Citations

Abstract INTRODUCTION We describe the reliability of remote self‐administered digital cognitive measures completed via the Mayo Test Drive (MTD) web‐based platform. METHODS A total of 1846 participants (mean age = 70, SD = 12, range 31–101; 48% male; 96% White; 99% non‐Hispanic; 97% cognitively unimpaired) with two to four complete MTD sessions at ∼7.5‐month intervals were included. Test‐retest reliability was assessed using single‐rating, absolute‐agreement, and two‐way mixed intraclass correlation coefficients (ICCs) with 95% confidence intervals. ICCs for in‐person‐administered traditional neuropsychological measures were compared to MTD for a subset of 244 participants. Analyses also compared reliability across demographic, residential, and session context subgroups. RESULTS Reliability was good for the MTD Composite (total ICC = 0.79 [0.77, 0.80]), and moderate‐to‐good for the primary outcome variables for each MTD subtest (total ICCs 0.70–0.83 for Stricker Learning Span and Symbols). The reliability of the remote self‐administered MTD was similar to in‐person‐administered cognitive measures. DISCUSSION MTD showed moderate‐to‐good reliability, supporting its use in longitudinal monitoring.

Inflammatory bowel disease (IBD) is driven by a breakdown in immune regulation and epithelial barrier function, yet the contribution of eosinophils to this process has remained poorly defined and controversial. While eosinophils infiltrate the intestinal mucosa during both flares and remission, their role in shaping disease outcomes is unclear. Our RNA-seq analyses of colonic eosinophils isolated from dextran sulfate sodium (DSS)-treated mice revealed a significant upregulation of cyclooxygenase (COX)-2 (gene name, Ptgs2 ). Eosinophil-specific deletion of COX-2 (Ptgs2 fl/fl eoCre +/− ) reduced IL-22 production and exacerbated DSS- and trinitrobenzene sulfonic acid (TNBS)-induced colitis, characterized by greater weight loss, higher disease activity, colon shortening, and epithelial injury. Administration of recombinant IL-22 reversed these phenotypes. Mechanistically, eosinophil-derived COX-2 enhanced IL-22 production by type 3 Innate lymphoid cells (ILC3s) through prostaglandin E2 (PGE 2 ) signaling. Consistently, Ptgs2 fl/fl eoCre +/− mice exhibited reduced colonic PGE 2 levels, while PGE 2 analog treatment restored IL-22 production and mucosal protection. Our findings identify eosinophil-derived COX-2 and PGE 2 as a critical regulator of IL-22 production during colitis, uncovering a eosinophil–ILC3 cross talk that safeguards the intestinal barrier and represents a promising therapeutic target in IBD.

Background: Mindfulness-based interventions may improve cardiovascular health (CVH) by supporting behavioral change across multiple risk factors. This study evaluated the impact of Mindfulness-Based Blood Pressure Reduction (MB-BP), a mindfulness program targeting hypertension-related behaviors ( Image 1 ), on CVH using the American Heart Association’s Life’s Essential 8 framework. Methods: This secondary analysis of parallel-group, phase 2 randomized clinical trial evaluated the effects of MB-BP on CVH in 201 participants with elevated office BP (≥120/80 mmHg). The MB-BP group (n=101) received an 8-week program focused on mindfulness training and education targeting diet, physical activity, medication adherence, alcohol use, and stress, whereas the control group (n=100) received enhanced usual care ( Image 2 ). CVH was assessed using available Life’s Essential 8 components: systolic blood pressure, body mass index (BMI), diet (DASH adherence), physical activity, smoking, and sleep duration. Generalized estimating equations evaluated intervention effects through six months. Results: At six months follow-up, MB-BP participants significantly improved composite CVH scores compared to controls (standardized mean difference: 0.144; 95% CI: 0.023, 0.266) ( Image 3 ). MB-BP influenced most CVH components in healthier directions at trend levels, with the strongest responses for physical activity (47.9 MET min/week; 95% CI: -16.5, 112.3), sleep (0.34 hours/night; 95% CI: -0.10, 0.78), systolic blood pressure (-4.95 mmHg; 95% CI: -10.34, 0.44) and DASH diet score (0.27, 95% CI: -0.15, 0.69). Conclusions: MB-BP led to modest but clinically significant improvements in CVH, driven by multiple Life’s Essential 8 components. These findings suggest that MB-BP may be an effective behavioral intervention to support CVH and reduce risk for cardiovascular disease. ClinicalTrials.gov Preregistration Identifiers: NCT03256890, NCT03859076

Objective To examine the potential errors of a general large language model (LLM) (ie, Claude 3.5 Sonnet) on data extraction from randomised controlled trials (RCTs). Design and setting An empirical study comparing Claude 3.5 Sonnet extractions against a human-performed verification dataset. The extraction tasks for Claude 3.5 Sonnet were based solely on original RCT portable document format (PDF) files. For PDFs that could not be directly extracted by Claude 3.5 Sonnet, optical character recognition was employed to convert them into text format before extraction. Participants A random sample of 664 trials was selected from a well-established trial bank and a final data pool was established based on rigorous manual cross-checking as a reference standard. Data sources PubMed, EMBASE, Scopus, Web of Science (all databases) and the Cochrane Central Register of Controlled Trials (CENTRAL) up to February 2023. Eligibility criteria for selecting studies RCTs on children involving medication and adverse events. Main outcome measures Claude 3.5 Sonnet was applied to extract the basic information (eg, trial design, population information and source of funding) and adverse outcomes (ie, name of adverse events, number of events). Claude 3.5 Sonnet outputs were compared against the final data pool and all errors were recorded. Results are presented as error rates and with 95% CI, estimated using a generalised linear mixed model. Results For the 664 trials, a total of 23 069 data cells were extracted via Claude 3.5 Sonnet, with 10 624 for basic information and 12 445 for adverse outcomes. The overall error rate for data extraction was 6.6% (95% CI 5.4% to 8.2%), with 5.7% (95% CI 5.2% to 6.1%) in basic information and 7.6% (95% CI 4.9% to 11.8%) in adverse outcomes. When stratified the 1542 total errors by error types, misallocation (assigning data to incorrect fields; 57.1%, 881/1542) and missed or omitted data (incomplete extraction of available data; 23.2%, 357/1542) accounted for the two most frequent errors, with misallocation occurring more in basic information (53.3%, 470/881), while missed or omitted data occurred more in adverse outcomes (96.1%, 343/357). Post hoc analysis examining the association between trial reporting quality (assessed using Consolidated Standards of Reporting Trials (CONSORT) 2025 and LLM data extraction error rates indicated that higher CONSORT adherence was associated with lower extraction error rates. Conclusions The data extraction error of Claude was relatively low, but it alerts LLM applications in evidence synthesis. Detailed checking for LLM outputs should be the primary consideration for evidence synthesisers.

Abstract Context Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, and consequences remain undefined. Objective To develop, validate, and deploy a natural language processing (NLP) pipeline to identify ITFs in radiology reports and assess their prevalence, features, and clinical outcomes. Design Retrospective cohort study. Setting Mayo Clinic sites (Rochester, Arizona, Florida, Mayo Clinic Health System). Participants Adults without prior thyroid disease undergoing thyroid-capturing imaging from July 1, 2017, to September 30, 2023. A transformer-based NLP pipeline identified ITFs and extracted nodule characteristics from image reports from multiple modalities and body regions. Outcomes ITF prevalence, downstream thyroid ultrasound, biopsy, thyroidectomy, and cancer diagnosis. Logistic regression identified demographic and imaging-related factors. Results Among 115 683 patients (mean age, 56.8 [SD 17.2]; 52.9% women), 9077 (7.8%) had an ITF (92.9% nodular). ITFs were more likely in women, older adults, higher BMI, and in imaging ordered by specialties different from Emergency Medicine. Compared with chest CT, ITFs were more likely via neck CT, PET, and nuclear medicine scans. Nodule characteristics were poorly documented, with size reported in 44% and other features in fewer than 15%. Compared with patients without ITFs, those with ITFs had higher odds of thyroid nodule diagnosis (OR 45, 95%CI 41.1-49.3), biopsy (OR 46.8, 95%CI 39.0-56.2) thyroidectomy (OR 55.8, 95%CI 31.3-99.3), and thyroid cancer diagnosis (OR 61.7, 95%CI 38.6-98.5). Most cancers were papillary (88.5%) and larger when detected after ITFs (2 cm SD 1.4) vs no ITF (1.3 cm SD 0.8). Conclusion ITFs were common and strongly associated with cascades leading to the detection of small, low-risk cancers, highlighting their role in overdiagnosis and the need for standardized reporting and more selective follow-up.

The regulation of the cardiomyocyte cell cycle is central to understanding heart regeneration. In adult mammals, cardiomyocytes withdraw from the cell cycle, limiting their ability to proliferate and repair heart tissue after injury. This process is controlled by intrinsic genetic programs and extrinsic signals, which together restrict the regenerative response in mature hearts. Understanding the mechanisms that regulate cardiomyocyte cell cycle activity is therefore critical for advancing cardiac regenerative medicine. In this review, we provide a comparative and integrated overview of cardiomyocyte cell cycle regulation in lower vertebrates and mammals, and discuss the major intrinsic factors that govern this process, including cyclin/CDK pathways, transcription factors and co-activators, oxygen and metabolic regulation, and epigenetic mechanisms. We also review the influence of hormones and growth factors, as well as the supportive roles of nonmyocyte populations in heart regeneration. By integrating findings across species, developmental stages, and regulatory levels, these findings highlight the complex regulatory network controlling cardiomyocyte proliferation and provide insight into potential therapeutic strategies for stimulating cardiac repair in the adult mammalian heart.

Introduction Increasing publication of fraudulent clinical trials poses a serious threat to evidence-based medicine. In the VITALITY Study I, we demonstrated that contamination by retracted trials significantly distorts evidence synthesis. The upcoming VITALITY Study II will take a step further and investigate how such problematic evidence undermines the credibility of guideline recommendations. Methods and analyses The VITALITY Study II will adopt a retrospective cohort design and will be structured as three work packages (WPs). To start with, a cohort of clinical practice guidelines (CPGs) that were contaminated by retracted trials and/or meta-analyses that included retracted trials will be established based on forward citation searching (WP1). Then, recommendations from these CPGs that used evidence from retracted trials and/or meta-analyses that synthesised these retracted trials will be re-evaluated after removing such problematic evidence, in terms of both the direction and strength of effect sizes (WP2). Finally, the subsequent impact on patient outcomes attributable to distorted recommendations will be estimated on a hypothetical population, measured by the number of expected benefit loss and the number of expected harm increment per 100 000 patients (WP3). Ethics and dissemination Formal ethical approval is not necessary for this study as it does not involve human or animal participants, nor does it involve the collection of primary data. We will disseminate the findings through publication in peer-reviewed journals and, whenever possible, presentations at academic conferences.

Abstract Background Current risk assessment tools for guiding direct oral anticoagulant (DOAC) therapy for patients with atrial fibrillation (AF) based on clinical risk factors demonstrate modest predictive performance limiting clinical impact. Additionally, while guidelines recommend periodic reassessment of risk over time, there remains an absence of modelling solutions for capturing evolving risk in AF patients. Methods Using UK electronic health records, we developed and validated the Transformer-based Risk assessment survival model (TRisk), an artificial intelligence model that predicts 12-month thromboembolic and bleeding events in AF patients by leveraging temporal patient journeys up to baseline. A cohort of 411,850 prevalent non-valvular AF patients aged ≥18 years between 2010 and 2020 was identified from 1,442 English general practices. Practices were randomly allocated to derivation (n=1,079) and external validation (n=363) cohorts. TRisk was compared with CHA 2 DS 2 -VASc and CHA 2 DS 2 -VA for thromboembolic event prediction, and HAS-BLED and ORBIT for bleeding prediction, with subgroup analyses by sex, age, and baseline characteristics. A second validation of TRisk was also performed on 16,218 US AF patients between 2010 and 2023. A decision model compared outcomes and healthcare costs for TRisk versus standard care. Findings TRisk achieved higher discrimination for thromboembolic event prediction (C-index: 0.82; 95% confidence interval [CI]: [0.81, 0.83]) as compared to CHA 2 DS 2 -VASc (0.71 [0.70, 0.73]) in UK validation. Application of TRisk to US data yielded similar C-index: 0.82 (0.80, 0.84). For bleeding prediction, TRisk (C-index: 0.70 [0.69–0.71]) outperformed both HAS-BLED (0.63; [0.61, 0.64]) and ORBIT (0.64; [0.63, 0.65]), with comparable US results (0.71; [0.69, 0.74]). The model remained well-calibrated across both populations and performed equitably across subgroups, including by race and during the COVID-19 pandemic. Impact analyses showed TRisk could reduce DOAC prescriptions by 8% in the UK and 7% in the US relative to guideline-recommended approaches, while preventing at least as many thromboembolic events. This refined approach would generate annual healthcare savings of £5.5 million and $456.2 million in the UK and US respectively among patients initiating DOACs, rising to £48.6 million and $1.8 billion when extended to all AF patients on DOACs. Interpretation TRisk enabled more precise prediction for both thromboembolic and bleeding events across AF populations in UK and US compared to established clinical scoring systems. Incorporating TRisk into routine AF care would result in substantial cost savings without compromising the identification of true high-risk patients. Funding None