Heart Rhythm Monitoring Research Articles

Advancing athlete safety through real-time ECG monitoring for enhanced cardiovascular health in sports performance

This research paper explores the implementation and efficacy of real-time electrocardiogram (ECG) monitoring systems for athletes, emphasizing their potential to significantly enhance safety and performance in sports settings. By utilizing advanced ECG technology, the study investigates how continuous, real-time heart rate and rhythm monitoring can aid in the immediate detection of cardiovascular anomalies during high-intensity activities. The research methodology incorporates the deployment of portable ECG devices in a controlled experimental setup, analyzing data from athletes during training sessions and competitive events. Results from the study highlight the system's ability to provide swift and accurate cardiac assessments, thereby enabling timely medical interventions. Moreover, the paper discusses the technical challenges associated with real-time ECG monitoring, such as signal interference and data accuracy, and addresses privacy and ethical considerations concerning the continuous collection of health data. The discussion extends to the implications of integrating such technology within sports medicine, suggesting that while the systems offer substantial benefits in monitoring and preventing cardiac issues, they also necessitate rigorous standards for data security and ethical oversight. The conclusion advocates for a balanced approach to the adoption of these technologies, proposing future research directions that focus on enhancing system reliability and integrating artificial intelligence to predict potential health risks proactively. This study contributes to the ongoing discourse in sports health technology by providing a comprehensive analysis of real-time ECG monitoring as a transformative tool for athlete healthcare management.

Ambulatory polygraphy as a screening tool for obstructive sleep apnea in combination with semi-continuous rhythm monitoring in patients with atrial fibrillation: a pilot study

Abstract Background Obstructive sleep apnea (OSA) is a common, yet underdiagnosed risk factor in atrial fibrillation (AF) patients. Polysomnography (PSG) is the gold standard for OSA diagnosis but is also costly, time-consuming, and labor-intensive. (Cardio)-respiratory polygraphy (PG) offers an ambulatory screening for OSA detection. Studying the impact of OSA diagnosis and treatment on AF recurrence will require scalable tools for semi-continuous heart rhythm monitoring. Purpose The NOXFib-AF pilot study assessed the feasibility of PG as an OSA screening tool in patients with AF. The study monitored AF recurrences using a Fitbit smartwatch for heart rhythm monitoring with the FibriCheck algorithm. This pilot assessed the feasibility and patient compliance. Methods Overnight OSA testing was performed with the Noxturnal T3 (NOX-T3s) PG device used at home by AF patients, followed by four weeks of heart rhythm monitoring. Both semi-continuous monitoring with the Fitbit Versa 2 smartwatch with FibriCheck algorithm, and spot-check measurements on a smartphone (twice daily and in case of symptoms) were used. Patients with OSA suspicion on PG (Apnea-Hypopnea Index (AHI) cut-off ≥ 11.1 based on previous studies) were referred for PSG confirmation. Patient satisfaction with the PG and Fitbit smartwatch was evaluated through questionnaires. Results Thirty symptomatic AF patients underwent an overnight PG-based OSA screening, achieving an overall success rate of 96.7% (29/30). Interim analysis of 19 patients who underwent PSG evaluation upon referral showed that 12 (63.2%) were correctly diagnosed with at least moderate OSA (i.e., AHI ≥ 15) and were eligible for reimbursed CPAP treatment. PG and PSG agreement for OSA classification was fair (Cohen’s kappa = 0.230), with 68.4% (13/19) correctly classified (normal-mild, moderate-severe). There was high patient adherence to wearing the smartwatch for four weeks, with median compliance (i.e., adherence to the expected number of measurements) of 96.9% (IQR: 94.3% – 97.6%). A median of 150 (IQR: 145 – 151) daily automatic measurements were performed. Spot-check measurements via the smartphone also showed high compliance (110%, IQR: 100.0% – 135.5%) and high patient motivation (i.e., consistency of performing measurements; 90.3%, IQR: 67.7% – 96.8%). Patients were positive for both PG screening (Figure 1A) and Fitbit-based FibriCheck monitoring (Figure 1B). Conclusions PG is a feasible approach as a home screening tool for OSA, positively perceived by patients. Also, the acceptance of semi-continuous Fitbit-based FibriCheck monitoring was high. In a follow-up study, both tools will be used to evaluate the impact of a structured OSA screening and treatment trajectory on AF burden.

Digital devices for heart rhythm monitoring in atrial fibrillation patients scheduled for elective electrical cardioversion. Kardiover study

Abstract Introduction the management of patients with recent-onset atrial fibrillation (AF) is to achieve sinus rhythm (SR) by electrical or pharmacological cardioversion (CV). However, frequently SR is spontaneously restored, making scheduled admission and/or transesophageal echocardiogram (TEE) unnecessary and therefore causing misutilization of healthcare resources. Emerging medical technology has allowed for accurate heart rhythm monitoring. Objective to evaluate the diagnostic ability of a smart device ECG monitor to detect spontaneous conversion to SR in AF patients, preventing unnecessary admission and providing an earlier management. Methods A prospective multicenter study (Kardiover study) was designed including patients with paroxysmal, persistent or first diagnosed AF scheduled for elective electrical CV in cardiology departments of 7 hospitals in Spain. Patients were asked to submit ECG recordings to a central Corelab daily, twice a day and whenever they present symptoms, until CV (spontaneous or scheduled) and a week afterwards. Whenever a spontaneous conversion to SR was detected, investigators were contacted to confirm SR and abort admission, likewise when AF recurrence after CV was detected. Patients’ satisfaction was evaluated using a test for perceived utility and value, convenience, and accessibility. Results A total of 74 patients were enrolled (age 62 ± 10 years). Twenty-two patients (30%) showed spontaneous conversion to SR correctly detected by the devices. 86% of the spontaneous CV occurred during the first week. Among 52 patients admitted for CV, 45 (88%) were discharged in SR. During follow up after conversion to SR (spontaneous or electrical), recurrences of AF occurred in 24 patients (34%). At the end of the follow-up 51 patients (69%) remained in SR. Due to the early detection of spontaneous conversion to SR, a total of 22 admissions and 16 TEE were prevented and these resources used for other patients. Patients’ adherence to the protocol in regard to ECG recording transmissions was high, the CoreLab received 93% of the expected transmissions. Patient’s overall satisfaction was also high with a punctuation of 9.1 over 10 in the feedback test. Conclusion Digital devices for heart rhythm monitoring can optimize the management of AF patients scheduled for CV, preventing unnecessary admissions and providing a more rational use of healthcare resources.Baseline characteristicsStudy design and results

External validation of a machine learning based classification algorithm for ambulatory heart rhythm diagnostics using smartphone-photoplethysmography - the SMARTBEATS algorithm study

Abstract Introduction Smartphone-photoplethysmography (PPG) can be used for heart rhythm monitoring. According to current guidelines, ECG verification is required for a new diagnosis of atrial fibrillation (AF). Accurate machine learning (ML) based automatic algorithms have the potential to facilitate clinical applications generating large numbers of PPG recordings, by offloading the need for manual over-read. Purpose The aim of this study was to evaluate the diagnostic performance of an automatic ML-based algorithm for heart rhythm diagnostics using smartphone-PPG recorded by patients with AF in an unsupervised ambulatory setting. Methods Patients undergoing direct current cardioversion (DCCV) at a university hospital for treatment of AF or atrial flutter (AFL) were asked to perform one-minute heart rhythm recordings post-cardioversion at least twice daily for 30 days. All participants were provided with an iPhone 7 smartphone running the CORAI Heart Monitor PPG application simultaneously with a single-lead ECG recording (KardiaMobile). The automatic algorithm uses support vector machines (SVM) to classify heart rhythm from smartphone-PPG recordings. The SVM classifier evaluated here was trained on ambulatory PPG recordings made by patients in a separate cardioversion cohort, ensuring complete independence between training and validation sets. PPG recordings in the validation cohort were analyzed by the automatic algorithm and diagnostic performance was calculated by comparing heart rhythm classification output from the SVM classifier to the heart rhythm diagnosis from the simultaneous ECG recordings. ECG recordings were interpreted independently by two cardiologists and were set as gold standard. Results The SVM classifier was trained on data from 153 patients with 11,749 PPG recordings, of which 5,873 (50.0%) were labelled as AF and 5,876 (50.0%) as sinus rhythm (SR), as assessed by manual reading. In the validation cohort, 280 patients, with a median age of 69.0 years (31% women), registered 18,005 simultaneous PPG and ECG recordings. Recordings interpreted as AFL on ECG (2.0%), as having insufficient quality on ECG (4.9%) or PPG (2.8%), and low certainty algorithmic classifications (1.2%) were excluded, leaving 16,057 PPG recordings. Included ECG recordings consisted of 71.2% interpreted as (SR) and 28.8% as AF. Algorithm classification of the PPG recordings in the validation cohort diagnosed AF (sensitivity) in 99.7% and SR (specificity) in 99.7% of the recordings, with an overall accuracy of 99.7%. F1-score was 99.4% and area under the ROC curve (AUC) was 0.999. Conclusion A machine learning based algorithm for automatic heart rhythm diagnostics showed excellent diagnostic performance for smartphone-PPG recordings in an unsupervised ambulatory setting, minimizing the need for ECG verification in cardioversion populations.

Implantable loop recorder via subscapular approach in 2.7kg neonate.

Implantable loop records allow continuous heart rhythm monitoring with the ability to be stored and viewed remotely. The limited use in the pediatric population stems from the unknown indications of use and feasibility of implantation. We describe the case of a 2.7kg female with Long QT3. A loop recorder helped identify breakthrough tachycardia and helped her transition to the next stage of care. Placement was at the left subscapular region with no complications. Implantable loop recorder placement is achievable in a 2.7kg patient at corrected gestational age 38weeks for LQT3 syndrome monitoring and management.

Machine learning-based prediction of new onset of atrial fibrillation after mitral valve surgery

Abstract Background New-onset postoperative atrial fibrillation (nPOAF) is a common complication after cardiac surgery (30–50%), being associated with unfavorable long-term outcomes. Using the Society of Thoracic Surgeons National Adult Cardiac Database, we used machine learning (ML) to predict nPOAF and related 30-day outcomes following mitral valve (MV) surgery. A total of 27,856 MV operations were performed at 910 centers between 7/1/2017 and 6/30/2020 on patients without AF or a prior permanent pacemaker. The primary endpoint was nPOAF postoperatively. ML techniques utilized included penalized logistic regression, gradient boosting, decision trees, and random forests. Results The overall incidence of nPOAF was 35.4% and that of new pacemaker insertion was 5.6%. Patients who developed nPOAF were older (67 ± 10 vs 60 ± 13 years), had more mitral valve stenosis (14.1% vs 11.7%), and hypertension (72.1% vs 63.3%). They underwent more mitral valve replacement (39.1% vs 32.7%) and coronary artery bypass grafting (23.9% vs 16%). For predicting nPOAF, ML methods offer sensitivity, specificity and precision superior to logistic regression. The accuracy rate was identical with penalized and non-penalized logistic regression (0.672). Conclusions Predicting nPOAF and its short-term sequelae following MV surgery remains highly challenging. Machine learning methods offer a moderate degree of improvement in predicting nPOAF even in large national-level studies, in the absence of multi-modal data, such as real-time wearables data, electrocardiograms, heart rhythm monitoring, or cardiac imaging.

TCT-127 Thirty-Day High-Grade AV Block Post Transcatheter Aortic Valve Replacement in Patients Discharged on Heart Rhythm Monitor

TCT-127 Thirty-Day High-Grade AV Block Post Transcatheter Aortic Valve Replacement in Patients Discharged on Heart Rhythm Monitor

A Comprehensive Review of Cryptogenic Stroke and Atrial Fibrillation: Real-World Insights Into the Role of Insertable Cardiac Monitors.

Cryptogenic stroke, a subtype of ischemic stroke with no identifiable cause after comprehensive evaluation, presents a unique challenge in stroke prevention. Atrial fibrillation (AF), a common risk factor for ischemic stroke, is often underdiagnosed in these patients due to its intermittent, asymptomatic nature. Early detection of AF is critical, as anticoagulation therapy significantly reduces the risk of recurrent stroke in AF patients. However, traditional short-term monitoring methods frequently fail to identify paroxysmal AF. Insertable cardiac monitors (ICMs) offer a novel solution by providing continuous, long-term heart rhythm monitoring, which has proven effective in detecting occult AF. Real-world data further support the clinical value of ICMs in guiding the initiation of anticoagulation therapy, ultimately improving stroke prevention strategies. Despite some limitations, such as false positives and the invasive nature of the device, ICMs have emerged as a critical tool in modern stroke management. As technology evolves, future advancements may further enhance AF detection by integrating artificial intelligence and wearable devices. This review provides a comprehensive overview of the role of AF in cryptogenic stroke, the importance of early detection, and the growing significance of ICMs in clinical practice.

Potassium Supplementation and Prevention of Atrial Fibrillation After Cardiac Surgery

Supplementing potassium in an effort to maintain high-normal serum concentrations is a widespread strategy used to prevent atrial fibrillation after cardiac surgery (AFACS), but is not evidence-based, carries risks, and is costly. To determine whether a lower serum potassium concentration trigger for supplementation is noninferior to a high-normal trigger. This open-label, noninferiority, randomized clinical trial was conducted at 23 cardiac surgical centers in the United Kingdom and Germany. Between October 20, 2020, and November 16, 2023, patients with no history of atrial dysrhythmias scheduled for isolated coronary artery bypass grafting (CABG) surgery were enrolled. The last study patient was discharged from the hospital on December 11, 2023. Patients were randomly assigned to a strategy of tight or relaxed potassium control (only supplementing if serum potassium concentration fell below 4.5 mEq/L or 3.6 mEq/L, respectively). Patients wore an ambulatory heart rhythm monitor, which was analyzed by a core laboratory masked to treatment assignment. The prespecified primary end point was clinically detected and electrocardiographically confirmed new-onset AFACS in the first 120 hours after CABG surgery or until hospital discharge, whichever occurred first. All primary outcome events were validated by an event validation committee, which was masked to treatment assignment. Noninferiority of relaxed potassium control was defined as a risk difference for new-onset AFACS with associated upper bound of a 1-sided 97.5% CI of less than 10%. Secondary outcomes included other heart rhythm-related events, clinical outcomes, and cost related to the intervention. A total of 1690 patients (mean age, 65 years; 256 [15%] females) were randomized. The primary end point occurred in 26.2% of patients (n = 219) in the tight group and 27.8% of patients (n = 231) in the relaxed group, which is a risk difference of 1.7% (95% CI, -2.6% to 5.9%). There was no difference between the groups in the incidence of at least 1 AFACS episode detected by any means or by ambulatory heart rhythm monitor alone, non-AFACS dysrhythmias, in-patient mortality, or length of stay. Per-patient cost for purchasing and administering potassium was significantly lower in the relaxed group (mean difference, $111.89 [95% CI, $103.60-$120.19]; P <.001). For AFACS prophylaxis, supplementation only when serum potassium concentration fell below 3.6 mEq/L was noninferior to the current widespread practice of supplementing potassium to maintain a serum potassium concentration greater than or equal to 4.5 mEq/L. The lower threshold of supplementation was not associated with any increase in dysrhythmias or adverse clinical outcomes. ClinicalTrials.gov Identifier: NCT04053816.

Patient Driven EKG Device Performance in Adults with Fontan Palliation.

The aim of this study was to evaluate the accuracy of the KardiaMobile (KM) device in adults with a Fontan palliation, and to assess the KM function as a screening tool for atrial arrhythmias. While patient driven electrocardiogram (EKG) devices are becoming a validated way to evaluate cardiac arrhythmias, their role for patients with congenital heart disease is less clear. Patients with single ventricle Fontan palliation have a high prevalence of atrial arrhythmias and represent a unique cohort that could benefit from early detection of atrial arrhythmias. This single center prospective study enrolled adult patients with Fontan palliation to use the KM heart rhythm monitoring device for both symptomatic episodes and asymptomatic weekly screening over a 1-year period. Accuracy was assessed by comparing the automatic KM interpretation (KM-auto) to an electrophysiologist overread (KM-EP) and traditional EKG. Fifty patients were enrolled and 510 follow-up transmissions were received. The sensitivity and specificity of enrollment KM-auto compared to EKG was 65% and 100%, respectively. The sensitivity and specificity of enrollment KM-auto compared to the KM-EP was 75% and 96%, respectively. In the adult Fontan palliation, the accuracy of the KM device to detect a normal rhythm was reliable and best with a physician overread. Abnormal or uninterpretable KM-auto device interpretations, symptomatic transmissions, and any transmissions with a high heart rate compared to a patient's normal baseline should warrant further review.

Dispositivos digitales para la monitorización del ritmo cardiaco en pacientes con fibrilación auricular programados para cardioversión eléctrica ambulatoria

Introduction and objectivesManagement in recent-onset atrial fibrillation (AF) is to achieve sinus rhythm (SR) by cardioversion (CV). However, frequently SR is spontaneously restored, making scheduled admission unnecessary and causing misutilization of healthcare resources. Emerging medical technology allows accurate heart rhythm monitoring. This study evaluated this technology in these patients, preventing unnecessary admission and providing an earlier management. MethodsA multicenter study was designed including patients with AF scheduled for elective electrical CV. Patients submitted ECG recordings to a central CoreLab daily, twice a day and whenever they present symptoms, until CV (spontaneous or scheduled) and a week afterwards. Whenever a spontaneous conversion to SR was detected, investigators were contacted to confirm SR and abort admission. Patients’ satisfaction was evaluated using a test for perceived utility, convenience, and accessibility. Results74 patients were enrolled (age 62±10 years). Twenty-two patients (30%) showed spontaneous conversion to SR. A total of 22 admissions and 16 transesophageal echocardiograms were prevented. Among 52 patients admitted for CV, 45 (88%) were discharged in SR. During follow-up after conversion to SR (spontaneous or electrical), recurrences of AF occurred in 24 patients (34%). At the end of the follow-up 51 patients (69%) remained in SR. The CoreLab received 93% of the expected ECG transmissions. Patient's overall satisfaction score was 9.1 over 10. ConclusionDigital devices for heart rhythm monitoring can optimize the management of AF patients scheduled for elective CV, preventing unnecessary admissions and providing a more rational use of healthcare resources.

Clinical presentation and genetic characterization of early-onset atrial fibrillation in patients affected by long QT syndrome: A single-center experience.

Early-onset atrial fibrillation (AF) has already been observed in approximately 2% of patients with genetically proven long QT syndrome (LQTS). This frequency is higher than population-based estimates of early-onset AF. However, the concomitant expression of AF in LQTS is likely underestimated. The purpose of this study was to examine the clinical presentation, genetic background, and outcomes of a cohort of patients with LQTS and early-onset AF referred to a single tertiary center. Twenty-seven patients diagnosed with congenital LQTS were included in the study based on the documentation of early-onset (age ≤50 years) clinical or subclinical AF episodes in all available medical records, including standard electrocardiograms, wearable monitor or cardiac implantable electronic devices. Seventeen patients experienced clinical AF during the follow-up period. Subclinical AF was detected in 10 patients through insertable or wearable cardiac monitors. In our series, the mean heart rate during AF episodes was found to be relatively low despite the patients' young age and the low or minimal effective doses of beta-blockers used for QTc interval control. All patients exhibiting LQTS and early-onset AF were genotype positive, carrying mutations in the KCNQ1 (66%), KCNH2, KCNE1, and SCN5A genes. Notably, most of these patients carried the same p.(R231C) mutation in the KCNQ1 gene (59%) and were from the same families, suggesting concurrent expression of familial AF and LQTS. LQTS patients are prone to developing clinical and subclinical AF, even at a younger age. The occurrence of early-onset AF in the LQTS population could be more frequent than previously assumed. AF should be considered as a potential dysrhythmia related to LQTS. Our study emphasizes the importance of carefully researching clinical and/or subclinical episodes of AF through strict heart rhythm monitoring in the LQTS population.

An Untethered Heart Rhythm Monitoring System with Automated AI‐Based Arrhythmia Detection for Closed‐Loop Experimental Application

AbstractThe heart produces bioelectrical signals, which can be measured as an electrocardiogram (ECG) for the detection of rhythm disturbances. Rapid and precise detection of these arrhythmias is crucial for their termination by closed‐looped therapeutic interventions to counteract detrimental effects. However, there is a current lack of such systems tailored for experimental cardiovascular applications. This hampers not only in‐depth mechanistic studies but also translational testing of new therapeutic strategies, especially in an untethered manner in awake animal models. To break new ground, recent advances to develop a non‐invasive AI‐supported heart rhythm monitoring system for untethered automated arrhythmia detection in a continuous manner is combined. This system is housed in a lightweight jacket for mobile use and includes an on‐skin ECG sensor, a low‐power microprocessor unit, a massive data storage unit, and a power‐management system. By implementing a novel hybrid algorithm based on so‐called heart rate (R‐R) variability and a case‐specific AI model, 100% sensitivity and 95% specificity is achieved in detecting atrial arrhythmias within 2 s upon initiation in adult rats. Thereby, the novel system sets the stage for advanced mechanistic studies and therapeutic testing, including closed‐loop applications aiming for the termination of a broad range of atrial arrhythmias.

The Usefulness of Outpatient Cardiac Telemetry in Patients with Cryptogenic Stroke.

Introduction: Atrial fibrillation (AF), apart from non-stenotic supracardiac atherosclerosis and neoplastic disease, is the leading cause of cryptogenic stroke, including embolic stroke of un-determined source (ESUS). The aim of our study was to determine the prevalence of AF in ESUS patients based on 30-day telemetric heart rate monitoring initiated within three months after stroke onset. Another aim was to identify factors that increase the likelihood of detecting subsequent AF among ESUS patients. Material and Methods: patients with first-ever stroke classified as per the ESUS definition were eligible for this study. All patients underwent outpatient 30-day telemetric heart rate monitoring. Results: In the period between 2020 and 2022, 145 patients were included. The mean age of all qualified patients was 54; 40% of eligible patients were female. Six patients (4.14%), mostly male patients (4 vs. 2), were diagnosed with AF within the study period. In each case, the diagnosis related to a patient whose stroke occurred in the course of large vessel occlusion. Episodes of AF were detected between day 1 and 25 after starting ECG monitoring. Out of the analyzed parameters that increase the probability of, A.F.; only supraventricular extrasystoles proved to be an independent factor regarding an increased risk of AF [OR 1.046, CI 95% 1.016-1.071, p-value < 0.01]. Conclusions: The use of telemetry heart rhythm monitoring in an outpatient setting can detect AF in 4% of ESUS patients who have undergone prior diagnostic procedures for cardiogenic embolism. Supraventricular extrasystoles significantly increases the likelihood of AF detection in patients with ESUS within three months following stroke. Comorbid coronary artery disease, diabetes and hypertension, rather than a single-factor clinical burden, increase the likelihood of AF detection in older ESUS patients. ESUS in the course of large vessel occlusion is probably associated with an increased likelihood of cardiogenic embolism.

Efficacy of smart device heart rhythm monitoring to detect spontaneous conversion to sinus rhythm in patients scheduled for electric cardioversion of atrial fibrillation. Kardiover Study

Abstract Introduction the management of patients with recent-onset atrial fibrillation (AF) is to achieve sinus rhythm (SR) by electrical or pharmacological cardioversion (CV). However, frequently SR is spontaneously restored, making scheduled admission and/or transesophageal echocardiogram (TEE) unnecessary and therefore causing misutilization of healthcare resources. Emerging medical technology has allowed for monitoring of heart rhythm abnormalities. Objective A prospective multicenter study was designed to evaluate the diagnostic ability of a smart device ECG monitor to detect spontaneous conversion to SR in AF patients, preventing unnecessary admission and providing an earlier management. Methods A prospective multicenter study was designed including patients with first diagnosed, paroxysmal or persistent AF scheduled for ambulatory electrical cardioversion in cardiology departments of 7 hospitals of Spain. Patients were asked to submit ECG recordings to a central Corelab daily, twice a day and whenever they present symptoms, until cardioversion (spontaneous or scheduled) and a week afterwards. Whenever a spontaneous conversion to SR was detected, investigators were contacted to confirm SR and abort admission, likewise when AF recurrence after cardioversion was detected. Patients’ satisfaction was evaluated using a test for perceived utility and value, convenience, and accessibility. Results A total of 62 patients were enrolled (age 62±10 years). Baseline characteristics of the study population are described in the Table. Fifteen patients (24%) did not undergo CV as they showed spontaneous conversion to SR. Among 47 patients admitted for CV, it was successful in 41 (87%). One patient aborted CV because of atrial thrombus on TEE. During follow up after conversion to SR (spontaneous or electrical), recurrences of AF occurred in 20 of 56 patients (36%) correctly detected by the devices. At the end of the follow-up 41 of 56 patients (73%) remained in SR. Due to the early detection of spontaneous conversion to SR, a total of 15 admissions and 9 TEE were prevented and these resources used for other patients. Adherence was high with a rate of ECG transmission over 80% in 56 patients (90%). Perceived satisfaction was also high with an overall punctuation of 9 over 10 in the patient’s feedback test. Conclusion Digital devices for heart rhythm monitoring can optimize the management of AF patients scheduled for CV, avoiding unnecessary admissions and providing a more rational use of healthcare resources.Table

ATRIAL FIBRILLATION IN A CIED POPULATION: RESULTS FROM A TELEMONITORING FOLLOW–UP

Abstract Background Telemedicine has emerged as a crucial tool in managing patients with Cardiac Implantable Electronic Devices (CIED), addressing the common challenge of the Atrial Fibrillation (AF) in cardiology. The incidence of AF in CIED recipients varies widely (30–70%), influenced by implant indication, device type, and population characteristics. This study aims to evaluate AF in an unselected, real–world CIED population, considering patients’ characteristics and the remote follow–up. Methods and Results 808 consecutive CIED recipients were evaluated between 2021 and 2023 in two Italian Division of Cardiology by collecting patients’ baseline characteristics and the scheduled remote follow–up data. Mean age was 75.6±12.6 years, 42% were females. 16.7% of the population was working actively and 73% of individuals were assisted by at least one caregiver, reflecting a diminished quality of life (EQ–5D score 8.9±4.3). Over a median follow–up of 20.6 months, 8.9% of patients died. 68.8% of the patients received a pacemaker, 19.3% an ICD and 11.9% a loop recorder. History of AF was present in 40.1% of the population, with a prevalence of permanent AF (46.6%). Ongoing anticoagulant therapy was documented in 303 patients (37.5%), 71% of whom were taking direct oral anticoagulants. Baseline CHA2DS2–VASC score was ≥3 in 79.7%, and the median HAS–BLED score was 1. During the observation period, scheduled remote transmissions revealed 719 AF episodes (15.7 episodes/patient/year), causing 21% of the overall remote alarms. Among patients without AF history, 69 (14.3%) experienced AF episodes (4.8 episodes/patient/year). Notably, 21.8% of the AF episodes lasted less than 10 minutes. Conclusions The wide spreading of heart rhythm monitoring technologies reveals the challenge of the subclinical AF in healthcare systems. This study, encompassing an unselected CIED population of elderly and frail patients with high AF prevalence, highlights AF as a primary cause of remote alerts and a substantial burden in telemonitoring controls. Telemedicine facilitated new AF diagnoses in 14.3% of individuals without a prior AF history and resulted a valuable tool considering the significant cardioembolic risk in these patients. However, the initiation of anticoagulation therapy remains debatable, especially for episodes of brief duration which in our experience exceeded 20% of the cases.

Atrial fibrillation incidence after coronary artery bypass graft surgery and percutaneous coronary intervention: the prospective AFAF cohort study

Objectives. Atrial fibrillation is a common arrhythmia in patients with ischemic heart disease. This study aimed to determine the cumulative incidence of new-onset atrial fibrillation after percutaneous coronary intervention or coronary artery bypass grafting surgery during 30 days of follow-up. Design. This was a prospective multi-center cohort study on atrial fibrillation incidence following percutaneous coronary intervention or coronary artery bypass grafting for stable angina or non-ST-elevation acute coronary syndrome. Heart rhythm was monitored for 30 days postoperatively by in-hospital telemetry and handheld thumb ECG recordings after discharge were performed. The primary endpoint was the cumulative incidence of atrial fibrillation 30 days after the index procedure. Results. In-hospital atrial fibrillation occurred in 60/123 (49%) coronary artery bypass graft and 0/123 percutaneous coronary intervention patients (p < .001). The cumulative incidence of atrial fibrillation after 30 days was 56% (69/123) of patients undergoing coronary artery bypass grafting and 2% (3/123) of patients undergoing percutaneous coronary intervention (p < .001). CABG was a strong predictor for atrial fibrillation compared to PCI (OR 80.2, 95% CI 18.1–354.9, p < .001). Thromboembolic stroke occurred in-hospital in one coronary artery bypass graft patient unrelated to atrial fibrillation, and at 30 days in two additional patients, one in each group. There was no mortality. Conclusion. New-onset atrial fibrillation during 30 days of follow-up was rare after percutaneous coronary intervention but common after coronary artery bypass grafting. A prolonged uninterrupted heart rhythm monitoring strategy identified additional patients in both groups with new-onset atrial fibrillation after discharge.

Home monitoring of fetal heart rhythm: Lived experiences of women with anti-SSA/Ro52 autoantibodies and their co-parents.

The aim of this study was to explore the parents' experiences of home monitoring of the fetal heart rhythm. Women with anti-SSA/Ro52 autoantibodies carry a 2%-3% risk of giving birth to a child with congenital heart block (CHB), following transplacental transfer and antibody-mediated inflammation in the fetal conduction system during 18th to 24th gestational week. Early detection and subsequent treatment have been reported to decrease morbidity and mortality. Therefore, home monitoring of the fetal heart rhythm by Doppler has been offered at our fetal cardiology center. This study was undertaken to explore the lived experience of the routine. Participants were recruited from a single fetal cardiology center. Consecutive sampling was used. The inclusion criteria were women with SSA/Ro52 antibodies who had undergone Doppler examinations within the last two and a half years at the hospital and had monitored the fetal heartbeat at home. A semi-structured questionnaire was created, and the participants were interviewed individually. The interviews were transcribed verbatim and analyzed according to qualitative content analysis. The overall theme was defined as "walking on thin ice," with six underlying categories: reality, different strategies, gain and loss, healthcare providers, underlying tension, and conducting the examinations again, all with a focus on how to handle the home monitoring during the risk period. Both the mother and the co-parent expressed confidence in their own abilities and that the monitoring provided them with the advantage of growing a bond with the expected child. However, all the participants described a feeling of underlying tension during the risk period. The results show that home monitoring is not experienced as complicated or a burden for the parents-to-be and should be considered a vital part of the chain of care for mothers at risk for giving birth to a child with CHB. However, explaining the teamwork between the different caregivers, for the patients involved, their areas of expertise, and how they collaborate with the patient continues to be a pedagogic challenge and should be developed further.

Determining The Risk of Atrial Fibrillation Paroxysm in Patients With Chronic Heart Failure With Intact and Reduced Ejection Fraction.

To determine predictors for the development of atrial fibrillation (AF) in patients with chronic heart failure (CHF) with preserved and reduced ejection fraction by echocardiography (EchoCG) according to an extended protocol with determination of diastolic function and left atrial global strain. Data of 168 patients with stage I-III CHF without a history of AF were analyzed. All patients underwent echocardiography according to an extended protocol with the determination of diastolic dysfunction (DD), left atrial ejection fraction (LA EF), and left atrial global strain (LA GS). Tissue Doppler imaging (TDI) was used to evaluate the early (E) and late (A) LV filling velocity and the early (E') and late (A') diastolic mitral annular velocity. In all patients, Holter ECG monitoring (HM ECG) of heart rhythm was performed for 3 days, and ECG monitoring with telemedicine technologies was performed for 7 days, 3 times a day for 3 minutes. The follow-up period was 3 months or until an AF episode. During the study, paroxysmal AF (pAF) was detected in 41 (24.4%) patients using various methods of heart rhythm monitoring. Complaints of palpitations were noted for 10 (24.4%) patients during pAF, which was recorded using a CardioQVARK® device, HM ECG or a 12-lead ECG. In 5 (12.2%) patients, daily ECG monitoring revealed pAF without associated complaints. HM ECG detected 8, 2, 4 (19.5%, 4.8%, and 9.7%) cases during 24, 48 and 72 hours, respectively; a single-channel CardioQVARK® detected 30 (73.2%) cases when used 3 times a day for 7 days. These results showed that AF frequently develops in CHF without accompanying symptoms. The method for detecting pAF with CardioQVARK® showed good results: it was twice more effective than HM ECG and three times more effective than 12-lead ECG. Also, according to ultrasound data, significant changes in the following parameters were noted in patients with AF: LA EF &lt;36% (OR 1.04, 95% CI: 1.02-1.08), p=0.003; LA GS &lt;9.9% (OR 1.16, 95% CI: 1.02-1.38), p&lt;0.001; TDI E med &lt;5.7 cm/s (OR 0.97, 95% CI: 0.94-1.00), p=0.026. Grade 2 DD did not show statistically significant results (OR 1.1, 95% CI: 0.7-1.5, p=0.54). However, it was detected more frequently in patients with AF, in 34% of cases, compared to 29% of cases in patients without AF, which requires further study on a larger patient sample. Patients with CHF have a high risk of developing pAF (24.4%). 75% of patients with AF do not feel the development of paroxysm. All CHF patients should undergo EchoCG with assessment of LA EF, TDI E med and LA GS to identify a group at risk for the development of AF. Heart rhythm remote monitoring with CardioQVARK® devices can be considered a reliable method for early detection of pAF and timely initiation of anticoagulant therapy in patients with CHF.

Real-world validation of smartphone-based photoplethysmography for rate and rhythm monitoring in atrial fibrillation.

Photoplethysmography- (PPG) based smartphone applications facilitate heart rate and rhythm monitoring in patients with paroxysmal and persistent atrial fibrillation (AF). Despite an endorsement from the European Heart Rhythm Association, validation studies in this setting are lacking. Therefore, we evaluated the accuracy of PPG-derived heart rate and rhythm classification in subjects with an established diagnosis of AF in unsupervised real-world conditions. Fifty consecutive patients were enrolled, 4 weeks before undergoing AF ablation. Patients used a handheld single-lead electrocardiography (ECG) device and a fingertip PPG smartphone application to record 3907 heart rhythm measurements twice daily during 8 weeks. The ECG was performed immediately before and after each PPG recording and was given a diagnosis by the majority of three blinded cardiologists. A consistent ECG diagnosis was exhibited along with PPG data of sufficient quality in 3407 measurements. A single measurement exhibited good quality more often with ECG (93.2%) compared to PPG (89.5%; P < 0.001). However, PPG signal quality improved to 96.6% with repeated measurements. Photoplethysmography-based detection of AF demonstrated excellent sensitivity [98.3%; confidence interval (CI): 96.7-99.9%], specificity (99.9%; CI: 99.8-100.0%), positive predictive value (99.6%; CI: 99.1-100.0%), and negative predictive value (99.6%; CI: 99.0-100.0%). Photoplethysmography underestimated the heart rate in AF with 6.6 b.p.m. (95% CI: 5.8 b.p.m. to 7.4 b.p.m.). Bland-Altman analysis revealed increased underestimation in high heart rates. The root mean square error was 11.8 b.p.m. Smartphone applications using PPG can be used to monitor patients with AF in unsupervised real-world conditions. The accuracy of AF detection algorithms in this setting is excellent, but PPG-derived heart rate may tend to underestimate higher heart rates.