BMJ open
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Versatile large language models (LLMs) have the potential to augment diagnostic decision-making by assisting diagnosticians, thanks to their ability to engage in open-ended, natural conversations and their comprehensive knowledge access. Yet the novelty of LLMs in diagnostic decision-making introduces uncertainties regarding their impact. Clinicians unfamiliar with the use of LLMs in their professional context may rely on general attitudes towards LLMs more broadly, potentially hindering thoughtful use and critical evaluation of their input, leading to either over-reliance and lack of critical thinking or an unwillingness to use LLMs as diagnostic aids. To address these concerns, this study examines the influence on the diagnostic process and outcomes of interacting with an LLM compared with a human coach, and of prior training vs no training for interacting with either of these 'coaches'. Our findings aim to illuminate the potential benefits and risks of employing artificial intelligence (AI) in diagnostic decision-making. ⋯ The Bern Cantonal Ethics Committee considered the study exempt from full ethical review (BASEC No: Req-2023-01396). All methods will be conducted in accordance with relevant guidelines and regulations. Participation is voluntary and informed consent will be obtained. Results will be published in peer-reviewed scientific medical journals. Authorship will be determined according to the International Committee of Medical Journal Editors guidelines.
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Cause-of-death discrepancies are common in respiratory illness-related mortality. A standard epidemiological metric, excess all-cause death, is unaffected by these discrepancies but provides no actionable policy information when increased all-cause mortality is unexplained by reported specific causes. To assess the contribution of unexplained mortality to the excess death metric, we parsed excess deaths in the COVID-19 pandemic into changes in explained versus unexplained (unreported or unspecified) causes. ⋯ Unexplained mortality contributed substantially to US pandemic period excess deaths. Onset of unexplained mortality in February 2020 coincided with previously reported increases in psychotropic use, suggesting possible psychiatric or injurious causes. Because underlying causes of unexplained deaths may vary by group or region, results suggest excess death calculations provide limited actionable information, supporting previous calls for improved cause-of-death data to support evidence-based policy.
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To rank and score 180 countries according to COVID-19 cases and fatality in 2020 and compare the results to existing pandemic vulnerability prediction models and results generated by standard epidemiological scoring techniques. ⋯ COVID-19 fatality can be a good proxy for countries' resources and system's resilience in managing the pandemic. These findings suggest that countries' economic and sociopolitical factors may behave in a more complex way as were believed. To explore these complex epidemiological associations, models can benefit enormously by taking advantage of methods developed in computer science and machine learning.
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To study the SARS-CoV-2 infection rate among hospital healthcare workers after the first wave of the COVID-19 pandemic, and provide more knowledge in the understanding of the relationship between infection, symptomatology and source of infection. ⋯ Healthcare workers caring for hospitalised COVID-19 patients were not at an increased risk of infection, most likely as a result of taking standard infection control measures into consideration. These data show that compliance with infection control measures is essential to control secondary transmission and constrain the spread of the virus.
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This article describes the protocol of an Ebola vaccine clinical trial which investigates the safety and immunogenicity of a two-dose prophylactic Ebola vaccine regimen comprised of two Ebola vaccines (Ad26.ZEBOV and MVA-BN-Filo) administered 56 days apart, followed by a booster vaccination with Ad26.ZEBOV offered at either 1 year or 2 years (randomisation 1:1) after the first dose. This clinical trial is part of the EBOVAC3 project (an Innovative Medicines Initiative 2 Joint Undertaking), and is the first to evaluate the safety and immunogenicity of two different booster vaccination arms in a large cohort of adults. ⋯ The protocol was approved by the National Ethics Committee of the Ministry of Health of the DRC (n°121/CNES/BN/PMMF/2019). The clinical trial was registered on 4 December 2019 on ClinicalTrials.gov. Trial activities are planned to finish in October 2022. All participants are required to provide written informed consent and no study-related procedures will be performed until consent is obtained. The results of the trial will be added on ClinicalTrials.gov, published in peer-reviewed journals and presented at international conferences.