Noseworthy, Peter A.

Background: Dofetilide, a commonly prescribed class III antiarrhythmic for atrial fibrillation (AF), currently requires a 3-month amiodarone washout period per FDA guidelines. We evaluated the safety of initiating dofetilide within this 3-month washout period. Methods: We performed a retrospective cohort study across all Mayo Clinic sites and identified patients using centralized datamart that were transitioned from amiodarone to dofetilide in less than 90 days. Patients were included and confirmed by manual chart review if they had been on amiodarone for ≥ 12 weeks and if available amiodarone level >0.3 mg/ml at the time of dofetilide initiation. Serial ECGs were assessed during the hospitalization for dofetilide initiation and at 3-, 6-, and 12-months follow-up to evaluate QT interval. Primary safety end point was torsade de pointes. Results: The final cohort included 66 patients with a mean age of 65 ±14 years; 71.0% were male; and the average BMI was 29.6 ±5.1 kg/m 2 . Of the 66 patients, 65 had a history of AF: 31.8% paroxysmal, 54.5% persistent, and 12.1% long-standing persistent. Permanent pacemakers and ICDs were present in 27.3% and 22.7% of patients. Patients received amiodarone for a median of 7.8 months at a mean daily dose of 187.1±48.3 mg (range: 100 – 400 mg), with a mean transition period of 44.2±20.3 days. Of 66 patients, 16 (24 %) transitioned within 30 days of stopping amiodarone—including 5 (8 %) within 14 days—while the remaining 50 (76 %) was between 30 and 90 days. A total of 24.2% (16/66) patients required dofetilide dose reduction due to QT prolongation and 10.6% of patients (7/66) required drug discontinuation. There was no difference in either discontinuation rate or dose reduction rate in patients with a transition period ≤30 days vs > 30 days [6.25% vs. 12% (p=0.85) and 12.5% vs. 28% (p=0.36), respectively]. No cases of torsades de pointes were observed during dofetilide initiation or follow up. Conclusion: In this cohort, dofetilide initiation less than 90 days after amiodarone discontinuation was not associated with increased torsades de pointes risk. These data challenge and support reconsideration of the blanket 3-month washout and suggest that a monitored, expedited rhythm-control transition is feasible and safe.

Background: Arrhythmogenic and dilated cardiomyopathies (ACM/DCM) are associated with adverse cardiovascular outcomes, including sudden death. Artificial intelligence (AI)-enabled electrocardiographic aging algorithms estimate biological age from 12-lead tracings and predict cardiovascular outcomes in the general population. However, their utility in genetic ACM/DCM has not been studied. Methods: Retrospective review of 1,045 genotype-positive ACM/DCM patients was used to identify those with a pathogenic/likely pathogenic variant in ClinGen-classified definitive/strong evidence ACM/DCM-susceptibility genes. Following exclusion of patients without a baseline ECG for analysis (e.g. paced rhythms), the AI-ECG age gap (AI-EAG) was calculated by subtracting chronological from AI-ECG age. Genes were grouped into functional categories: desmosomal ( PKP2, DSP, DSG2, DSC2, JUP ), nuclear envelope ( LMNA ), sarcomeric ( TTN, MYH7, TNNT2 ), cytoskeleton/Z-disc ( FLNC, DES, DMD, BAG3 ), and regulatory/ion channel ( PLN, RBM20, SCN5A ). Cardiac MRI data included left ventricular structure, function, and late gadolinium enhancement (LGE) presence and pattern. Mann-Whitney U was used for group comparisons; results are shown as median (IQR). Results: Overall, 824 patients (52.8% male; median age of 40.7 years, IQR 26.5–53.4; and median AI-EAG of 7.49 years, IQR 0.43–15.26) were included. DES variant-positive patients had the highest (19.98 years, IQR 9.66–23.21) and BAG3 variant-positive patients the lowest (–0.95 years, IQR -6.05–7.61) AI-EAGs. Among gene groups, nuclear envelope had the highest (15.12 years, IQR 6.79–25.17) and sarcomeric the lowest (5.75 years, IQR -0.69-14.01) AI-EAGs. Cardiac MRI was available for 538/824 (65%) of which 233/538 (43.3%) had LGE. No significant difference in AI-EAG was observed between LGE-positive and -negative patients (6.99 vs. 7.94 years; p=0.831). However, several LGE patterns were associated with significantly higher AI-EAGs: subepicardial (9.88 vs. 6.84; p=0.004), transmural (13.83 vs. 7.25; p=0.012), apical (12.89 vs. 7.17; p=0.002), and septal (8.91 vs. 7.19; p=0.016). Conclusion: AI-EAG varies by gene and functional group, possibly reflecting gene-specific myocardial remodeling. While certain LGE patterns were linked to increased biological aging, overall LGE status was not. These findings suggest AI-EAG may capture disease activity that is distinct from LGE and could serve as a complementary, non-invasive biomarker in genetic ACM/DCM.

ABSTRACT Introduction Etripamil is a fast‐acting intranasally self‐administered calcium‐channel blocker developed for termination of paroxysmal supraventricular tachycardia (PSVT). Prior studies have demonstrated safety and efficacy of etripamil for PSVT termination following an initial medically supervised test dose during sinus rhythm. NODE‐303 is an open‐label, single‐arm study that evaluated etripamil for multiple, at‐home PSVT episodes, without test dose before first use. Methods Patients applied an ECG monitor at symptom onset and self‐administered etripamil (70 mg) if a vagal maneuver was unsuccessful. ECG monitoring occurred for ≥ 1 h following study drug administration. A repeat 70‐mg dose was introduced during the study for symptoms persisting 10 min after the first dose. Safety measures included treatment‐emergent adverse events (TEAEs) and ECG arrhythmia‐surveillance. Efficacy measures were captured for PSVT termination during treatment of each of the multiple episodes. Results 1054 perceived PSVT episodes were etripamil‐treated in 503 of 1116 patients enrolled. TEAEs within 24 h were mostly mild or moderate and localized: 30.2% of patients experienced nasal discomfort, nasal congestion (13.9%), rhinorrhea (13.1%), epistaxis (7.4%). TEAE frequencies decreased across multiple PSVT episodes and were similar for single versus repeat doses. For first PSVT episodes, 70.5% of patients converted to sinus rhythm by 60 min post etripamil (median time to conversion = 18.3 min [14.2–25.6]). Conversion in earlier episodes was consistently predictive of conversion in subsequent episodes. Conclusions Etripamil nasal spray self‐administered in a real‐world setting was well tolerated, effective, and had a consistent safety profile as a single‐ or repeat‐dose regimen across multiple PSVT episodes. Trial Registration: ClinicalTrials.gov NCT04072835

Abstract Atrial fibrillation (AF) is increasingly diagnosed early, close to its first occurrence due to: (i) increased public awareness with self-screening; (ii) health care initiatives including population screening and opportunistic case finding; and (iii) increased use and surveillance of implantable cardiac devices. At its onset, AF is often low burden, and cardiovascular co-morbidities may be absent or at an early stage. Thus, the management of recent-onset AF has become an issue of growing importance. Professional guidelines have traditionally focused on anticoagulant thromboprophylaxis, generally recommending a cautious approach to rhythm control, and priority has been given to rate control to alleviate symptoms. In recent guidelines, the importance of managing lifestyle and co-morbidities has increased. The AF-SCREEN collaboration proposes that a vigorous approach to active management of recent-onset AF may be warranted. This includes addressing co-morbidities and promoting healthy lifestyles to prevent the emergence or progression of AF and associated cardiovascular disease, as well as the initiation of active rhythm control ± anticoagulation to prevent AF-related morbidity and mortality, including stroke and heart failure (HF). Intuitively, intervention early after AF onset would be beneficial since lifestyle and co-morbidity management, plus rhythm control and anticoagulation, are important contributors to improved outcomes in patients with established AF, but robust evidence is lacking for recent-onset AF. There is a delicate balance between achieving favourable outcomes such as preventing strokes, HF and AF progression vs the complications and potential adverse effects of interventions. Given the serious long-term consequences, innovative approaches are necessary to determine the value and risks of initiating active therapy very early in the course of AF. More data are needed to guide the best management of recent-onset AF, bearing AF burden in mind. Long-term studies using large national databases linked to electronic medical records and rhythm monitoring devices offer excellent opportunities. Shorter-term studies focusing on reducing AF burden to slow AF progression and studies focusing on outcomes such as HF could be used in both randomized clinical trials and observational cohort studies.

INTRODUCTION: The SPEC-AI Nigeria trial (NCT05438576) was designed to use artificial intelligence (AI) to screen for pregnancy-related cardiomyopathy in the peripartum period. Using data from this study, we evaluated the utility of AI-predicted delta age (adjusted AI-predicted age − chronological age) as a surrogate for biological age. METHODS: We included 1,187 pregnant and postpartum women enrolled between August 2022 and September 2023 with follow-up through May 2024. Standard 12-lead electrocardiograms (ECGs) were recorded at study entry to generate AI age predictions. Artificial intelligence-predicted age was adjusted using estimated reference ranges obtained from a community-dwelling cohort of 25,144 individuals with AI-ECG age estimated and documented chronological age. Logistic and Cox-proportional hazards regression were used to examine associations with comorbid cardiovascular conditions and maternal mortality, respectively. RESULTS: Adjusted AI-predicted age was significantly higher among women with any cardiovascular condition, peripartum cardiomyopathy, or who died within 18 months (7, 14, and 23 years older, respectively) compared to those without these conditions who had values similar to the normal reference ranges (adjusted AI-predicted age difference less than 1 year). Artificial intelligence-predicted delta age greater than the 75th percentile was associated with an odds ratio (OR) of 2.06 for any cardiovascular condition, OR of 4.98 for left ventricular systolic dysfunction, and a hazard ratio of 32.81 for all-cause mortality; all values of P<.001. CONCLUSIONS/IMPLICATIONS: Artificial intelligence-ECG-derived biological age appears to be a potentially useful measure of cardiovascular health status and risk among pregnant and postpartum women. However, its role in monitoring maternal health requires further exploration.

Background: Deciding to use oral anticoagulation (OAC) for stroke prevention in patients with atrial fibrillation (AF) is complex. For many, the decision between treatment and non-treatment requires a primary tradeoff between the risks of potential stroke and increased bleeding. Hypothesis: We hypothesized that patient values and empiric stroke risk measured by CHA 2 DS 2 -VASc score would influence OAC decisions. Methods: We conducted a secondary analysis of a randomized clinical trial where eligible clinicians and patients were independently randomized to one of two decision aids (DAs) – a patient decision aid and/or an encounter decision aid. Eligible patients were adults with AF with CHA 2 DS 2 -VASc≥1 for men or ≥2 for women. Patients newly prescribed (OAC-naive subgroup) or already taking OAC (OAC-experienced subgroup) were included. We assessed patient values using a 5-point Likert scale between stroke prevention and bleeding risk after SDM during a clinical encounter. We report preliminary results using descriptive statistics and adjusted analysis to investigate the effects of CHA 2 DS 2 -VASc and expressed values on OAC use. Results: 1005 patients were included in the analysis. 828 (82%) patients valued stroke prevention over bleeding risk. Among the OAC-naive group, 175 (63%) valued stroke prevention more than bleed avoidance, 58 (20%) valued bleed avoidance more than stroke prevention, and 47 (17%) were neutral. In the unadjusted analysis, patients were more likely to value stroke prevention if they were OAC-experienced (p<0.001), older (p<0.001), female (p< 0.001), had patient-reported bleeding (p=0.003), or if CHA 2 DS 2 -VASc ≥ 2 if male, ≥3 if female (p<0.001) Table 1 . After adjustments, there were significant associations for OAC use among patients who valued stroke prevention (OR 5.35, 95%CI 3.13-9.13, p<0.001) or had higher CHA 2 DS 2 -VASc (OR 2.03, 95%CI 1.26-3.27, p=0.004). Patients who valued bleed avoidance had an opposing association not to use OAC (OR 0.23, 95%CI 0.11-0.48, p<0.001). Conclusions: Patients with elevated risk (CHA 2 DS 2 -VASc score, age, and female), and those who reported a prior bleeding event valued stroke prevention more than bleeding avoidance. Both empiric stroke risk and patient values were associated with the decision to use OAC. While the tradeoff between stroke prevention and bleeding risk is only one aspect of the decision-making process, these results indicate variability in patient values may influence OAC use.

Abstract Advancements in machine learning and computing methods have given new life and great excitement to one of the most essential diagnostic tools to date—the electrocardiogram (ECG). The application of artificial intelligence‐enabled ECG (AI‐ECG) has resulted in the ability to identify electrocardiographic signatures of conventional and unique variables and pathologies, giving way to tremendous clinical potential. However, what these AI‐ECG models are detecting that the human eye is missing remains unclear. In this article, we highlight some of the recent developments in the field and their potential clinical implications, while also attempting to shed light on the physiologic and pathophysiologic features that enable these models to have such high diagnostic yield. © 2022 American Physiological Society. Compr Physiol 12:3417‐3424, 2022.