How to Integrate Sex and Gender Medicine into Medical and Allied Health Profession Undergraduate, Graduate, and Post-Graduate Education: Insights from a Rapid Systematic Literature Review and a Thematic Meta-Synthesis.

Sex and gender are concepts that are often misunderstood and misused, being utilized in a biased, preconceived, interchangeable way. Sex and gender medicine is generally overlooked, despite the profound impact of sex and gender on health outcomes. The aims of the present rapid systematic literature review were (i) to assess the extent to which sex- and gender-sensitive topics are covered in medical courses; (ii) to assess the need for and willingness toward integrating/incorporating sex and gender medicine into health-related education; (iii) to identify barriers and facilitators of the process of implementation of sex and gender medicine in medical teaching, mentoring, and training; and (iv) to evaluate the effectiveness of interventional projects targeting curriculum building and improvement for future gender-sensitive physicians. Seven themes were identified by means of a thematic analysis, namely, (i) how much sex- and gender-based medicine is covered by medical courses and integrated into current medical curricula, (ii) the knowledge of sex and gender medicine among medical and allied health profession students, (iii) the need for and willingness toward acquiring sex- and gender-sensitive skills, (iv) how to integrate sex- and gender-based medicine into medical curricula in terms of barriers and facilitators, (v) existing platforms and tools to share knowledge related to sex and gender medicine, (vi) sex- and gender-based medicine aspects in the post-medical education, and (vii) the impact of sex- and gender-sensitive topics integrated into medical curricula. Based on the identified gaps in knowledge, further high-quality, randomized trials with larger samples are urgently warranted to fill these gaps in the field of implementation of gender medicine in educating and training future gender-sensitive physicians.

Systematic Review and Meta-Analysis of Tocilizumab Therapy versus Standard of Care in over 15,000 COVID-19 Pneumonia Patients during the First Eight Months of the Pandemic.

BACKGROUND: Tocilizumab is an anti-IL-6 therapy widely adopted in the management of the so-called "cytokine storm" related to SARS-CoV-2 virus infection, but its effectiveness, use in relation to concomitant corticosteroid therapy and safety were unproven despite widespread use in numerous studies, mostly open label at the start of the pandemic. METHODS: We performed a systematic review and meta-analysis of case-control studies utilising tocilizumab in COVID-19 on different databases (PubMed/MEDLINE/Scopus) and preprint servers (medRxiv and SSRN) from inception until 20 July 2020 (PROSPERO CRD42020195690). Subgroup analyses and meta-regressions were performed. The impact of tocilizumab and concomitant corticosteroid therapy or tocilizumab alone versus standard of care (SOC) on the death rate, need for mechanical ventilation, ICU admission and bacterial infections were assessed. RESULTS: Thirty-nine studies with 15,531 patients (3657 cases versus 11,874 controls) were identified. Unadjusted estimates (n = 28) failed to demonstrate a protective effect of tocilizumab on survival (OR 0.74 ([95%CI 0.55-1.01], p = 0.057), mechanical ventilation prevention (OR 2.21 [95%CI 0.53-9.23], p = 0.277) or prevention of ICU admission (OR 3.79 [95%CI 0.38-37.34], p = 0.254). Considering studies with adjusted, estimated, tocilizumab use was associated with mortality rate reduction (HR 0.50 ([95%CI 0.38-0.64], p < 0.001) and prevention of ICU admission (OR 0.16 ([95%CI 0.06-0.43], p < 0.001). Tocilizumab with concomitant steroid use versus SOC was protective with an OR of 0.49 ([95%CI 0.36-0.65], p < 0.05) as was tocilizumab alone versus SOC with an OR of 0.59 ([95%CI 0.34-1.00], p < 0.001). Risk of infection increased (2.36 [95%CI 1.001-5.54], p = 0.050; based on unadjusted estimates). CONCLUSION: Despite the heterogeneity of included studies and large number of preprint articles, our findings from the first eight of the pandemic in over 15,000 COVID-19 cases suggested an incremental efficacy of tocilizumab in severe COVID-19 that were confirmed by subsequent meta-analyses of large randomized trials of tocilizumab. This suggests that analysis of case-control studies and pre-print server data in the early stages of a pandemic appeared robust for supporting incremental benefits and lack of major therapeutic toxicity of tocilizumab for severe COVID-19.

Big Data for Biomedical Education with a Focus on the COVID-19 Era: An Integrative Review of the Literature.

Medical education refers to education and training delivered to medical students in order to become a practitioner. In recent decades, medicine has been radically transformed by scientific and computational/digital advances-including the introduction of new information and communication technologies, the discovery of DNA, and the birth of genomics and post-genomics super-specialties (transcriptomics, proteomics, interactomics, and metabolomics/metabonomics, among others)-which contribute to the generation of an unprecedented amount of data, so-called 'big data'. While these are well-studied in fields such as medical research and methodology, translational medicine, and clinical practice, they remain overlooked and understudied in the field of medical education. For this purpose, we carried out an integrative review of the literature. Twenty-nine studies were retrieved and synthesized in the present review. Included studies were published between 2012 and 2021. Eleven studies were performed in North America: specifically, nine were conducted in the USA and two studies in Canada. Six studies were carried out in Europe: two in France, two in Germany, one in Italy, and one in several European countries. One additional study was conducted in China. Eight papers were commentaries/theoretical or perspective articles, while five were designed as a case study. Five investigations exploited large databases and datasets, while five additional studies were surveys. Two papers employed visual data analytical/data mining techniques. Finally, other two papers were technical papers, describing the development of software, computational tools and/or learning environments/platforms, while two additional studies were literature reviews (one of which being systematic and bibliometric).The following nine sub-topics could be identified: (I) knowledge and awareness of big data among medical students; (II) difficulties and challenges in integrating and implementing big data teaching into the medical syllabus; (III) exploiting big data to review, improve and enhance medical school curriculum; (IV) exploiting big data to monitor the effectiveness of web-based learning environments among medical students; (V) exploiting big data to capture the determinants and signatures of successful academic performance and counteract/prevent drop-out; (VI) exploiting big data to promote equity, inclusion, and diversity; (VII) exploiting big data to enhance integrity and ethics, avoiding plagiarism and duplication rate; (VIII) empowering medical students, improving and enhancing medical practice; and, (IX) exploiting big data in continuous medical education and learning. These sub-themes were subsequently grouped in the following four major themes/topics: namely, (I) big data and medical curricula; (II) big data and medical academic performance; (III) big data and societal/bioethical issues in biomedical education; and (IV) big data and medical career. Despite the increasing importance of big data in biomedicine, current medical curricula and syllabuses appear inadequate to prepare future medical professionals and practitioners that can leverage on big data in their daily clinical practice. Challenges in integrating, incorporating, and implementing big data teaching into medical school need to be overcome to facilitate the training of the next generation of medical professionals. Finally, in the present integrative review, state-of-art and future potential uses of big data in the field of biomedical discussion are envisaged, with a focus on the still ongoing "Coronavirus Disease 2019" (COVID-19) pandemic, which has been acting as a catalyst for innovation and digitalization.