Citations

Background Early detection of left and right ventricular systolic dysfunction (LVSD and RVSD respectively) in children can lead to intervention to reduce morbidity and death. Existing artificial intelligence algorithms can identify LVSD and RVSD in adults using a 12‐lead ECG; however, its efficacy in children is uncertain. We aimed to develop novel artificial intelligence–enabled ECG algorithms for LVSD and RVSD detection in pediatric patients. Methods and Results We identified 10 142 unique pediatric patients (age≤18) with a 10‐second, 12‐lead surface ECG within 14 days of a transthoracic echocardiogram, performed between 2002 and 2022. LVSD was defined quantitatively by left ventricular ejection fraction (LVEF). RVSD was defined semiquantitatively. Novel pediatric models for LVEF ≤35% and LVEF <50% achieved excellent test areas under the curve of 0.93 (95% CI, 0.89–0.98) and 0.88 (95% CI, 0.83–0.94) respectively. The model to detect LVEF <50% had a sensitivity of 0.85, specificity of 0.80, positive predictive value of 0.095, and negative predictive value of 0.995. In comparison, the previously validated adult data‐derived model for LVEF <35% achieved an area under the curve of 0.87 (95% CI, 0.84–0.90) for LVEF ≤35% in children. A novel pediatric model for any RVSD detection reached a test area under the curve of 0.90 (0.87–0.94). Conclusions An artificial intelligence–enabled ECG demonstrates accurate detection of both LVSD and RVSD in pediatric patients. While adult‐trained models offer good performance, improvements are seen when training pediatric‐specific models.

ABSTRACT Over the past two decades, there has been increasing interest in the diagnosis and management of schwannomas of the inner ear including hearing rehabilitation with cochlear implants. However, tumor nomenclature and classification within the literature have been variable and oftentimes cumbersome. The term “intralabyrinthine schwannoma” is in common use when describing these tumors but is a potential source of confusion given that people often use the term “labyrinth” or “labyrinthine” to refer to the vestibular component of the inner ear only (i.e., labyrinthectomy or the translabyrinthine approach). During the Ninth Quadrennial Conference on Vestibular Schwannoma and Other Cerebellopontine Angle Lesions in Bergen, Norway, in May 2023, a multidisciplinary group of conference participants met and discussed issues pertaining to current terminology and classifications to enhance clarity and to reflect recent advances in tumor management and hearing rehabilitation. Although a variety of terms have been previously used to describe inner ear schwannomas, consensus was achieved on the term “inner ear schwannoma (IES)” to describe eighth nerve schwannomas of the cochlea, vestibule, or semicircular canals. Subgroups under this term comprise intravestibular, intracochlear, or intravestibulocochlear inner ear schwannomas (low complexity tumors), inner ear schwannomas with transfundal extension into the internal auditory canal but without modiolar involvement (intermediate complexity tumors), and inner ear schwannomas with transfundal extension with modiolar involvement (high complexity tumors). The details of the recommendations for an updated and simplified tumor nomenclature centered around tumor control and hearing rehabilitation with cochlear implantation are presented.

BACKGROUND Despite an overall poor prognosis, about 15% of patients with advanced-stage tubo-ovarian high-grade serous carcinoma (HGSC) survive 10 or more years after standard treatment. METHODS We evaluated the tumor microenvironment of this exceptional, understudied group using a large international cohort enriched for long-term survivors (LTS; 10+ years; n = 374) compared with mid-term (MTS; 5–7.99 years; n = 433) and short-term survivors (STS; 2–4.99 years; n = 416). Primary tumor samples were immunostained and scored for intraepithelial and intrastromal densities of 10 immune-cell subsets (including T cells, B cells, plasma cells, myeloid cells, PD-1 + cells, and PD-L1 + cells) and epithelial content. RESULTS Positive associations with LTS compared with STS were seen for 9 of 10 immune-cell subsets. In particular, the combination of intraepithelial CD8 + T cells and intrastromal B cells showed near 5-fold increased odds of LTS compared with STS. All of these associations were stronger in tumors with high epithelial content and/or the C4/Differentiated molecular subtype, despite immune-cell densities generally being higher in tumors with low epithelial content and/or the C2/Immunoreactive molecular subtype. CONCLUSION The tumor microenvironment of HGSC LTS is distinguished by the intersection of T and B cell coinfiltration, high epithelial content, and C4/differentiated molecular subtype, features which may inspire new approaches to immunotherapy. FUNDING Ovarian Cancer Research Program (OCRP) of the Congressionally Directed Medical Research Program (CDMRP), U.S. Department of Defense (DOD); American Cancer Society; BC Cancer Foundation; Canada’s Networks of Centres of Excellence; Canadian Cancer Society; Canadian Institutes of Health Research; Cancer Councils of New South Wales, Victoria, Queensland, South Australia, and Tasmania, Cancer Foundation of Western Australia; Cancer Institute NSW; Cancer Research UK; Deutsche Forschungsgesellschaft; ELAN Funds of the University of Erlangen-Nuremberg; Fred C. and Katherine B. Andersen Foundation; Genome BC; German Cancer Research Center; German Federal Ministry of Education and Research, Programme of Clinical Biomedical Research; Instituto de Salud Carlos III; Mayo Foundation; Minnesota Ovarian Cancer Alliance; Ministerio de Economía y Competitividad; Medical Research Council (MRC); National Center for Advancing Translational Sciences; National Health and Medical Research Council of Australia (NHMRC); Ovarian Cancer Australia; Peter MacCallum Foundation; Sydney West Translational Cancer Research Centre; Terry Fox Research Institute; The Eve Appeal (The Oak Foundation); UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; University of Pittsburgh School of Medicine; U.S. National Cancer Institute of the National Institutes of Health; VGH & UBC Hospital Foundation; Victorian Cancer Agency.

Abstract Background Heart failure (HF) and atrial fibrillation (AF) are intertwined, sharing common risk factors and influencing each other in a reciprocal manner. While left ventricular diastolic dysfunction (LVDD) stands as a hallmark of HF's hemodynamic profile, its direct correlation with heightened AF risk remains uncertain. Our recent validation of an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm for LVDD detection has opened new avenues. Yet, whether AI-ECG-detected LVDD correlates with long-term AF risk remains unexplored. Methods We performed a retrospective study among all patients with a comprehensive LVDD assessment from the test population of the AI-ECG LVDD study between September 2001 and June 2022. Patients with prior documented AF according to health records or previous ECG were excluded. Patients were classified by AI-ECG as normal diastolic function (DF), grade 1 (G1), grade 2 (G2), or grade 3 (G3) LVDD. We assessed the risk of AF across AI-ECG LVDD grade, with normal DF as reference, with competing risk models. Results Of 97,023 patients free of AF at baseline, 63,533 (65.4%), 10,776 (11.1%), 18,940 (19.5%), and 3,774 (3.9%) were classified as normal DF, G1-LVDD, G2-LVDD, and G3-LVDD, respectively. Worse AI-ECG LVDD was associated with older age, lower left ventricular ejection fraction (LVEF), and higher rates of HF, diabetes, hypertension, chronic pulmonary disease, renal failure, and cardiovascular disease (p-of-trend&lt;0.001 for all). Over a median follow-up of 4.8 years (interquartile range 1.8-9.2 years), new-onset AF occurred in 6,795 (7.0%) patients. In multivariable survival analysis, adjusted to multiple risk factors including LVEF and clinical HF, G2 and G3 LVDD, representing patients with high filling pressures, were independently associated with a higher AF-risk [G2-LVDD: adjusted hazard ratio (aHR) 1.64 (95% confidence interval (95%CI) 1.52-1.73), G3-LVDD: aHR 2.24 (95%CI 2.02-2.48)]. Conclusion The AI-ECG LVDD algorithm independently predicts long-term AF risk, regardless of LVEF and clinical HF status, highlighting its potential for identifying high-risk populations and guiding proactive monitoring and management.

Abstract Background Etripamil nasal spray (NS) is a fast-acting, self-administered calcium-channel blocker in development for the conversion of AV-nodal dependent paroxysmal supraventricular tachycardia (PSVT) in a medically unsupervised setting. Prior studies show favorable safety and efficacy in converting single episodes of PSVT to sinus rhythm (SR). Purpose In NODE-303, patient-reported outcome (PRO) instruments assessed quality of life (QoL) over multiple etripamil-treated episodes of PSVT. Methods NODE-303 was an event-driven, multi-center, open-label Phase 3 study in North and South American patients with documented PSVT that evaluated the safety and efficacy of etripamil in PSVT termination, over multiple episodes and without the need for prior test dosing. Enrolled patients who perceived PSVT symptoms applied an ambulatory ECG cardiac monitoring system (CMS), performed a pre-trained vagal maneuver and, if symptoms persisted, self-administered etripamil NS 70 mg. A study amendment allowed a repeat dose (etripamil NS, 70 mg) if symptoms persisted 10 min after the first dose. Each patient could self-treat up to 4 episodes. Safety was assessed through adverse events, clinical data, and ECG CMS recordings. The Treatment Satisfaction Questionnaire for Medication (TSQM; validated for acute episodic assessments) and other PROs were administered, and healthcare utilization data were acquired. Patients completed PROs at baseline (BL), monthly, and per PSVT episode, which collected information on symptoms, episode characteristics, rescue medications, and emergency room visits. Additional PROs were the Brief Illness Perception Questionnaire (BIPQ), Cardiac Anxiety Questionnaire (CAQ), and 36-Item Short Form Health Survey (SF-36). Results There were higher proportions of patients reporting mild, minimal or no disease severity, every 6 months, than at BL; extremely severe, severe, and moderate disease severity was reported by smaller proportions of patients than at BL, though incomplete surveys at later visits may limit this analysis. Anxiety and stress about future PSVT episodes were consistently reduced from BL. Measures of treatment satisfaction, effectiveness, and convenience were consistent across multiple episodes, and were at levels considered favorable for the TSQM instrument (Table 1). Rates of emergency-room visits and hospital admissions across multiple, treated PSVT episodes were similar to those observed in trials assessing single episodes (Table 2). The BIPQ, CAQ or SF-36 had no notable changes from BL. Conclusions Etripamil self-administration was associated with patient-reported improvements in degree of disease severity, decreased anxiety and stress over future PSVT episodes, and levels of treatment satisfaction, effectiveness, and convenience considered favorable for respective PRO instrument. Using a symptom-prompted, self-administered treatment for PSVT could potentially improve QoL measures and reduce healthcare resource utilization.

Abstract Background The determination of left ventricular diastolic dysfunction (LVDD) and filling pressure in patients with significant (&gt;moderate) mitral regurgitation (MR) poses a complex challenge. We recently validated an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm to detect LVDD and estimate LV filling pressures. Methods This retrospective study sought to examine the risk of all-cause mortality across AI-ECG LVDD grades. Patients from the AI-ECG LVDD study test cohort who underwent transthoracic echocardiography confirming significant MR and an ECG within fourteen days of each other at Mayo Clinic between 09/2001 and 06/2022 were included. LVDD status was determined based on the index ECG, and patients were categorized into groups representing normal diastolic function (NDF) or LVDD grades 1 (G1), 2 (G2), or 3 (G3). Results Of 4,019 patients with significant MR (mean age 69.8, 49.0% women), 1,175 (29.2%), 1,881 (46.8%), and 963 (24.0%) were classified by AI-ECG as NDF/G1-LVDD, G2-LVDD, and G3-LVDD, respectively. The median mitral effective regurgitant orifice area was 26 mm² (interquartile range 20-36 mm²). Over a median follow-up of 3.5 years, 1,636 (40.7%) patients died. In multivariable survival analysis adjusted for multiple risk factors, a worse AI-ECG LVDD grade was independently associated with an increased death risk [G2DD: adjusted hazard ratio (aHR) 1.98 (95% confidence interval (95% CI) 1.63-2.40), G3DD: aHR 2.59 (95% CI 2.09-3.20)]. These findings were consistent when accounting for mitral valve intervention and among patients with &gt;moderate MR or after mitral valve intervention. Conclusion In patients with significant MR, the grading of LVDD by AI-ECG is independently associated with all-cause mortality.

Joyce, Kelsey E., Catherine A. Campbell, Arthur R. Bradwell, Samuel J.E. Lucas, Christopher T. Lewis, Rebekah A.I. Lucas, and Mark Edsell; for the Birmingham Medical Research Expeditionary Society (BMRES). The environmental impact of a high-altitude medical research expedition. High Alt Med Biol. 26:140–147, 2025. Introduction: Scientists must begin examining the environmental cost(s) of their research. The purpose of this study was to evaluate a component of the environmental impact of a high-altitude medical research expedition by totaling the carbon dioxide (CO 2 ) emissions calculated from as many direct and indirect sources as possible. Methods: Eighteen individuals flew from London to Bagdogra (via Delhi), and then drove onward to Lachung (via Gangtok) where they began their ascent on foot to 4,800 m (Kanchenjunga National Park, Sikkim). Several research experiments were conducted throughout the expedition, which required use of a laboratory centrifuge, solid CO 2 (specimen storage), rechargeable laptop computers and battery-powered oximeters. International Civil Aviation Organization calculators estimated aviation CO 2 production. Land emissions were calculated for Mahindra vehicles. Solid waste was weighed and CO 2 emissions estimated for its incineration. Results : Total CO 2 emissions equated to ∼16.7 tonnes from the following sources: air and land transportation of expedition team (87.3%); sublimation and transportation of solid CO 2 (7.7%), waste incineration (0.58%), generator transportation and gasoline (12 l) combustion (0.48%), and battery transportation (3.3%). Conclusions : Air travel contributed the most to the overall environmental cost of the research expedition. Further investigation is required to contextualize these findings in relation to lab-based alternative(s).