Noseworthy, Peter A

INTRODUCTION: Building on prior results, we hypothesized that an electrocardiogram (ECG)-enabled machine learning (ML) model could be used to detect advanced chronic liver disease (CLD). METHODS: A cohort with CLD and 12-lead ECGs was matched with controls from electronic health records. A ML model was trained as a binary classifier. RESULTS: There are 12,930 patients with CLD and 64,577 controls in the cohort. The model's discriminative ability to classify CLD showed an area under the receiver-operating characteristic curve 0.858 (95% confidence interval: 0.850–0.866), and at the chosen threshold, CLD ECGs had 12 times higher odds of being classified as CLD (diagnostic odds ratio 12.33, 95% confidence interval: 11.16–13.63). DISCUSSION: An ECG-enabled ML model affords great promise in identifying advanced CLD in low resource areas.

Hypertension is the leading modifiable risk factor for atrial fibrillation (AF) and is estimated to be present in >70% of AF patients. This Frontiers Review was prepared by 29 expert members of the AF-SCREEN International Collaboration to summarize existing evidence and knowledge gaps on links between hypertension, AF, and their cardiovascular sequelae; simultaneous screening for hypertension and AF; and the prevention of AF through antihypertensive therapy. Hypertension and AF are inextricably connected. Both are easily diagnosed, often silent, and frequently treated inadequately. Together, they additively increase the risk of ischemic stroke, heart failure, and many types of dementia, resulting in greater all-cause mortality, considerable disease burden, and increased health care expenditures. Automated upper arm cuff blood pressure devices with implemented technology can be used to simultaneously detect both hypertension and AF. However, positive screening for AF with an oscillometric blood pressure monitor still requires ECG confirmation. The current evidence suggests that high-risk individuals aged ≥65 years or with treatment-resistant hypertension could benefit from AF screening. Since antihypertensive therapy effectively lowers AF risk, particularly in individuals with left ventricular dysfunction, hypertension should be the key target for AF prediction and prevention rather than merely a comorbidity of AF. Nevertheless, several important gaps in knowledge need to be filled over the next years, including the ideal method and selection of patients for simultaneous screening of hypertension and AF and the optimal antihypertensive drug class and blood pressure targets for AF prevention.

Background Left ventricular diastolic dysfunction (LVDD) predicts mortality in patients in cardiac intensive care units. An artificial intelligence enhanced ECG (AIECG) algorithm can predict LVDD and mortality in general populations but has not been examined in cardiac intensive care units. Methods This historical cohort study included consecutive adults admitted to Mayo Clinic cardiac intensive care unit from 2007 to 2018 with an admission AIECG. The AIECG assigned the LVDD grade (0–3). Medial mitral E/e' ratio >15 on transthoracic echocardiogram (TTE) defined elevated filling pressures. In‐hospital and 1‐year mortality was evaluated, before and after multivariable adjustment. Results We included 11 868 patients (median age 69.5 years, 37.7% female); 48% had heart failure and 44% had acute coronary syndromes. AIECG LVDD grade was 0 (normal), 33%; 1, 7%; 2, 39%; and 3, 21%. In‐hospital and 1‐year mortality increased in each higher AIECG LVDD grade. After adjustment, each higher AIECG LVDD grade was associated with higher in‐hospital (adjusted odds ratio [OR], 1.22 [95% CI, 1.13–1.32]) and 1‐year mortality (adjusted hazard ratio [HR], 1.23 [95% CI, 1.19–1.29]); this persisted after adjustment for TTE measurements. Patients with grade 2 or 3 LVDD by AIECG and medial mitral E/e' ratio >15 by TTE had the highest in‐hospital (adjusted OR, 2.54 [95% CI, 1.69–3.88]) and 1‐year (adjusted HR, 2.03 [95% CI, 1.65–2.48]) mortality, whereas patients meeting either of these criteria had similar, elevated mortality. Conclusions The AIECG LVDD grade was strongly associated with in‐hospital and 1‐year mortality in patients in cardiac intensive care units, even after adjusting for clinical variables and TTE measurements. Patients with concordant AIECG and TTE for elevated filling pressures were at highest risk.

Abstract Objective To evaluate the effectiveness of multiple decision aid strategies in promoting high quality shared decision making for prevention of stroke in patients with non-valvular atrial fibrillation. Design Cluster randomized controlled trial. Setting Six academic medical centers in the United States. Participants Patient participants were aged ≥18 with a diagnosis of non-valvular atrial fibrillation, at risk for stroke (CHA 2 DS 2 -VASc ≥1 for men, ≥2 for women), and scheduled for a clinical appointment to discuss stroke prevention strategies. Participating clinicians were those who manage stroke prevention strategies for participating patients. Intervention Patients were randomized to use a patient decision aid or usual care; clinicians were randomized to use an encounter decision aid or usual care with all participating patients. Main outcome measures Primary outcome measures were quality of shared decision making measured by OPTION12, knowledge of atrial fibrillation and its management, and decisional conflict. Results 1117 participants across six sites were included in the analysis. Compared with usual care, the combined use of both the patient decision aid and the encounter decision aid improved the quality of shared decision making (adjusted mean difference 12.1 (95% confidence interval (CI) 8.0 to 16.2; P<0.001), improved patients’ knowledge (odds ratio 1.68 (95% CI 1.35 to 2.09; P<0.001), and reduced patients’ decisional conflict (adjusted mean difference −6.3 (95% CI −9.6 to −3.1; P<0.001). Statistically significant improvements were also observed with the encounter decision aid alone versus usual care for all three outcomes and with the patient decision aid alone versus usual care for quality of shared decision making and knowledge. No important differences were observed in treatment choices for stroke prevention or in participants’ satisfaction. No statistically significant difference in the length of visit across study groups was detected. Conclusion Patients who received any decision aid (encounter decision aid, patient decision aid, or both) had lower decisional conflict, better shared decision making, and greater knowledge than those receiving no decision aid, except for the effect of the patient decision aid on decisional conflict, which did not reach statistical significance. The study establishes that use of either pre-visit or in-visit decision aids individually or in combination is advantageous compared with usual care. Trial registration ClinicalTrials.gov NCT04357288 .

AbstractIntroductionLittle is known regarding the prevalence and prognostic implications of non‐sustained ventricular tachycardia (NSVT) in patients with wild‐type transthyretin cardiac amyloidosis (ATTRwt‐CA). We aimed to investigate the prevalence of NSVT in patients with ATTRwr‐CA, and the association of NSVT with sustained ventricular arrhythmias (VA) and all‐cause mortality.MethodsIn a cohort of ATTRwt‐CA patients from 2011 to 2022 without prior sustained VA, we ascertained the presence and characteristics of NSVT during clinically indicated ambulatory Holter monitoring. Patients were stratified based on the presence of NSVT at baseline. The primary and secondary endpoints of sustained VA and all‐cause mortality, respectively, were assessed during follow‐up.ResultsThe cohort included 217 patients with ATTRwt‐CA (95% males, median age 75 years; median NYHA class 2). Baseline Holter monitoring demonstrated NSVT in 116 (53%) patients. During a median follow‐up of 27 months (IQR 16–45) after the index Holter monitor, 11 (5.1%) patients reached the primary endpoint of sustained VA (incidence 1.8 per 100 person‐years, all monomorphic VT), and 46 (21%) patients died. In univariable Cox proportional hazard model, NYHA class 3 or 4 heart failure (p = .048), the presence of NSVT (p = .04), the duration of longest NSVT run (p = .029), and the percentage of ventricular ectopy (p < .001) were associated with the primary outcome. When adjusting for age and NYHA class 3 or 4 heart failure, the presence of NSVT remained associated with the primary outcome (p = .03). All‐cause mortality was not significantly different between patients with and without NSVT. A cutoff for ventricular ectopy burden of 0.5%, the median for all patients in this study, was associated with increased risk in sustained VA (log‐rank p = .004) and mortality (log‐rank p = .02).ConclusionNSVT is highly prevalent among ATTRwt‐CA patients undergoing clinically indicated Holter monitoring and may confer an increased risk of incident sustained VA.

BACKGROUND: Differentiating wide complex tachycardias (WCTs) into ventricular tachycardia (VT) and supraventricular wide tachycardia via 12-lead ECG interpretation is a crucial but difficult task. Automated algorithms show promise as alternatives to manual ECG interpretation, but direct comparison of their diagnostic performance has not been undertaken. METHODS: Two electrophysiologists applied 3 manual WCT differentiation approaches (ie, Brugada, Vereckei aVR, and VT score). Simultaneously, computerized data from paired WCT and baseline ECGs were processed by 5 automated WCT differentiation algorithms (WCT Formula, WCT Formula II, VT Prediction Model, Solo Model, and Paired Model). The diagnostic performance of automated algorithms was compared with manual ECG interpretation approaches. RESULTS: A total of 212 WCTs (111 VT and 101 supraventricular wide tachycardia) from 104 patients were analyzed. WCT Formula demonstrated superior accuracy (85.8%) and specificity (87.1%) compared with Brugada (75.2% and 57.4%, respectively) and Vereckei aVR (65.3% and 36.4%, respectively). WCT Formula II achieved higher accuracy (89.6%) and specificity (85.1%) against Brugada and Vereckei aVR. Performance metrics of the WCT Formula (accuracy 85.8%, sensitivity 84.7%, and specificity 87.1%) and WCT Formula II (accuracy 89.8%, sensitivity 89.6%, and specificity 85.1%) were similar to the VT score (accuracy 84.4%, sensitivity 93.8%, and specificity 74.2%). Paired Model was superior to Brugada in accuracy (89.6% versus 75.2%), specificity (97.0% versus 57.4%), and F1 score (0.89 versus 0.80). Paired Model surpassed Vereckei aVR in accuracy (89.6% versus 65.3%), specificity (97.0% versus 75.2%), and F1 score (0.89 versus 0.74). Paired Model demonstrated similar accuracy (89.6% versus 84.4%), inferior sensitivity (79.3% versus 93.8%), but superior specificity (97.0% versus 74.2%) to the VT score. Solo Model and VT Prediction Model accuracy (82.5% and 77.4%, respectively) was superior to the Vereckei aVR (65.3%) but similar to Brugada (75.2%) and the VT score (84.4%). CONCLUSIONS: Automated WCT differentiation algorithms demonstrated favorable diagnostic performance compared with traditional manual ECG interpretation approaches.

BACKGROUND: Whether vigorous exercise increases risk of ventricular arrhythmias for individuals diagnosed and treated for congenital long QT syndrome (LQTS) remains unknown. METHODS: The National Institutes of Health–funded LIVE-LQTS study (Lifestyle and Exercise in the Long QT Syndrome) prospectively enrolled individuals 8 to 60 years of age with phenotypic and/or genotypic LQTS from 37 sites in 5 countries from May 2015 to February 2019. Participants (or parents) answered physical activity and clinical events surveys every 6 months for 3 years with follow-up completed in February 2022. Vigorous exercise was defined as ≥6 metabolic equivalents for >60 hours per year. A blinded Clinical Events Committee adjudicated the composite end point of sudden death, sudden cardiac arrest, ventricular arrhythmia treated by an implantable cardioverter defibrillator, and likely arrhythmic syncope. A National Death Index search ascertained vital status for those with incomplete follow-up. A noninferiority hypothesis (boundary of 1.5) between vigorous exercisers and others was tested with multivariable Cox regression analysis. RESULTS: Among the 1413 participants (13% <18 years of age, 35% 18–25 years of age, 67% female, 25% with implantable cardioverter defibrillators, 90% genotype positive, 49% with LQT1, 91% were treated with beta-blockers, left cardiac sympathetic denervation, and/or implantable cardioverter defibrillator), 52% participated in vigorous exercise (55% of these competitively). Thirty-seven individuals experienced the composite end point (including one sudden cardiac arrest and one sudden death in the nonvigorous group, one sudden cardiac arrest in the vigorous group) with overall event rates at 3 years of 2.6% in the vigorous and 2.7% in the nonvigorous exercise groups. The unadjusted hazard ratio for experience of events for the vigorous group compared with the nonvigorous group was 0.97 (90% CI, 0.57–1.67), with an adjusted hazard ratio of 1.17 (90% CI, 0.67–2.04). The upper 95% one-sided confidence level extended beyond the 1.5 boundary. Neither vigorous or nonvigorous exercise was found to be superior in any group or subgroup. CONCLUSIONS: Among individuals diagnosed with phenotypic and/or genotypic LQTS who were risk assessed and treated in experienced centers, LQTS-associated cardiac event rates were low and similar between those exercising vigorously and those not exercising vigorously. Consistent with the low event rate, CIs are wide, and noninferiority was not demonstrated. These data further inform shared decision-making discussions between patient and physician about exercise and competitive sports participation. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02549664.

Background The study aimed to describe the patterns and trends of initiation, discontinuation, and adherence of oral anticoagulation (OAC) in patients with new‐onset postoperative atrial fibrillation (POAF), and compare with patients newly diagnosed with non‐POAF. Methods and Results This retrospective cohort study identified patients newly diagnosed with atrial fibrillation or flutter between 2012 and 2021 using administrative claims data from OptumLabs Data Warehouse. The POAF cohort included 118 366 patients newly diagnosed with atrial fibrillation or flutter within 30 days after surgery. The non‐POAF cohort included the remaining 315 832 patients who were newly diagnosed with atrial fibrillation or flutter but not within 30 days after a surgery. OAC initiation increased from 28.9% to 44.0% from 2012 to 2021 in POAF, and 37.8% to 59.9% in non‐POAF; 12‐month medication adherence increased from 47.0% to 61.8% in POAF, and 59.7% to 70.4% in non‐POAF. The median time to OAC discontinuation was 177 days for POAF, and 242 days for non‐POAF. Patients who saw a cardiologist within 90 days of the first atrial fibrillation or flutter diagnosis, regardless of POAF or non‐POAF, were more likely to initiate OAC (odds ratio, 2.92 [95% CI, 2.87–2.98]; P <0.0001), adhere to OAC (odds ratio, 1.08 [95% CI, 1.04–1.13]; P <0.0001), and less likely to discontinue (odds ratio, 0.83 [95% CI, 0.82–0.85]; P <0.0001) than patients who saw a surgeon or other specialties. Conclusions The use of and adherence to OAC were higher in non‐POAF patients than in POAF patients, but they increased over time in both groups. Patients managed by cardiologists were more likely to use and adhere to OAC, regardless of POAF or non‐POAF.