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Heart failure (HF) encompasses a diverse clinical spectrum, including instances of transient HF or HF with recovered ejection fraction, alongside persistent cases. This dynamic condition exhibits a growing prevalence and entails substantial healthcare expenditures, with anticipated escalation in the future. It is essential to classify HF patients into three groups based on their ejection fraction: reduced (HFrEF), mid-range (HFmEF), and preserved (HFpEF), such as for diagnosis, risk assessment, treatment choice, and the ongoing monitoring of heart failure. Nevertheless, obtaining a definitive prediction poses challenges, requiring the reliance on echocardiography. On the contrary, an electrocardiogram (ECG) provides a straightforward, quick, continuous assessment of the patient's cardiac rhythm, serving as a cost-effective adjunct to echocardiography. In this research, we evaluate several machine learning (ML)-based classification models, such as K-nearest neighbors (KNN), neural networks (NN), support vector machines (SVM), and decision trees (TREE), to classify left ventricular ejection fraction (LVEF) for three categories of HF patients at hourly intervals, using 24-hour ECG recordings. Information from heterogeneous group of 303 heart failure patients, encompassing HFpEF, HFmEF, or HFrEF classes, was acquired from a multicenter dataset involving both American and Greek populations. Features extracted from ECG data were employed to train the aforementioned ML classification models, with the training occurring in one-hour intervals. To optimize the classification of LVEF levels in coronary artery disease (CAD) patients, a nested cross-validation approach was employed for hyperparameter tuning. HF patients were best classified using TREE and KNN models, with an overall accuracy of 91.2% and 90.9%, and average area under the curve of the receiver operating characteristics (AUROC) of 0.98, and 0.99, respectively. Furthermore, according to the experimental findings, the time periods of midnight-1 am, 8-9 am, and 10-11 pm were the ones that contributed to the highest classification accuracy. The results pave the way for creating an automated screening system tailored for patients with CAD, utilizing optimal measurement timings aligned with their circadian cycles., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Al Younis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background and Objective: Heart failure (HF) is a multi-faceted and life-threatening syndrome that affects more than 64.3 million people worldwide. Current gold-standard screening technique, echocardiography, neglects cardiovascular information regulated by the circadian rhythm and does not incorporate knowledge from patient profiles. In this study, we propose a novel multi-parameter approach to assess heart failure using heart rate variability (HRV) and patient clinical information., Methods: In this approach, features from 24-hour HRV and clinical information were combined as a single polar image and fed to a 2D deep learning model to infer the HF condition. The edges of the polar image correspond to the timely variation of different features, each of which carries information on the function of the heart, and internal illustrates color-coded patient clinical information., Results: Under a leave-one-subject-out cross-validation scheme and using 7,575 polar images from a multi-center cohort (American and Greek) of 303 coronary artery disease patients (median age: 58 years [50-65], median body mass index (BMI): 27.28 kg/m 2 [24.91-29.41]), the model yielded mean values for the area under the receiver operating characteristics curve (AUC), sensitivity, specificity, normalized Matthews correlation coefficient (NMCC), and accuracy of 0.883, 90.68%, 95.19%, 0.93, and 92.62%, respectively. Moreover, interpretation of the model showed proper attention to key hourly intervals and clinical information for each HF stage., Conclusions: The proposed approach could be a powerful early HF screening tool and a supplemental circadian enhancement to echocardiography which sets the basis for next-generation personalized healthcare., Competing Interests: Declaration of Competing Interest The authors declare no competing interests about the content or interpretation of the data in the present study., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Current guidelines recommend a rhythm control strategy in patients with symptomatic atrial fibrillation (AF) while catheter ablation has been shown to be a safer and more efficacious approach than antiarrhythmic medications., Methods: HECMOS was a nationwide snapshot survey of cardiorenal morbidity in hospitalized cardiology patients. In this sub-study, we included 276 cases who had a history of AF, particularly on the rhythm strategy, and catheter ablation procedures had been performed before the index admission., Results: Among 276 AF patients (mean age: 76.4 ± 11.5 years, 58 % male), 60.9 % (N = 168) had persistent AF and 39.1 % (N = 108) had paroxysmal AF. Heart failure was the main cause of admission in 54.3 % (N = 145) of the patients, while 14.1 % (N = 39) were admitted due to paroxysmal AF, 7.3 % (N = 20) due to bradyarrhythmic reasons, and 6.5 % (N = 18) suffered from acute coronary syndrome. Most importantly, heart failure with reduced ejection fraction was present in 76 (27 %) patients. Only 10 patients out of the total (3 %, mean age 59.7 years) had undergone AF ablation while electrical cardioversion had been attempted in 37 (13.4 %) patients. Interestingly, in this AF population with heart failure, 3.6 % (N = 10) had a defibrillator implanted (4 single-chamber), and only 1.5 % (N = 4) had a cardiac resynchronization therapy defibrillator (CRT-D)., Conclusion: High prevalence of persistent AF was detected in hospitalized patients, with heart failure being the leading cause of admission and main co-morbidity. Rhythm control strategies are notably underused, along with CRT-D implantation in patients with AF and heart failure., Competing Interests: Declaration of competing interest None., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: Medical treatment for heart failure with preserved ejection (HFpEF) and heart failure with mildly reduced ejection fraction (HFmrEF) has weaker evidence compared with reduced ejection fraction, despite recent trials with an angiotensin receptor neprilysin inhibitor (ARNI) and sodium glucose co-transporter 2 inhibitors (SGLT2is)., Objectives: The authors aimed to estimate the aggregate therapeutic benefit of drugs for HFmrEF and HFpEF., Methods: The authors performed a systematic review of MEDLINE, CENTRAL, and Web of Science for randomized trials including patients with heart failure (HF) and left ventricular ejection fraction (LVEF) >40%, treated with angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (analyzed together as renin-angiotensin system inhibitors [RASi]), beta-blockers (BBs), mineralocorticoid receptor antagonists (MRAs), digoxin, ARNI, and SGLT2i. An additive component network meta-analysis was performed. The primary outcome was a composite of cardiovascular (CV) death and first hospitalization for heart failure (HHF); secondary outcomes were CV death, total HHF, and all-cause mortality., Results: The authors identified 13 studies with a total of 29,875 patients and a mean LVEF of 56.3% ± 8.7%. ARNI, MRA, and SGLT2i separately, but not RASi, BB, or digoxin, reduced the primary composite outcome compared with placebo. The combination of ARNI, BB, MRA, and SGLT2i was the most effective (HR: 0.47 [95% CI: 0.31-0.70]); this was largely explained by the triple combination of ARNI, MRA, and SGLT2i (HR: 0.56 [95% CI 0.43-0.71]). Results were similar for CV death (HR: 0.63 [95% CI 0.43-0.91] for ARNI, MRA, and SGLT2i) or total HHF (HR: 0.49 [95% CI 0.33-0.71] for ARNI, MRA, and SGLT2i) alone. In a subgroup analysis, only SGLT2i had a consistent benefit among all LVEF subgroups, whereas the triple combination had the greatest benefit in HFmrEF, robust benefit in patients with LVEF 50% to 59%, and a statistically marginal benefit in patients with LVEF ≥60%., Conclusions: In patients with HF and LVEF>40%, the quadruple combination of ARNI, BB, MRA, and SGLT2i provides the largest reduction in the risk of CV death and HHF; driven by the robust effect of the triple combination of ARNI, MRA, and SGLT2i. The benefit was more pronounced in HFmrEF patients., Competing Interests: Funding Support and Author Disclosures Dr Konstantinides is a consultant to Daiichi-Sankyo, Bayer AG, Boston Scientific, Penumbra Inc, and LumiraDx; and he has received honoraria for lectures from Bristol-Myers Squibb–Pfizer, Boston Scientific, and MSD. Dr Giamouzis has received honoraria for lectures and/or advisory boards from AstraZeneca, Bayer, Boehringer Ingelheim, ELPEN Pharmaceuticals, Genesis Pharma, Menarini Hellas, Novartis, Pfizer, Roche, and Servier. Dr Cooper is research consultant for Abiomed. Dr Butler is a consultant to Abbott, Adrenomed, American Regent, Arca Biopharma, Amgen, Applied Therapeutic, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardiac Dimension, Cardior CVRx, Cytokinetics, Edwards Lifesciences, Element Science, Fast Biomedical, G3 Pharmaceutical, Innolife, Impulse Dynamics, Imbria, Inventiva, Lexicon, Lilly, LivaNova Janssen, Johnson & Johnson, Medtronic, Merck, Occlutech, Nestle, Novartis, Novo Nordisk, Pfizer, Pharmacosmos, Pharmain, Roche, Sanofi, Sequana, SQ Innovation, 3live, Velakor, and Vifor. Dr Giannakoulas has received honoraria for lectures and/or advisory boards from AstraZeneca, Boehringer Ingelheim, Novartis, Servier, Roche, Pfizer, ELPEN Pharmaceuticals, and Genesis Pharma. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Heart Failure (HF) significantly impacts approximately 26 million people worldwide, causing disruptions in the normal functioning of their hearts. The estimation of left ventricular ejection fraction (LVEF) plays a crucial role in the diagnosis, risk stratification, treatment selection, and monitoring of heart failure. However, achieving a definitive assessment is challenging, necessitating the use of echocardiography. Electrocardiogram (ECG) is a relatively simple, quick to obtain, provides continuous monitoring of patient's cardiac rhythm, and cost-effective procedure compared to echocardiography. In this study, we compare several regression models (support vector machine (SVM), extreme gradient boosting (XGBOOST), gaussian process regression (GPR) and decision tree) for the estimation of LVEF for three groups of HF patients at hourly intervals using 24-hour ECG recordings. Data from 303 HF patients with preserved, mid-range, or reduced LVEF were obtained from a multicentre cohort (American and Greek). ECG extracted features were used to train the different regression models in one-hour intervals. To enhance the best possible LVEF level estimations, hyperparameters tuning in nested loop approach was implemented (the outer loop divides the data into training and testing sets, while the inner loop further divides the training set into smaller sets for cross-validation). LVEF levels were best estimated using rational quadratic GPR and fine decision tree regression models with an average root mean square error (RMSE) of 3.83% and 3.42%, and correlation coefficients of 0.92 (p<0.01) and 0.91 (p<0.01), respectively. Furthermore, according to the experimental findings, the time periods of midnight-1 am, 8-9 am, and 10-11 pm demonstrated to be the lowest RMSE values between the actual and predicted LVEF levels. The findings could potentially lead to the development of an automated screening system for patients with coronary artery disease (CAD) by using the best measurement timings during their circadian cycles., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Al Younis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Purpose: Cardiovascular disease is commonly accompanied by renal dysfunction. Multimorbidity in hospitalized patients impacts unfavorably on prognosis and hospital stay. We aimed to illustrate the contemporary burden of cardiorenal morbidity across inpatient cardiology care in Greece., Methods: The Hellenic Cardiorenal Morbidity Snapshot (HECMOS) used an electronic platform to collect demographic and clinically relevant information about all patients hospitalized on March 3, 2022, in Greece. The participating institutions covered all levels of inpatient cardiology care and most of the country's territories to collect a real-world, nation representative sample., Results: A total of 923 patients (men 68.4%, median age 73 ± 14.8 years) were admitted to 55 different cardiology departments. 57.7% of the participants were aged >70 years. Hypertension was highly prevalent and present in 66% of the cases. History of chronic HF, diabetes mellitus, atrial fibrillation, and chronic kidney disease was present in 38%, 31.8%, 30%, and 26%, respectively. Furthermore, 64.1% of the sample exhibited at least one of these 4 entities. Accordingly, a combination of ≥2 of these morbid conditions was recorded in 38.7%, of ≥3 in 18.2%, whereas 4.3% of the sample combined all 4 in their medical history. The most common combination was the coexistence of heart failure-atrial fibrillation accounting for 20.6% of the sample. Nine of 10 nonelectively admitted patients were hospitalized due to acute HF (39.9%), acute coronary syndrome (33.5%), or tachyarrhythmias (13.2%)., Conclusion: HECMOS participants carried a remarkable burden of cardio-reno-metabolic disease. HF in conjunction with atrial fibrillation was found to be the most prevalent combination among the studied cardiorenal nexus of morbidities in the whole study population., (Copyright © 2023 Hellenic Society of Cardiology. Published by Elsevier B.V. All rights reserved.)

Objective: To provide a systematic review, critical appraisal, assessment of performance and generalisability of all the reported prognostic models for heart failure (HF) in patients with type 2 diabetes (T2D)., Methods: We performed a literature search in Medline, Embase, Central Register of Controlled Trials, Cochrane Database of Systematic Reviews and Scopus (from inception to July 2022) and grey literature to identify any study developing and/or validating models predicting HF applicable to patients with T2D. We extracted data on study characteristics, modelling methods and measures of performance, and we performed a random-effects meta-analysis to pool discrimination in models with multiple validation studies. We also performed a descriptive synthesis of calibration and we assessed the risk of bias and certainty of evidence (high, moderate, low)., Results: Fifty-five studies reporting on 58 models were identified: (1) models developed in patients with T2D for HF prediction (n=43), (2) models predicting HF developed in non-diabetic cohorts and externally validated in patients with T2D (n=3), and (3) models originally predicting a different outcome and externally validated for HF (n=12). RECODe (C-statistic=0.75 95% CI (0.72, 0.78), 95% prediction interval (PI) (0.68, 0.81); high certainty), TRS-HFDM (C-statistic=0.75 95% CI (0.69, 0.81), 95% PI (0.58, 0.87); low certainty) and WATCH-DM (C-statistic=0.70 95% CI (0.67, 0.73), 95% PI (0.63, 0.76); moderate certainty) showed the best performance. QDiabetes-HF demonstrated also good discrimination but was externally validated only once and not meta-analysed., Conclusions: Among the prognostic models identified, four models showed promising performance and, thus, could be implemented in current clinical practice., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Prolonged repolarization duration is a significant total mortality (TM) predictor in post-myocardial infarction patients., Aim: We examined the clinical significance of QT interval that was extracted from a Short Resting Holter ECG (SRH ECG - 30-min duration) as a TM predictor in heart failure (HF) patients., Methods: One hundred forty-five HF patients (male = 84%, mean age = 64 ± 12 years, mean LVEF = 33 ± 10%) underwent an SRH ECG recording for 30 min. These high-resolution ECG signals were analyzed and the QT interval was calculated and corrected according to the Fridericia formula. After 42.1 months, 26 patients died., Results: Univariate analysis for Deceased and Living groups: QTc:455 ± 33 ms vs 441 ± 32 ms (p = 0.04), LVEF:32 ± 10% vs 34 ± 9% (p < 0.5), Mean Heart Rate: 73 ± 11 bpm vs 69 ± 12 bpm (p = 0.2), SDNN/HRV: 45 ± 42 ms vs 41 ± 29 ms (p = 0.4), QRS: 123 ± 26 ms vs 119 ± 29 ms (p = 0.5). Multivariate Cox regression analysis with model adjusted for QTc, Mean Heart Rate, LVEF, QRS, revealed that QTc-Fridericia interval was an independent TM predictor (H.R.:1.017, 95% C.I.: 1.003-1.030, p = 0.01). The cut-off point of 490 ms (90th percentile) in the same model presented HR: 2.9 for TM (95%C.I.: 1.066-7.882, p = 0.03). Kaplan Meier curves depicted a clear difference in survival between the two patients' groups (QTc Group≥490 ms vs QTc Group <490 ms). The curve diverge was important (log-rank, p = 0.02)., Conclusion: A fast risk stratification approach with SRH ECG recording is an efficient method for flash evaluation of mortality risk in HF patients., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Valvular heart disease (VHD) in non-valvular atrial fibrillation (AF) is a puzzling clinical entity. The aim of this study was to evaluate the prognostic effect of significant VHD (sVHD) among patients with non-valvular AF., Methods: This is a post-hoc analysis of the MISOAC-AF trial (NCT02941978). Consecutive inpatients with non-valvular AF who underwent echocardiography were included. sVHD was defined as the presence of at least moderate aortic stenosis (AS) or aortic/mitral/tricuspid regurgitation (AR/MR/TR). Cox regression analyses with covariate adjustments were used for outcome prediction., Results: In total, 983 patients with non-valvular AF (median age 76 [14] years) were analyzed over a median follow-up period of 32 [20] months. sVHD was diagnosed in 575 (58.5%) AF patients. sVHD was associated with all-cause mortality (21.6%/yr vs. 6.5%/yr; adjusted HR [aHR] 1.55, 95% confidence interval [CI] 1.17-2.06; p = 0.02), cardiovascular mortality (16%/yr vs. 4%/yr; aHR 1.70, 95% CI 1.09-2.66; p = 0.02) and heart failure-hospitalization (5.8%/yr vs. 1.8%/yr; aHR 2.53, 95% CI 1.35-4.63; p = 0.02). The prognostic effect of sVHD was particularly evident in patients aged < 80 years and in those without history of heart failure (p for interaction < 0.05, in both subgroups). After multivariable adjustment, moderate/severe AS and TR were associated with mortality, while AS and MR with heart failure-hospitalization., Conclusion: Among patients with non-valvular AF, sVHD was highly prevalent and beared high prognostic value across a wide spectrum of clinical outcomes, especially in patients aged < 80 years or in the absence of heart failure. Predominantly AS, as well as MR and TR, were associated with worse prognosis., (© 2021. The Author(s).)

Diabetes mellitus (DM) is an established risk factor for atherosclerotic cardiovascular disease (CVD), and patients with DM are at a two to four-fold higher cardiovascular risk, including myocardial infraction, unstable angina, stroke, and heart failure. All of the above have arisen interest in CVD preventive strategies by the use of non-invasive methods, such as risk scores. The most common approach is to consider DM as a CVD equivalent and, therefore, to treat patients with DM in a similar way to those who required secondary CVD prevention. However, this approach has been disputed as all patients with DM do not have the same risk for CVD, and since other potentially important factors within the context of DM, such as DM duration, presence of albuminuria, and comorbidities, should be taken into consideration. Thus, the second and third approach is the application of risk models that were either developed initially for the general population or designed specifically for patients with DM, respectively. This review summarizes the evidence and implications for clinical practice regarding these scores. Up to date, several models that can be applied to the diabetic population have been proposed. However, only a few meet the minimum requirement of adequate external validation. In addition, moderate discrimination and poor calibration, which might lead to inaccurate risk estimations in populations with different characteristics, have been reported. Therefore, future research is needed before recommending a specific risk model for universal clinical practice in the management of diabetes., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background and Objectives: The proper use of oral anticoagulants is crucial in the management of non-valvular atrial fibrillation (AF) patients. Left atrial appendage closure (LAAC) may be considered for stroke prevention in patients with AF and contraindications for long-term anticoagulant treatment. We aimed to assess anticoagulation status and LAAC indications in patients with AF from the HECMOS (Hellenic Cardiorenal Morbidity Snapshot) survey. Materials and Methods: The HECMOS was a nationwide snapshot survey of cardiorenal morbidity in hospitalized cardiology patients. HECMOS used an electronic platform to collect demographic and clinically relevant information from all patients hospitalized on 3 March 2022 in 55 different cardiology departments. In this substudy, we included patients with known AF without mechanical prosthetic valves or moderate-to-severe mitral valve stenosis. Patients with prior stroke, previous major bleeding, poor adherence to anticoagulants, and end-stage renal disease were considered candidates for LAAC. Results: Two hundred fifty-six patients (mean age 76.6 ± 11.7, 148 males) were included in our analysis. Most of them (n = 159; 62%) suffered from persistent AF. The mean CHA2DS2-VASc score was 4.28 ± 1.7, while the mean HAS-BLED score was 1.47 ± 0.9. Three out of three patients with a a CHA2DS2-VASc score of 0 or 1 (female) were inappropriately anticoagulated. Sixteen out of eighteen patients with a CHA2DS2-VASc score 1 or 2 (if female) received anticoagulants. Thirty-one out of two hundred thirty-five patients with a CHA2DS2-VASc score > 1 or 2 (if female) were inappropriately not anticoagulated. Relative indications for LAAC were present in 68 patients with NVAF (63 had only one risk factor and 5 had two concurrent risk factors). In detail, 36 had a prior stroke, 17 patients had a history of major bleeding, 15 patients reported poor or no adherence to the anticoagulant therapy and 5 had an eGFR value < 15 mL/min/1.73 m2 for a total of 73 risk factors. Moreover, 33 had a HAS-BLED score ≥ 3. No LAAC treatment was recorded. Conclusions: Anticoagulation status was nearly optimal in a high-thromboembolic-risk population of cardiology patients who were mainly treated using NOACs. One out of four AF patients should be screened for LAAC. [ABSTRACT FROM AUTHOR]

Cardiac rehabilitation (CR) is a complex intervention that improves functional capacity and quality of life in patients with heart failure (HF). Besides exercise training (ET), CR includes aggressive risk factor management, education about medication adherence, stress management, and psychological support. Current guidelines strongly recommend CR as an integral part of chronic and stable HF patient care. However, CR programs are underused for multiple reasons, namely, low physician referral and patient adherence, high cost, and lack of awareness. In this review, we present existing evidence of the beneficial effects of ET and CR in HF with reduced and preserved ejection fraction, the underlying pathophysiologic mechanisms by which exercise might alleviate symptoms, and the different types of exercise that can be used in HF. Current guidelines supporting the use of CR, reasons for its underutilization, and home-based CR as an alternative or adjunct to traditional center-based programs are also described. [ABSTRACT FROM AUTHOR]