Publications

BACKGROUND: Despite advances in diagnostic capabilities and therapeutic options for aortic stenosis (AS), evidence suggests substantial underdiagnosis and care delays in real-world practice. This study examines patterns and disparities in AS diagnosis following echocardiographic identification, quantifying delays in diagnosis and subsequent care.

METHODS: Using the Optum® Market Clarity Dataset (2016-2023), we identified patients with first echocardiographic evidence of moderate or severe AS. Time-to-event analyses examined delays between echocardiographic findings and formal diagnosis (defined by ICD code assignment), subsequent imaging, and interventions. Analyses were stratified by severity, demographics, and care setting.

RESULTS: Among 2366 moderate and 1327 severe AS patients, 22.0% and 38.3% received formal diagnoses within one year of echocardiogram, respectively. Cumulative incidence of AS diagnosis at one year was lower in women vs men (moderate: 17.3% vs 27.8%; severe: 33.8% vs 43.0%) and non-White vs White patients (moderate: 11.4% vs 24.6%; severe: 25.8% vs 40.4%; all P ≤ 0.0001). Formal diagnosis was associated with increased likelihood of subsequent care (composite of follow-up imaging or aortic valve replacement) (moderate AS: HR 1.68, P < 0.0001; severe AS: HR 2.25, P < 0.0001).

CONCLUSIONS: This analysis reveals substantial delays in formal ICD-coded AS diagnosis following its echocardiographic detection, with concerning disparities across demographic groups. These findings suggest gaps between clinical recognition and formal documentation of AS, with implications for care continuum.

CLINICAL PERSPECTIVES: What Is New?•Using a large, real-world integrated claims and EMR database, this study demonstrates that fewer than one-quarter of patients with echocardiographically confirmed moderate AS and fewer than 40% with severe AS receive a formal ICD-coded diagnosis within one year, with substantially lower rates among women and non-White patients.What Are the Clinical Implications?•These findings reveal a critical gap between echocardiographic detection of AS and formal clinical documentation, suggesting that administrative claims data alone may substantially underestimate the true burden of AS in the population.•Formal AS diagnosis was independently associated with a significantly higher likelihood of receiving subsequent care - including surveillance imaging and aortic valve replacement - underscoring that closing the documentation gap may be a meaningful lever for improving outcomes and reducing disparities in AS management.

BACKGROUND: Ambulatory cardiac monitoring (ACM) is fundamental to arrhythmia evaluation, yet robust comparative evidence among alert-based monitoring strategies is lacking.

OBJECTIVE: To compare diagnostic yield and downstream clinical and economic outcomes among arrhythmia diagnosis-naïve Medicare Fee-For-Service (FFS) beneficiaries receiving mobile cardiac telemetry (MCT) or ambulatory event monitoring (AEM).

METHODS: Using 100% Medicare FFS claims from 2020 to 2022, this retrospective cohort study included beneficiaries aged 65 years or older, excluding those with prior arrhythmia diagnoses, antiarrhythmic medication use, or rhythm-management procedures. Cohorts were iRhythm MCT, Other MCT, and AEM; inverse probability of treatment weighting (IPTW) balanced baseline characteristics. Outcomes included diagnostic yield at 90 days, retesting at 180 days, and clinical events and costs at one year.

RESULTS: Among 441,792 eligible beneficiaries, 17,773 received iRhythm MCT (4%), 368,830 Other MCT (83%), and 55,189 AEM (13%). After IPTW, 90-day diagnostic yield was higher with iRhythm MCT (49.5%) than Other MCT (40%; HR 0.79 [95% CI, 0.77-0.81]) and AEM (39.1%; HR 0.76 [95% CI, 0.74-0.78]). Retesting at 180 days was more frequent with iRhythm MCT (8.8%) than Other MCT (6.3%; HR 0.70 [95% CI, 0.66-0.74]) and AEM (7.2%; HR 0.81 [95% CI, 0.76-0.87]). Pacemaker implantation was more common with iRhythm MCT; no differences were identified in hospitalizations, emergency visits, or heart failure.

CONCLUSIONS: Diagnostic yield and retesting varied across ACM platforms, though residual confounding cannot be excluded. No differences were identified in outcomes, utilization, or costs. Randomized trials are warranted to determine true differences in platform performance.

Randomized controlled trials (RCTs) remain the cornerstone of causal inference on the safety and efficacy of medicinal products. But their limited follow-up, controlled settings, and narrowly defined data collection to balance the burden to patients and maintain study feasibility often results in unaddressed important questions for health authorities and other clinical decision makers. Linkage of RCT data to routinely collected health data [real-world data (RWD)] offers a mechanism for addressing these gaps by extending observations and outcomes assessment into routine practice. This paper synthesizes methodological and operational considerations for RCTs with RWD linkage, drawing on deterministic, probabilistic, referential, and privacy-preserving record linkage methodologies and on four case studies that span different indications and regional settings: a long-term follow-up of a human papillomavirus vaccine trial using deterministic linkage via universal Personal Identity Numbers; a U.S. linkage of a respiratory syncytial virus vaccine trial to administrative health claims using privacy-preserving tokenization; and two transcatheter aortic valve replacement trials linked to Medicare claims to reproduce randomized treatment-effect estimates and to assess transportability to the broader Medicare population. We offer actionable methodological considerations and recommendations, drawing on the case studies and the broader linkage literature. Progress beyond the current state will require global health authority guidance specific to linking clinical trials with routinely collected data, shared benchmarks for evaluating linkage approaches, routine reporting and assessments of impact of use cases on regulatory and reimbursement decisions. Linkage of clinical trial data with routinely collected data sources can meaningfully accelerate clinical development and inform health authority and other clinical decision making.

BACKGROUND: The utility of routine troponin testing to identify recurrent myocardial infarction (MI) after an incident MI is unclear. We assessed the incidence and prognosis of recurrent MIs identified from centralized troponin review in patients from the Myocardial Ischemia and Transfusion (MINT) trial.

METHODS: The MINT trial randomized patients with acute MI and anemia to a liberal versus restrictive red blood cell transfusion strategy. Suspected recurrent MIs were identified through both site-report and centralized review of troponin levels collected for 3 days following randomization. Differences in cardiac, non-cardiac, and all-cause death at 30 and 180 days were compared across patients with any site-reported MI, only centrally identified MI, and no recurrent MI.

RESULTS: Among 3,504 patients, 275 (7.8%) had a recurrent MI within 30 days; 119 (43.3%) by site-report, and 156 (56.7%) by central troponin review only. Rates of cardiac and all-cause death at 30 and 180 days were highest for patients with site-reported MI, intermediate for centrally identified MI, and lowest for no recurrent MI; rates of non-cardiac death did not vary. Patients with only centrally identified recurrent MI had an increased risk of cardiac death at 30 days (RR 1.9, 95% CI 1.0-3.4) and 180 days (RR 1.7, 95% CI 1.1-2.7) compared to those without recurrent MI.

CONCLUSIONS: In patients with acute MI and anemia, centralized troponin review identified more than half of all recurrent MI events. Patients with centrally identified MI had a higher risk of cardiac death than those with no recurrent MI.

TRIAL REGISTRATION: ClinicalTrials.gov NCT02981407 https://clinicaltrials.gov/study/NCT02619136.

BACKGROUND: Reported adverse events (AEs) to the Food and Drug Administration Adverse Event Reporting System (FAERS) have suggested an increased rate of serious AEs (SAEs) during the COVID-19 pandemic, but the extent to which this may be related to overall changes in reporting during this time period is uncertain. Accordingly, we aimed to evaluate trends in SAE reporting across commercially available ultrasound enhancing agent (UEA) brands as a function of overall trends in AE reporting.

METHODS: We retrospectively analyzed the FAERS public database, 2014-2024, to evaluate risks of UEAs overall and by brand, compared to similar contrast media.

RESULTS: Between 2014 and 2024, 21,960,760 AEs were reported to FAERS, of which 11,450,891 (52.1%) were categorized as SAEs. Overall SAE reports to FAERS increased from 678,953 in 2014 to 1,368,393 in 2021 before subsequently declining to 1,065,845 in 2024 (-7.9% change from 2021 to 2024). During the same period, overall death reports to FAERS increased from 124,055 in 2014 to 195,207 in 2018 before declining to 147,046 in 2024. During this period of decline, there was a 23.9% relative increase in SAEs to UEAs which peaked in 2023 at 350 before declining to 326 in 2024. Deaths attributed to SAEs increased from 1 in 2014 to 19 in 2023 before declining to 9 in 2024. Overall, these data suggest that 11.2% of the observed increase in SAEs to UEAs can be attributed to reporting changes. Despite changes in relative risks for SAEs, absolute SAE rates remained small and lower than other types of contrast media.

CONCLUSIONS: In this analysis of the FAERS dataset, 2014-2024, 11.2% of SAEs to UEAs were attributable to temporal changes in AE reporting. Absolute risks are small and declining, suggesting broad safety of UEAs as a class. Collectively, these results support continued use of UEAs, but motivate improved safety screening and preparedness to mitigate small but existing risks.

BACKGROUND: Artificial intelligence-enabled quantitative coronary computed tomography angiography (AI-QCCTA) offers automated assessment of coronary plaque burden and morphology. Although AI-QCCTA has improved diagnostic consistency and downstream testing efficiency, its prognostic value for major adverse cardiovascular events (MACE) has not been comprehensively quantified.

METHODS: We systematically searched PubMed, Embase, and Cochrane through October 2025 for studies evaluating AI-based plaque analysis in patients without prior MACE undergoing CCTA. Outcomes of interest were pooled using random-effects GLMM models, and prognostic associations were synthesized using inverse-variance random-effects meta-analysis of hazard ratios (HRs). The primary endpoint was MACE; secondary outcomes included myocardial infarction (MI), revascularization, angina, stroke, and mortality. Subgroup analysis was done to identify the association of different plaque characteristics in predicting MACE/MI/Death.

RESULTS: Ten studies (n = 20,195) were included. Across six cohorts (n = 18,804), pooled rates were: all-cause mortality 1.20% (95% CI 0.38-3.77%), cardiovascular mortality 0.32% (0.21-0.48%), MACE 5.07% (1.25-18.46%), MI 1.30% (0.41-3.99%), and revascularization 13.09% (6.57-24.40%). AI-enabled plaque burden predicted MACE (HR 1.95, 95% CI 1.29-2.94; I2 = 99%), consistent in sensitivity analysis as per same AI platform use (HR 1.88, 95% CI 1.15-3.07). Low-attenuation plaque showed the strongest association (HR 2.95, 95% CI 1.95-4.45).

CONCLUSIONS: AI-QCCTA provides prognostic value beyond stenosis severity, with vulnerable plaque characteristics-particularly low-attenuation and non-calcified plaque most strongly predicting adverse cardiovascular outcomes. These findings support the integration of AI-enabled plaque analysis into contemporary risk stratification.

BACKGROUND: Whether the 2025 American Society of Echocardiography (ASE) diastolic dysfunction (DD) algorithm (DD25) improves mortality prognostication compared to the 2016 algorithm (DD16) in real-world practice is uncertain.

METHODS: We applied the DD25 algorithm to adult transthoracic echocardiography reports across a large academic multisite echocardiography laboratory from 2018 2024, linked to state mortality data, and determined reclassification of DD and mortality risk.

RESULTS: Of 12,948 included (age 62.8 ± 18.1, 51.4% women, 55.8% outpatient), 10,205 (78.8%) had diastology quantified by the 2016 and 2025 guidelines. Of these, 2,601 (25.5%) were reclassified by DD25 with increases in DD grade in 1,428 (54.9%) and decreases in 1,173 (45.1%). Among those reclassified, 2,391 (91.9%) had a single grade change in DD severity. A larger proportion of female patients (52% vs 48.7%) were classified as having DD by DD25 versus DD16. The rate of indeterminate DD was lower by DD25 (1,358 [10.4%]) vs DD16 (1,983 [15.3%]). The DD25 algorithm improved discrimination of mortality risk compared to DD16 (difference in areas under the curve = 0.02; 95% CI, 0.001-0.04; P = .03), although the magnitude of the associated risk across the follow-up period was similar after multivariable adjustment (P value for comparison of adjusted hazard ratios = .67).

CONCLUSIONS: In a large academic health system, one-quarter of patients had reclassification of diastolic function by the 2025 ASE diastology guidelines. As compared to the 2016 algorithm, the 2025 algorithm resulted in a larger proportion with DD, less indeterminate diastolic function, and improved discrimination of mortality.