Clinical implementation of 3D deep learning techniques in predicting touch-up lesions for atrial fibrillation patients undergoing cryoablation.

Electrocardiogram (ECG) classification is essential for accurately detecting and tracking heart rhythm disorders. This study proposes a multi-class ECG classification framework for identifying cardiac arrhythmias like Atrial Fibrillation (AF), Ventricular Fibrillation (VF), Normal Rhythm (NR), and Ventricular Tachycardia (VT). The ECG signals were decomposed using Variational Mode Decomposition (VMD), and higher-order statistics as well as entropy-based features were extracted from each mode. Multi-task Particle Swarm Optimization (MT-PSO) was employed to reduce redundant features and enhance the discriminative capability of the dataset. Multiple machine-learning models were evaluated, and optimized feature set led to clear performance improvements. The best results were obtained using LightGBM (ACC 0.993), HistGradientBoost (0.991), XGBoost (0.990), and ExtraTrees (0.990). Execution time also decreased for several models after optimization. Confusion-matrix and ROC analyses confirmed reliable detection across all four cardiac classes, and comparison with reported works shows that the proposed framework offers competitive or improved performance for ECG classification.

Atrial fibrillation and sudden cardiac death, a nested case-control study looking at cardiac pathology.

ABSTRACTVentricular arrhythmias (VAs) as life‐threatening heart rhythm disorders, reduced connexin43 (Cx43) is one of the mechanisms of VAs. Cx43 is the predominant ventricular gap junction protein essential for cardiac electrical conduction; the absence in the mouse heart results in sudden arrhythmic death. However, the mechanism linking Cx43 downregulation and VA formation remains unclear. Here it is aimed to elucidate the molecular mechanism by which Cx43 deficiency leads to VAs using Cx43 knockout (Cx43‐KO) induced pluripotent stem‐derived cardiomyocytes and cardiac‐specific conditional Cx43‐KO (Cx43‐cKO) mice. It is shown that Cx43‐KO induced arrhythmic phenotype and decreased proline content both in vitro and in vivo. Mechanistically, Cx43 interacts with the amino acid transporter SNAT2 (sodium‐dependent neutral amino acid transporter). Cx43 deficiency reduces SNAT2 expression, impairing proline transport and metabolism. This disruption leads to mitochondrial dysfunction, oxidative stress, abnormal calcium handling, and arrhythmias. Exogenous proline supplementation rescued the arrhythmic phenotype in Cx43‐cKO mice by restoring metabolic balance. In conclusion, it is suggested that Cx43 deficiency leads to VAs through SNAT2‐mediated proline metabolic reprogramming. Targeting proline metabolism may therefore offer novel therapeutic strategies for VAs.

Cardiomyopathies, heart rhythm and conduction disorders as phenotypic manifestation of genetic variants in large cohort of cardiac patients: results of whole-genome study.

Atrial fibrillation and flutter are heart rhythm disorders frequently associated with multiple other chronic conditions, complicating their management and requiring optimized care. Analyzing pre-atrial fibrillation and flutter comorbidity patterns could enable proactive, preventive, and personalized healthcare. This population-based nested case-control study analyzed data from the Korean National Health Insurance Corporation (2002-2019). Adults aged ≥19 years with at least three years of recorded claims were included. Cases were individuals newly diagnosed with atrial fibrillation and flutter between 2007 and 2019 following a washout period (2002-2006). Controls were matched 1:4 using stratified random sampling. Using 5-year disease histories, BEHRT, a transformer-based model, predicted atrial fibrillation and flutter, while BERTopic identified sex-specific multimorbidity patterns. Predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC). BEHRT achieved an AUC of 0.80 for predicting atrial fibrillation and flutter among 600,030 participants (8,661 cases and 591,369 controls). BERTopic analysis revealed sex-specific multimorbidity patterns: aortic aneurysm, hypertensive heart disease, and chronic obstructive pulmonary disease were common in males, while Alzheimer's disease, Parkinson's disease, and rheumatic heart disease were prominent in females. The combination of BEHRT and BERTopic demonstrated the ability to predict atrial fibrillation and flutter based on multimorbid histories while identifying distinct sex-specific disease patterns. These findings underscore the potential for artificial intelligence to enhance personalized healthcare and optimize prevention and management strategies for chronic conditions.

Heart-rhythm disorders and related congenital anomalies in children often remain silent until physical activitybrings on symptoms. We report an 11-year-old girl who experienced her first signs of heart disease only after exertion. Although late detection of such anomalies can sometimes be fatal, careful clinical examination may reveal these conditions early.

Effectiveness and Safety of Apixaban Initiation Following Newly-Diagnosed Atrial Fibrillation in Patients With Kidney Failure on Hemodialysis.

Heart rhythm disorders in children are characterized by disturbances in impulse generation or conduction, which may lead to both benign and life-threatening conditions. Aim - to summarize current approaches to the early diagnosis and management of children with life-threatening arrhythmias (LTA), taking into account international recommendations and personal clinical experience, which should contribute to improving the quality of medical care in Ukraine. The most common arrhythmia in childhood is tachycardia. LTA often manifest without previously diagnosed heart disease and require immediate diagnosis and risk stratification. The true incidence of ventricular arrhythmias in children remains unknown, and clinical manifestations vary significantly depending on age and type of arrhythmia. Timely detection of LTA is crucial to prevent the development of left ventricular dilation and dysfunction, which can be reversible with appropriate therapy. Given the wide range of clinical scenarios — from incidental findings during routine examinations to syncopal events with high risk — there is a need to standardize approaches to the diagnosis and management of ventricular tachyarrhythmias in the pediatric population. Based on the European Society of Cardiology (2022) recommendations, approved by the Association for European Paediatric and Congenital Cardiology, a national Clinical Guideline «Life-Threatening Arrhythmias in Children» and the corresponding Standard of Medical Care were developed and approved by the Ministry of Health of Ukraine in 2025 (Order of the Ministry of Health of Ukraine No. 1235 dated August 6, 2025). Conclusions. Early diagnosis and risk stratification of Life-threatening arrhythmias (LTA) in children are key points for preventing the development of severe complications. The implementation of the national Standard and Clinical Guidelines (Order of the Ministry of Health No. 1235 of 06.08.2025) generalizes treatment approaches and significantly improves the quality of medical care for children with complex rhythm disorders. The authors declare that there is no conflict of interest.

Atrial fibrillation (AF) is the most common type of heart rhythm disorder worldwide. Early recognition of brief episodes of atrial fibrillation can provide important diagnostic information and lead to prompt treatment. AF is mainly characterized by an irregular heartbeat. Today, many personal devices such as smartphones, smartwatches, smart rings, or small wearable medical devices can detect heart rhythm. Sensors can acquire different types of heart-related signals and extract the sequence of inter-beat intervals, i.e., the instantaneous heart rate. Various algorithms, some of which are very complex and require significant computational resources, are used to recognize AF based on inter-beat intervals (RR). This study aims to verify the possibility of using neural networks algorithms directly on a microcontroller connected to sensors for AF detection. Sequences of 25, 50, and 100 RR were extracted from a public database of electrocardiographic signals with annotated episodes of atrial fibrillation. A custom 1D convolutional neural network (1D-CNN) was designed and then validated via a 5-fold subject-wise split cross-validation scheme. In each fold, the model was tested on a set of 3 randomly selected subjects, which had not previously been used for training, to ensure a subject-independent evaluation of model performance. Across all folds, all models achieved high and stable performance, with test accuracies of 0.963 ± 0.031, 0.976 ± 0.022, and 0.980 ± 0.023, respectively, for models using 25 RR, 50 RR, and 100 RR sequences. Precision, recall, F1-score, and AUC-ROC exhibited similarly high performance, confirming robust generalization across unseen subjects. Performance systematically improved with longer RR windows, indicating that richer temporal context enhances discrimination of AF rhythm irregularities. A complete Edge AI prototype integrating a low-power ECG analog front-end, an ARM Cortex M7 microcontroller and an IoT transmitting module was utilized for realistic tests. Inferencing time, peak RAM usage, flash usage and current absorption were measured. The results obtained show the possibility of using neural network algorithms directly on microcontrollers for real-time AF recognition with very low power consumption. The prototype is also capable of sending the suspicious ECG trace to the cloud for final validation by a physician. The proposed methodology can be used for personal screening not only with ECG signals but with any other signal that reproduces the sequence of heartbeats (e.g., photoplethysmographic, pulse oximetric, pressure, accelerometric, etc.).

Transthyretin (ATTR) amyloidosis is a progressive disease that can present as isolated cardiac involvement or as a combination with systemic manifestations, including polyneuropathy, gastrointestinal tract disorders, and ophthalmopathy. The disease is associated with the deposition of unstable breakdown products of transthyretin tetramers, a plasma protein responsible for transporting thyroxine and retinol. ATTR is most commonly hereditary (ATTRm/ATTRv), caused by mutations in the transthyretin gene, but it can also occur in an acquired, non-hereditary “wild-type” form (ATTRwt), which develops in older adults. Cardiac involvement in ATTR amyloidosis resembles hypertrophic or restrictive cardiomyopathy, manifesting as symptoms of heart failure, rhythm disorders, and conduction abnormalities. Diagnosis is challenging due to the rarity of the disease, nonspecific symptoms, and the difficulties of performing endomyocardial biopsy. The verification of the diagnosis increasingly relies on modern imaging methods such as gadolinium-enhanced magnetic resonance imaging and technetium-99m pyrophosphate myocardial scintigraphy. The presented clinical case describes a 56-year-old patient with amyloid cardiomyopathy, which manifested as a combination of progressive rhythm and conduction disturbances (atrial fibrillation, trifascicular block, pauses up to 4,7 seconds, and runs of ventricular tachycardia) against the background of gradually decreasing left ventricular ejection fraction and marked diastolic dysfunction. These clinical syndromes necessitated the exclusion of secondary causes of myocardial involvement. The diagnosis was confirmed without biopsy – through the use of modern imaging techniques, including contrast-enhanced cardiac MRI and 99mTc-pyrophosphate scintigraphy, in accordance with current recommendations. This case illustrates the possibility of early detection and successful treatment of ATTRwt amyloidosis using advanced diagnostic methods in real-world clinical practice. These methods help refine the disease’s prevalence, improve diagnostic accuracy, and ensure timely treatment, significantly influencing the prognosis and quality of life.

Abstract Background Atrial fibrillation (AF) is the most common heart rhythm disorder and sudden cardiac death (SCD) is a major public health concern. Growing evidence indicates an association between AF and SCD[1-2], yet research into the relationship has been challenged by shared risk factors between AF and ischaemic heart disease, diabetes, and heart failure - prevalent conditions also commonly associated with SCD. Purpose We aimed to investigate our hypothesis that AF remains associated with a higher risk of SCD in young individuals, independent of ischaemic heart disease, diabetes, and heart failure. Methods This study was performed as a Danish, register-based, nationwide, matched cohort study using the Sudden Cardiac Death in the Young Register from 1st January 2000 to 31st December 2019 in individuals aged 0-35 years. Follow-up began at the latest of 1st January 2000, date of immigration, or date of birth. Exposure was defined as presence of an AF diagnosis. Outcomes of interest were SCD and all-cause mortality without SCD (ACM). Follow-up ended at the first date of SCD, ACM, emigration, 35th birthday, or 31st December 2019. Multivariable cause-specific cox regression models were employed with age as a time scale, adjusted for sex, ischaemic heart disease, diabetes, heart failure, and cancer, with results presented as hazard ratios (HR) of SCD and competing risk of ACM. Then, a 1:4 matching of exposed AF patients with unexposed non-AF patients upon sex, birth-year in 2-year intervals, entry time, ischaemic heart disease, diabetes, heart failure, dilated cardiomyopathy, and hypertrophic cardiomyopathy - was performed. Results are presented as cumulative incidences from time of AF diagnosis/matching and HR of SCD and competing risk of ACM. Results The study included 4.42 million individuals, of which 4,346 had AF. Average ages were 14 years (51% male) in non-AF patients versus 29 years (68% male) in AF patients. Compared with non-AF patients, AF patients had a significantly higher HR of SCD: 16.32 (CI: 9.61-27.70) and ACM: 7.45 (5.95-9.32) respectively. After adjustments, AF patients retained higher HR of SCD (4.76 (CI: 2.53-8.96) and ACM (5.01 (CI: 3.95-6.36). Post matching of 3414 AF patients to 13,656 non-AF patients, cumulative incidences of SCD and ACM remained higher in AF patients with HR of SCD of 7.93 (CI 2.39-26.32) and ACM of 6.02 (CI 3.97-9.11). Conclusion(s) This study suggests that AF remains a risk factor for SCD and ACM in the young population, even after adjusting for ischaemic heart disease, diabetes, and heart failure. This association persisted in the matched cohort, further matched upon dilated and hypertrophic cardiomyopathy. Future studies should explore which features define AF patients at highest risk of SCD, examining potential underlying mechanisms. This could help determine whether AF could warrant inclusion in SCD risk assessment for implantable cardioverter defibrillator implantation in young individuals.Multivariable Cox Models

Abstract Introduction Atrial fibrillation (AF) is the most common heart rhythm disorder. It can lead to serious adverse outcomes such as thromboembolism and heart failure resulting to increased mortality. The use of omics such as proteomics and epigenomics may enable discovery of novel targets related to AF pathogenesis and help uncover the molecular pathways involved. Purpose To compare the expression of total proteome and miRNAs in atrial tissue samples from patients with AF and subjects with sinus rhythm (SR) and determine potential interactions connected to AF. Methods Right atrial appendages (RAA) were collected from patients undergoing open-heart surgery (study START). Twenty-eight tissue samples were included in proteomic analysis with AF (n=17) and SR (n= 11), and 27 samples were included in epigenomic analysis, AF (n=9) and SR (n= 18). RNA and proteins were extracted using a phenol-based method. Proteomic analysis was done with an LC-MS/MS system by a label- free- based quantitative approach (LFQ). MiRNAs were analyzed using the untargeted TaqMan OpenArray Human Advanced miRNA panel. Proteomic and epigenomic data were analyzed using bioinformatics tools. Results In AF compared to SR, 132 proteins were found to be overexpressed, while 80 proteins were underexpressed. From epigenetic analysis 10 miRNAs were found to be upregulated and 5 downregulated in AF compared to SR. Among them, 10 miRNAs were predicted to interact with 48 differentially expressed proteins identified in the proteomic analysis. A notable interaction was identified between ENC1 and miR-224-5p. ENC1 was underexpressed (abundance ratio AF/SR = 0.01, p = 0.021), while hsa-miR-224-5p was upregulated (RQ = 2.099, p = 0.024). miR-224-5p is involved in various biological processes, including the regulation of cell proliferation, migration, and apoptosis. ENC1is a member of the kelch-related family of actin-binding proteins and plays a role in the oxidative stress response. Conclusions A previously unreported potential interaction between ENC1 and miR-224-5p has been identified. Both miR-224-5p and ENC1 contribute to maintaining cellular homeostasis. Disruptions in these processes could lead to altered expression levels of miR-224-5p and ENC1, potentially affecting cellular function and stress response mechanisms. Further investigation is necessary to validate these miRNA-protein interactions and appreciate their potential contribution in AF pathogenesis.

Electrocardiogram (ECG) analysis is one of the most essential tools for identifying cardiac rhythm abnormalities and assessing cardiovascular health [1], [2]. Accurate interpretation of ECG signals is crucial for detecting disorders such as arrhythmias, atrial fibrillation, and other irregular heart activities that can lead to severe medical complications [3], [4]. However, traditional diagnostic methods heavily rely on manual inspection by clinicians, which is not only labor-intensive but also susceptible to subjective bias and diagnostic inconsistencies [5]. To address these limitations, this research presents an intelligent and automated ECG signal analysis framework utilizing Deep Recurrent Neural Networks (DRNNs) for reliable classification of heart rhythm disorders [6], [7]. The proposed approach leverages the temporal learning capabilities of recurrent architectures such as Long ShortTerm Memory (LSTM) and Gated Recurrent Unit (GRU) networks to model the complex time-dependent characteristics inherent in ECG sequences [8], [9]. By doing so, the system effectively captures both short-term and long-term dependencies in heartbeat patterns, enabling more precise identification of abnormal cardiac activity [10]. Prior to model training, several signal preprocessing techniques—including denoising, baseline drift removal, segmentation, and feature scaling—are applied to enhance signal quality and reduce artifacts caused by noise or motion interference [11], [12]. Subsequently, a feature extraction phase converts raw ECG data into time– frequency representations to enrich the model’s understanding of rhythm morphology and improve classification accuracy [13], [14]. The proposed model is trained and validated using publicly available benchmark datasets such as MIT-BIH Arrhythmia and PTB Diagnostic ECG Database [15], [16], ensuring generalizability across diverse cardiac conditions and patient profiles. Comprehensive performance evaluation reveals that the DRNN-based system significantly outperforms traditional machine learning algorithms—including Support Vector Machines (SVMs), Random Forests, and Decision Trees—achieving superior results in accuracy, sensitivity, and specificity [17], [18]. Moreover, the system demonstrates robust generalization on unseen ECG data, confirming its potential for real-world deployment in both clinical environments and wearable health monitoring devices [19], [20]. Overall, this study presents a data-driven, intelligent ECG analysis solution capable of real-time arrhythmia detection and continuous cardiac monitoring [21], [22]. The proposed framework not only enhances diagnostic precision but also supports physicians in clinical decision-making, ultimately contributing to faster, more reliable, and accessible cardiac healthcare systems. With further refinement, integration with IoT-based platforms and edge computing technologies could transform this framework into a cornerstone of next-generation AI-assisted cardiovascular care [23]–[25].

The six-minute walk test is an easy-to-perform, informative, and well-tolerated diagnostic method for patients with various diseases. It is most widely used for the assessment of pulmonary and cardiovascular diseases. It is used to assess physical performance and the effectiveness of treatment and medical rehabilitation (with serial assessments). Objective. To review the literature data on the role of the six-minute walk test in patients with various types of atrial fibrillation, including after surgical treatment of heart rhythm disorders. Materials and methods. The scientific papers available in the electronic databases PubMed, eLibrary, MedLine, Science Direct, and Research Gate were searched with search queries corresponding to the keywords of this article. Results. Currently, there are few studies on the use of the six-minute walk test in patients with atrial fibrillation. The studies generally evaluate the distance covered in 6 minutes and the heart rate before and after the test. This test is used in medical rehabilitation programs for patients after radiofrequency ablation of pulmonary veins. Conclusion. The relative safety of the six-minute walk test and reliability of the results, ease of use and good tolerability enable the use of the test in comorbid patients with a history of cardiovascular diseases. Further clinical studies are still relevant.

Background: Current rates of cardiovascular morbidity among professional athletes depend not only on the sport type, but also on gender, age, ethnicity, screening strategies, and level of physical activity, its frequency, duration and intensity. Biochemical, immunological, hormonal, and psychological parameters are used as overtraining markers; however, they are not accurate enough for prediction of overtraining. In this regard, leukocyte indices calculated from a routine hematology test seem promising. Aim: To screen for cardiovascular disorders in a group of professional athletes with standard cardiological assessment methods, to evaluate the prognostic significance of leukocyte indices in the diagnosis of endogenous inflammation and overtraining, and to compare the values of leukocyte indices with the competitive results of the athletes. Methods: This was an observational cross-sectional, single stage, uncontrolled study in a random subject sample. From September 2021 to August 2022, we examined 180 highly qualified professional athletes on an outpatient basis. The athletes were practicing highly dynamic sport types (contact sport types such as combat sports, ice hockey, and football were excluded). All athletes had a routine hematology test (blood samples were taken 2 to 3 days before competitions) followed by calculation of hematological leukocyte indices: systemic inflammation response index (SIRI), systemic inflammation index (SII), aggregate index of systemic inflammation (AISI), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), leukocyte intoxication index (LII), lymphocyte index (LI), and lymphocyte-to-monocyte ratio index (LMRI). The instrumental cardiovascular assessments included electrocardiography (ECG), 24-hour ECG monitoring, 24-hour blood pressure monitoring, cycling exercise functional test, and echocardiography (EchoCG). The study endpoints were adverse events occurring during the competition: 1) sports injuries during competition evaluated by a staff doctor of the national team; 2) deterioration of athletic performance compared to that shown by the athlete during training sessions (evaluated by a group of trainers). Results: The cohort consisted of 180 highly qualified professional athletes (orienteering, alpine skiing, biathlon, athletics, and swimming), with a mean age of 20.55 ± 2.69 years, including 42.2% (n = 76) women and 57.8% (n = 104) men. A high percentage of individuals with varying degrees of arterial hypertension (AH) were identified based on 24-hour blood pressure monitoring: mild AH, mostly at night, was found in 18.3% (n = 33) of the cases, while severe night AH in 7.2% (n = 13) of the cases. 24-hour ECG monitoring showed the following heart rhythm and conduction disorders: incomplete right bundle branch block in 15% (n = 27), sinus arrhythmia in 48.3% (n = 87), and atrial rhythm in 7.8% (n = 14). At EchoCG, the most common change was an apical or median chord of the left ventricle (44.4%, n = 80). In 13 (7.2%) of the patients, the cycling exercise test was discontinued due to an inadequate increase in diastolic blood pressure. Among the 90 athletes who had a valid assessment of their sports injury history, 26 (28.9%) had a sports injury. Deterioration in athletic performance was recorded in 39 cases (48.1%) of the 81 checkup lists available for the analysis. SIRI, SII, AISI, NLR, PLR, and MLR were significant predictors of deterioration in athletic performance. The deterioration of the competitive sports results was associated with SIRI ≥ 2.097 (sensitivity 53.85%, specificity 85.71%; AUC = 0.713, p 0.001), SII ≥ 616.95 (sensitivity 56.41%, specificity 76.19%; AUC = 0.705, p 0.001), AISI ≥ 180.15 (sensitivity 97.44%, specificity 45.24%; AUC = 0.733, p 0.001). LMRI ≥ 4.44 had 100.00% sensitivity and 60.94% specificity in the prediction of sports injuries (AUC = 0.870, p 0.001). Conclusion: A preliminary screening for cardiovascular disorders aimed primarily at identifying those associated with a sudden cardiac death, is necessary when conducting an in-depth medical examination of athletes. LMRI (threshold value ≥ 4.44), which reflects the relationship between the affecter and effector components of the immune process, can be considered a promising marker of the risk of sports-related injuries.

Background and Aims: The treatment of chronic lymphocytic leukemia (CLL) with Bruton’s tyrosine kinase (BTK) inhibitor Ibrutinib is a widely used and effective therapy, with a good safety profile. However, studies and post-marketing survaillance showed an increased risk of bleeding (up to 30% of the patients) and heart rhythm disorders (up to 6% of the patients). In the last few years new BTK inibitor agents were produced, trying to improve the efficacy and safety of Ibrutinib. The aim of this retrospective monocentric study was to analize the safety of the treatment with diffent BTK inhibitors, with particular reference to bleeding complications. Methods: We collected the data of 114 patients with the diagnosis of chronic lymphocytic leukemia treated with BTK inhibitors in the Azienda Ospedaliero Universitaria delle Marche and authorized by the Internal ethical committee and General affair committee from 2009 to 2024. Results: The median age at diagnosis was 68.5 years (standard deviation 10.3 years). 75 of the patients (66%) were male and 23 patients (20%) already had a known cardiac disease (not including arterial hypertension). 78 patients (68%) were treated with Ibrutinib (34 as a first line treatment, 28 as a second line, 13 as a third line, 3 as a fourth line); 28 with Acalabrutinib (22 as a first line, 5 as a second line, 1 as a third line); 10 with Zanubrutinib (5 as a first line, 4 as a second line, 1 as a third line) and 1 with Pirtobrutinib (as a third line treatment). 11 patients (10%) had a concomitant treatment with anticoagulants. Bleeding occurred in 5 patients, but only 2 were majors, and none was fatal. 2 events were in patients treated with Ibrutinib, 2 with Zanubrutinib, 1 with Acalabrutinib. Only one of bleeding events occurred during anticoagulant therapy. 8 patients (7%) had an atrial fibrillation onset or resurgence, all during the Ibrutinib treatment. Conclusions: In this study the treatment with BTK inhibitors had a cardiac safety profile comparable to known data (7% vs. 6%), but none of the events was associated with the new inhibitors. The bleeding safety profile was significantly better than the one reported with Ibrutinib (4% vs. 20%), but almost all BTK inhibitors had at least one event. This study confirms the safety of the new agents, of which post-marketing survaillance data are still to be known.

Introduction: Atrial fibrillation (AF) is the most common heart rhythm disorder and is associated with several potentially life-threatening complications. Its global prevalence is rising, particularly among aging populations. In Saudi Arabia, data regarding the prevalence of AF remains limited. Various risk factors, including advanced age, metabolic syndrome and lifestyle habits, contribute to the increasing incidence of AF. Objective: This study aims to identify the most significant modifiable risk factors associated with the incidence of AF in individuals aged 60 years and older at the time of initial diagnosis, with the goal of reducing related complications and overall morbidity. Methodology: This is a retrospective study that examined the specific risk factors associated with AF in older individuals at a tertiary hospital. All patients aged ≥ 60 years who were newly diagnosed with AF were included. Results: This study included 211 consecutive patients at a large tertiary hospital in Jeddah, Saudi Arabia. The mean age at diagnosis was 74 ± 9 years. Overweight individuals with a BMI of 25–29.9 kg/m² accounted for 30.8% of the sample. Additionally, 29.3% had hypertension and 23.4% had diabetes. Regarding cardiac comorbidities, 34.3% had ischemic heart disease and 34.9% had heart failure. Non-cardiac conditions included pneumonia 12.9% and a history of pulmonary embolism 3.8%. Conclusion: Our research emphasizes the critical role of modifiable factors such as elevated BMI in influencing the risk of AF and highlights the most common comorbidities requiring targeted interventions, particularly the management of hypertension and diabetes, to reduce the burden of AF in the older adult population.

Epidemiological data show that up to 30% of people who survive the acute phase of COVID-19 experience long-term cardiovascular symptoms (shortness of breath, chest pain and discomfort, palpitations, exercise intolerance, fatigue, sleep disturbances). Numerous studies conducted in different regions of the world have found that after recovery from COVID-19, patients, regardless of age, race, gender and cardiovascular risk factors, are at increased risk of developing cardiovascular complications, including new or progressive inflammatory heart disease, heart failure, myocardial infarction, coronary artery disease, cardiomyopathy, thromboembolism, arrhythmias and ischemic stroke. The SARS-CoV-2 virus causes not only direct damage to cardiomyocytes and other cells of the cardiovascular system, but also systemic inflammation and coagulopathy, which can aggravate comorbid cardiovascular diseases. The use of functional and instrumental research methods revealed various types of subclinical and clinical cardiac damage in most patients with post-COVID syndrome (regardless of the severity of the acute phase of COVID-19 and concomitant conditions). The high prevalence of post-COVID syndrome of the cardiovascular type requires a comprehensive multidisciplinary approach to diagnosis, treatment and rehabilitation of patients. All authors of published studies, meta-analyses and systematic reviews emphasize the importance of continuous monitoring of the cardiovascular system for at least one year after the infection has resolved. The aim of our review article is to justify the need to study the pathophysiology of post-COVID cardiovascular syndrome to discover therapeutic targets and develop targeted treatments.

Atrial fibrillation (AF), the most common cardiac arrhythmia, shows marked sex differences in clinical presentation, treatment response and outcomes. Although prevalence is similar, women often experience more severe symptoms, higher rates of adverse drug effects and reduced treatment efficacy. To investigate the underlying sex-specific AF mechanisms, we developed and validated male and female human atrial cardiomyocyte models that integrate sex-based differences in electrophysiology and calcium (Ca2+) handling under normal sinus rhythm (nSR) and chronic AF (cAF) conditions. Although the model parameterizations and assumptions (based on limited human data) may not capture the full spectrum of clinical variability, the models reproduced key reported sex-dependent differences in human atrial cardiomyocyte action potential (AP) and Ca2+ transient (CaT) dynamics. Simulations revealed that both sexes exhibited shortened effective refractory periods and wavelengths in cAF vs. nSR. Females were more prone to delayed afterdepolarizations (DADs), whereas males were more susceptible to AP duration (APD) and CaT amplitude (CaTAmp) alternans. Population-based modelling identified distinct parameter associations with arrhythmia mechanisms: DAD vulnerability was associated with enhanced ryanodine receptor Ca2+ sensitivity in females, and alternans in males correlated with reduced L-type Ca2+ current maximal conductance. Pharmacological simulations revealed sex-specific responses to antiarrhythmic therapies. In males, multiple drug combinations restored APD at 90% repolarization (APD90), CaTAmp and reduced alternans susceptibility, whereas females responded to only one combination improving APD90 and CaTAmp but with minimal impact on DAD risk. These findings underscore the need for sex-specific therapeutic strategies and support use of computational modelling in guiding precision medicine against AF. KEY POINTS: Atrial fibrillation (AF) is a common heart rhythm disorder that presents differently in males and females, but how the underlying mechanisms differ in males and females is not fully understood. We developed and validated computer models of male and female human atrial cardiomyocytes that incorporate known sex differences in ion channels and calcium handling under normal sinus rhythm and AF conditions. Under normal rhythm, males and females showed distinct electrical activity, which became less pronounced in AF. In AF, both sexes showed reduced effective refractory period and wavelength and depressed calcium transients. Males were more susceptible to electrical alternans, whereas females showed a greater tendency for calcium-driven delayed afterdepolarizations. Simulated drug treatments showed greater benefit in male models, particularly with combinations targeting multiple potassium channels, whereas female models showed limited response. These results highlight the need for sex-specific approaches to treating AF and may help guide future drug development.