Citations

ABSTRACT Background Data on the global prevalence of alarm features in the general population and among individuals with disorders of gut–brain interaction (DGBI) are limited. Methods We analysed data from the Rome Foundation Global Epidemiology Study to estimate the prevalence of fourteen self‐reported alarm features in the global population and among individuals with Rome IV defined DGBI, including 54,127 participants from 26 countries. Differences between participants with and without DGBI were evaluated in a sample excluding those with self‐reported organic gastrointestinal disease, using univariable logistic regression. Analyses were stratified by age (< 50 vs. ≥ 50 years). Results Alarm features were reported by 63.1% of participants aged < 50 years and 51.8% of those aged ≥ 50 years. Individual self‐reported alarm features ranged from 0.9% to 18.3% in younger participants to 0.3%–13.3% in older participants. Haematemesis was the least frequently reported feature, while a major change in bowel movements was the most frequent in both age groups. Self‐reported alarm features were more frequent among participants with than without DGBI (< 50 years: 75.3% vs. 50.7%; OR 3.0 [2.8–3.1]; ≥ 50 years: 67.5% vs. 38.8%; OR 3.3 [3.1–3.5]). Participants with DGBI were also more likely to report multiple alarm features. Discussion Self‐reported alarm features are common in the general population and more prevalent among individuals with DGBI. These findings underscore the importance of interpreting alarm features within a broader clinical context rather than in isolation. Further studies are needed to clarify the diagnostic utility of alarm features in unselected populations, particularly among individuals with DGBI.

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 Background Precise delineation of non-contrast-enhancing tumor (nCET) in glioblastoma (GB) is critical for maximal safe resection, yet routine imaging cannot reliably separate infiltrative tumor from vasogenic edema. The aim of this study was to develop and validate an automated method to identify peritumoral subregions compatible with nCET and assess its prognostic value. Methods Pre-operative T2-weighted and FLAIR MRI from 940 patients with newly diagnosed GB in four multicenter cohorts were analyzed. A deep-learning model segmented enhancing tumor, edema and necrosis; a non-local, spatially varying finite mixture model was applied to identify edema subregions characterized by relatively lower FLAIR hyperintensity, hypothesized to reflect nCET-related tissue. The ratio of these subregions to total edema volume defined the T2/FLAIR Heterogeneity Index (TFHI). Associations between TFHI and overall survival (OS) were examined with Kaplan–Meier curves and multivariable Cox regression. Results Higher TFHI values stratified patients with shorter OS. In the NCT03439332, TFHI above the optimal threshold was associated with a twofold increased hazard of death (hazard ratio [HR] 2.07, 95 % confidence interval 1.33-3.21; P = .0013) and a reduction in median survival of 98 days. Significant, though smaller, prognostic effects were confirmed in GLIOCAT & BraTS (HR= 1.37; P = .047), OUS (HR = 1.37; P = .0032) and pooled analysis (HR= 1.26; P = .0008). TFHI remained an independent predictor after adjustment for age, extent of resection and MGMT methylation. Conclusions We present a reproducible, server-hosted tool for automated identification of imaging-defined, putative nCET-related peritumoral subregions and TFHI biomarker extraction that enables independent prognostic stratification. This approach provides a quantitative framework for studying peritumoral heterogeneity in GB.

Abstract Metabolic disorders such as obesity, type 2 diabetes, and dyslipidaemia are major drivers of cardiovascular risk and have reached epidemic levels in Western populations. Recent advances in clinical research have uncovered unexpected and often beneficial effects of pharmacological classes of metabolic drugs on cardiovascular outcomes, revealing complex interactions between metabolism and cardiac pathology. Despite their clinical efficacy, the molecular and cellular mechanisms through which many of these agents act remain only partially understood. This gap in knowledge underscores the urgent need for fundamental research that not only dissects the biology of metabolic disorders and cardiovascular disease but also reveals the mechanistic basis of existing and emerging therapies, thereby enabling rational therapeutic development. This scientific statement, developed by researchers from the European Society of Cardiology (ESC) Council on Basic Cardiovascular Science and several ESC Working Groups, provides a state-of-the-art overview of the emerging molecular and cellular pathways linking metabolic abnormalities with vascular and cardiac disease. By illuminating these critical connections and unresolved questions, this article aims to catalyse innovation in the prevention and management of cardiovascular disease in the context of metabolic dysfunction and to suggest new directions for future research.

Abstract The environmental impact of computer-aided diagnosis (CADx) in colonoscopy is unknown. The potential to reduce greenhouse gas emissions by limiting unnecessary polypectomies may be offset by emissions associated with CADx devices. We quantified and compared the carbon footprint of colonoscopy with and without CADx. Life-cycle carbon emissions associated with endoscopic snares, polyp traps, histopathology, and CADx devices were estimated using life-cycle assessment software. The effect of CADx was estimated by the carbon dioxide equivalent (CO2e) emissions related to outcomes from a prospective cohort of patients who underwent colonoscopy with optical diagnosis under a leave-in-situ strategy (i.e. rectosigmoid polyps ≤5 mm predicted as non-neoplastic were not removed) with and without CADx assistance. We analyzed 1134 individuals (median age 67 years, 59% male) with 1716 colorectal polyps. Colonoscopy with CADx reduced the number of snares and polyp traps from 567 to 543 (difference: 24) and histopathology submissions from 1343 to 1278 (difference: 65). However, the total carbon footprint increased from 832 kg CO2e (95%CI 815 to 847) without CADx to 946 kg CO2e (95%CI 927 to 965) with CADx, corresponding to an absolute increase of 114 kg CO2e (95%CI 80 to 150) or 0.10 kg CO2e per colonoscopy. Using CADx under a leave-in-situ strategy increased the environmental burden of colonoscopy.

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.

Abstract The aim of this international meta-analysis was to quantify the predictive value of BMI for incident fracture and relationship of this risk with age, sex, follow-up time, and BMD. A total of 1 667 922 men and women from 32 countries (63 cohorts), followed for a total of 16.0 million person-years were studied. 293 325 had FN BMD measured (2.2 million person-years follow-up). An extended Poisson model in each cohort was used to investigate relationships between WHO-defined BMI categories (Underweight: &lt;18.5 kg/m2; Normal: 18.5-24.9 kg/m2; Overweight: 25.0-29.9 kg/m2; Obese I: 30.0-34.9 kg/m2; Obese II: ≥35.0 kg/m2) and risk of incident osteoporotic, major osteoporotic and hip fracture (HF). Inverse-variance weighted β-coefficients were used to merge the cohort-specific results. For the subset with BMD available, in models adjusted for age and follow-up time, the hazard ratio (95% CI) for HF comparing underweight with normal weight was 2.35 (2.10-2.60) in women and for men was 2.45 (1.90-3.17). Hip fracture risk was lower in overweight and obese categories compared to normal weight [obese II vs normal: women 0.66 (0.55-0.80); men 0.91 (0.66-1.26)]. Further adjustment for FN BMD T-score attenuated the increased risk associated with underweight [underweight vs normal: women 1.69 (1.47-1.96); men 1.46 (1.00-2.13)]. In these models, the protective effects of overweight and obesity were attenuated, and in both sexes, the direction of association reversed to higher fracture risk in Obese II category [Obese II vs Normal: women 1.24 (0.97-1.58); men 1.70 (1.06-2.75)]. Results were similar for other fracture outcomes. Underweight is a risk factor for fracture in both men and women regardless of adjustment for BMD. However, while overweight/obesity appeared protective in base models, they became risk factors after additional adjustment for FN BMD, particularly in the Obese II category. This effect in the highest BMI categories was of greater magnitude in men than women. These results will inform the second iteration of FRAX®.

INTRODUCTION: Bloating, distention, and gas-related gastrointestinal (GI) symptoms are frequently reported by patients across the spectrum of disorders of gut-brain interaction (DGBI). We aimed to characterize these using latent class modeling in a large multinational survey. METHODS: A nationwide survey of adults in the United States, United Kingdom, and Mexico used quota sampling for demographic balance. It included Rome IV diagnostic questions, Intestinal Gas Questionnaire, Patient Health Questionnaires for anxiety and depression (PHQ-4) and somatization (PHQ-12), quality of life (PROMIS Global-10), and lifestyle questions. Latent class analysis was performed using “depmix” in RStudio 4.2.3. RESULTS: A total of 3,471 subjects experiencing bloating and/or distention (mean age 43 years, 57% female) were included. Using 42 demographic and pertinent clinical variables, latent class analysis revealed 6 distinct clusters. The first 2 clusters demonstrated limited-to-moderate impairment in health-related quality of life (HRQoL), with both characterized by some degree of dietary and supplement associations; however, cluster 2 lacked specific triggers observed in other clusters. The subsequent 2 clusters showed favorable HRQoL and mild gas-related symptoms, with only cluster 4 exhibiting distinct dietary triggers. The final 2 clusters, associated with bowel dysfunction, showed a higher prevalence of irritable bowel syndrome (IBS) with constipation and IBS mixed in cluster 5, and IBS with diarrhea in cluster 6. These bowel dysfunction clusters exhibited severe gas symptoms in the preceding 24 hours and greater HRQoL impairment compared with the other 4 clusters. Notably, cluster 5 was linked to dietary triggers, whereas cluster 6 was defined by psychosocial comorbidities. DISCUSSION: Bloating and distention patients are likely driven by variable influences of dietary, psychological, and bowel dysfunction. Further studies are needed to identify mechanisms and titrate treatment suited to specific mechanistic drivers.

ABSTRACT Ventricular arrhythmias (VA), including ventricular tachycardia and fibrillation, are critical cardiac conditions that are often managed by catheter ablation among those unresponsive to pharmacologic therapy. The choice of anesthesia and sedation regimens for VA ablations may impact arrhythmia inducibility and hemodynamic stability, which can affect procedural success and complication rates. This systematic review and meta-analysis aimed to compare the efficacy and safety of sedation versus general anesthesia (GA) among patients undergoing VA ablation. The review was prospectively registered on PROSPERO (CRD42023441553). Database searches were conducted across five major databases from inception to March 9, 2024 to identify randomized trials or observational studies including adult patients undergoing ablations for VA. Screening and data extraction were completed in duplicate. Risk-of-bias assessments were conducted using ROBINS-I as all included studies were observational, and the quality of evidence was evaluated using the GRADE framework. Six observational studies (N = 16,435) were included. No significant differences were found between sedation and GA for total procedure time (MD: −14.16 minutes; 95%CI: −38.61 to 10.29 minutes), arrhythmia non-inducibility (RR: 0.73; 95% CI: 0.33–1.58), acute ablation success (RR: 1.06; 95% CI: 0.65–1.71), or procedural complications (RR: 0.72; 95% CI: 0.28–1.85). However, sedation was associated with significantly lower intraprocedural hemodynamic instability (RR: 0.28; 95% CI: 0.12–0.70). These findings indicate that while sedation and GA have comparable outcomes, sedation may be associated with less hemodynamic instability during VA ablation. However, more high-quality studies are needed to confirm these results.