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Advances in Atrial Fibrillation: Mechanisms, Diagnosis, and Emerging Therapies
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Advances in Atrial Fibrillation: Mechanisms, Diagnosis, and Emerging Therapies

A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Cardiology".

Deadline for manuscript submissions: 1 September 2026 | Viewed by 3596

Special Issue Editors

Dr. Angelica Cersosimo

E-Mail Website
Guest Editor
Department of Experimental and Clinical Medicine, Magna Graecia University, Catanzaro, Italy
Interests: atrial fibrillation; heart failure; cardiac arrhythmias
Dr. Vincenzo Mirco La Fazia

E-Mail Website
Guest Editor
Texas Cardiac Arrhythmia Institute, St David's Medical Center, Austin, TX, USA
Interests: cardiac arrhythmias, atrial fibrillation; heart failure; arrhythmia; sudden cardiac death; catheter ablation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Atrial fibrillation (AF) represents the most prevalent sustained cardiac arrhythmia in clinical practice, affecting millions worldwide and conferring a five-fold increased risk of ischemic stroke. Despite substantial progress in understanding its pathophysiology, AF continues to pose major diagnostic and therapeutic challenges. Several studies have demonstrated that AF can be detected in up to 30% of patients with embolic stroke of undetermined source (ESUS) during long-term follow-up, underscoring its critical but often elusive role in cerebrovascular disease.

Emerging evidence also suggests that AF is not always the direct cause of stroke but may serve as a marker of underlying atrial pathology. The concept of atrial cardiomyopathy, defined by structural, electrical, and functional abnormalities of the atrial myocardium, has gained prominence as a potential precursor to AF and stroke. Structural remodeling, altered electrophysiological properties, and delayed atrial conduction have been identified as early hallmarks of this condition, offering novel insights into preclinical disease states. Understanding the interplay between atrial remodeling and thromboembolic risk may enable the earlier identification of high-risk patients and the development of targeted preventive strategies.

Our aim in launching this Special Issue is to provide a comprehensive overview of the latest advances in the mechanisms, diagnosis, and treatment of AF. By integrating insights from clinical, translational, and basic research, we aim to bridge the gap between pathophysiological understanding and practical management. Topics of interest include novel biomarkers of atrial cardiomyopathy, innovative diagnostic tools such as wearable and implantable monitoring devices, and emerging therapeutic strategies that extend beyond traditional rate and rhythm control approaches.

Cutting-edge research contributions are encouraged, particularly studies that explore the molecular mechanisms underlying atrial remodeling, the role of inflammation and fibrosis in AF progression, and the application of artificial intelligence in arrhythmia detection and risk stratification.

We invite original research articles, systematic reviews, meta-analyses, and expert perspectives that advance the understanding of AF from its subclinical manifestations to advanced disease stages. By highlighting novel diagnostic modalities, therapeutic innovations, and preventive strategies, this Special Issue will foster multidisciplinary collaboration and guide the next generation of precision medicine approaches in atrial fibrillation.

Dr. Angelica Cersosimo
Dr. Vincenzo Mirco La Fazia
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Medicina is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cardiac arrhythmias
  • atrial fibrillation
  • heart failure
  • arrhythmia
  • sudden cardiac death
  • catheter ablation

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Published Papers (5 papers)

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Research

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11 pages, 1510 KB  
Article
Effects of Diazepam Addition to Standard Treatment of Atrial Fibrillation in Emergency Department Settings: A Unicentric Retrospective Study
by Kristina Vidović, Josip Krnić and Benjamin Benzon
Medicina 2026, 62(5), 861; https://doi.org/10.3390/medicina62050861 - 30 Apr 2026
Viewed by 430
Abstract
Background and Objectives: Diazepam, a GABAA receptor agonist with sympatholytic properties, is sometimes co-administered with antiarrhythmic agents in the emergency management of atrial fibrillation (AF), yet evidence supporting this practice is remarkably limited. Given the established role of sympathetic activation in the [...] Read more.
Background and Objectives: Diazepam, a GABAA receptor agonist with sympatholytic properties, is sometimes co-administered with antiarrhythmic agents in the emergency management of atrial fibrillation (AF), yet evidence supporting this practice is remarkably limited. Given the established role of sympathetic activation in the initiation and maintenance of AF, we investigated whether adjunctive diazepam influences treatment outcomes. Materials and Methods: This single-centre retrospective cohort study included 72 hemodynamically stable patients presenting with AF to the emergency department of University Hospital Centre Split, Croatia. Patients were stratified by treatment strategy into a rhythm control group (n = 33, receiving any Class IC/III antiarrhythmic) and a rate control only group (n = 39, beta-blockers and/or digoxin). Diazepam was administered orally at the physician’s discretion (median dose 5 mg). Primary outcomes were rhythm conversion and achievement of a heart rate < 110 bpm. Secondary outcomes included changes in heart rate, blood pressure, and time to therapeutic goal. Results: Diazepam was administered to 32 patients (44.4%). In the rate control stratum, spontaneous rhythm conversion was significantly higher with diazepam (40.0% vs. 9.5%; OR 6.33, 95% CI 1.06–37.78, p = 0.046), corresponding to a model-predicted increase in conversion probability from 8% to 33%. This effect was absent in the rhythm control group (64.3% vs. 64.7%; OR 0.98, p = 1.000). Diazepam increased the odds of achieving HR < 110 bpm by 3.46-fold (95% CrI 0.63–23.1, posterior probability of benefit 92%) in the rate control group. Diazepam-treated patients in the rate control group had longer median time to therapeutic goal (4.2 vs. 2.8 h, p = 0.005). In the rhythm control group, diazepam was associated with reduced variability in diastolic blood pressure response (p = 0.006). Conclusions: Adjunctive diazepam was associated with a significantly higher rate of spontaneous rhythm conversion in AF patients receiving rate control therapy only, consistent with sympatholysis removing a key factor sustaining the arrhythmia. This effect was not observed when Class IC/III antiarrhythmics were co-administered, suggesting that diazepam’s benefit is context-dependent. These hypothesis-generating findings warrant prospective validation, with attention to thromboembolic risk in patients who convert unexpectedly. Full article
(This article belongs to the Special Issue Advances in Atrial Fibrillation: Mechanisms, Diagnosis, and Emerging Therapies)
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11 pages, 519 KB  
Article
Predictive Value of Preoperative Left Atrial Coupling Indices for Postoperative Atrial Fibrillation After Isolated CABG
by Hasan Ali Sinoplu, Atilla Koyuncu, Cennet Yıldız, Fatma Nihan Turhan Çağlar, Dilay Karabulut, Hasan Toz, Mehmet Pişirici, Büşra Mavi, Atakan Arpaç and Alparslan Şahin
Medicina 2026, 62(2), 353; https://doi.org/10.3390/medicina62020353 - 10 Feb 2026
Viewed by 546
Abstract
Background and Objectives: Postoperative atrial fibrillation (POAF) is the most common arrhythmia after coronary artery bypass grafting (CABG) and is linked to adverse outcomes. This study evaluated the predictive value of the Left Atrial Coupling Index (LACI) for POAF and compared two calculation [...] Read more.
Background and Objectives: Postoperative atrial fibrillation (POAF) is the most common arrhythmia after coronary artery bypass grafting (CABG) and is linked to adverse outcomes. This study evaluated the predictive value of the Left Atrial Coupling Index (LACI) for POAF and compared two calculation methods, LACI1 and the novel LACI2. Materials and Methods: This prospective study included 130 patients undergoing isolated CABG between January 2022 and June 2023. Preoperative echocardiography was performed to calculate conventional parameters and LACI values: LACI1 = LAVI/TDI-septal a′ and LACI2 = LAVI/min (TDI-septal a′, TDI-lateral a′). Patients were classified into POAF (+) and POAF (−) groups. Clinical, echocardiographic, and outcome data were compared. Logistic regression and receiver operating characteristic (ROC) analyses were performed. Results: POAF occurred in 59 patients (45.4%). Those with POAF were older, had more diabetes mellitus(DM), hypertension(HT), and higher EuroSCORE II values (all p < 0.05). POAF was associated with longer hospitalization and higher in-hospital mortality. Both LACI1 (4.21 ± 2.62 vs. 2.94 ± 1.02, p < 0.001) and LACI2 (4.27 ± 2.60 vs. 2.96 ± 1.02, p < 0.001) were significantly higher in the POAF group. In multivariate analysis, LACI1 (OR 1.45, p = 0.020) and LACI2 (OR 1.50, p = 0.004) remained independent predictors. ROC analysis showed numerically higher discriminatory performance for LACI2 (AUC = 0.690, specificity 74.5%) compared with LACI1 (AUC = 0.677, specificity 67.6%). Conclusions: LACI is an independent predictor of POAF after CABG. The novel LACI2 demonstrated numerically higher predictive performance compared with LACI1 and may improve preoperative risk stratification and guide preventive strategies. Full article
(This article belongs to the Special Issue Advances in Atrial Fibrillation: Mechanisms, Diagnosis, and Emerging Therapies)
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13 pages, 3199 KB  
Article
Heart Rate Variability Nomogram Predicts Atrial Fibrillation in Patients with Moderate to High Burden of Premature Ventricular Complexes
by Koray Kalenderoglu, Mert Ilker Hayiroglu, Tufan Cinar, Faysal Saylik, Gokcem Ayan Bayraktar, Melih Oz, Miray Ozer Oz, Kadir Gurkan and Tolga Aksu
Medicina 2026, 62(2), 243; https://doi.org/10.3390/medicina62020243 - 23 Jan 2026
Cited by 1 | Viewed by 761
Abstract
Background and Objectives: There is a well-established correlation between premature ventricular contractions (PVCs) and atrial fibrillation (AF), with a higher burden of PVCs increasing the likelihood of new-onset AF. This study aims to investigate the impact of heart rate variability (HRV) on the [...] Read more.
Background and Objectives: There is a well-established correlation between premature ventricular contractions (PVCs) and atrial fibrillation (AF), with a higher burden of PVCs increasing the likelihood of new-onset AF. This study aims to investigate the impact of heart rate variability (HRV) on the onset of AF in patients with moderate to high burdens of PVCs, as observed through 24 h ambulatory electrocardiogram (ECG) analysis. Materials and Methods: Our study was a retrospective analysis involving 187 patients at a single tertiary center. We analyzed PVC counts from 24 h ECG recordings, categorizing the patients into groups based on whether they developed AF or not. Additionally, we developed a nomogram to estimate the risk of AF development in these patients. Results: A new-onset AF was detected in 16% of the cohort. Analysis of 24 h ambulatory ECG data revealed statistically significant increases in the SDNN index, RMSSD, PNN50, total power (TP), and low-frequency (LF) values in AF patients. To estimate the risk of AF, a risk prediction nomogram was created using high-frequency (HF), LF, SDNN index, and PNN50. Among these variables, PNN50 was identified as the strongest predictor in the multivariable model. Additionally, a decision curve analysis demonstrated that the nomogram offers a net clinical benefit for detecting AF in patients when the baseline threshold risk exceeds 15%. Conclusions: Our study found that among patients with AF who had a moderate to high burden of PVCs using 24 h ambulatory ECGs, several HRV parameters were elevated. This increased autonomic instability may play a role in the development and persistence of AF episodes. Full article
(This article belongs to the Special Issue Advances in Atrial Fibrillation: Mechanisms, Diagnosis, and Emerging Therapies)
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Review

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19 pages, 1595 KB  
Review
Circulating microRNAs in Atrial Fibrillation: Clinical Significance and Future Perspectives
by Caglar Ozmen
Medicina 2026, 62(6), 1126; https://doi.org/10.3390/medicina62061126 - 9 Jun 2026
Viewed by 196
Abstract
Atrial fibrillation (AF) remains one of the most clinically demanding arrhythmias in contemporary cardiology—not because its mechanisms are unknown, but because what we know does not yet translate into precise, individualized management. Existing risk scores predict adverse outcomes reasonably well at the population [...] Read more.
Atrial fibrillation (AF) remains one of the most clinically demanding arrhythmias in contemporary cardiology—not because its mechanisms are unknown, but because what we know does not yet translate into precise, individualized management. Existing risk scores predict adverse outcomes reasonably well at the population level but perform inadequately for individual patients, and the molecular substrate driving disease progression remains largely invisible at the bedside. MicroRNAs (miRNAs), small non-coding RNA molecules of 20–25 nucleotides found stably in peripheral blood, have attracted considerable attention as potential biomarkers capable of bridging this gap. Their involvement in atrial fibrosis, electrical remodeling, and inflammatory signaling is mechanistically well-grounded. Whether this mechanistic plausibility can be translated into clinical utility is the central question this review addresses. We summarize the biological rationale for circulating miRNAs as AF biomarkers, review the most consistently replicated miRNA expression findings across clinical studies and meta-analyses, and appraise what the evidence supports—and what it does not—regarding diagnostic accuracy, prognostic value, and clinical decision-making applications. We also outline what the field needs to accomplish to move from promising findings to routine clinical use. Full article
(This article belongs to the Special Issue Advances in Atrial Fibrillation: Mechanisms, Diagnosis, and Emerging Therapies)
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14 pages, 615 KB  
Review
Artificial Intelligence Applied to Electrocardiograms Recorded in Sinus Rhythm for Detection and Prediction of Atrial Fibrillation: A Scoping Review
by Ziga Mrak, Franjo Husam Naji and Dejan Dinevski
Medicina 2026, 62(1), 199; https://doi.org/10.3390/medicina62010199 - 17 Jan 2026
Cited by 1 | Viewed by 1210
Abstract
Background and Objectives: Subclinical paroxysmal atrial fibrillation (AF) is often undetected by conventional screening strategies, until complications emerge. Artificial intelligence (AI) applied to sinus rhythm electrocardiograms has emerged as a promising tool to identify individuals with occult AF and to predict the risk [...] Read more.
Background and Objectives: Subclinical paroxysmal atrial fibrillation (AF) is often undetected by conventional screening strategies, until complications emerge. Artificial intelligence (AI) applied to sinus rhythm electrocardiograms has emerged as a promising tool to identify individuals with occult AF and to predict the risk of future incident AF. This scoping review synthesizes evidence from original studies evaluating AI models trained on sinus rhythm ECGs for AF detection or AF prediction. Materials and Methods: A comprehensive search of MEDLINE, Embase, Web of Science, Scopus, and IEEE Xplore was conducted to identify peer-reviewed studies from inception to November 2025. Eligible studies included original investigations in which the model input was a sinus rhythm ECG and the outcome was either paroxysmal AF or new-onset AF. Extracted variables included cohort characteristics, ECG acquisition parameters, AI architecture, model predictive performance, AF prediction horizon, clinical outcomes, and validation strategy. Risk of bias was assessed using PROBAST. Results: Nineteen studies met the inclusion criteria. Retrospective datasets ranging from several thousand to over one million ECGs and convolutional or deep neural network AI architectures were used in most studies. AI-ECG models demonstrated high diagnostic accuracy for detecting subclinical AF (ten studies; AUROC 0.75–0.90) and for predicting long-term new-onset AF (six studies; AUROC 0.69–0.85) from a single sinus rhythm ECG. Robust external validation was reported in eleven studies. Combining AI-ECG models with clinical risk factors improved AF predictive performance in several reports. Key limitations across studies included retrospective design, patient selection, limited calibration reporting, and sparse prospective impact data. Conclusions: AI-based analysis of sinus rhythm ECGs can detect occult AF and stratify future AF risk with moderate-to-high accuracy across multiple populations and healthcare systems. However, rigorous prospective trials, evaluating clinical benefit, cost-effectiveness, calibration across demographic groups, and real-world implementation, are required before broad adoption in clinical practice. Full article
(This article belongs to the Special Issue Advances in Atrial Fibrillation: Mechanisms, Diagnosis, and Emerging Therapies)
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