Yao, Xiaoxi

Abstract Since its introduction in 2002, left atrial appendage closure (LAAC) has rapidly expanded as an alternative to anticoagulation in patients with atrial fibrillation at high risk of stroke. Harmonized processes for data collection, analysis, and reporting in LAAC trials are essential to enhance research quality and improve clinical practice. The Left Atrial Appendage Academic Research Consortium (LAARC) initiative is an independent collaboration of academic research organizations, cardiology and neurology experts, clinical trialists, and regulatory authorities from the USA, Europe, and Asia. The consortium engaged clinical experts, regulators—including the US Food and Drug Administration (FDA), European Notified Bodies, and Japan’s Pharmaceuticals and Medical Devices Agency (PMDA)—and industry leaders to define standardized study elements and endpoints for LAAC trials. Key considerations included alignment with prior Academic Research Consortium initiatives, procedural and mechanistic insights, and clinical relevance. Consensus definitions were proposed for mortality, stroke, bleeding, and device performance, along with composite endpoints for safety and effectiveness. The proposed LAARC consensus definitions aim to standardize endpoint reporting, improve comparability across studies, and support regulatory and clinical trial applications for this evolving therapy through broad dissemination in the peer-reviewed literature.

Abstract Background Hospital‐at‐home programs (HaH) in the United States have evolved to include a virtual‐hybrid delivery model, where all physician encounters are virtual and partnered with a home care team. Objective To examine whether a virtual hybrid HaH program enabled by technology has similar clinical outcomes to traditional brick‐and‐mortar (B&M) hospital care. Methods We conducted a pragmatic trial at three hospitals, randomizing 1150 acutely ill patients requiring hospital care between July 10, 2023, and October 31, 2023 one‐to‐one into two groups: intervention (HaH) and control (B&M). The primary analysis was an intention‐to‐treat non‐inferiority analysis of the primary outcome, which was a composite of 30‐day all‐cause mortality and unplanned readmissions. Secondary outcomes included 30‐day readmission, all‐cause mortality, and patient experience. Results The mean age was 67.8 (standard deviation [SD] 16.3) years, and 52.2% were female. The primary outcome occurred in 99 (17.3%) HaH patients and 114 (19.8%) B&M patients (odds ratio [OR] 0.85, 95% confidence interval [CI] 0.63–1.14, p = .28), meeting the non‐inferiority criterion. Thirty‐day unplanned readmission occurred in 84 (14.7%) HaH patients and 101 (17.5%) B&M patients (OR 0.81, 95% CI 0.59–1.11, p = .19). Thirty‐day all‐cause mortality occurred in 25 (4.4%) HaH patients and 19 (3.3%) B&M patients (OR 1.34, 95% CI 0.73–2.46, p = .35). No HaH patients died while receiving their hospital care at home. HaH program was associated with a higher likelihood of patients reporting feeling extremely comfortable or very comfortable (84.4% HaH; 60.9% B&M, p = .001). Conclusion A hybrid HaH model is a safe and comfortable alternative to traditional B&M hospital care.

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.

Introduction: Asymptomatic LV systolic dysfunction is often underdiagnosed, leading to missed opportunities for treatment. In a recently completed pragmatic RCT, an AI algorithm performed on the ECGs ordered as part of routine practice increased early diagnosis of low EF. The current study aimed to understand whether the effectiveness of the AI algorithm integrated into routine care differed by the socioeconomic status of the patient. Methods: The main findings of the RCT were previously published. Clinicians in the intervention group had access to AI results (i.e., a positive or negative screening result, with positive results indicating a high likelihood of low EF). When a positive result was found, clinicians in the intervention group received an alert that encouraged them to order TTE if considered clinically appropriate. Clinicians in the control group did not have access or received alerts. Area deprivation index (ADI) was used to measure area-level social determinants of health. This study included 16,992 patients (control 8,225; intervention: 8,767) who had ECG performed for any indications between 8/5/2019 and 3/31/2020, no prior HF, and a valid address to derive ADI. The primary endpoint was a new diagnosis of EF≤50% within 3 months. Results: The mean age was 60.5±17.6 y. AI increased the diagnosis of low EF in the overall cohort (OR 1.42 [1.13, 1.78], p=0.01). The magnitude of benefit was greater in patients with higher socioeconomic status, e.g., living in an area that is less deprived (OR 1.88 [1.16, 3.05]), with higher median income, lower poverty rate, higher education level, better housing conditions, and higher proportion of white-collar workers, although the interaction was not statistically significant (Figure). Conclusions: AI enables early diagnosis of low EF and the magnitude of benefit might be numerically greater in patients with higher socioeconomic status, possibly due to variations in access to or referral for subsequent testing.

BACKGROUND: Following regulatory approval, medical devices may be used “off-label.” Patent foramen ovale (PFO) closure is indicated to reduce recurrent stroke but has been proposed for other indications, including migraine, transient ischemic attack, and diving decompression illness. We sought to evaluate PFO closure rates and indications relative to the timing of regulatory approval and publication of key randomized trials. METHODS: We performed a retrospective cohort study using the OptumLabs Data Warehouse of US commercial insurance enrollees from 2006 to 2019. We quantified PFO closure among individuals with ≥2 years of preprocedure coverage to establish indications, classified hierarchically as stroke/systemic embolism, migraine, transient ischemia attack, or other. RESULTS: We identified 5315 patients undergoing PFO closure (51.8% female, 29.2%≥60 years old), which increased from 4.75 per 100 000 person-years in 2006 to 6.60 per 100 000 person-years in 2019. Patients aged ≥60 years accounted for 29.2% of closures. Procedure volumes corresponded weakly with supportive clinical publications and device approval. Among patients with PFO closure, 58.6% underwent closure for stroke/systemic embolism, 10.2% for transient ischemia attack, 8.8% for migraine, and 22.4% for other indications; 17.6% of patients had atrial fibrillation at baseline; and 11.9% developed atrial fibrillation postprocedure. Those aged ≥60 years and male were less likely to undergo closure for migraine than stroke/systemic embolism. CONCLUSIONS: From 2006 to 2019, PFO closure use was consistently low and corresponded weakly with clinical trial publications and regulatory status. Nearly half of patients underwent PFO closure for indications unapproved by the Food and Drug Administration. Regulators and payers should coordinate mechanisms to promote utilization for approved indications to ensure patient safety and should facilitate clinical trials for other possible indications.

Introduction: Recently, an artificial intelligence (AI) algorithm was validated for identifying ECG signatures of atrial fibrillation (AF) risk during normal sinus rhythm. Traditionally, socioeconomically disadvantaged populations are less likely to receive novel or guideline-recommended treatments, and have high chronic disease burden, including cardiovascular diseases. There have also been concerns about new technologies creating a digital divide, worsening existing health disparities. Hypothesis: An AI algorithm will detect AF risk unequally across patients with different levels of social determinants of health (SDOH). Methods: The initial prospective, non-randomized, interventional study leveraged EHR and digital technologies to prospectively enroll 1004 patients with a broad range of AI-ECG risks of AF, who received continuous cardiac rhythm monitoring for up to 30 days. The Area Deprivation Index (ADI) was used as a composite measure of SDOH which is comprised of indicators spanning four domains: income, education, employment, and house quality. 904 intervention patients linked to the ADI data were matched to 904 real-world control patients derived from eligible but unenrolled patients. Those with ADI under 33% were defined as having better SODH; and patients with ADI above 33% were defined as having worse SODH. Results: Median age was 74 years and 38% were women. After matching, the intervention and control arms were balanced in all baseline characteristics, including HF, HTN, diabetes, stroke, CAD and ADI. A hazard ratio of 3.11 (P<0.001) was computed when comparing intervention to control for primary AF diagnosis outcome. In patients with worse SDOH, the intervention increased AF detection from 2.6% to 8.8% (HR 3.63 [2.09, 6.32]); in the better SDOH, the intervention increased AF detection from 3.9% to 9.3% (2.41 [1.23, 4.74]). Conclusions: An AI-guided AF screening program increased the detection of AF in both patients with better or worse SDOH. The current study validates the use of AI in historically disadvantaged populations displaying the possibility for broad implementation with decreased possibility of perpetuating disparities.

Introduction: Previous studies have shown inconsistent changes in the rates of adverse cardiovascular events after daylight savings time (DST) transitions. In this large-scale, U.S.-based nationwide study, we sought to investigate the association of DST transitions with the rates of adverse cardiovascular events. Methods: The study cohort included 36,116,951 unique individuals from de-identified administrative claims data of the OptumLabs Data Warehouse®. There were 74,722 total adverse cardiovascular events during the week of DST transition and the control weeks (two weeks prior and after) in spring and autumn of 2015-2019. We used Bayesian hierarchical Poisson regression models to estimate the event rate ratios (ERR) representing the ratio of composite adverse cardiovascular event rates (acute myocardial infarction, stroke, cardiogenic shock, cardiac arrest, and sudden death) between DST transition weeks and control weeks. Results: Our results showed an average increase of 3% [95% uncertainty interval; -3% to 10%] and 4% [-2% to 12%] in the rate of adverse cardiovascular events during Monday and Friday of the spring DST transition week, respectively. The probability of spring DST transition being associated with a moderate-to-large increase in the event rates (ERR>1.10) was estimated to be <6% for Monday and Friday, and <1% for the remaining days. During autumn DST transition, the probability of any decrease in adverse cardiovascular event rates was estimated to be <46% and a moderate-to-large decrease in the event rates to be <4% across all days of the week. Conclusions: Spring DST transition week had a suggestive association with a minor increase in adverse cardiovascular event rates on Monday and Friday. The probability of this association to be of clinically meaningful magnitude was estimated to be very low. We did not observe any evidence suggestive of a change in adverse cardiovascular event rates immediately following autumn DST transition. Taken together, our findings, based on a large, diverse cohort from across the United States, suggest that DST transitions are unlikely to significantly impact the rate of cardiovascular events.

Background Little is known about outcomes following heart failure (HF) hospitalization among adults with congenital heart disease (CHD) in the United States. We aim to compare the outcomes of HF versus non‐HF hospitalizations in adults with CHD. Methods and Results Using a national deidentified administrative claims data set, patients with adult congenital heart disease (ACHD) hospitalized with and without HF (ACHDHF+, ACHDHF−) were characterized to determine the predictors of 90‐day and 1‐year mortality and quantify the risk of mortality, major adverse cardiac and cerebrovascular events, and health resource use. Cox proportional hazard regression was used to compare ACHDHF+ versus ACHDHF− for risk of events and health resource use. Of 26 454 unique ACHD admissions between January 1, 2010 and December 31, 2020, 5826 (22%) were ACHDHF+ and 20 628 (78%) were ACHDHF−. The ACHD HF+ hospitalizations increased from 6.6% to 14.0% ( P <0.0001). Over a mean follow‐up period of 2.23 ± 2.19 years, patients with ACHDHF+ had a higher risk of mortality (hazard ratio [HR], 1.86 [95% CI, 1.67–2.07], P <0.001), major adverse cardiac and cerebrovascular events (HR, 1.73 [95% CI, 1.63–1.83], P <0.001) and health resource use including rehospitalization (HR, 1.09 [95% CI, 1.05–1.14], P <0.001) and increased postacute care service use (HR, 1.56 [95% CI, 1.32–1.85], P <0.001). Cardiology clinic visits within 30 days of hospital admission were associated with lower 90‐day and 1‐year all‐cause mortality (odds ratio [OR], 0.62 [95% CI, 0.49–0.78], P <0.001; OR, 0.69 [95% CI, 0.58–0.83], P <0.001, respectively). Conclusions HF hospitalization is associated with increased risk of mortality and morbidity with high health resource use in patients with ACHD. Recent cardiology clinic attendance appears to mitigate these risks.

Introduction: Using a digital process that leverages electronic health records (EHRs) can ease many of the challenges presented by the traditional enrollment process for clinical trials. We tested if automated batch enrollment using a technology-enabled subject recruitment system (TESRS) enhances recruitment while preserving representation of research subjects for the study population in our study setting. Methods: An ongoing community-based prospective adult cohort study was used to randomize 600 subjects who were eligible by age and residential address to TESRS (n = 300) and standard mailing method (n = 300), respectively, for 3 months. Then, TESRS was initiated and included automatic identification of patients’ preference for being contacted (online patient portal vs postal mail) from EHRs and automatic sending out of invitation letters followed by completion of a short online survey for checking eligibility and the digital consent process if eligible. We compared (1) median time to consent from invitation sent out per subject and total subjects recruited after a 3-month recruitment period, (2) the estimated study staff’s time, and (3) representation of sociodemographic characteristics (e.g., age, sex, race, SES measured by HOUSES index, and rural residence) between subjects recruited via TESRS and those via traditional mailing methods. Results: Median age of randomized subjects (n = 600) was 63 years with 52.0% female and 89.2% non-Hispanic White. Over a 3-month period, results showed consent rate via TESRS was 13% (39/297) similar to 11% (31/295) via standard mailing. However, recruitment was significantly faster with the TESRS approach (median 7 vs 26 days) given the study staff’s effort. Study staff’s time saved by using TESRS compared to standard mailing approach was estimated at 40 min per subject (equivalent to 200 h for 300 subjects). No significant differences in characteristics of research subjects from the study population were found. Conclusion: Our study demonstrated the utility of TESRS as a subject recruitment digital technology which significantly enhanced the recruitment effort while reducing the study staff burden of recruitment while maintaining the consistency of characteristics of recruited subjects. The strategy and support for implementing and testing TESRS in other study settings should be considered.