BACKGROUND:Multimorbidity is common in atrial fibrillation (AF), particularly in older patients who generally have multiple cardiovascular (CV) and non-CV conditions. OBJECTIVE:To describe how chronic conditions accumulate in younger patients with AF. METHODS:Patients aged <65 years with incident AF from 2013 to 2019 (N = 3462) were matched 1:1 on age (±5 years) and sex to referents from the same community. Onset of 20 chronic conditions (6 CV-related and 14 non-CV) was ascertained from 3 years before index through December 31, 2022. Andersen-Gill models estimated associations between AF or referent status and accumulation of conditions. RESULTS:The mean age was 55.1 (8.8) years for both patients with AF and referents; 70.9% were male. Before index, 24.8% of patients with AF had no chronic conditions, whereas 32.3% of referents had 0 conditions. The accumulation of conditions was accelerated in patients with AF compared with referents, with the strongest associations within the first year after diagnosis/index for both CV-related (hazard ratio [HR], 3.80; 95% confidence interval [CI], 3.30-4.37) and non-CV conditions (HR, 2.42; 95% CI, 2.14-2.74). Stronger associations were observed for CV-related conditions, in women, and in the youngest age group. After 1 year, increased accumulation of CV-related conditions for patients with AF was observed in women (HR, 1.36; 95% CI, 1.13-1.63) but not men, and for those aged <50 (HR, 1.50; 95% CI, 1.13-1.99) and 50-54 years (HR, 1.43; 95% CI, 1.09-1.86) only. CONCLUSION:Patients aged <65 years with AF have an increased accumulation of chronic conditions compared with those without AF, in particular within the first year after AF diagnosis.

Background: Contemporary data on trends in survival after incident atrial fibrillation (AF) are limited. Methods: Residents of a 27-county area in southern Minnesota and western Wisconsin with new-onset atrial fibrillation or atrial flutter between 2013 and 2023 were identified. An electronic algorithm requiring 1 inpatient code or 2 outpatient codes separated by >7 days but within 1 year was used to define AF. Patients were followed for all-cause mortality through March 31, 2025. Standardized mortality ratios of observed versus expected survival were calculated, and time trends in survival were examined using Cox regression adjusting for demographics, cardiovascular risk factors, comorbid conditions, and area-level measures of socioeconomic status and rurality. Results: There were 44,930 individuals identified with incident AF from 2013-2023 (56.4% male; mean (SD) age 72.8 (13.5) years; 95.8% were non-Hispanic white). Within the first 90 days, the risk of all-cause mortality was greatly elevated compared with individuals of a similar age and sex distribution in the general population (standardized mortality ratios 12.6, 95% CI, 12.1-13.0 and 3.8, 95% CI, 3.6-4.0 for the first 30 days and 31 to 90 days after diagnosis, respectively). This excess risk was observed for all age groups but was greatest in the youngest age group (standardized mortality ratios among 18-64 year olds for the first 30 days: 49.9, 95% CI, 44.6-55.7 and 31 to 90 days: 11.1, 95% CI: 9.4-13.1; Figure ). In the youngest age group, the excess risk persists through 5 years post AF, however, in the oldest age group the excess risk only persisted through 1 year. Survival within the first 90 days improved over the study period (adjusted hazard ratio [aHR], 0.88; 95% CI, 0.79-0.99 for 2023 vs 2013); likewise, among 90-day survivors, survival improved between 2013 and 2023 (aHR,0.82; 95% CI, 0.76-0.88). These trends were driven by improvements in the younger age groups, particularly for death among 90-day survivors (aHR for 18-64 years, 0.66, 95% CI, 0.52-0.83; 65-74 years: 0.77, 95% CI: 0.65-0.90; 75-84 years, 0.84, 95% CI: 0.75-0.95; 85+ years, 0.99, 95% CI: 0.98-1.01). Conclusion: In a Midwestern community, the excess risk of death is high within the first 90 days after incident AF. Furthermore, survival after AF has improved between 2013 and 2023, with the improvement greatest in younger age groups.

Background The burden and pathophysiologic mechanisms of myocardial infarction (MI) in younger patients remain understudied. Prior studies have been limited by selected cohorts and lack of awareness of nonatherothrombotic causes. Objectives We sought to determine the incidence and outcomes of MI according to a unique pathophysiologic mechanism in a large community cohort aged ≤65 years, and to evaluate sex-differences in etiology Methods We identified all residents of Olmsted County, Minnesota, USA, age ≤65 years who experienced an event associated with a cardiac troponin T >99th percentile of upper reference range (≥0.01 ng/mL) from January 2003 to March 2018. Records and imaging were individually scrutinized. Patients classified as MI were assigned to 1 of 6 adjudicated pathophysiologic mechanisms: atherothrombosis, spontaneous coronary artery dissection (SCAD), embolism, vasospasm, myocardial infarction with nonobstructed coronary arteries not meeting another category (MINOCA-U), and supply/demand mismatch secondary myocardial infarction. We determined incidence and long-term all-cause and cardiovascular mortality for each group. Results There were 4,116 myocardial injury events in 2,780 patients (36% women) over 15 years. Excluding periprocedural MI, 1,474 events were classified as index MI, of which 68% were caused by atherothrombosis. The population incidence of MI was much lower in women, particularly in MI caused by atherothrombosis (48 vs 137 per 100,000 person years and 23 vs 105 per 100,000 person-years). Incidence of SCAD was much higher in women (3.2 vs 0.9 per 100,000 person-years) with 55% of cases misclassified as MINOCA or atherothrombosis at index presentation. Women with atherothrombosis were similar in age to men (55 ± 8 years vs 54 ± 8 years), with similar disease extent at angiography but greater burden of risk factors. Proportionately, nonatherothrombotic causes comprised the majority of MI in women (atherothrombosis 47% vs 75%, secondary myocardial infarction [SSDM] 34% vs 19%, SCAD 11% vs 0.7%, embolism 2% vs 2%, vasospasm 3% vs 1%, MINOCA-U 3% vs 2%). The 5-year all-cause mortality was highest after SSDM (SSDM 33%, atherothrombosis 8%, embolism 8%, SCAD 0%) with low cardiovascular mortality in all groups. Conclusions This community-based study demonstrates nonatherothrombotic causes comprise an important burden of acute MI in persons age ≤65 years, particularly women. These cause-specific findings have implications for individualized management and risk stratification and provide epidemiologic benchmarking for future studies.

Background Whether frail, elderly patients with atrial fibrillation (AF) on a vitamin K antagonist (VKA) should switch to a direct-acting oral anticoagulant (DOAC) was studied in the FRAIL-AF trial and remains controversial. Objectives The purpose of this study was to evaluate, in the COMBINE-AF data set, the impact on clinical outcomes of switching frail, elderly AF patients from VKA to DOAC. Methods COMBINE-AF consists of individual patient-level data from 71,683 patients with AF in 4 randomized clinical trials comparing DOAC vs warfarin. Frailty was evaluated using a frailty index derived from a modified Rockwood’s Accumulation Model including 18 age-related conditions. Patients with a frailty index score above the median were considered frail. Prespecified outcomes were stroke or systemic embolic events, bleeding events, death, and a net clinical outcome combining these events. Results We identified 5,913 patients who were frail, elderly (age ≥75 years), and VKA-experienced and 52,721 patients who did not meet all 3 of these criteria. Patients were randomized to a standard-dose (SD) DOAC or warfarin. After 27 months median follow-up, there was no heterogeneity in treatment effect with SD-DOAC vs warfarin among those who met all 3 criteria vs those who did not for the endpoints of stroke or systemic embolic events (HR: 0.83 vs 0.81; Pint = 0.75) or for death (HR: 0.95 vs 0.91; Pint = 0.54). Major bleeding was similar with SD-DOAC vs warfarin in frail, elderly, VKA-experienced patients (HR: 1.06 [95% CI: 0.90-1.25]), while it was significantly reduced with SD-DOAC in patients without all 3 criteria (HR: 0.82 [95% CI: 0.76-0.89]; Pint = 0.007). Likewise, the net clinical outcome was similar in the frail, elderly, VKA-experienced patients with SD-DOAC vs warfarin (HR: 1.01 [95% CI: 0.91-1.13]), while significantly reduced with SD-DOAC patients without all 3 criteria (HR: 0.89 [95% CI: 0.85-0.93]; Pint = 0.028). Fatal and intracranial bleeding were significantly reduced with SD-DOAC in both subgroups to a similar degree (both Pint > 0.05), while gastrointestinal bleeding with SD-DOAC was increased to a greater degree in frail, elderly, VKA-experienced patients (HR: 1.83 [95% CI: 1.42-2.36]) compared with those without all 3 criteria (HR: 1.23 [95% CI: 1.09-1.39]; Pint = 0.006). Conclusions Frail, elderly, VKA-experienced patients with AF switched to SD-DOAC experienced significant reductions in stroke or systemic embolism, fatal and intracranial bleeding, and death. Gastrointestinal bleeding was increased with SD-DOAC, while major bleeding and the primary net clinical outcome were similar. Based on these findings, SD-DOAC is a reasonable choice for frail, elderly, VKA-experienced patients to reduce stroke and systemic embolism, death, and the most serious types of bleeding.

Background: Atrial fibrillation (AF) is the most common sustained arrhythmia with prevalence increasing over the last decade. However, data on recent temporal trends in incidence of AF have been inconsistent, with some reports of increasing trends over time and others indicating no change in incidence over time. Therefore, we aimed to determine how the incidence of AF has changed over the last decade in a community in the Midwest USA. Methods: Between 2013 and 2023, adults (aged 18 and older) with incident AF were identified in a 27-county region in the Midwest. AF was identified using diagnostic codes by employing an electronic algorithm requiring 1 inpatient code or 2 outpatient codes separated by >7 days but within 1 year. For total rates, age - and sex-adjusted incidence rates were standardized to the 2010 US total population. Poisson regression was used to calculate the incidence rate ratio of AF for 2023 vs 2013. Results: We identified 44,930 individuals with incident AF from 2013 to 2023. Of these, 56.4% were male, the mean (SD) age was 72.8 (13.5) years, and 95.8% were non-Hispanic white. The age-and sex-adjusted incidence rates (per 1,000) and 95% confidence intervals standardized to the 2010 US total population were 5.24 (5.07-5.41) in 2013, 5.73 (5.56-5.91) in 2018, and 5.44 (5.28-5.61) in 2023. Although a drop in incidence was observed corresponding to the COVID-19 pandemic, a small increase in the overall incidence of AF was observed over time. The overall incidence rate ratio (95% CI) for 2023 vs 2013 was 1.07 (1.02-1.11), P=0.003. The incidence rates were higher in men compared to women and increased with older age ( Figure 1 ). However, differences in AF incidence by sex were greatest in the youngest age group and attenuated with older age (incidence rate ratio (95% CI): 2.18 (2.10-2.28) for ages 18-64 years, 1.76 (1.70-1.83) for ages 65-74 years, 1.38 (1.33-1.42) for ages 75-84 years, and 1.23 (1.18-1.28) for ages 85 years and older). Conclusion: In this 27-county region in the Midwest, although small in magnitude, a statistically significant increase in AF incidence was observed over time from 2013 to 2023. Furthermore, the incidence of AF was higher in men compared with women, especially in younger age groups.

Introduction: Cardiovascular risks following SARS-CoV-2 infection are incompletely defined. We evaluated evolving cardiovascular outcomes across COVID-19 variant eras using a large community-based cohort to inform risk stratification and clinical care. Methods: We conducted a retrospective cohort study of 162,471 adults with COVID-19 between March 2020 and December 2023 using the Rochester Epidemiology Project. Patients were stratified by variant era (Pre-Delta, Delta, and Omicron). Cardiovascular outcomes included major adverse cardiovascular events (MACE: myocardial infarction, stroke, death), ischemic and inflammatory heart disease, thrombotic events, and dysrhythmias. Diagnoses were identified using ICD-10 codes and validated in a subset. Cumulative incidence was estimated using Kaplan-Meier and competing risk models. Cox proportional hazards regression was used to assess differences by era and age. Results: MACE occurred in 4,922 patients, primarily in those ≥80 (2-year incidence: 17%). Event rates peaked within 30 days post-infection, with marked variation by variant. In patients ≥80, 30-day MACE risk was highest in the Pre-Delta (HR 3.85; 95% CI, 3.14–4.71) and Delta (HR 2.72; 95% CI, 2.13–3.47) eras versus Omicron. After 30 days, event rates fell and era differences narrowed. Thrombotic events (n=2,090; 1.4%) decreased across eras. Ischemic and inflammatory heart disease rates were stable. Myocarditis/pericarditis were rare (0.1%) without age trends. Dysrhythmias affected 6,765 patients (2-year incidence: 4.9%) and rose with age (2.0% in <40 vs. 19.9% in ≥80). Within 30 days, risk was higher in the Pre-Delta and Delta eras for age ≥40, especially ≥80 (Delta HR 3.08; 95% CI, 2.08–4.56) and 60–79 (HR 2.23; 95% CI, 1.75–2.85). Among those 40–59, Delta posed the highest risk (HR 2.74; 95% CI, 1.94–3.86 vs. Pre-Delta HR 1.77; 95% CI, 1.26–2.49). No differences were observed in <40. Beyond 30 days, risk converged across variants. Conclusion: Cardiovascular risk after SARS-CoV-2 infection was concentrated in the first 30 days, with attenuation thereafter. While MACE and thrombotic event rates declined over time, early dysrhythmia risk varied by variant and age, especially in older adults. These findings define a time-sensitive, variant-specific risk window and support short-term, risk-stratified post-COVID monitoring. This work informs targeted follow-up protocols by infection era and age, with implications for quality improvement, resource use, and equitable care.

Background: Many patients diagnosed with COVID-19 have persistent cardiovascular symptoms but whether this represents a true cardiac process is unclear. This study assessed whether symptoms associated with long COVID among patients referred for cardiovascular evaluation are associated with objective abnormalities on cardiac testing to explain their clinical presentation.Methods: A retrospective cohort study of 40,462 unique patients diagnosed with COVID-19 at our tertiary referral was conducted and identified 363 patients with persistent cardiovascular symptoms a minimum of 4 weeks after PCR confirmed COVID-19 infection. Patients had no cardiovascular symptoms prior to COVID-19 infection. Each patient was referred for cardiovascular evaluation at a tertiary referral center. The incidence and etiology of abnormalities on cardiovascular testing among patients with long COVID symptoms are reported here. The cohort was subsequently divided into three categories based on the dominant circulating severe acute respiratory syndrome coronavirus 2 variant at the time of initial infection for further analysis.Results: Among 40,462 unique patients diagnosed with COVID-19 at our tertiary referral center from April 2020 to March 2022, 363 (0.9%) patients with long COVID were evaluated by Cardiology for possible cardiac sequelae from COVID and formed the main study cohort. Of these, 229 (63%) were vaccinated and 47 (12.9%) had severe initial infection receiving inpatient treatment for COVID prior to developing long COVID symptoms. Symptoms were associated with a cardiac cause in 85 (23.4%), of which 52 (14.3%) were attributed to COVID; 39 (10.7%) with new cardiac disease from COVID, and 13 (3.6%) to worsening of pre-existing cardiac disease after COVID infection. The median troponin change in 45 patients with troponin measurements within 4 weeks of acute infection was +4 ng/dl (9 to 13 ng/dl). Among the total cohort with long COVID, 83.7% were diagnosed during the pre-Delta phase, 13.2% during the Delta phase, and 3.1% during the Omicron phase of the pandemic. There were six cases of myocarditis, 11 rhythm disorders, eight cases of pericarditis, five suspected cases of endothelial dysfunction, and 33 cases of autonomic dysfunction.Conclusion: This pragmatic retrospective cohort study suggests that patients with long COVID referred for cardiovascular evaluation infrequently have new, objective cardiovascular disease to explain their clinical presentation. A multidisciplinary, patient-centered approach is warranted for symptom management along with conservative use of diagnostic testing.

Importance:Sleep disordered breathing (SDB) is a well-established contributor to cardiovascular morbidity, mediated by intermittent hypoxemia, autonomic dysregulation, and endothelial dysfunction. Patients with hypertrophic cardiomyopathy (HCM) may be especially at risk for SDB, but the clinical impact of SDB in this population remains unclear. Objective:To define the prevalence and subtypes of SDB in HCM and examine their association with echocardiographic parameters and cardiac biomarker expression. Design, Setting, and Participants:A prospective cohort study was conducted between April 18, 2018, and January 15, 2024, at a single tertiary referral center specializing in HCM care. Adults with HCM (left ventricular wall thickness ≥15 mm or pathogenic variants) were recruited from an institutional registry. Patients diagnosed with SDB or current pregnancy were excluded. Patients underwent polysomnography, with comparative assessment of echocardiographic, electrocardiographic, and biomarker indices. Observers were blinded to polysomnographic results. Data analysis was performed from April 11, 2024, to July 25, 2024. Exposures:SDB classified via polysomnography using apnea-hypopnea index thresholds, with subtypes including obstructive sleep apnea and central sleep apnea and with event severity, hypoxemia, and sleep architecture disruption quantified. Main Outcomes and Measures:Echocardiographic indices, cardiac biomarker expression, functional status, apnea-hypopnea index, and overnight hypoxemia. Results:Among 154 patients (median [IQR] age, 60 [48-68] years; 102 [66.2%] male), 91 (59.1%) were diagnosed with SDB. Those with SDB, compared with those without SDB, had higher left ventricular mass index (median [IQR], 128 [107-161] vs 109 [96-134] g/m2; P = .03), E/e' ratio (median [IQR], 12.5 [10.0-15.0] vs 10.0 [8.3-14.5]; P = .04), and baseline troponin-T level (median [IQR], 0.013 [0.009-0.022] vs 0.011 [0.007-0.015] ng/mL [to convert to micrograms per liter, multiply by 1]; P = .04) and greater overnight troponin-T level increases (change in median [IQR], 0.0021 [-0.0029 to 0.0062] vs 0.0002 [-0.0022 to 0.0026] ng/mL; P = .02). New York Heart Association class II or III symptoms were more common in those with SDB (48 [52.7%] vs 17 [27.0%]; P = .005). Hypertension and diabetes were more prevalent among patients with SDB than without SDB (hypertension: 67 [73.6%] vs 36 [57.1%]; P = .03; diabetes: 14 [15.4%] vs 3 [4.8%]; P = .04), whereas rates of atrial fibrillation and prior myectomy did not differ significantly between groups. Conclusions and Relevance:This study suggests that undiagnosed SDB is highly prevalent in patients with HCM and that SDB is associated with adverse myocardial remodeling, greater diastolic dysfunction, and elevated troponin-T levels, indicating subclinical myocardial injury. SDB may contribute to HCM pathophysiology and symptom burden, supporting the rationale for randomized clinical trials to determine the impact of treating SDB on symptoms and clinical outcomes in patients with HCM.

Differing definitions and questionable prognostic significance have caused confusion and controversy around the applicability of the current definitions of periprocedural and perioperative myocardial infarction in clinical practice. In this Clinical Outlook, we review the definitions and the clinical and prognostic relevance of the various entities and provide implications for clinical practice.

Hypertension is the single most important modifiable risk factor for preventable disability and death worldwide and disproportionately affects socially disadvantaged populations. We face a paradox-blood pressure control is low and recent trends suggest it is even declining, despite the availability of inexpensive and effective therapies. A variety of barriers on the system, patient, and healthcare provider side hinder effective drug-based risk factor management. Clinical inertia represents a major barrier on the clinician side, as well as workload and limited education. Common barriers on the patient side include limited English proficiency, low health literacy, and nonadherence with misaligned incentives, limited resources, lack of structured clinical pathways, and reimbursement issues. New innovations in the field of RNA-targeted therapies and device-based interventions could prevent and potentially even cure diseases previously designated as chronic health conditions, such as hypertension. Such novel therapies could potentially overcome several major barriers to effective treatment, including nonadherence. Drug development of novel, long-acting treatments requires consideration of specific clinical trial design aspects, including safety collection, benefit: risk assessment, the development and assessment of novel, qualitative surrogate end points, such as time-in-therapeutic range, the use of representative trial settings as well as the definition of standard of care in placebo-controlled trials, which should be of reasonably high-quality allowing for credible evaluation of effectiveness. Here, we provide an overview on barriers to effective treatment and a framework for trials assessing novel treatments for cardiovascular disease risk factors, including early and broad implementation programs.

OBJECTIVE:To contemporaneously reappraise the incidence-rate, prevalence, and natural history of hypertrophic cardiomyopathy (HCM) in Olmsted County, Minnesota, from 1984 to 2015. PATIENTS AND METHODS:A validated medical-record linkage system collecting information for residents of Olmsted County was used to identify all cases of HCM between January 1, 1984, and December 31, 2015. After adjudication of records from Mayo Clinic and Olmsted Medical Center, data relating to diagnoses and outcomes were abstracted. The calculated incidence rate and prevalence were standardized to the US 1980 White population (age- and sex-adjusted) and compared with a prior study examining the years 1975-1984. RESULTS:Two hundred seventy subjects with HCM were identified. The age- and sex-adjusted incidence rate was 6.6 per 100,000 person-years, and the point prevalence of HCM on January 1, 2016, was 89 per 100,000 population. The incidence rate and point prevalence of HCM on January 1, 2016, standardized to the US 1980 White population (age- and sex-adjusted), were 6.7 (95% CI, 7.1 to 8.8) per 100,000 person-years and 81.5 per 100,000 population, respectively. The incidence rate of HCM increased each decade since the index study. Individuals with HCM had a higher overall standardized mortality rate than the general population with an observed to expected HR of 1.44 (95% CI, 1.21 to 1.71; P<.001) which improved by each decade. CONCLUSION:The incidence and prevalence of HCM are higher than rates reported from a prior study in the same community examining the years 1975-1984, but lower than other study cohorts. The risk of mortality in HCM remains higher than expected, albeit with improvement in rates of mortality observed each decade during the study period.

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.

Artificial intelligence enabled interpretation of electrocardiogram waveform images (AI-ECG) can identify patterns predictive of future adverse cardiac events. We hypothesized such an approach, which is well described in general medical and surgical patients, would provide prognostic information with respect to the risk of cardiac complications and overall mortality in patients undergoing hematopoietic cell transplantation (HCT) for blood malignancy. We retrospectively subjected ECGs obtained pre-HCT to an externally trained, deep learning model designed to predict risk of atrial fibrillation (AF). Included were 1,377 patients (849 autologous HCT and 528 allogeneic HCT recipients). Median follow-up was 2.9 years. The three-year cumulative incidence of AF was 9% (95% CI: 7-12%) in autologous HCT patients and 13% (10-16%) in allogeneic HCT patients. In the entire cohort, pre-HCT AI-ECG estimate of AF risk correlated highly with development of clinical AF (Hazard Ratio (HR) 7.37, 3.53-15.4, p <0.001), inferior overall survival (HR: 2.4; 1.3-4.5, p = 0.004), and greater risk of non-relapse mortality (HR 3.36, 1.39-8.13, p = 0.007), without increased risk of relapse. Significant associations with mortality were only noted in allo HCT recipients, where the risk of non-relapse mortality was greater. Compared to calcineurin inhibitor-based graft versus host disease prophylaxis, the use of post-transplantation cyclophosphamide resulted in greater 90-day incidence of AF (13% versus 5%, p = 0.01), corresponding to temporal changes in AI-ECG AF prediction post HCT. In summary, AI-ECG can inform risk of post-transplant cardiac outcomes and survival in HCT patients and represents a novel strategy for personalized risk assessment after HCT.

BACKGROUND:Decisions about stroke prevention strategies in atrial fibrillation (AF) typically balance thromboembolism reduction against increased bleeding from oral anticoagulation therapy (OAC). When determining eligibility for OAC, guidelines recommend calculation of thromboembolic event rates using a validated score such as CHA2DS2-VASc. In contrast, routine calculation of bleeding scores is not recommended, in part because many patient factors associated with an increased risk of bleeding are associated with an even larger increased risk of ischemic stroke. We set out to characterize patients by paired stroke and bleeding risk scores to understand the level of concordance. METHODS:Between 2010 and 2016, we identified 20,451 AF patients in the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF) I and II Registries. We grouped patients by stroke and bleeding risk pairings: low and high stroke risk (CHA2DS2-VASc < and ≥2), low and high bleeding risk (ORBIT < and ≥ 4) and described treatment rates with OAC and antiplatelet (AP) therapy. RESULTS:Most patients (68.6 %) were at high stroke and low bleeding risk. Patients at high bleeding risk (19.4 %) had high stroke risk (98.5 %). Treatment rates differed with combined OAC + AP therapy highest for patients at high stroke and bleeding risks. Ischemic and bleeding events were also highest in this group. CONCLUSIONS:Nearly all AF patients in this cohort with high bleeding risk (ORBIT score ≥ 4) had high stroke risk (CHA2DS2-VASc ≥ 2), supporting that bleeding risk should not obviate the need for stroke prevention. In contrast, most at high stroke risk were at low bleeding risk (ORBIT <4), supporting OAC for the majority. Bleeding scores, in combination with factors that specifically indicate a higher risk of bleeding, may identify patients who might be candidates for alternative stroke prevention such as left atrial appendage occlusion devices or bleeding mitigation strategies such as de-escalation of antiplatelet therapy.

Aims Recently, deep learning artificial intelligence (AI) models have been trained to detect cardiovascular conditions, including hypertrophic cardiomyopathy (HCM), from the 12-lead electrocardiogram (ECG). In this external validation study, we sought to assess the performance of an AI-ECG algorithm for detecting HCM in diverse international cohorts. Methods and results A convolutional neural network-based AI-ECG algorithm was developed previously in a single-centre North American HCM cohort (Mayo Clinic). This algorithm was applied to the raw 12-lead ECG data of patients with HCM and non-HCM controls from three external cohorts (Bern, Switzerland; Oxford, UK; and Seoul, South Korea). The algorithm's ability to distinguish HCM vs. non-HCM status from the ECG alone was examined. A total of 773 patients with HCM and 3867 non-HCM controls were included across three sites in the merged external validation cohort. The HCM study sample comprised 54.6% East Asian, 43.2% White, and 2.2% Black patients. Median AI-ECG probabilities of HCM were 85% for patients with HCM and 0.3% for controls (P < 0.001). Overall, the AI-ECG algorithm had an area under the receiver operating characteristic curve (AUC) of 0.922 [95% confidence interval (CI) 0.910-0.934], with diagnostic accuracy 86.9%, sensitivity 82.8%, and specificity 87.7% for HCM detection. In age- and sex-matched analysis (case-control ratio 1:2), the AUC was 0.921 (95% CI 0.909-0.934) with accuracy 88.5%, sensitivity 82.8%, and specificity 90.4%. Conclusion The AI-ECG algorithm determined HCM status from the 12-lead ECG with high accuracy in diverse international cohorts, providing evidence for external validity. The value of this algorithm in improving HCM detection in clinical practice and screening settings requires prospective evaluation.

We investigated the association of daylight saving time (DST) transitions with the rates of adverse cardiovascular events in a large, US-based nationwide study. The study cohort included 36,116,951 unique individuals from deidentified administrative claims data of the OptumLabs Data Warehouse. There were 74,722 total adverse cardiovascular events during DST transition and the control weeks (2 weeks before and after) in spring and autumn of 2015-2019. We used Bayesian hierarchical Poisson regression models to estimate event rate ratios representing the ratio of composite adverse cardiovascular event rates between DST transition and control weeks. There was an average increase of 3% (95% uncertainty interval, −3% to −10%) and 4% (95% uncertainty interval, −2% to −12%) in adverse cardiovascular event rates during Monday and Friday of the spring DST transition, respectively. The probability of this being associated with a moderate-to-large increase in the event rates (estimate event rate ratio, >1.10) was estimated to be less than 6% for Monday and Friday, and less than 1% for the remaining days. During autumn DST transition, the probability of any decrease in adverse cardiovascular event rates was estimated to be less than 46% and a moderate-to-large decrease in the event rates to be less than 4% across all days. Results were similar when adjusted by age. In conclusion, spring DST transition had a suggestive association with a minor increase in adverse cardiovascular event rates but with a very low estimated probability to be of clinical importance. Our findings suggest that DST transitions are unlikely to meaningfully impact the rate of cardiovascular events.