Citations

Coronavirus disease 2019 (COVID-19) is a global pandemic that is wreaking havoc on the health and economy of much of human civilization. Electrophysiologists have been impacted personally and professionally by this global catastrophe. In this joint article from representatives of the Heart Rhythm Society, the American College of Cardiology, and the American Heart Association, we identify the potential risks of exposure to patients, allied healthcare staff, industry representatives, and hospital administrators. We also describe the impact of COVID-19 on cardiac arrhythmias and methods of triage based on acuity and patient comorbidities. We provide guidance for managing invasive and noninvasive electrophysiology procedures, clinic visits, and cardiac device interrogations. In addition, we discuss resource conservation and the role of telemedicine in remote patient care along with management strategies for affected patients.

Background: The optimal timing of catheter ablation for atrial fibrillation (AF) in reference to the time of diagnosis is unknown. We sought to assess the impact of the duration between first diagnosis of AF and ablation, or diagnosis-to-ablation time (DAT), on AF recurrence following catheter ablation. Methods: We conducted a systematic electronic search for observational studies reporting the outcomes associated with catheter ablation for atrial fibrillation stratified by diagnosis-to-ablation time. The primary meta-analysis using a random effects model assessed AF recurrence stratified by DAT ≤1 year versus >1 year. A secondary analysis assessed outcomes stratified by DAT ≤3 years versus >3 years. Results: Of the 632 screened studies, 6 studies met inclusion criteria for a total of 4950 participants undergoing AF ablation for symptomatic AF. A shorter DAT ≤1 year was associated with a lower relative risk of AF recurrence compared with DAT >1 year (relative risk, 0.73 [95% CI, 0.65–0.82]; P <0.001). Heterogeneity was moderate (I 2 =51%). When excluding the one study consisting of only patients with persistent AF, the heterogeneity improved substantially (I 2 =0%, Cochran’s Q P =0.55) with a similar estimate of effect (relative risk, 0.78 [95% CI, 0.71–0.85]; P <0.001). Conclusions: Shorter duration between time of first AF diagnosis and AF ablation is associated with an increased likelihood of ablation procedural success. Additional study is required to confirm these results and to explore implementation of earlier catheter AF ablation and patient outcomes within the current AF care pathway. Visual Overview A visual overview is available for this article.

Background: Deep learning algorithms derived in homogeneous populations may be poorly generalizable and have the potential to reflect, perpetuate, and even exacerbate racial/ethnic disparities in health and health care. In this study, we aimed to (1) assess whether the performance of a deep learning algorithm designed to detect low left ventricular ejection fraction using the 12-lead ECG varies by race/ethnicity and to (2) determine whether its performance is determined by the derivation population or by racial variation in the ECG. Methods: We performed a retrospective cohort analysis that included 97 829 patients with paired ECGs and echocardiograms. We tested the model performance by race/ethnicity for convolutional neural network designed to identify patients with a left ventricular ejection fraction ≤35% from the 12-lead ECG. Results: The convolutional neural network that was previously derived in a homogeneous population (derivation cohort, n=44 959; 96.2% non-Hispanic white) demonstrated consistent performance to detect low left ventricular ejection fraction across a range of racial/ethnic subgroups in a separate testing cohort (n=52 870): non-Hispanic white (n=44 524; area under the curve [AUC], 0.931), Asian (n=557; AUC, 0.961), black/African American (n=651; AUC, 0.937), Hispanic/Latino (n=331; AUC, 0.937), and American Indian/Native Alaskan (n=223; AUC, 0.938). In secondary analyses, a separate neural network was able to discern racial subgroup category (black/African American [AUC, 0.84], and white, non-Hispanic [AUC, 0.76] in a 5-class classifier), and a network trained only in non-Hispanic whites from the original derivation cohort performed similarly well across a range of racial/ethnic subgroups in the testing cohort with an AUC of at least 0.930 in all racial/ethnic subgroups. Conclusions: Our study demonstrates that while ECG characteristics vary by race, this did not impact the ability of a convolutional neural network to predict low left ventricular ejection fraction from the ECG. We recommend reporting of performance among diverse ethnic, racial, age, and sex groups for all new artificial intelligence tools to ensure responsible use of artificial intelligence in medicine.

Atrial fibrillation (AF) is an important comorbidity in patients with end-stage renal disease (ESRD) undergoing dialysis that portends increased health care utilization, morbidity, and mortality in this already high-risk population. Patients with ESRD have a particularly high stroke risk, which is further compounded by AF. However, the role of anticoagulation for stroke prophylaxis in ESRD and AF is debated. The ESRD population presents a unique challenge because of the combination of elevated stroke and bleeding risks. Warfarin has been traditionally used in this population, but it is associated with significant risks of minor and major bleeding, particularly intracranial, thus leading many clinicians to forgo anticoagulation altogether. When anticoagulation is prescribed, rates of adherence and persistence are poor, leaving many patients untreated. The direct oral anticoagulants (DOACs) may offer an alternative to warfarin in ESRD patients, but these agents have not been extensively studied in this population and uncertainties regarding comparative effectiveness (versus warfarin, each other, and no treatment) remain. In this review, we discuss the current evidence on the risk and benefits of anticoagulants in this challenging population and comparisons between warfarin and DOACs, and review future directions including options for non-pharmacologic stroke prevention.