in those with acute pulmonary oedema, where increased cardiac filling pressures and elevated systemic blood pressures occur in the absence of, or with minimal systemic fluid accumulation. However, the 2021 European heart failure guidelines have downgraded the use of vasodilators due to two recent studies and several contemporary meta-analyses failing to show benefit in terms of survival. Thus, there remains no firm recommendation suggesting the use of vasodilator treatment over usual care. In addition, despite repeated efforts to develop new vasodilatory agents, no novel therapy has outperformed traditional AHF management. In parallel with the development of novel vasodilators, changing the design of clinical trials for AHF to consider phenotype diversity of AHF patients remains an unmet need. New randomized clinical trials should particularly focus on subgroups that may mechanistically derive benefit from vasodilators, which may entail moving enrolment of patients to clinical settings close to moment of decompensation, such as the emergency department.

Heart failure (HF) is a global health burden characterized by high morbidity and mortality, necessitating advancements in diagnostic and therapeutic approaches. Molecular diagnostics, encompassing genomics, transcriptomics, proteomics, metabolomics, and epigenetics, offer unprecedented insights into HF pathogenesis, aiding early diagnosis, risk stratification, and personalized management. This state-of-the-art review critically examines recent developments in molecular diagnostics in HF, evaluates their translational potential, and highlights key challenges in clinical implementation. Emerging tools such as liquid biopsy, multi-omics integration, and artificial intelligence (AI)-driven platforms are explored. We propose strategies to enhance clinical translation, equity in access, and utility in guiding treatment, thereby advancing precision cardiovascular medicine

Background Atrial fibrillation (AF) and atrial cardiomyopathy (AtCM) share overlapping pathophysiological processes, with abnormalities in atrial structure and function being key contributors to disease progression. Aim This study aimed to assess echocardiographic parameters and circulating biomarkers in middle-aged AF patients without previously known overt heart disease, to explore early markers of atrial dysfunction and AtCM. Methods Prospective, consecutive patients (n = 970) who had been admitted for symptomatic AF to our hospital from January 2016 to January 2018 were screened for participation in the study. A total of 70 patients met the inclusion criteria: stable sinus rhythm, age between 40 and 60 years, and structurally normal hearts assessed by conventional two-dimensional echocardiography (2DE). They were separated into two groups: new-onset AF (n = 33) and recurrent episodes of paroxysmal AF (n = 37). Thirty age-matched healthy subjects were enrolled in the control group. All patients underwent 2DE assessment with volumetric and speckle-tracking analyses. Galectin-3, high-sensitivity troponin I (hsTnI), and high-sensitivity C-reactive protein (hsCRP) were measured. Results Significant structural and functional impairments were observed in both atria among AF patients, with the left atrium (LA) showing more pronounced abnormalities. Key parameters, such as LA reservoir and contractile strain, as well as electromechanical delay (EMD), were notably reduced. Individuals with paroxysmal AF exhibited elevated galectin-3 and hsTnI concentrations compared to both new-onset AF patients and controls, indicating more advanced fibrosis and myocardial stress. Furthermore, LA stiffness index and strain measures correlated strongly with galectin-3 levels. Conclusion In middle-aged patients without overt heart disease, advanced echocardiographic parameters (particularly strain and EMD), combined with biomarkers such as galectin-3 and hsTnI, represent sensitive markers for early atrial dysfunction and AtCM. The integration of these diagnostic tools may improve early detection, facilitate risk assessment, and support timely therapeutic interventions to prevent the progression of AF.

Background: Dilated cardiomyopathy (DCM) is a major cause of heart failure and arrhythmic mortality; yet, its association with cerebrovascular events, particularly in the absence of atrial fibrillation (AF), remains insufficiently explored. Purpose: This study aimed to determine the prevalence, mechanisms, and anatomical distribution of stroke in patients with DCM and to assess the role of AF and structural remodeling in stroke risk. Methods: We retrospectively analyzed 471 patients who died with DCM at the Emergency County Clinical Hospital of Bihor between 1 January 2022 and 31 December 2024. Clinical records, neuroimaging, autopsy reports, and histopathological data were reviewed. Stroke subtypes were classified according to TOAST criteria (large artery atherosclerosis, cardioembolic, small vessel disease, other determined, undetermined) and hemorrhagic categories (intracerebral, subarachnoid). Demographic, echocardiographic, and comorbidity data were compared between patients with and without cerebrovascular events. Results: Of 471 patients with DCM, 45 (9.6%) had concomitant stroke: pure ischemic in 32 (71.1%), 7 (15.6%) showed ischemic with hemorrhagic transformation, and primary hemorrhagic in 6 (13.3%). The parietal lobe was most frequently affected. AF was present in 26 patients (57.8%) and was significantly associated with ischemic stroke (p = 0.004), though embolic strokes also occurred in sinus rhythm. Patients with stroke had significantly lower left ventricular ejection fraction (28.0 ± 13.7% vs. 34.0 ± 11.2%, p = 0.007) and larger atrial dimensions. Histopathological findings confirmed acute and chronic ischemic injury patterns, including “red neurons,” white matter vacuolization, and gliotic scarring. Conclusions: Stroke is a frequent and often underdiagnosed complication in DCM, predominantly ischemic and embolic in nature. Importantly, embolic events were observed even in patients without AF, suggesting that atrial remodeling in DCM may independently predispose to cerebrovascular risk. These results underscore the need for refined preventive strategies, including careful atrial assessment and exploration of whether anticoagulation may benefit selected high-risk DCM patients without AF, a question that requires confirmation in prospective trials. Potential embolic sources in DCM include atrial cardiopathy and left ventricular thrombus in the setting of severe systolic dysfunction; therefore, careful ventricular as well as atrial assessment is warranted in high-risk DCM.

BACKGROUND AND AIMS:The role of gender in decision-making for oral anticoagulation in patients with atrial fibrillation (AF) remains controversial. METHODS:The population cohort study used electronic healthcare records of 16 587 749 patients from UK primary care (2005-2020). Primary (composite of all-cause mortality, ischaemic stroke, or arterial thromboembolism) and secondary outcomes were analysed using Cox hazard ratios (HR), adjusted for age, socioeconomic status, and comorbidities. RESULTS:78 852 patients were included with AF, aged 40-75 years, no prior stroke, and no prescription of oral anticoagulants. 28 590 (36.3%) were women, and 50 262 (63.7%) men. Median age was 65.7 years (interquartile range 58.5-70.9), with women being older and having other differences in comorbidities. During a total follow-up of 431 086 patient-years, women had a lower adjusted primary outcome rate with HR 0.89 vs. men (95% confidence interval [CI] 0.87-0.92; P < .001) and HR 0.87 after censoring for oral anticoagulation (95% CI 0.83-0.91; P < .001). This was driven by lower mortality in women (HR 0.86, 95% CI 0.83-0.89; P < .001). No difference was identified between women and men for the secondary outcomes of ischaemic stroke or arterial thromboembolism (adjusted HR 1.00, 95% CI 0.94-1.07; P = .87), any stroke or any thromboembolism (adjusted HR 1.02, 95% CI 0.96-1.07; P = .58), and incident vascular dementia (adjusted HR 1.13, 95% CI 0.97-1.32; P = .11). Clinical risk scores were only modest predictors of outcomes, with CHA2DS2-VA (ignoring gender) superior to CHA2DS2-VASc for primary outcomes in this population (receiver operating characteristic curve area 0.651 vs. 0.639; P < .001) and no interaction with gender (P = .45). CONCLUSIONS:Removal of gender from clinical risk scoring could simplify the approach to which patients with AF should be offered oral anticoagulation.

Consumer-grade wearable technology has the potential to support clinical research and patient management. Here, we report results from the RATE-AF trial wearables study, which was designed to compare heart rate in older, multimorbid patients with permanent atrial fibrillation and heart failure who were randomized to treatment with either digoxin or beta-blockers. Heart rate (n = 143,379,796) and physical activity (n = 23,704,307) intervals were obtained from 53 participants (mean age 75.6 years (s.d. 8.4), 40% women) using a wrist-worn wearable linked to a smartphone for 20 weeks. Heart rates in participants treated with digoxin versus beta-blockers were not significantly different (regression coefficient 1.22 (95% confidence interval (CI) -2.82 to 5.27; P = 0.55); adjusted 0.66 (95% CI -3.45 to 4.77; P = 0.75)). No difference in heart rate was observed between the two groups of patients after accounting for physical activity (P = 0.74) or patients with high activity levels (>= 30,000 steps per week; P = 0.97). Using a convolutional neural network designed to account for missing data, we found that wearable device data could predict New York Heart Association functional class 5 months after baseline assessment similarly to standard clinical measures of electrocardiographic heart rate and 6-minute walk test (F1 score 0.56 (95% CI 0.41 to 0.70) versus 0.55 (95% CI 0.41 to 0.68); P = 0.88 for comparison). The results of this study indicate that digoxin and beta-blockers have equivalent effects on heart rate in atrial fibrillation at rest and on exertion, and suggest that dynamic monitoring of individuals with arrhythmia using wearable technology could be an alternative to in-person assessment. ClinicalTrials.gov identifier: NCT02391337. In a substudy of the RATE-AF trial, which compared heart rate control therapy using digoxin or the beta-blocker bisoprolol, heart rate and physical activity data collected using a wearable device showed equivalent heart rate control by the two drugs and could be used to predict future heart failure functional class as well as standard clinical measurements.

IntroductionThe echocardiographic measurement of left ventricular ejection fraction (LVEF) is fundamental to the diagnosis and classification of patients with heart failure (HF).MethodsThis paper aimed to quantify LVEF automatically and accurately with the proposed pipeline method based on deep neural networks and ensemble learning. Within the pipeline, an Atrous Convolutional Neural Network (ACNN) was first trained to segment the left ventricle (LV), before employing the area-length formulation based on the ellipsoid single-plane model to calculate LVEF values. This formulation required inputs of LV area, derived from segmentation using an improved Jeffrey’s method, as well as LV length, derived from a novel ensemble learning model. To further improve the pipeline’s accuracy, an automated peak detection algorithm was used to identify end-diastolic and end-systolic frames, avoiding issues with human error. Subsequently, single-beat LVEF values were averaged across all cardiac cycles to obtain the final LVEF.ResultsThis method was developed and internally validated in an open-source dataset containing 10,030 echocardiograms. The Pearson’s correlation coefficient was 0.83 for LVEF prediction compared to expert human analysis (p < 0.001), with a subsequent area under the receiver operator curve (AUROC) of 0.98 (95% confidence interval 0.97 to 0.99) for categorisation of HF with reduced ejection (HFrEF; LVEF<40%). In an external dataset with 200 echocardiograms, this method achieved an AUC of 0.90 (95% confidence interval 0.88 to 0.91) for HFrEF assessment.ConclusionThe automated neural network-based calculation of LVEF is comparable to expert clinicians performing time-consuming, frame-by-frame manual evaluations of cardiac systolic function.

Atrial fibrillation (AF) remains the most common cardiac arrhythmia worldwide and is associated with significant morbidity and mortality. The European Society of Cardiology (ESC)/European Association for Cardio-Thoracic Surgery (EACTS) have recently released the 2024 guidelines for the management of AF. This review highlights 10 novel aspects of the ESC/EACTS 2024 Guidelines. The AF-CARE framework is introduced, a structural approach that aims to improve patient care and outcomes, comprising of four pillars: [C] Comorbidity and risk factor management, [A] Avoid stroke and thromboembolism, [R] Reduce symptoms by rate and rhythm control, and [E] Evaluation and dynamic reassessment. Additionally, graphical patient pathways are provided to enhance clinical application. A significant shift is the new emphasis on comorbidity and risk factor control to reduce AF recurrence and progression. Individualized assessment of risk is suggested to guide the initiation of oral anticoagulation to prevent thromboembolism. New guidance is provided for anticoagulation in patients with trigger-induced and device-detected sub-clinical AF, ischaemic stroke despite anticoagulation, and the indications for percutaneous/surgical left atrial appendage exclusion. AF ablation is a first-line rhythm control option for suitable patients with paroxysmal AF, and in specific patients, rhythm control can improve prognosis. The AF duration threshold for early cardioversion was reduced from 48 to 24 h, and a wait-and-see approach for spontaneous conversion is advised to promote patient safety. Lastly, strong emphasis is given to optimize the implementation of AF guidelines in daily practice using a patient-centred, multidisciplinary and shared-care approach, with the simultaneous launch of a patient version of the guideline.

This is a commentary article, there is no abstract section.

IntroductionRecent advances in machine learning provide new possibilities to process and analyse observational patient data to predict patient outcomes. In this paper, we introduce a data processing pipeline for cardiogenic shock (CS) prediction from the MIMIC III database of intensive cardiac care unit patients with acute coronary syndrome. The ability to identify high-risk patients could possibly allow taking pre-emptive measures and thus prevent the development of CS.MethodsWe mainly focus on techniques for the imputation of missing data by generating a pipeline for imputation and comparing the performance of various multivariate imputation algorithms, including k-nearest neighbours, two singular value decomposition (SVD)—based methods, and Multiple Imputation by Chained Equations. After imputation, we select the final subjects and variables from the imputed dataset and showcase the performance of the gradient-boosted framework that uses a tree-based classifier for cardiogenic shock prediction.ResultsWe achieved good classification performance thanks to data cleaning and imputation (cross-validated mean area under the curve 0.805) without hyperparameter optimization.ConclusionWe believe our pre-processing pipeline would prove helpful also for other classification and regression experiments.

Background Intravenous beta-blockers are commonly used to manage patients with acute atrial fibrillation (AF) and atrial flutter (AFl), but the choice of specific agent is often not evidence-based. Methods A prospectively-registered systematic review and meta-analysis of randomised trials (PROSPERO: CRD42020204772) to compare the safety and efficacy of intravenous beta-blockers against alternative pharmacological agents. Results Twelve trials comparing beta-blockers with diltiazem, digoxin, verapamil, anti-arrhythmic drugs and placebo were included, with variable risk of bias and 1152 participants. With high heterogeneity (I 2 = 87%; p < 0.001), there was no difference in the primary outcomes of heart rate reduction (standardised mean difference − 0.65 beats/minute compared to control, 95% CI − 1.63 to 0.32; p = 0.19) or the proportion that achieved target heart rate (risk ratio [RR] 0.85, 95% CI 0.36–1.97; p = 0.70). Conventional selective beta-1 blockers were inferior for target heart rate reduction versus control (RR 0.33, 0.17–0.64; p < 0.001), whereas super-selective beta-1 blockers were superior (RR 1.98, 1.54–2.54; p < 0.001). There was no significant difference between beta-blockers and comparators for secondary outcomes of conversion to sinus rhythm (RR 1.15, 0.90–1.46; p = 0.28), hypotension (RR 1.85, 0.87–3.93; p = 0.11), bradycardia (RR 1.29, 0.25–6.82; p = 0.76) or adverse events leading to drug discontinuation (RR 1.03, 0.49–2.17; p = 0.93). The incidence of hypotension and bradycardia were greater with non-selective beta-blockers (p = 0.031 and p < 0.001). Conclusions Across all intravenous beta-blockers, there was no difference with other medications for acute heart rate control in atrial fibrillation and flutter. Efficacy and safety may be improved by choosing beta-blockers with higher beta-1 selectivity. Graphical abstract

Background The prevalence of combined heart failure (HF) and atrial fibrillation (AF) is rising, and these patients suffer from high rates of mortality. This study aims to provide robust data on factors associated with death, uniquely supported by post-mortem examination. Methods A retrospective cohort study of hospitalized adults with a clinical diagnosis of HF and AF at a tertiary centre in Romania between 2014 and 2017. A standardized post-mortem examination was performed where death occurred within 24 h of admission, when the cause of death was not clear or by physician request. National records were used to collect mortality data, subsequently categorized and analysed as HF-related death, vascular death and non-cardiovascular death using Cox proportional hazards regression. Results A total of 1009 consecutive patients with a mean age of 73 ± 11 years, 47% women, NYHA class 3.0 ± 0.9, left ventricular ejection fraction (LVEF) 40.1 ± 11.0% and 100% anticoagulated were followed up for 1.5 ± 0.9 years. A total of 291 (29%) died, with post-mortems performed on 186 (64%). Baseline factors associated with mortality were dependent on the cause of death. HF-related death in 136 (47%) was associated with higher NYHA class (hazard ratio [HR] 2.45 per one class increase, 95% CI 1.73–3.46; p < 0.001) and lower LVEF (0.95 per 1% increase, 0.93–0.97; p < 0.001). Vascular death occurred in 75 (26%) and was associated with hypertension (HR 2.83, 1.36–5.90; p = 0.005) and higher LVEF (1.08 per 1% increase, 1.05–1.11; p < 0.001). Non-cardiovascular death in 80 (28%) was associated with clinical obesity (HR 2.20, 1.21–4.00; p = 0.010) and higher LVEF (1.10 per 1% increase, 1.06–1.13; p < 0.001). Across all causes, there was no relationship between mortality and AF type ( p = 0.77), HF type ( p = 0.85) or LVEF ( p = 0.58). Conclusions Supported by post-mortem data, the cause of death in HF and AF patients is heterogeneous, and the relationships with typical markers of mortality are critically dependent on the mode of death. The poor prognosis in this group demands further attention to improve management beyond anticoagulation. Graphical Abstract