Abstract Background Elevated pulmonary capillary wedge pressure (PCWP) is known to drive atrial fibrillation (AF). However, it remains unknown if non-invasive Cardiovascular Magnetic Resonance (CMR) - derived PCWP could predict the future risk of AF. This study investigated whether a CMR-derived measure of PCWP could predict future AF. Methods We enrolled 202 participants (mean age 76.2±4.2 years) from the LOOP study, each receiving implantable loop recorder (ILR) for continuous rhythm monitoring over 4 years. CMR imaging quantified left atrial volume (LAV) and left ventricular mass (LVM), allowing calculation of a validated sex-specific equation derived PCWP. Cox proportional hazards analysis identified independent variables associated with incident AF. Results Eighty-six participants (42.6%) manifested AF during follow-up. Individuals with AF exhibited significantly higher CMR-PCWP (16.1±2.8 vs. 14.7±2.3 mmHg, p<0.01) and greater LAV. Univariate regression highlighted that PCWP ≥16 mmHg was significantly associated with incident AF (hazard ratio 2.73). Stepwise Cox regression confirmed that PCWP ≥16 mmHg and the CHARGE-AF score remained independently associated with AF, with PCWP conveying higher hazard ratio (2.88, p<0.001). Kaplan-Meier analysis reinforced the importance of this threshold for AF onset, demonstrating a significantly increased probability of arrhythmia over time and emphasising its decisive clinical impact. Conclusion Elevated CMR-PCWP is associated with AF in older, high-stroke-risk individuals, underscoring the role of subclinical diastolic dysfunction in promoting arrhythmogenesis. Incorporating non-invasive PCWP assessment into routine CMR evaluation may enhance risk stratification, allowing prompt identification of at-risk patients and enabling earlier, precise, targeted measures for AF prevention.

To determine whether exercise training patterns were associated with the incidence and timing of ventricular arrhythmia in veteran male endurance athletes. One-hundred-and-six healthy male endurance athletes (cyclists/triathletes) aged >50y undertaking >10h/week of exercise for >15y underwent clinical assessment, cardiac magnetic resonance (CMR) and implantable loop recorder (ILR) implantation. Daily exercise was tracked with computerised exercise tracking devices. Athletes were followed up for ventricular arrhythmia on ILR; ventricular tachycardia (VT) and non-sustained VT (NSVT). Fifty-five ventricular arrhythmia events occurred (median follow-up 796 days); 3 (5.5%) VT and 52 (94.5%) NSVT in 25 (23.5%) athletes. Myocardial fibrosis was significantly more prevalent in athletes with ventricular arrhythmia than those without ventricular arrhythmia (19 (76.0%) vs 31 (38.3%), P<001).The incidence of exercise-related ventricular arrhythmia was 0.4/1000 hours of exercise versus non-exercise-related ventricular arrhythmia incidence of 0.01/1000 hours of non-exercise. All three sustained VT cases occurred during exercise in athletes with fibrosis and were preceded by NSVT. There were no training differences between athletes with and without ventricular arrhythmia over two years and in the month prior to each arrhythmic event. A significant proportion of highly trained male veteran athletes developed ventricular arrhythmia which was predominantly NSVT and was strongly associated with myocardial fibrosis. Acute exercise exposure was associated with an increased risk of developing ventricular arrhythmia but chronic exercise load was not. Our findings therefore highlight myocardial fibrosis as a potential pro-arrhythmic substrate upon which intense exercise may trigger arrhythmogenesis in certain male veteran athletes.

Prevalence of clinically significant bradyarrhythmias in patients implanted with loop recorders for cryptogenic stroke: a manifestation of atrial cardiomyopathy?

Implantable loop recorder (ILR) explant has traditionally been performed in catheterization (cath) labs, with bed-based recovery lasting more than 60 min. This conventional model can strain cath lab resources, delay urgent interventional procedures, and inconvenience patients. Currently, there are no standardized guidelines for streamlined ambulatory pathways for ILR removal. To evaluate the feasibility, safety, and efficiency of a nurse-led, chair-based ambulatory pathway for ILR explant. A prospective, single-centre quality improvement project was conducted over a 4-month period. Patients were admitted via reception and transferred to a side room, bypassing the cath lab. Explant procedures were performed by trained nurses with consultant oversight available. Post-procedure, patients recovered in a chair in side room for 10-15 min before discharge. Standard wound care and safety instructions were provided. Safety monitoring, efficiency metrics, and patient satisfaction questionnaires were collected. A 201 patients were enrolled in this study. We compared 101 patients who underwent ILR explant through the ambulatory chair-based pathway to 100 patients who underwent consultant-led cath lab- based traditional pathway. In the new nurse-led chair-based pathway, there were no infections, bleeding, or major complications occurred. One case required consultant intervention due to a deep implant. Patient satisfaction was uniformly high, with no complaints reported. Compared to the traditional model, the new pathway reduced cath lab occupancy and bed utilization. Notably, no cancellations occurred during the study period because of cath lab worklaod, whereas in the cath lab era, cases were often delayed or cancelled due to scheduling conflicts with urgent procedures or using cath lab beds as escalation plan. A nurse-led, chair-based ILR explant pathway is safe, efficient, and highly acceptable to patients. It reduces reliance on cath lab infrastructure, eliminates procedure cancellations, optimizes resource utilization, and has significant implications for reducing waiting list backlogs. This model is reproducible and may inform best practice protocols in other centres.

Subclinical atrial fibrillation (SCAF) poses an increased stroke risk, but whether oral anticoagulation for SCAF prevents stroke is unclear. We sought to investigate the treatment effect of SCAF screening according to measures of cardiac structure and function. This was an echocardiographic substudy of the LOOP (Atrial Fibrillation Detected by Continuous ECG Monitoring) study, which randomized older people at risk of stroke to usual care or an implantable loop recorder (ILR) with monitoring for SCAF and subsequent oral anticoagulation. A subset (24% of trial population) underwent echocardiography to measure left ventricular size and function, left atrial volume and strain, and valvular pathology. The primary outcome was a composite of stroke or systemic embolism. The study included 1422 participants (ILR: n=1001; control: n=421; mean age: 74 years; men: 54%). During follow-up, 354 (25%) were diagnosed with AF (ILR versus control: 30% versus 12%). During a median follow-up of 5.5 years (interquartile range, 4.9-5.9 years), 55 (4%) developed the primary outcome (ILR versus control: 3.9% versus 3.8%). No conventional measure of cardiac structure and function modified the treatment effect from randomization. However, left atrial contraction strain significantly modified the treatment effect (Pinteraction=0.003), such that a lower risk of the primary outcome was noted from ILR with lower left atrial contraction strain values (hazard ratio [HR], 0.38 [95% CI, 0.16-0.87], for participants with contraction strain<16.5%). In a post hoc analysis of the LOOP study, conventional echocardiographic measures did not modify the effect of SCAF screening for stroke prevention. However, a significant stroke risk reduction was observed from ILR randomization among participants with reduced left atrial contraction strain.

Drug-induced QT prolongation after successful inpatient loading of class III antiarrhythmics may occur during routine outpatient care. Insertable cardiac monitors offer continuous signals but are limited by single-lead configuration. We hypothesized that a spatially aware deep learning system (3DRECON-QT) can reconstruct spatial information from a single lead vector to quantify QT/QTc and identify high-risk prolongation. We developed 3DRECON-QT using a multitask encoder-decoder that ingests a 10-s single-lead signal, reconstructs 12 leads, and predicts QT/QTc. The model was developed using 12-lead ECGs with clinician-adjudicated QT/RR from a large health system and tested in an external center with different ECG hardware. Continuous monitoring performance was assessed in a public dofetilide-loading data set with serial ECGs. In a real-world cohort of outpatients on dofetilide or sotalol presenting to the hospital or emergency room for any reason, rates of ventricular arrhythmias and QT prolongation were assessed. Device validation was tested in patients with insertable cardiac monitor recordings paired with clinical 12-lead ECGs. 3DRECON-QT classified prolonged QTc from single-lead signals with area under the receiver operating characteristics curve, 0.942 (mean absolute error, 17.5 ms) in the internal test set and 0.943 (mean absolute error, 21.1 ms) externally. During continuous dofetilide monitoring, predictions correlated with ground truth (r, 0.851; mean absolute error, 17.8 ms; area under the receiver operating characteristics curve, 0.936 for prolonged QTc, 0.816 for ≥15% QTc rise). QTc prediction from true insertable cardiac monitor recordings showed r=0.824 and mean absolute error, 17.5 ms. In outpatients on class III antiarrhythmics (n=1676), 16.5% had high-risk QTc prolongation. Ventricular arrhythmia events were 3.97% versus 0.86% without prolongation (adjusted odds ratio, 4.24 [95% CI, 1.81-9.90]). 3DRECON-QT detected these events with area under the receiver operating characteristics curve 0.94 (F1 score, 0.60). A single-lead, deep-learning approach can achieve guideline-level measurement accuracy, enable continuous QTc surveillance from nonstandard ECG vectors, and identify clinically meaningful outpatient QTc prolongation associated with a >4-fold increase in serious ventricular arrhythmias. This strategy may enhance safety monitoring after class III antiarrhythmic initiation and support targeted intervention.

To summarise contemporary strategies to detect atrial fibrillation (AF) after stroke/transient ischemic attack (TIA) with emphasis on implantable loop recorders (ILRs), evaluate who should receive anticoagulation in device detected AF/atrial high-rate episodes, and evaluate biomarkers that increase the likelihood of detecting AF. ILRs substantially increase AF detection beyond 12-36 months of monitoring. General population screening with ILRs increases AF diagnosis without a definitive stroke reduction. For subclinical/device detected AF, anticoagulation may reduce stroke but comes at the expense of increased bleeding. The burden of AF, biomarkers and atrial cardiomyopathy markers show promise to stratify risk and guide extended monitoring. An individualized approach is needed to identify who benefits most from ILR and subsequent anticoagulation. Research priorities include outcome-powered trials after stroke/TIA, the role of AF burden in decision making and the role of wearables within clinical pathways.

Insertable cardiac monitors (ICMs) provide long-term continuous monitoring for arrhythmia diagnosis and management for various clinical indications. However, little data exists on comprehensive real-world arrhythmia diagnostic yield and therapy rates in patients indicated for ICMs with validated artificial intelligence (AI) algorithms enabling large-scale, automated adjudication of ICM-detected episodes. We report the largest real-world analysis of arrhythmia detection as well as medical and procedural therapies in patients with ICMs implanted for guideline-approved indications with long-term monitoring. Patients who received a Reveal LINQ ICM between October 1, 2016, and June 30, 2020, with ≥ 1 year of follow-up were identified in two databases (Medtronic CareLink data warehouse, N = 12 020, and Optum Clinformatics Data Mart claims database, N = 17 037) to analyze arrhythmia detections and therapeutic interventions, respectively. Patients were categorized by clinical indication for ICM placement. All device-detected ECGs were identified and processed through arrhythmia-specific AI algorithms. Therapeutic interventions included procedural interventions (cardiovascular implantable electronic device implantation, cardioversions, and ablations) and medication initiation or titration (antiarrhythmics, rate-control medications, and oral anticoagulants) after ICM implant. Mean (SD) follow-up in the CareLink and Clinformatics claims databases was 24.6 (12.7) and 40.8 (15.6) months, respectively. Of the 12 020 patients in the arrhythmia detection analysis, 7284 (60.6%) had ≥ 1 arrhythmia detected (56.3% in the suspected AF population; 80.1% in the AF management population), and 376 (28.9%) had ≥ 2 arrhythmias detected during long-term follow-up. Among syncope patients with arrhythmia(s) detected, 71.2% had a finding other than pause/bradycardia; 50.4% of cryptogenic stroke patients and 62.6% of AF management patients with arrhythmias had ≥ 1 finding other than AF. Of the 17 037 patients in the therapeutic interventions analysis, 9820 (57.6%) had a therapeutic action post-ICM insertion, with 25% of all patients receiving a procedural intervention, and > 50% undergoing a medication adjustment. Mean (SD) follow-up to first arrhythmia detection was 7 (9) months. Mean (SD) duration from ICM insertion to therapeutic action was 13 (13) months for procedures and 7 (11) months for medication initiation. Long-term continuous monitoring with ICMs enables identification of multiple arrhythmias that may have otherwise remained undetected and rules out arrhythmias in ~40% regardless of indication. Medication adjustments and/or procedural interventions related to the management of arrhythmias were observed in over half of ICM recipients during long-term follow-up.

Post-stroke atrial fibrillation (AFib) is a frequent yet undetected complication, particularly in resource-limited settings, where systematic screening remains challenging. Timely identification is essential for guiding anticoagulation strategies and reducing recurrent stroke risk. This scoping review synthesizes evidence on predictive strategies integrating artificial intelligence, circulating biomarkers, and advanced rhythm-monitoring modalities in adults with ischemic stroke or transient ischemic attack without known AFib. Predictive variables from conventional clinical scores and modern AI-based models were harmonized into a unified framework, highlighting incremental contributions from natriuretic peptides, imaging radiomics, and electronic health record-derived laboratory parameters. A novel analytical construct-area under the curve (AUC)-cost-feasibility mapping-was introduced to compare diagnostic strategies, including risk scores, handheld and patch electrocardiography, smartwatch-based photoplethysmography (with ECG confirmation required for diagnosis), and implantable loop recorders, with explicit consideration of scalability in low- and middle-income countries. Based on this synthesis, a tiered diagnostic pathway is proposed, combining clinical risk stratification with biomarker-guided triage (particularly NT-proBNP and MR-proANP) to inform allocation of extended monitoring resources, thereby optimizing diagnostic yield and cost-effectiveness. Persistent knowledge gaps include the absence of standardized biomarker thresholds, limited head-to-head evaluations of AI-enabled workflow in post-stroke populations, insufficient external validation in diverse populations, and a lack of prospective cost-effectiveness analyses. By integrating predictive domains, quantifying performance-cost trade-offs, and outlining an implementation-oriented, risk-stratified strategy, this review aims to inform AFib screening after stroke from theoretical innovation toward context-adapted clinical application, offering a structured framework to guide both research and practice in diverse healthcare environments.

Embolic stroke of undetermined source (ESUS) is frequently attributable to atrial fibrillation (AF), yet remains undetected when episodes are brief or asymptomatic. Digital health-enabled cardiac monitoring offers novel pathways for secondary prevention. Implantable loop recorders (ILRs) provide continuous long-term rhythm surveillance, while wearable ECG devices offer greater accessibility but with uncertain diagnostic yield and economic value. We evaluated the cost-effectiveness of ILR versus wearable AF monitoring and usual care in ESUS. A cohort-based Markov model simulated 1,000 ESUS patients (mean age 65 years) over a 10-year horizon from the German statutory health insurance perspective. Clinical inputs included AF detection rates (ILR: 15-25%; wearables: 5-10%), risk reduction in ischemic stroke with oral anticoagulation, and mortality/disability utilities. Costs (2024 €, 3% discount) captured device acquisition, implantation, follow-up, stroke care, and anticoagulation. Outcomes included incremental cost-effectiveness ratio (ICER) and incremental net monetary benefit (NMB) at willingness-to-pay thresholds of €20,000, €30,000, and €50,000/QALY. Deterministic and probabilistic sensitivity analyses, including expected value of perfect information (EVPI), were performed. ILR yielded 0.23 additional QALYs compared with wearables at an incremental cost of €2,160, resulting in a base-case ICER of €9,391/QALY. In a high-risk subgroup, the ICER decreased to €5,520/QALY. Probabilistic analysis demonstrated >90% probability of cost-effectiveness at €30,000/QALY, with moderate EVPI. These findings align with meta-analytic evidence (RR 3.88 for AF detection; RR 0.75 for stroke reduction) and indicate that prolonged monitoring (≥12 months) maximises yield. Digital health-enabled ILR monitoring is likely cost-effective for AF detection after ESUS, particularly in high-risk patients. Wearables may serve as an adjunct but deliver lower value. Results support targeted ILR implementation in post-ESUS care pathways and integration into digital health-driven guideline and reimbursement frameworks.

The use of insertable cardiac monitors (ICM) for arrhythmia monitoring continues to grow steadily. However, ICM performance remains less than perfect, and the volume of transmitted data poses a challenge to clinics. Here, we evaluate the impact of three improvements implemented in the LUX-Dx II+ ICM for atrial fibrillation (AF), pause, and bradycardia detection. Enhanced AF and pause algorithms were evaluated using real-world ECG data and compared against the predecessor LUX-Dx algorithms. Optimized nighttime (11 p.m.-7 a.m.) programming settings were simulated on LUX-Dx data to evaluate the reduction of non-actionable nocturnal bradycardia (>30bpm) and pause (<5s) detections. The novel AF algorithm reduced false positives by 34% in the training dataset and 38% in the test dataset while maintaining >98% sensitivity relative to the legacy algorithm. False positive reduction and relative sensitivity were even higher (74% and 100%, respectively) in a subset of patients with more sensitive AF programming settings. The enhanced pause algorithm reduced false positives by 62.5% in the training set and 48.6% in the test set, while maintaining 100% relative sensitivity. Application of adjusted nocturnal detection thresholds reduced the number of nighttime bradycardia and pause episodes by 98% and 90%, corresponding to an overall episode reduction of 75% and 56%, respectively. The enhanced ICM algorithms and programming settings substantially reduced false positive AF and pause detections as well as non-actionable nighttime bradycardia and pause detections. These enhancements are expected to improve ICM performance and workflow in the device clinic.

The role of echocardiography is critical in the diagnostic evaluation and management of ischemic stroke, especially cryptogenic stroke, in which the cause is unknown. About 15-30% of ischemic strokes are caused by cardiogenic embolism, making cardiac imaging a critical component of evaluation. Guidelines from the American Heart Association and the American College of Cardiology highlight the importance of echocardiography and mobile cardiac telemetry or implantable loop recorders to identify possible sources of cardiac embolism and monitor for atrial fibrillation, thus guiding secondary prevention.Transthoracic echocardiography (TTE) is widely used as an initial tool to assess cardiac structure and function, detect intracardiac thrombi, and evaluate valvular abnormalities. Transesophageal echocardiography (TEE), as well as cardiac CT and MRI, offer enhanced visualization of certain cardiac structures, identifying embolic sources not readily visible on TTE, such as left atrial appendage thrombi and patent foramen ovale (PFO).The comprehensive diagnostic approach for cryptogenic stroke (CS) includes brain imaging (CT or MRI), neurovascular imaging, electrocardiography (ECG), and vascular ultrasound.Echocardiography plays a crucial role in assessing left atrial and ventricular thrombi, valvular disease, and aortic plaques. Additionally, advancements in echocardiography, such as real-time three-dimensional imaging, are emphasized for their potential to enhance stroke prevention and management strategies.

External validation of atrial fibrillation risk scores in heart failure under continuous device surveillance.

The coronavirus disease 2019 (COVID-19) pandemic has revealed a close and multifaceted relationship between viral infection, systemic inflammation, and cardiovascular health. Among the cardiac complications of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), atrial fibrillation (AF)-especially new-onset atrial fibrillation (NOAF)-has emerged as a major determinant of disease severity and prognosis. Clinical studies and meta-analyses show that 5-10% of hospitalized COVID-19 patients develop AF, with markedly higher rates in critically ill individuals. Both pre-existing and NOAF are independently associated with increased risks of intensive care admission, mechanical ventilation, thromboembolic events, and mortality. The underlying mechanisms involve a combination of cytokine-mediated inflammation, endothelial dysfunction, microvascular injury, and dysregulation of the renin-angiotensin-aldosterone system (RAAS). Viral downregulation of angiotensin-converting enzyme 2 (ACE2) receptors contributes to myocardial fibrosis, while hypoxia, oxidative stress, and autonomic imbalance further promote electrical remodeling and arrhythmogenesis. Post-infectious studies indicate that atrial structural changes and autonomic dysfunction may persist for months, predisposing survivors to recurrent arrhythmias. Technological advances in telecardiology and digital medicine have provided new tools for early detection and long-term monitoring. Wearable electroencephalography (ECG) devices, implantable loop recorders (ILRs), and artificial intelligence (AI)-based diagnostic algorithms enable continuous rhythm surveillance and individualized management, improving outcomes in post-COVID patients. This review summarizes current evidence on the epidemiology, pathophysiology, clinical implications, and monitoring strategies of AF in COVID-19. It underscores the importance of integrating telemedicine and AI-assisted diagnostics into cardiovascular care to mitigate the long-term arrhythmic and systemic consequences of SARS-CoV-2 infection.

The clinical utility of implantable cardiac monitors (ICMs) for atrial fibrillation (AF) detection following cryptogenic stroke or embolic stroke of undetermined source (ESUS) is well established. However, the optimal timing for ICM implantation to maximize diagnostic yield remains uncertain. To systematically review the literature and conduct a meta-analysis to determine whether earlier ICM implantation after cryptogenic stroke or ESUS ischemic stroke improves detection rates and reduces the time to AF diagnosis. A comprehensive search of PubMed, Embase, and Cochrane CENTRAL was conducted from inception to June 2025, without language restrictions. References of retrieved articles and relevant reviews were manually searched. We included observational studies or randomized trials reporting ICM use in patients with ESUS or cryptogenic stroke/transient ischemic attack (TIA), providing data on AF detection rates and/or timing metrics (stroke-to-ICM interval, ICM-to-AF interval). Two reviewers independently screened studies and extracted data. Disagreements were resolved by consensus or third-party adjudication. Data were extracted following Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Study-level AF detection rates were modeled using logit-transformed proportions and pooled using random-effects models (REML). Mixed-effects meta-regressions assessed the effect of timing (stroke-to-ICM interval) on AF detection and diagnostic delay, adjusting for ICM monitoring duration. The primary outcomes were pooled AF detection rate and mean time from ICM implantation to AF diagnosis. Timing of implantation was assessed as a continuous and categorical (early, intermediate, delayed) variable. Forty-seven studies (N = 6918 patients) were included. The pooled AF detection rate was 27.3% (95% CI: 24.6-30.2), with substantial heterogeneity (I2 = 80.8%). Early ICM implantation (<31.5 days from index event) was associated with a higher AF detection rate compared with delayed implantation (30.0% vs 23.7%; p = 0.0017), independent of monitoring duration. Stratified meta-regression confirmed that delayed implantation was associated with lower AF detection even after adjusting for ICM duration. For each additional day of delay in ICM implantation, the time from AF diagnosis increased by an additional 0.32 days on average, even after accounting for monitoring duration (p = 0.0007). These findings suggest that earlier ICM implantation enhances AF detection after ESUS or cryptogenic stroke and shortens diagnostic delay. Optimizing timing of post-stroke monitoring may improve patient selection for anticoagulation and reduce recurrent stroke risk.CRD 420251064227.

Background/Objectives: Arrhythmic recurrence is a common issue affecting a significant percentage of patients undergoing transcatheter ablation (TCA) of Atrial Fibrillation (AF). The use of artificial intelligence (AI) for the identification of electrocardiographic predictors of post-ablation recurrence may offer a valuable and cost-effective approach to improve risk stratification and optimize follow-up. This study aims to investigate the relationship between post-procedural electrocardiographic (ECG) P-wave parameters, measured using AI, and AF recurrence in patients undergoing transcatheter ablation (TCA). Methods: Seventy-four patients (age 62.36 ± 10.4 years) with a diagnosis of AF were retrospectively analyzed. ECGs were processed using AI software to analyze P-wave-related variables. All patients had either an implantable loop recorder (ILR) or another form of cardiac implantable electronic device (CIED). Results: Post-procedural P-wave amplitude in lead II (PwA in lead II) showed a significant association with AF recurrence, defined as an average arrhythmic burden >6% at one-year follow-up. Conclusions: These findings underscore the potential of PwA in lead II as a biomarker for the follow-up of patients undergoing TCA and highlight the contribution of AI in the analysis of electrocardiographic parameters predictive of AF recurrence. Together, these results may contribute to the development of early risk-stratification strategies following catheter ablation.

Cardiac arrhythmias remain one of the leading causes of cardiovascular morbidity and mortality worldwide. Over the past decade, diagnostic and therapeutic approaches have undergone a profound transformation driven by technological innovation, artificial intelligence (AI), and evidence-based medicine. This review analyzes the main advances in arrhythmia diagnosis and management, emphasizing the global perspective and its implementation in Latin America, particularly in Mexico, Colombia, and Ecuador. A narrative review was conducted using the Scientific Method and the DMAIC framework, analyzing twenty peer-reviewed publications, clinical trials, and international guidelines published between 2014 and 2024. The evidence reveals a transition from conventional electrocardiographic methods such as 24-hour Holter monitoring to extended adhesive patch ECGs, implantable loop recorders, and wearable devices supported by AI algorithms, which have significantly improved diagnostic precision and early detection of subclinical arrhythmias. Therapeutically, clinical trials such as EAST-AFNET 4, CABANA, EARLY-AF, and STOP AF First demonstrated that early rhythm-control strategies, particularly catheter and cryoballoon ablation, provide better rhythm maintenance, reduce cardiovascular events, and modify the natural course of atrial fibrillation. Furthermore, the integration of telecardiology, device remote monitoring, and cardiogenetic evaluation is progressively redefining contemporary arrhythmia care. Despite persistent disparities in access and infrastructure, Latin American countries are adopting hybrid diagnostic and therapeutic models aligned with international standards. In conclusion, modern arrhythmia management has evolved into a proactive, technology-driven, and patient-centered discipline, where early rhythm control, AI-assisted monitoring, and regional collaboration are essential to improve outcomes and achieve equitable cardiovascular care worldwide.

BACKGROUND Implantable loop recorders (ILRs) are important tools in diagnosing unexplained syncope and palpitations through prolonged rhythm monitoring. However, ILRs can produce false-positive arrhythmia detections, due to signal oversensing and undersensing, which can complicate clinical interpretation. Oversensing typically involves P waves, T waves, or myopotentials; however, simultaneous oversensing and undersensing of multiple waveform components is rare. We report a case of R-wave oversensing of P waves and T waves, with undersensing of QRS complexes, resulting in erroneous atrial fibrillation (AF) alerts. CASE REPORT A 73-year-old woman with hypertension and hyperlipidemia presented with recurrent lightheadedness, palpitations, and hypotension. After an unrevealing initial workup, a Biotronik Biomonitor III ILR was implanted. Within 3 months, the device flagged over 200 episodes of AF and several ventricular fibrillation episodes, despite the patient remaining asymptomatic. Careful signal review revealed a triple-sensing issue of cardiac signals, leading to misclassification of arrhythmias. The sensing filter was reprogrammed from 10 Hz to 24 Hz, resulting in elimination of false-positive detections. Following reprogramming, the patient remained asymptomatic with no further inappropriate arrhythmia alerts and did not require additional interventions. CONCLUSIONS This case highlights a rare example of R-wave oversensing and undersensing by an ILR, emphasizing the importance of individualized device programming to optimize diagnostic accuracy. Additionally, it illustrates that unconventional implantation sites, such as the right parasternal region, can produce unique sensing challenges. Careful review of device signals and appropriate reprogramming can correct oversensing issues, preventing unnecessary interventions and improving patient management.

Introduction: Patients who suffer from cryptogenic stroke (CS) are routinely screened for asymptomatic paroxysmal atrial fibrillation (AF) with implantable loop recorders (ILRs). The clinical risk factors associated with AF after CS are not fully defined, and it is a common perception that ILRs are not helpful in younger patients with CS. Research Questions/Objectives: To identify which clinical characteristics are associated with AF detection via ILR in patients who have suffered CS. To identify if there is an age cut-off, below which ILR implantation is likely to be futile in patients with CS. Methods: A retrospective cohort study was conducted on patients with CS who underwent ILR implantation at Thomas Jefferson University Hospital from 04/2019 to 04/2021. Patients were excluded from the analysis if there was &lt;6 months of ILR follow-up, delayed ILR placement (&gt;1 year after CS), or pre-existing (known) AF. Baseline demographics and clinical characteristics were collected (Table 1). Patients with and without AF detection within 1 year of CS were compared and multivariable logistic regression was applied to the univariate predictors that were significant (Table 2). Analyses were run in R Studio 4.4.2. Results: We identified a total of 282 patients with CS who received ILRs. Of these 282 patients, 218 formed the study group after applying exclusion criteria (age 63.45±10.58 years, 45% female). AF was detected within 1 year of CS in 47 patients (21.6%) with a mean time from CS to AF detection of 125.30± 94.64 days. In univariate analyses, AF was statistically significantly associated with older age, LAVI, CHA2DS2-VASc score, LVEF%, CKD stage, and presence of atrial runs (Table 1). After multivariable adjustment (Table 2), CKD stage 5 (OR 14.4, p=0.0168), atrial runs (OR 3.77, p=0.0079), and age (OR 1.11, p=0.0056) remained significantly associated with AF detection. However, there were 5 patients below the age of 60 who had AF detected. No significant differences were observed in sex, race, BMI, or other comorbidities. Conclusions: Stage 5 CKD, atrial runs, and age showed significant association with AF detection after cryptogenic stroke. Although age was statistically significant, the OR was low (1.11), and 5 patients below the age of 60 had AF detected. Renal failure and atrial runs were the strongest associates of AF detection after CS. We conclude that there should be no minimum age cut-off for ILR implantation in CS patients.

Background: The implantable loop recorder (ILR) is the most sensitive method for detecting atrial fibrillation (AF) following a cryptogenic stroke. However, to date, no study has demonstrated that it significantly reduces the rate of recurrent ischemic stroke. Objective: To assess the cumulative incidence of recurrent ischemic stroke in patients with a prior cryptogenic stroke who received an ILR, and to evaluate whether stroke recurrence is associated with device-detected AF. Methods: We conducted an observational study including consecutive patients with cryptogenic stroke who received an ILR in four academic centres in France. Prior to implantation, all patients underwent a standardized diagnostic workup, including cerebral CT angiography, brain MRI, carotid ultrasound, echocardiography, and at least 24 hours of ECG monitoring. Patients were followed from the date of ILR implantation until the first recurrence of stroke (primary endpoint), death from any cause (competing event), or end of follow-up (defined as ILR explant, last remote transmission, or final device interrogation). Device-detected AF and initiation of oral anticoagulation were analysed as time-dependent covariates in the univariate and multivariate analyses. Cause-specific Cox proportional Hazards model was used as the primary analysis. Results: We included 1,001 patients (median age 68 years [IQR 59–75]; 41% female; median CHA2DS2-VASc score 4 [IQR 3–5]). Over a median follow-up of 1.9 years, 67 recurrent ischemic strokes were recorded, yielding a cumulative incidence of 3.4% per year. ILR-detected AF occurred in 275 patients (27%). In univariate analysis, AF not treated with anticoagulation was associated with a significantly higher risk of recurrent stroke (HR 3.47, 95% CI 1.08–11.11, p=0.037), whereas AF with anticoagulation was not (HR 1.26, 95% CI 0.67–2.34, p=0.473). These associations remained consistent after multivariate adjustment for age, sex, peripheral artery disease, and renal function (HR 3.27, 95% CI 1.01–10.61, p=0.048 for untreated AF; HR 1.01, 95% CI 0.52–1.98, p=0.971 for anticoagulated AF). Conclusion: Among patients with cryptogenic stroke monitored with an ILR, recurrent ischemic stroke remains a significant concern. Device-detected AF is associated with a higher risk of recurrent stroke only when not treated with oral anticoagulation. These findings support early initiation of anticoagulation in patients with device-detected AF to reduce risk of stroke recurrence.