Supermarket/hypermarket opportunistic screening for atrial fibrillation (SHOPS-AF) using sensors embedded in the handles of supermarket trolleys: A feasibility study.

BACKGROUND: Atrial fibrillation (AF) increases the risk of death, stroke, heart failure, cognitive decline, and healthcare costs but is often asymptomatic and undiagnosed. There is currently no national screening program for AF. The advent of validated hand-held devices allows AF to be detected in non-healthcare settings, enabling screening to be undertaken within the community. METHOD AND RESULTS: In this novel observational study, we embedded a MyDiagnostick single lead ECG sensor into the handles of shopping trolleys in four supermarkets in the Northwest of England: 2155 participants were recruited. Of these, 231 participants either activated the sensor or had an irregular pulse, suggesting AF. Some participants agreed to use the sensor but refused to provide their contact details, or consent to pulse assessment. In addition, some data were missing, resulting in 203 participants being included in the final analyses. Fifty-nine participants (mean age 73.6 years, 43% female) were confirmed or suspected of having AF; 20 were known to have AF and 39 were previously undiagnosed. There was no evidence of AF in 115 participants and the remaining 46 recordings were non-diagnostic, mainly due to artefact. Men and older participants were significantly more likely to have newly diagnosed AF. Due to the number of non-diagnostic ECGs (n = 46), we completed three levels of analyses, excluding all non-diagnostic ECGs, assuming all non-diagnostic ECGs were masking AF, and assuming all non-diagnostic ECGs were not AF. Based on the results of the three analyses, the sensor's sensitivity (95% CI) ranged from 0.70 to 0.93; specificity from 0.15 to 0.97; positive predictive values (PPV) and negative predictive values (NPV) ranged from 0.24 to 0.56 and 0.55 to 1.00, respectively. These values should be interpreted with caution, as the ideal reference standard on 1934 participants was imperfect. CONCLUSION: The study demonstrates that the public will engage with AF screening undertaken as part of their daily routines using hand-held devices. Sensors can play a key role in identifying asymptomatic patients in this way, but the technology must be further developed to reduce the quantity of non-diagnostic ECGs.

Tuberculosis Preventive Treatment Update - U.S. President's Emergency Plan for AIDS Relief, 36 Countries, 2016-2023.

Tuberculosis (TB) is the leading cause of death among persons with HIV. In 2022, an estimated 167,000 TB-related deaths occurred globally among persons with HIV. TB preventive treatment (TPT) helps prevent TB disease and is recommended for persons at high risk for developing TB, including those with HIV. TPT, when taken with antiretroviral treatment (ART), can reduce TB-attributable deaths among persons with HIV. In 2018, the U.S. President's Emergency Plan for AIDS Relief (PEPFAR) program committed to offer one course of TPT to all eligible clients receiving ART. This analysis describes trends in TPT initiation and completion among PEPFAR-supported programs in 36 countries in Africa, Central and South America, and Asia during fiscal years (FYs) 2017-2023. Overall, TPT initiation rates peaked in FY19, a possible sign of programmatic saturation. TPT initiation among clients who had been on ART <6 months reached 59%, and overall completion rates up to 87% were reported. Approximately 13 million persons with HIV have completed TPT since FY17, but widespread adoption of shorter regimens, patient-centered approaches, and electronic medical record systems might be needed to ensure full TPT coverage. Through PEPFAR's partnership with national HIV programs, TPT has become the standard of care for persons with HIV.

Assessment and evaluation of prescribing competences: A systematic review and recommendations.

AIMS: Since assessment of prescribing competence is a key promoter of student learning and achievement, we aim to summarize existing national-level approaches, provide a systematic review of current literature, indicate the frequency of various methodologies, and make recommendations to promote and extend existing practice. METHODS: Regulatory body websites were accessed for details of national examinations. PubMed, Embase, the Allied and Complementary Medicine, and CINAHL databases were systematically searched in August 2023 for studies in English from Europe, North America, Australia and New Zealand reporting assessment of prescribing competencies among students/practitioners. Additional articles were identified through citation tracking. RESULTS: National approaches are described for several jurisdictions. A total of 20 514 articles were retrieved, of which 54 met the inclusion criteria. Most articles came from the UK, with medical students and qualified doctors most frequently featured. Multiple choice formats were most common, with short answer questions, calculations and scenario-based skills tests also featured. Direct observations of skills through Objective Structured Clinical Examinations and similar methods were less commonly described. Test reliability generally employed Classical Test Theory. Costs of developing and delivering assessments, differential attainment by demographics, and predictive validity were not indicated. CONCLUSION: We recommend measurement of the predictive validity of prescribing competence assessments, the routine inclusion of performance by demographic characteristics, extension of competence assessments to professions other than medicine, and structured reporting of methods and findings, including costs and cost-effectiveness. Situational judgement tests would be a valuable addition to assessment practices.

A scoping review of artificial intelligence in medical education: BEME Guide No. 84.

BACKGROUND: Artificial Intelligence (AI) is rapidly transforming healthcare, and there is a critical need for a nuanced understanding of how AI is reshaping teaching, learning, and educational practice in medical education. This review aimed to map the literature regarding AI applications in medical education, core areas of findings, potential candidates for formal systematic review and gaps for future research. METHODS: This rapid scoping review, conducted over 16 weeks, employed Arksey and O'Malley's framework and adhered to STORIES and BEME guidelines. A systematic and comprehensive search across PubMed/MEDLINE, EMBASE, and MedEdPublish was conducted without date or language restrictions. Publications included in the review spanned undergraduate, graduate, and continuing medical education, encompassing both original studies and perspective pieces. Data were charted by multiple author pairs and synthesized into various thematic maps and charts, ensuring a broad and detailed representation of the current landscape. RESULTS: The review synthesized 278 publications, with a majority (68%) from North American and European regions. The studies covered diverse AI applications in medical education, such as AI for admissions, teaching, assessment, and clinical reasoning. The review highlighted AI's varied roles, from augmenting traditional educational methods to introducing innovative practices, and underscores the urgent need for ethical guidelines in AI's application in medical education. CONCLUSION: The current literature has been charted. The findings underscore the need for ongoing research to explore uncharted areas and address potential risks associated with AI use in medical education. This work serves as a foundational resource for educators, policymakers, and researchers in navigating AI's evolving role in medical education. A framework to support future high utility reporting is proposed, the FACETS framework.