Artificial Intelligence-Based Atrial Fibrillation Recognition Method for Motion Artifact-Contaminated Electrocardiogram Signals Preprocessed by Adaptive Filtering Algorithm.

Atrial fibrillation (AF) is a common arrhythmia, and out-of-hospital, wearable, long-term electrocardiogram (ECG) monitoring can help with the early detection of AF. The presence of a motion artifact (MA) in ECG can significantly affect the characteristics of the ECG signal and hinder early detection of AF. Studies have shown that (a) using reference signals with a strong correlation with MAs in adaptive filtering (ADF) can eliminate MAs from the ECG, and (b) artificial intelligence (AI) algorithms can recognize AF when there is no presence of MAs. However, no literature has been reported on whether ADF can improve the accuracy of AI for recognizing AF in the presence of MAs. Therefore, this paper investigates the accuracy of AI recognition for AF when ECGs are artificially introduced with MAs and processed by ADF. In this study, 13 types of MA signals with different signal-to-noise ratios ranging from +8 dB to -16 dB were artificially added to the AF ECG dataset. Firstly, the accuracy of AF recognition using AI was obtained for a signal with MAs. Secondly, after removing the MAs by ADF, the signal was further identified using AI to obtain the accuracy of the AF recognition. We found that after undergoing ADF, the accuracy of AI recognition for AF improved under all MA intensities, with a maximum improvement of 60%.

Clinical outcomes of catheter ablation for atrial fibrillation, atrial flutter, and atrial tachycardia in wild-type transthyretin amyloid cardiomyopathy: a proposed treatment strategy for catheter ablation in each arrhythmia.

AIMS: Wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM) is often accompanied by atrial fibrillation (AF), atrial flutter (AFL), and atrial tachycardia (AT), which are difficult to control because beta-blockers and antiarrhythmic drugs can worsen heart failure (HF). This study aimed to investigate the outcomes of catheter ablation (CA) for AF/AFL/AT in patients with ATTRwt-CM and propose a treatment strategy for CA. METHODS AND RESULTS: A cohort study was conducted on 233 patients diagnosed with ATTRwt-CM, including 54 who underwent CA for AF/AFL/AT. The background of each arrhythmia and the details of the CA and its outcomes were investigated. The recurrence-free rate of AF/AFL/AT overall in ATTRwt-CM patients with multiple CA was 70.1% at 1-year, 57.6% at 2-year, and 44.0% at 5-year follow-up, but CA significantly reduced all-cause mortality [hazard ratio (HR): 0.342, 95% confidence interval (CI): 0.133-0.876, P = 0.025], cardiovascular mortality (HR: 0.378, 95% CI: 0.146-0.981, P = 0.045), and HF hospitalization (HR: 0.488, 95% CI: 0.269-0.889, P = 0.019) compared with those without CA. There was no recurrence of the cavotricuspid isthmus (CTI)-dependent AFL, non-CTI-dependent simple AFL terminated by one linear ablation, and focal AT originating from the atrioventricular (AV) annulus or crista terminalis eventually. Twelve of 13 patients with paroxysmal AF and 27 of 29 patients with persistent AF did not have recurrence as AF. However, all three patients with non-CTI-dependent complex AFL not terminated by a single linear ablation and 10 of 13 cases with focal AT or multiple focal ATs originating beyond the AV annulus or crista terminalis recurred even after multiple CA. CONCLUSION: The outcomes of CA for ATTRwt-CM were acceptable, except for multiple focal AT and complex AFL. Catheter ablation may be aggressively considered as a treatment strategy with the expectation of improving mortality and hospitalization for HF.

Antiarrhythmic drug therapy and catheter ablation in patients with paroxysmal or persistent atrial fibrillation: a systematic review and meta-analysis.

BACKGROUND: Catheter ablation and antiarrhythmic drug therapy are utilized for rhythm control in atrial fibrillation (AF), but their comparative effectiveness, especially with contemporary treatment modalities, remains undefined. We conducted a systematic review and meta-analysis contrasting current ablation techniques against antiarrhythmic medications for AF. METHODS: We searched PubMed, SCOPUS, Cochrane CENTRAL, and Web of Science until November 2023 for randomized trials comparing AF catheter ablation with antiarrhythmics, against antiarrhythmic drug therapy alone, reporting outcomes for > 6 months. Four investigators extracted data and appraised risk of bias (ROB) with ROB 2 tool. Meta-analyses estimated pooled efficacy and safety outcomes using R software. RESULTS: Twelve trials (n = 3977) met the inclusion criteria. Catheter ablation was associated with lower AF recurrence (relative risk (RR) = 0.44, 95%CI (0.33, 0.59), P ˂ 0.0001) and hospitalizations (RR = 0.44, 95%CI (0.23, 0.82), P = 0.009) than antiarrhythmic medications. Catheter ablation also improved the physical quality of life component score (assessed by a 36-item Short Form survey) by 7.61 points (95%CI -0.70-15.92, P = 0.07); but, due to high heterogeneity, it was not statistically significant. Ablation was significantly associated with higher procedural-related complications [RR = 15.70, 95%CI (4.53, 54.38), P < 0.0001] and cardiac tamponade [RR = 9.22, 95%CI (2.16, 39.40), P = 0.0027]. All-cause mortality was similar between the two groups. CONCLUSIONS: For symptomatic AF, upfront catheter ablation reduces arrhythmia and hospitalizations better than continued medical therapy alone, albeit with moderately more adverse events. Careful patient selection and risk-benefit assessment are warranted regarding the timing of ablation.

Initial real-world data on catheter ablation in patients with persistent atrial fibrillation using the novel lattice-tip focal pulsed-field ablation catheter.

AIMS: Technological advancements have contributed to the enhanced precision and lesion flexibility in pulsed-field ablation (PFA) by integrating a three-dimensional mapping system combined with a point-by-point ablation strategy. Data regarding the feasibility of this technology remain limited to some clinical trials. This study aims to elucidate initial real-world data on catheter ablation utilizing a lattice-tip focal PFA/radiofrequency ablation (RFA) catheter in patients with persistent atrial fibrillation (AF). METHODS AND RESULTS: Consecutive patients who underwent catheter ablation for persistent AF via the lattice-tip PFA/RFA catheter were enrolled. We evaluated acute procedural data including periprocedural data as well as the clinical follow-up within a 90-day blanking period. In total, 28 patients with persistent AF underwent AF ablation either under general anaesthesia (n = 6) or deep sedation (n = 22). In all patients, pulmonary vein isolation was successfully achieved. Additional linear ablations were conducted in 21 patients (78%) with a combination of successful anterior line (n = 13, 46%) and roof line (n = 19, 68%). The median procedural and fluoroscopic times were 97 (interquartile range, IQR: 80-114) min and 8.5 (IQR: 7.2-9.5) min, respectively. A total of 27 patients (96%) were interviewed during the follow-up within the blanking period, and early recurrent AF was documented in four patients (15%) including one case of recurrent AF during the hospital stay. Neither major nor minor procedural complication occurred. CONCLUSION: In terms of real-world data, our data confirmed AF ablation feasibility utilizing the lattice-tip focal PFA/RFA catheter in patients with persistent AF.

Is Stroke risk analysis (SRA) a reliable method for predicting atrial fibrillation? A systematic review.

INTRODUCTION: Atrial fibrillation is responsible for a considerable number of cases of cardioembolism, accounting for 17% to 30% of the etiologies of all strokes. The software known as Stroke Risk Analysis (SRA) detects patients at high risk of paroxysmal atrial fibrillation by analyzing a continuous electrocardiogram recorded over different periods of time. OBJECTIVES: This article aims to carry out a systematic review investigating the effectiveness of the SRA method in predicting the risk of stroke patients having paroxysmal atrial fibrillation as the cause of the event. METHODS: The methods correspond to the format of the International Prospective Register of Systematic Reviews Protocol, according to CRD Identification Code: CRD42021253974. A systematic search was carried out in BMJB, PubMed/MEDLINE, Science Direct and LILACS. Six cohort studies met the inclusion criteria, representing a total of 2,088 participants with stroke, and compared the detection of patients with paroxysmal atrial fibrillation on the continuous recording electrocardiogram with a time variation of 1 to 48h with the use of SRA. RESULTS: Studies have shown that SRA has a high negative predictive value (between 96 and 99.1%) and can contribute to the selection of patients at high risk of paroxysmal atrial fibrillation to be referred for implantable cardiac monitoring to continue the investigation. CONCLUSIONS: A sequential combination of SRA with implantable cardiac monitoring is a promising strategy for detecting undiagnosed paroxysmal atrial fibrillation. Thus, the SRA can act as a cost-effective pre-selection tool to identify patients at higher risk of having paroxysmal atrial fibrillation as a possible cause of stroke and who may benefit from implantable cardiac monitoring. However, the lack of randomized studies is a limitation that must be considered.

Repurposing Metformin for the Treatment of Atrial Fibrillation: Current Insights.

Metformin is an orally effective anti-hyperglycemic drug that despite being introduced over 60 years ago is still utilized by an estimated 120 to 150 million people worldwide for the treatment of type 2 diabetes (T2D). Metformin is used off-label for the treatment of polycystic ovary syndrome (PCOS) and for pre-diabetes and weight loss. Metformin is a safe, inexpensive drug with side effects mostly limited to gastrointestinal issues. Prospective clinical data from the United Kingdom Prospective Diabetes Study (UKPDS), completed in 1998, demonstrated that metformin not only has excellent therapeutic efficacy as an anti-diabetes drug but also that good glycemic control reduced the risk of micro- and macro-vascular complications, especially in obese patients and thereby reduced the risk of diabetes-associated cardiovascular disease (CVD). Based on a long history of clinical use and an excellent safety record metformin has been investigated to be repurposed for numerous other diseases including as an anti-aging agent, Alzheimer's disease and other dementias, cancer, COVID-19 and also atrial fibrillation (AF). AF is the most frequently diagnosed cardiac arrythmia and its prevalence is increasing globally as the population ages. The argument for repurposing metformin for AF is based on a combination of retrospective clinical data and in vivo and in vitro pre-clinical laboratory studies. In this review, we critically evaluate the evidence that metformin has cardioprotective actions and assess whether the clinical and pre-clinical evidence support the use of metformin to reduce the risk and treat AF.

Non-cardiac comorbidities in heart failure: an update on diagnostic and management strategies.

Managing non-cardiac comorbidities in heart failure (HF) requires a tailored approach that addresses each patient's specific conditions and needs. Regular communication and coordination among healthcare providers is crucial to providing the best possible care for these patients. Poorly controlled hypertension contributes to left ventricular remodeling and diastolic dysfunction, emphasizing the importance of optimal blood pressure control while avoiding adverse effects. Among HF patients with diabetes, SGLT2 inhibitors and mineralocorticoid receptor antagonists have shown promise in reducing HF-related morbidity and mortality. Chronic kidney disease exacerbates HF and vice versa, forming the vicious cardiorenal syndrome, so disease-modifying therapies should be maintained in HF patients with comorbid CKD, even with transient changes in kidney function. Anemia in HF patients may be multifactorial, and there is growing evidence for the benefit of intravenous iron supplementation in HF patients with iron deficiency with or without anemia. Obesity, although a risk factor for HF, paradoxically offers a better prognosis once HF is established, though developing treatment strategies may improve symptoms and cardiac performance. In HF patients with stroke and atrial fibrillation, anticoagulation therapy is recommended. Among HF patients with sleep-disordered breathing, continuous positive airway pressure may improve sleep quality. Chronic obstructive pulmonary disease often coexists with HF, and many patients can tolerate cardioselective beta-blockers. Cancer patients with comorbid HF require careful consideration of cardiotoxicity risks associated with cancer therapies. Depression is underdiagnosed in HF patients and significantly impacts prognosis. Cognitive impairment is prevalent in HF patients and impacts their self-care and overall quality of life.

Left atrial appendage closure in a patient previously implanted with an interatrial shunt device: a case report.

Patients with previous interatrial shunt device (IASD) implantation may face greater challenges during future left atrial interventional procedures. Herein, we report the first case of left atrial appendage closure (LAAC) in a patient with previous IASD implantation. The patient successfully underwent LAAC using the LAmbre device without complications.

Multiscale dilated convolutional neural network for Atrial Fibrillation detection.

Atrial Fibrillation (AF), a type of heart arrhythmia, becomes more common with aging and is associated with an increased risk of stroke and mortality. In light of the urgent need for effective automated AF monitoring, existing methods often fall short in balancing accuracy and computational efficiency. To address this issue, we introduce a framework based on Multi-Scale Dilated Convolution (AF-MSDC), aimed at achieving precise predictions with low cost and high efficiency. By integrating Multi-Scale Dilated Convolution (MSDC) modules, our model is capable of extracting features from electrocardiogram (ECG) datasets across various scales, thus achieving an optimal balance between precision and computational savings. We have developed three MSDC modules to construct the AF-MSDC framework and assessed its performance on renowned datasets, including the MIT-BIH Atrial Fibrillation Database and Physionet Challenge 2017. Empirical results unequivocally demonstrate that our technique surpasses existing state-of-the-art (SOTA) methods in the AF detection domain. Specifically, our model, with only a quarter of the parameters of a Residual Network (ResNet), achieved an impressive sensitivity of 99.45%, specificity of 99.64% (on the MIT-BIH AFDB dataset), and an [Formula: see text] score of 85.63% (on the Physionet Challenge 2017 AFDB dataset). This high efficiency makes our model particularly suitable for integration into wearable ECG devices powered by edge computing frameworks. Moreover, this innovative approach offers new possibilities for the early diagnosis of AF in clinical applications, potentially improving patient quality of life and reducing healthcare costs.

Observational study protocol for an arrhythmia notification feature.

INTRODUCTION: Screening for atrial fibrillation (AF) in the general population may help identify individuals at risk, enabling further assessment of risk factors and institution of appropriate treatment. Algorithms deployed on wearable technologies such as smartwatches and fitness bands may be trained to screen for such arrhythmias. However, their performance needs to be assessed for safety and accuracy prior to wide-scale implementation. METHODS AND ANALYSIS: This study will assess the ability of the WHOOP strap to detect AF using its WHOOP Arrhythmia Notification Feature (WARN) algorithm in an enriched cohort with a 2:1 distribution of previously diagnosed AF (persistent and paroxysmal) and healthy controls. Recruited participants will collect data for 7 days with the WHOOP wrist-strap and BioTel ePatch (electrocardiography gold-standard). Primary outcome will be participant level sensitivity and specificity of the WARN algorithm in detecting AF in analysable windows compared with the ECG gold-standard. Similar analyses will be performed on an available epoch-level basis as well as comparison of these findings in important subgroups. ETHICS AND DISSEMINATION: The study was approved by the ethics board at the study site. Participants will be enrolled after signing an online informed consent document. Updates will be shared via clinicaltrials.gov. The data obtained from the conclusion of this study will be presented in national and international conferences with publication in clinical research journals. TRIAL REGISTRATION NUMBER: NCT05809362.

The relationship between ambulatory arterial stiffness index and incident atrial fibrillation.

BACKGROUND: The ambulatory arterial stiffness index (AASI) is an indirect measure of blood pressure variability and arterial stiffness which are atrial fibrillation (AF) risk factors. The relationship between AASI and AF development has not been previously investigated and was the primary aim of this study. METHODS: This was an observational cohort study of adults (aged 18-85 years) in sinus rhythm, who underwent 24-h ambulatory blood pressure monitoring (ABPM) for the diagnosis of hypertension or its control. RESULTS: Eight hundred and twenty-one patients (49% men) aged 58.7 ± 15.3 years were followed up for a median of 4.0 years (3317 patient-years). In total, 75 patients (9.1%) developed ≥1 AF episode during follow-up. The mean AASI was 0.46 ± 0.17 (median 0.46). AASI values (0.52 ± 0.16 vs. 0.45 ± 0.17; p < .001) and the proportion of AASI values above the median (65.3% vs. 48.4%; p = .005) were greater among the patients who developed AF versus those that did not respectively. AASI significantly correlated with age (r = .49; 95% confidence interval: 0.44-0.54: p < .001). On Kaplan-Meier analysis, higher baseline AASI by median, tertiles, and quartiles were all significantly associated with AF development (X2: 10.13; p < .001). On Cox regression analyses, both a 1-standard deviation increase and AASI > median were independent predictors of AF, but this relationship was no longer significant when age was included in the model. CONCLUSIONS: AASI is an independent predictor of AF development. However, this relationship becomes insignificant after adjustment for age which is higher correlated with AASI.

In Silico TRials guide optimal stratification of ATrIal FIbrillation patients to Catheter Ablation and pharmacological medicaTION: the i-STRATIFICATION study.

AIMS: Patients with persistent atrial fibrillation (AF) experience 50% recurrence despite pulmonary vein isolation (PVI), and no consensus is established for secondary treatments. The aim of our i-STRATIFICATION study is to provide evidence for stratifying patients with AF recurrence after PVI to optimal pharmacological and ablation therapies, through in silico trials. METHODS AND RESULTS: A cohort of 800 virtual patients, with variability in atrial anatomy, electrophysiology, and tissue structure (low-voltage areas, LVAs), was developed and validated against clinical data from ionic currents to electrocardiogram. Virtual patients presenting AF post-PVI underwent 12 secondary treatments. Sustained AF developed in 522 virtual patients after PVI. Second ablation procedures involving left atrial ablation alone showed 55% efficacy, only succeeding in the small right atria (<60 mL). When additional cavo-tricuspid isthmus ablation was considered, Marshall-PLAN sufficed (66% efficacy) for the small left atria (<90 mL). For the bigger left atria, a more aggressive ablation approach was required, such as anterior mitral line (75% efficacy) or posterior wall isolation plus mitral isthmus ablation (77% efficacy). Virtual patients with LVAs greatly benefited from LVA ablation in the left and right atria (100% efficacy). Conversely, in the absence of LVAs, synergistic ablation and pharmacotherapy could terminate AF. In the absence of ablation, the patient's ionic current substrate modulated the response to antiarrhythmic drugs, being the inward currents critical for optimal stratification to amiodarone or vernakalant. CONCLUSION: In silico trials identify optimal strategies for AF treatment based on virtual patient characteristics, evidencing the power of human modelling and simulation as a clinical assisting tool.

Procedure Volume and Outcomes With WATCHMAN Left Atrial Appendage Occlusion.

BACKGROUND: Procedure volumes are associated with outcomes for many cardiovascular procedures, leading to guidelines on minimum volume thresholds for certain procedures; however, the volume-outcome relationship with left atrial appendage occlusion is poorly understood. As such, we sought to determine the relationship between hospital and physician volume and WATCHMAN left atrial appendage occlusion procedural success overall and with the new generation WATCHMAN FLX device. METHODS: We performed an analysis of WATCHMAN procedures (January 2019 to October 2021) from the National Cardiovascular Data Registry LAAO Registry. Three-level hierarchical generalized linear models were used to assess the adjusted relationship between procedure volume and procedural success (device released with peridevice leak <5 mm, no in-hospital major adverse events). RESULTS: Among 87 480 patients (76.2±8.0 years; 58.8% men; mean CHA2DS2-VASc score, 4.8±1.5) from 693 hospitals, the procedural success rate was 94.2%. With hospital volume Q4 (greatest volume) as the reference, the likelihood of procedural success was significantly less among Q1 (odds ratio [OR], 0.66 [CI, 0.57-0.77]) and Q2 (OR, 0.78 [CI, 0.69-0.90]) but not Q3 (OR, 0.95 [CI, 0.84-1.07]). With physician volume Q4 (greatest volume) as the reference, the likelihood of procedural success was significantly less among Q1 (OR, 0.72 [CI, 0.63-0.82]), Q2 (OR, 0.79 [CI, 0.71-0.89]), and Q3 (OR, 0.88 [CI, 0.79-0.97]). Among WATCHMAN FLX procedures, there was attenuation of the volume-outcome relationships, with statistically significant but modest absolute differences of only ≈1% across volume quartiles. CONCLUSIONS: In this contemporary national analysis, greater hospital and physician WATCHMAN volumes were associated with increased procedure success. The WATCHMAN FLX transition was associated with increased procedural success and less heterogeneity in outcomes across volume quartiles. These findings indicate the importance of understanding the volume-outcome relationship for individual left atrial appendage occlusion devices.

Screening for Unrecognized HFpEF in Atrial Fibrillation and for Unrecognized Atrial Fibrillation in HFpEF.

Because of the bidirectional relationship between atrial fibrillation (AF) and heart failure with preserved ejection fraction (HFpEF), individuals with either condition require consideration of screening for the other. In this review, we summarize current evidence and rationale for screening for occult HFpEF in adults with clinical AF; and occult AF in patients with clinically recognized HFpEF. Assessment of pretest probability for occult HFpEF in symptomatic AF patients may help guide additional testing such as exercise right heart catheterization to diagnose HFpEF and guide HFpEF-specific therapies. In patients with HFpEF, AF screening will identify cases of occult AF where anticoagulation may decrease stroke risk, and correlation of previously unknown AF episodes with paroxysmal symptoms may prompt consideration for rhythm control. Therefore, screening may help clinicians understand the etiology of the often-overlapping symptoms, and it may help guide treatments to slow progression of both conditions and their complications.

Left atrial function in middle-aged men and women with and without paroxysmal atrial fibrillation: Data from the Akershus Cardiac Examination (ACE) 1950 study.

PURPOSE: To assess left atrial (LA) function in individuals with known paroxysmal atrial fibrillation (AF) compared with healthy and nonhealthy individuals without atrial fibrillation. METHODS: The Akershus Cardiac Examination 1950 Study included 3,706 individuals all born in 1950. LA strain assessment of reservoir (LASr), conduit (LAScd) and contractile (LASct) functions were performed in all participants by investigators blinded to clinical data. Participants with cardiovascular disease, obesity, diabetes, pulmonary or renal disease were defined as nonhealthy, and those without as healthy. Patients with paroxysmal AF were identified through medical history and ECG documentation. RESULTS: LA strain assessment was feasible in 3,229 (87%) of the participants (50% women). The healthy group (n = 758) had significantly higher LASr and LAScd than the nonhealthy (n = 2,376), but LASct was similar between the groups. Participants with paroxysmal AF had significantly lower values of all strain parameters than the other groups. Multivariable logistic regression showed a significantly reduced probability of having AF per standard deviation increase in LASr and LASct. A nonlinear restricted cubic spline model fitted better with the association of LASr with paroxysmal AF than the linear model, and LA strain values below the population mean associated with an increased probability of having AF, but for values above the population mean no such association was present. CONCLUSION: Compared to participants without AF, those with known paroxysmal AF had significantly lower values of all LA strain parameters during sinus rhythm. Lower values of LA strain were associated with a significantly increased probability of having AF.

xECGArch: a trustworthy deep learning architecture for interpretable ECG analysis considering short-term and long-term features.

Deep learning-based methods have demonstrated high classification performance in the detection of cardiovascular diseases from electrocardiograms (ECGs). However, their blackbox character and the associated lack of interpretability limit their clinical applicability. To overcome existing limitations, we present a novel deep learning architecture for interpretable ECG analysis (xECGArch). For the first time, short- and long-term features are analyzed by two independent convolutional neural networks (CNNs) and combined into an ensemble, which is extended by methods of explainable artificial intelligence (xAI) to whiten the blackbox. To demonstrate the trustworthiness of xECGArch, perturbation analysis was used to compare 13 different xAI methods. We parameterized xECGArch for atrial fibrillation (AF) detection using four public ECG databases ( n = 9854 ECGs) and achieved an F1 score of 95.43% in AF versus non-AF classification on an unseen ECG test dataset. A systematic comparison of xAI methods showed that deep Taylor decomposition provided the most trustworthy explanations ( + 24 % compared to the second-best approach). xECGArch can account for short- and long-term features corresponding to clinical features of morphology and rhythm, respectively. Further research will focus on the relationship between xECGArch features and clinical features, which may help in medical applications for diagnosis and therapy.