Introduction:The PRESERVE EF study proposed a two-step algorithm for risk stratification in post-myocardial infarction (MI) patients with mid-range and preserved left ventricular ejection fraction (LVEF). This method assessed the performance of a two-step, programmed ventricular stimulation (PVS)-inclusive approach in identifying high-risk post-MI patients with LVEF ≥40%. This report presents findings from the 8-year follow-up. Methods:The primary endpoint was the occurrence of a major arrhythmic event, defined as sustained ventricular tachycardia/fibrillation, appropriate implantable cardioverter-defibrillator (ICD) activation, or sudden cardiac death (SCD). We included a total of 575 consecutive patients (mean age 57 years, LVEF 50.8%). Of them, 204 (35.5%) had at least one positive non-invasive risk factor. Forty-one of 152 patients undergoing PVS were inducible; 37 (90.2%) of them received an ICD. Results:During a mean follow-up of 106 ± 14.5 months, no SCDs were observed, while 12 ICDs (the major arrhythmic event prevalence in patients with ICD implantation reaching 29.3%) were appropriately activated. The updated performance metrics of the proposed approach were as follows: sensitivity 100% (95% CI: 73.5%-100%), specificity 94.8% (95% CI: 92.5-96.5%), positive predictive value 29.3% (95% CI: 17.2-45.0%), and negative predictive value 100% (95% CI: 99.3%-100%). Notably, events occurred only in patients with an LVEF 40%-50% and a history of ST-Elevation Myocardial Infarction. Conclusion:The PRESERVE EF study demonstrates that a simple, two-step, non-invasive risk factor-guided approach, followed by programmed ventricular stimulation, can effectively identify a subgroup of post-MI patients with preserved or mid-range LVEF ≥40 who are at high risk for major arrhythmic events. Clinical Trial Registration:Clinicaltrials.gov, identifier NCT02124018.

Currently efforts are being undertaken to establish and bring into clinical practice the field of virtual cardiac electrophysiology. The basic premise lies in acquiring an accurate whole-heart model based both on anatomy and electrophysiological properties of every myocardial voxel. Subsequently, one option is to perform a virtual electrophysiology study, with no constraints regarding site and number of extrasystoles in order to assess arrhythmogenic potential of the ventricle (ventricular arrhythmia risk prediction). The alternative, in cases with documented ventricular arrhythmia, would be to fine-tune the model into being able to simulate the clinical arrhythmia and then assess its mechanism, establishing vulnerable sites and thus ablation targets in order to guide the subsequent interventional procedure (virtual arrhythmia ablation targeting). Once clinical evidence supports vEP value in terms of accuracy and safety, it could be expected that even induced, nonclinical, arrhythmias could be targeted. Finally, advances in the field of computational power and artificial intelligence, including radiomics, along with stereotactic arrhythmia radioablation could render the future of arrhythmia management and treatment virtually unrecognizable in the not-so-distant future. The present mini review will attempt to familiarize clinicians with the tenets and current state of vEP, especially in the current phase where larger prospective clinical studies are required for further advancement, as well as offer a glimpse at potential future directions of this approach.

Cardiac resynchronization therapy (CRT) represents a cornerstone in the management of patients with heart failure and electrical dyssynchrony, improving symptoms, reducing hospitalizations, and prolonging survival. CRT can be delivered via a pacemaker (CRT-P) or an ICD (CRT-D). Despite its widespread use, the mortality benefit of CRT-D over CRT-P remains uncertain, as no head-to-head randomized trials have been designed to directly compare the two modalities, making device selection a frequent clinical dilemma. In practice, CRT-D accounts for 70–80% of CRT implantations in developed countries, yet solid evidence demonstrating its superiority over CRT-P is lacking. Specific patient groups, including those with non-ischemic cardiomyopathy, advanced age, multiple comorbidities, or limited life expectancy, may derive limited incremental benefit from CRT-D, which should be balanced against device costs and specific risks such as lead failure and inappropriate shocks. The present review aims to provide a comprehensive comparison between CRT-D and CRT-P, focusing on the existing body of evidence, criteria for patient selection, comparative clinical outcomes, and risk–benefit considerations for clinical decision-making.

Improving clinical prediction of sudden cardiac death is a crucial step in the management of patients with hypertrophic cardiomyopathy. However, finding the optimal method for risk evaluation has been challenging, given the complexity and the wide variation in clinical phenotypes. This is particularly important, as these patients are often of younger age and defibrillator implantation is associated with a low but tangible long-term risk of adverse events. A number of risk factors, including degree of hypertrophy, presence of syncope and family history of sudden cardiac death, have typically been considered to indicate a higher risk. The European risk score for prediction of sudden cardiac death is widely used; however, it may not apply well in patients with specific forms of the condition, such as those with extreme hypertrophy. Increasing evidence suggests that the presence and extent of myocardial fibrosis assessed with cardiac magnetic resonance imaging should be considered in clinical decision-making. Some research suggests that integrating electrophysiological studies into traditional risk assessment models may further optimize risk prediction and significantly improve accuracy in detecting high risk patients. Novel cardiac imaging techniques, better understanding of the genetic substrate and artificial intelligence-based algorithms may prove promising for risk refinement. The present review article provides an updated and in-depth viewpoint.

Purpose: Syncope remains a common medical problem. Recently, the role of dedicated syncope units and implantable loop recorders has emerged in the investigation of unexplained syncope. This study aims to investigate the possibilities for a more rational and targeted use of various diagnostic tools. Methods: In this retrospective single-center study, 196 patients with unexplained syncope were included between March 2019 and February 2023. Various diagnostic tools were utilized during the investigation, according to clinical judgement. Patients were retrospectively allocated into Group A (including those who, among other tests, underwent loop recorder insertion) and Group B (including patients investigated without loop recorder implantation). Data were compared with Group C, including patients assessed prior to syncope unit establishment. Results: There was no difference between Group A (n = 133) and Group B (n = 63) in the diagnostic yield (74% vs. 76%, p = 0.22). There were significant differences between Groups A and B regarding age (67.3 ± 16.9 years vs. 48.3 ± 19.1 years, p < 0.001) and cause of syncope (cardiogenic in 69% of Group A, reflex syncope in 77% of Group B, p < 0.001). Electrocardiography-based diagnosis occurred in 55% and 19% of Groups A and B, respectively (p < 0.001). The time to diagnosis was 4.2 ± 2.7 months in Group A and 7.5 ± 5.6 months in Group B (p < 0.001). In Group C, the diagnostic yield was 57.9% and the electrocardiography-based diagnostic yield was 18.3%. Conclusions: A selective use of loop recorders according to clinical and electrocardiographic characteristics increases the effectiveness of the structured syncope unit approach and further preserves financial resources.

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/m2 [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.

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.

Introduction and Objectives: In patients with Post-Acute Sequelae of Coronavirus 2 infection (PASC), a post infectious autonomic dysfunction may be one of the underlying mechanisms. Patients often present with exercise intolerance and exaggerated heart rate response to exercise. We report a single centre experience of patients with PACS and suspected autonomic dysfunction. Methods: Forty-two patients evaluated in the Outpatient Cardiology Department with suspected PASC were included in the study. Patients complained of compromised exercise performance persisting >3 months after recovery from COVID-19 infection, compared to the pre-COVID-19 period. The patients were evaluated with 12-lead electrocardiogram, echocardiography, 24-hour ECG ambulatory monitoring and either exercise stress test or a 6-minute walk test. Results: All 42 patients demonstrated an exaggerated chronotropic response, defined as the inappropriate increase in heart rate before the 6th minute of exercise >100% of the age-predicted maximal heart rate value with reproduction of clinical symptoms. In addition, 24-hour ambulatory electrocardiography revealed an increased mean heart rate of 92 beats/minute and decreased mean standard deviation of sequential 5-minute N-N interval (SDNN) of 74.4 ms. Pharmaceutical treatment with b-blockers, ivabradine or both was administrated in 29 (69%) resulting in symptomatic improvement in 82.8% of those under treatment. However, residual symptoms persisted in 69% of patients after 3 months. Conclusions: In patients with “Post-acute COVID-19” syndrome, we found an excessive chronotropic response to exercise suggesting autonomic dysfunction as the underlying mechanism of symptoms. Treatment with beta blockers or ivabradine resulted in clinical improvement but a substantial proportion of patients remained symptomatic.

Arrhythmic sudden cardiac death (SCD) has an annual prevalence of 1 per 1000 while 75% of the victims suffer from ischemic and 10% from non-ischemic or hypertrophic cardiomyopathy. Altogether, these three entities account for more than 80% of the total SCD victims. Guidelines for implantable cardiac defibrillators are still dominated by LVEF<30% from the MADIT II study. In terms of arrhythmic risk stratification, the PRESERVE-EF study restored in clinical practice the two-step arrhythmic risk stratification approach based on Electrocardiographic non-invasive risk factors (NIRFs) guiding to electrophysiological study. In our times with the multiple cardiac imaging methods and artificial intelligence applications availability, this two-step approach based on integrated arrhythmia mechanisms detection, emerges as an efficient SCD risk stratification paradigm for these three entities but also for the patients with congenital heart disease.

Objective: The objective of this study was to provide data on implantable loop recorder (ILR)-based atrial fibrillation (AF) rates, recurrent stroke rates, and predictors of AF in patients with cryptogenic stroke (CS) after 1, 6, 12, 24, and 36 months of follow-up. Methods: We searched MEDLINE/PubMed, Cochrane Central Register of Controlled Trials, EMBASE, Web of Science, and reference lists of retrieved reports, which were published by April 30, 2023, which was the date of our last search. We utilized random-effects meta-analysis for detection rates, and meta-regression analysis, t-test (for normally distributed variables), and Mann-Whitney (for skewed variables) for predictor factors. Results: Thirteen studies were analyzed, which included data from 3,377 patients with CS or embolic stroke of undetermined source. The ILR-based AF rates in patients with CS were 4.73% (95% confidence interval [CI] 3.91–5.71) at 1 month, 13.45% (95% CI 12.19–14.81) at 6 months, 17.5% (95% CI 16.25–18.82) at 12 months, 20.69% (95% CI 19–22.49) at 24 months, and 25.98% (95% CI 23.21–28.58) at 36 months. Age and CHA2DS2-VASc score were positively associated with AF detection. Specifically, the mean difference of age and CHA2DS2-VASc score in the group with AF versus the group without AF was 7.47 (95% CI 4.58–10.36, P < 0.001) and 0.75 (95% CI 0.22–1.28, P = 0.01), respectively. Finally, AF detection was positively associated with recurrent strokes with an estimated risk ratio of 1.27 (95% CI 0.69–2.31). Conclusions: There is a correlation between AF detection rate and ILR monitoring duration. One out of eight patients was diagnosed with AF after 6 months of follow-up and about one quarter after 3 years. Our results demonstrate the critical use of ILRs, especially in older patients, and in patients with high CHA2DS2-VASc scores.

BACKGROUND:The aim of this study was to develop a structured 2-step approach, based on noninvasive diagnostic criteria, that led to an electrophysiology study in patients with unexplained syncope. METHODS AND RESULTS:Two independent cohorts were used: the derivation cohort with 665 patients based on electronic health record data to develop our 2-step diagnostic approach, and the validation cohort based on 160 prospectively screened patients, presenting with unexplained syncope episodes. Noninvasive electrocardiographic and imaging markers and an electrophysiology study-based invasive assessment were combined. A positive diagnostic approach according to our study's prespecified criteria resulted in a decision to proceed with a permanent pacemaker/implantable cardioverter-defibrillator. The primary end point was the time until the event of recurrent syncope (syncope-free survival). Number needed to treat was calculated for patients with a positive diagnostic approach. The number of patients with unexplained syncope and borderline sinus bradycardia needed to treat was 5, and the number of patients with unexplained syncope and bundle branch block needed to treat was 3 over a mean follow-up of ≈4 years. After the structured 2-step approach, the primary outcome occurred in 14 of 82 (17.1%) with a pacemaker/implantable cardioverter-defibrillator and 19 of 57 (33%) with a negative approach, with a mean follow-up of ≈2.5 years (29.29±12.58 months, P=0.03). CONCLUSIONS:The low number needed to treat in the derivation cohort and the low percentage of syncope recurrence in the validation cohort supports the proposed 2-step electrophysiology-inclusive algorithm as a potentially low-cost, 1-day, structured tool for these patients.

AbstractBackgroundRisk stratification for sudden cardiac death in post‐myocardial infarction (post‐MI) patients remains a challenging task. Several electrocardiographic noninvasive risk factors (NIRFs) have been associated with adverse outcomes and were used to refine risk assessment. This study aimed to evaluate the performance of NIRFs extracted from 45‐min short resting Holter ECG recordings (SHR), in predicting ventricular tachycardia inducibility with programmed ventricular stimulation (PVS) in post‐MI patients with preserved left ventricular ejection fraction (LVEF).MethodsWe studied 99 post‐MI ischemia‐free patients (mean age: 60.5 ± 9.5 years, 86.9% men) with LVEF ≥40%, at least 40 days after revascularization. All the patients underwent PVS and a high‐resolution SHR. The following parameters were evaluated: mean heart rate, ventricular arrhythmias (premature ventricular complexes, couplets, tachycardias), QTc duration, heart rate variability (HRV), deceleration capacity, heart rate turbulence, late potentials, and T‐wave alternans.ResultsPVS was positive in 24 patients (24.2%). HRV, assessed by the standard deviation of normal‐to‐normal R–R intervals (SDNN), was significantly decreased in the positive PVS group (42 ms vs. 51 ms, p = .039). SDNN values <50 ms were also associated with PVS inducibility (OR 3.081, p = .032 in univariate analysis, and 4.588, p = .013 in multivariate analysis). No significant differences were identified for the other NIRFs. The presence of diabetes, history of ST‐elevation MI (STEMI) and LVEF <50% were also important predictors of positive PVS.ConclusionsHRV assessed from SHR, combined with other noninvasive clinical and echocardiographic variables (diabetes, STEMI history, LVEF), can provide an initial, practical, and rapid screening tool for arrhythmic risk assessment in post‐MI patients with preserved LVEF.

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.

Syncope in patients with bundle branch block (BBB) is often due to advanced atrioventricular (AV) block. The objective of the present "real-world" study was to evaluate the optimal management in patients with unexplained syncope and BBB and to identify factors that predict the recurrence of syncope. This is a single-center observational prospective registry of 131 consecutive patients undergoing invasive electrophysiology study (EPS) for recurrent unexplained presyncope or syncope attacks and BBB. When the EPS-derived diagnosis was reached, a decision to proceed with a permanent pacemaker was offered to the patient. An implantable loop recorder was inserted in the rest of the population. A total of 131 consecutive patients with unexplained syncope and BBB (67.2% male; age 63.7 ± 16.5 years) underwent EPS during the study period. The distribution of conduction disturbance patterns was as follows: isolated left bundle branch block (LBBB): 23.7%; LBBB with first AV block: 8.4%; isolated right bundle branch block (RBBB): 10.7%; RBBB with first AV block: 8.4%; isolated left anterior/posterior fascicular block: 13%; left anterior/posterior fascicular block with first AV block: 5.3%; isolated bifascicular block: 16.8%; and bifascicular block with first AV block: 13.7%. In the multivariate analysis, the only predictors of recurrent syncope were bifascicular block (hazard ratio (HR): 4.16, 95% confidence interval (CI): 1.29, 13.41, P: 0.017) and HV interval ≥ 60 msec (HR: 3.58, 95% CI: 1.12, 11.46, P: 0.032). An EPS-based strategy identifies a subset of patients who will benefit from permanent pacing. HV interval ≥ 60 msec and the presence of a bifascicular block were strongly related to syncope recurrence.

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.

Risk stratification for sudden cardiac death in dilated cardiomyopathy is a field of constant debate, and the currently proposed criteria have been widely questioned due to their low positive and negative predictive value. In this study, we conducted a systematic review of the literature utilizing the PubMed and Cochrane library platforms, in order to gain insight about dilated cardiomyopathy and its arrhythmic risk stratification utilizing noninvasive risk markers derived mainly from 24 h electrocardiographic monitoring. The obtained articles were reviewed in order to register the various electrocardiographic noninvasive risk factors used, their prevalence, and their prognostic significance in dilated cardiomyopathy. Premature ventricular complexes, nonsustained ventricular tachycardia, late potentials on Signal averaged electrocardiography, T wave alternans, heart rate variability and deceleration capacity of the heart rate, all have both some positive and negative predictive value to identify patients in higher likelihood for ventricular arrhythmias and sudden cardiac death. Corrected QT, QT dispersion, and turbulence slope–turbulence onset of heart rate have yet to establish a predictive correlation in the literature. Although ambulatory electrocardiographic monitoring is frequently used in clinical practice in DCM patients, no single risk marker can be used for the selection of patients at high-risk for malignant ventricular arrhythmic events and sudden cardiac death who could benefit from the implantation of a defibrillator. More studies are needed in order to establish a risk score or a combination of risk factors with the purpose of selecting high-risk patients for ICD implantation in the context of primary prevention.

Testing for myocardial ischemia in patients presenting with sustained monomorphic Ventricular Tachycardia(VT) even without evidence of acute myocardial infarction is a tempting strategy that is frequently utilized in clinical practice. Monomorphic VT is mainly caused by re-entry around chronic myocardial scar and active ischemia has no role in its pathogenesis, thus making testing for ischemia futile, at least in theory. This systematic literature review sought to address the usefulness of ischemia testing (mainly coronary angiography) in patients presenting with monomorphic VT through 8 selected studies after evaluating a total of 130 published manuscripts. Particularly, we sought to unveil whether coronary angiography and possibly concomitant revascularization leads to lesser tachycardia recurrence. Our conclusion can be summarized as follows: this approach whether combined with revascularization or not, does not seem to reduce VT recurrence nor does it affect mortality in such patients. Even though most of the published literature points at this direction, validation from randomized controlled trials is imperative.