Citations

Abstract Cardiovascular disease is the leading cause of morbidity and mortality globally, imposing a substantial patient burden. Digital biomarkers derived from digital health technologies enable quantifiable, near-continuous, real-world capture of pathophysiological signals and are increasingly used across cardiovascular medicine. Their growth is often supported by big data analytics, artificial intelligence and connected sensors within the Internet of Things. This scientific statement systematically reviews digital biomarkers, their clinical utility across the cardiovascular care continuum, and summarizes major methodological and implementation challenges. We searched PubMed/MEDLINE, Embase and Scopus for phase III–IV cardiovascular trials published between 1 January 2019 and 1 August 2024 that collected digital biomarkers. We identified 541 records and included 32 trials (40 reports) enrolling 32 246 participants (44.71% women; mean age 66.2 ± 11.0 years). Heart failure was the most frequent target condition (16 trials, 50%), followed by cardiac implantable electronic devices trials (12 trials, 38%). Digital biomarkers included cardiac rhythm and heart rate, blood pressure, body weight, impedance-based measures, haemodynamic pressures, and physical activity and sleep patterns captured using diverse sensor technologies. Methodological quality was good (modal quality score 5; range 3–7), although most trials were unblinded. Current studies suggest potential clinical utility in selected cardiovascular conditions. Implementation remains challenging because of measurement variability, privacy and regulatory requirements, affordability and reimbursement barriers and inequities in access. Robust validation and outcome- and cost-effectiveness evidence are still needed. Registration number: CRD42024573879.

Abstract Objective To describe the development and implementation of an automated platform for genomic risk prediction that integrates multiple data types. Materials and methods Using the REDCap infrastructure, we constructed the R4 (Recruitment, Results, and Risk Reduction) platform to intake data from clinical sites, partner laboratories, participant surveys, and electronic health record (EHR) data across 13 institutions. Results The R4 Portal successfully integrated data to generate genome-informed risk assessments (GIRAs) across 11 conditions for a 23 840 person cohort. Testing phases and quality control led to network-wide protocols ensuring consistency and accuracy. Discussion As the science of estimating disease risk evolves, standardized and high-throughput methods of collecting and manipulating complex data are required. Platforms should be open-source, modular, and reusable, ensuring flexibility, security, and integration across healthcare environments. Conclusion The electronic MEdical Records and GEnomics (eMERGE) network successfully generated and returned comprehensive risk profiles using logic and data specific to 11 conditions in a secure and semi-automated fashion employing a customized REDCap database.

Background Radionuclide SPECT/computed tomography (CT) is standard for diagnosing transthyretin cardiac amyloidosis (ATTR-CM), but the prognostic value of quantitative metrics remains incompletely defined. We investigated their prognostic utility and additive value beyond existing staging systems. Methods Retrospective study of patients undergoing technetium-99m-pyrophosphate (PYP) SPECT/CT, including consecutive clinically referred patients (October 2023 to 2024) and trial participants with positive scans from January 2022. Myocardial PYP was quantified using standardized uptake values (SUV mean and SUV max ) and volumetric measures [percent injected dose (%ID), cardiac amyloid activity (CAA)]. Major adverse cardiovascular events (MACEs) comprised heart failure hospitalization or death. Cox and Kaplan–Meier analyses assessed associations; likelihood ratio testing and change in area under the curve (AUC) evaluated the additive prognostic value to existing staging systems. Results Among 43 patients with ATTR-CM, 16 experienced MACE over a median 518 days. AUCs ranged from 0.74 to 0.88 at 3 months and 0.56–0.62 at 12 months. All variables trended toward association with MACE: SUV mean ( P = 0.02), SUV max ( P = 0.03), %ID ( P = 0.06), and CAA ( P = 0.06). After age adjustment, cut-points for SUV max (5.8) and SUV mean (3.5) remained associated with MACE. Adding imaging variables to the National Amyloidosis Centre and Columbia staging systems did not significantly improve prognostic accuracy (Δ χ 2 : 0.40–2.48, P = 0.11–0.53). Interobserver reproducibility was high (intraclass correlation coefficients = 0.89–0.99). Conclusion Quantitative Tc-99m–PYP SPECT/CT metrics were associated with short-term outcomes in ATTR-CM, but did not improve established staging systems. Findings are hypothesis-generating and require validation in larger cohorts.

Diffusion MRI (dMRI) enables assessment of white matter microstructural abnormalities in Alzheimer's disease (AD), and multisite datasets enable more robust modeling of non-biological variation that can confound analyses. The Alzheimer's Disease Neuroimaging Initiative (ADNI) includes over 10 dMRI protocols, necessitating robust methods to model protocol-related variability when pooling data. Here, we compared three harmonization approaches: (1) mixed-effects models, (2) ComBat-GAM, and (3) eHarmonize, a reference-based lifespan method. We assessed their ability to reduce protocol-related variability in diffusion tensor imaging fractional anisotropy (FA) and mean diffusivity (MD) while preserving associations with cognitive impairment (CI), and amyloid-beta (Aβ) and tau PET burden in 1,086 ADNI3/4 participants. All approaches yielded more closely aligned FA/MD distributions across protocols. Associations with clinical indicators of CI were highly consistent across approaches, whereas PET associations were less widespread and more variable. Overall, multiple strategies effectively modeled protocol-related variability while preserving AD-related associations.

Background Recurrent pericarditis may be mediated through inappropriate activation of the NACHT, leucine‐rich repeat, and pyrin domain‐containing protein 3 inflammasome. Pharmaceutically manufactured cannabidiol is an oral formulation that inhibits NACHT, leucine‐rich repeat, and pyrin domain‐containing protein 3 inflammasome activation and development of pericarditis in a preclinical model. Methods This Phase 2, open‐label, multicenter trial included adult patients with symptomatic recurrent pericarditis: pericarditis chest pain ≥4 on an 11‐point numerical rating scale with an elevated C‐reactive protein (≥1 mg/dL) or at least mild pericardial inflammation on cardiac magnetic resonance imaging. At enrollment, patients were on stable doses of non‐steroidal anti‐inflammatory drugs, colchicine, and/or corticosteroids. Cannabidiol was administered during an 8‐week treatment period and an optional 18‐week extension period when background therapy was tapered and discontinued. The primary efficacy end point was change in patient‐reported pericarditis pain. Secondary end points included normalization of C‐reactive protein and percentage of patients with recurrences. Results Among 27 patients (18 women, mean age 53 years), baseline maximal numerical rating scale pain score was 5.8±1.7, and 10 patients had elevated C‐reactive protein. At Week 8, maximal numerical rating scale pain score was 2.1±1.8, and median time to numerical rating scale score ≤2 was 5 days. Among the 10 patients with baseline C‐reactive protein elevation, C‐reactive protein was normal at Week 8 in 8 patients (80%). During the extension period, 17 (71%) of 24 patients remained free of pericarditis recurrence. A serious adverse event leading to cannabidiol discontinuation occurred in 1 patient. Conclusions In symptomatic patients with recurrent pericarditis, pharmaceutically manufactured cannabidiol appears safe and associated with reductions in pericarditis pain and systemic inflammation. Registration URL: clinicaltrials.gov ; Unique Identifier: NCT05494788.

Abstract Obesity has emerged as one of the most significant health challenges, with prevalence rates exceeding 30% in many regions and contributing substantially to the burden of cardiovascular disease (CVD). This review synthesized findings from clinical trials, systematic reviews, and narrative reviews. Key outcomes assessed included heart failure symptoms, echocardiographic parameters, incidence of atrial fibrillation (AF), inflammation biomarkers, and overall cardiovascular morbidity and mortality. Across studies, obesity was consistently linked with elevated risk of coronary heart disease, AF, stroke, and heart failure with preserved ejection fraction (HFpEF). Central adiposity and ectopic fat depots, especially epicardial fat, emerged as critical mediators of CVD progression. Semaglutide, tirzepatide, and other agents have demonstrated robust effects in reducing weight, improving functional capacity, and attenuating cardiac remodeling, with additional benefits in lowering inflammation markers and natriuretic peptides independent of weight loss. Notably, patients with AF and obesity-related HFpEF appeared to experience greater symptomatic and functional improvements with semaglutide compared with those without AF. Conversely, evidence on the obesity paradox and metabolically healthy obesity revealed heterogeneity, with some subgroups demonstrating preserved or even improved survival despite excess adiposity, though these effects may be confounded by differences in cardiorespiratory fitness and lead time biases. Obesity remains a powerful risk factor for CVD, mediated through both metabolic and structural pathways. The advent of anti-obesity pharmacotherapies represents a watershed moment for cardiology, offering disease-modifying potential in obesity-related heart failure and beyond. Future research should refine the understanding of obesity phenotypes, and the role of fat distribution and cardiorespiratory fitness.

Abstract Genetic studies have significantly advanced our understanding of tauopathies, yet the genetic aetiology of Pick’s disease, a rare 3-Repeat tauopathy, remains unclear. The MAPT p.A152T variant has been identified as a risk factor for Alzheimer’s disease and progressive supranuclear palsy, but its role in Pick’s disease is unknown. In this study, we examined the prevalence of MAPT p.A152T in the largest series of neuropathologically confirmed Pick’s disease cases to date (n = 401). Through genotyping, we identified a single mutation carrier in the Pick’s disease cohort (minor allele frequency = 0.12%). We previously reported MAPT p.A152T at a 0.20% frequency in healthy controls (n = 2456), suggesting that it does not associate with 3-Repeat tauopathy risk. To further investigate the effect of the variant on MAPT transcript expression, we used bulk RNA sequencing in Alzheimer’s disease and progressive supranuclear palsy A152T mutation carriers. We did not detect significant differences in 4-Repeat tau levels, though preliminary trends may indicate more nuanced effects that need to be examined with long-read sequencing in a larger series. Overall, our study suggests that MAPT p.A152T does not increase Pick’s disease risk and may instead be linked to 4-Repeat or mixed tau pathologies, warranting further functional investigation.

ABSTRACT Background Olfactory neuroblastoma (ONB) exhibits variable recurrence patterns, with significant late recurrences occurring years after treatment. We investigated cutoff periods to define late recurrence and identified predictors that distinguish patients at risk of late recurrence from those considered cured. Methods From a multi‐institutional cohort of 219 ONB patients treated at nine centers, we analyzed 77 patients with documented recurrence. Using a 48‐month cutoff to define early (< 48 months) versus late (≥ 48 months) recurrence, we evaluated 35 clinical, anatomic, and treatment variables using Firth penalized logistic regression across three comparisons: (1) late versus early recurrence timing, (2) late recurrence versus no recurrence, and (3) early recurrence versus no recurrence. Results Thirty‐four of the 77 (44.2%) recurrences were classified as late. Among the 77 patients who recurred, smaller tumor volume (OR 0.243, p = 0.035) and lower novel Dulguerov staging (OR 0.802, p = 0.038) were associated with late, rather than early recurrence. When patients with late recurrence were compared to those who remained disease‐free, radiographic skull base bone involvement was the strongest independent predictor (OR 2.90, 95% CI 1.14–8.64, p = 0.025), and this effect strengthened after adjusting for tumor volume (OR 3.80, p = 0.029). Pathologic dural invasion (OR 3.29, p = 0.013), Kadish stage (OR 2.02, p = 0.026), and T‐stage (OR 1.32, p = 0.040) were also significant. Conclusions A 48‐month cutoff effectively stratifies ONB recurrence risk. Skull base bone involvement independently predicts recurrence when compared to nonrecurrent cases and uniquely persists as a risk factor for late recurrence. These findings establish skull base bone involvement as a novel biomarker for risk‐stratified surveillance protocols.