AUTHOR=Salter-Volz Aysha E. , Oyasu Abigail , Yeh Chen , Muhammad Lutfiyya N. , Woitowich Nicole C. 

TITLE=Sex and Gender Bias in Covid-19 Clinical Case Reports

JOURNAL=Frontiers in Global Women's Health

VOLUME=2

YEAR=2021

URL=https://www.frontiersin.org/journals/global-womens-health/articles/10.3389/fgwh.2021.774033

DOI=10.3389/fgwh.2021.774033

ISSN=2673-5059

ABSTRACT=<p>Clinical case reports circulate relevant information regarding disease presentation and describe treatment protocols, particularly for novel conditions. In the early months of the Covid-19 pandemic, case reports provided key insights into the pathophysiology and sequelae associated with Covid-19 infection and described treatment mechanisms and outcomes. However, case reports are often subject to selection bias due to their singular nature. To better understand how selection biases may have influenced Covid-19-releated case reports, we conducted a bibliometric analysis of Covid-19-releated case reports published in high impact journals from January 1 to June 1, 2020. Case reports were coded for patient sex, country of institutional affiliation, physiological system, and first and last author gender. Of 494 total case reports, 45% (<italic>n</italic> = 221) of patients were male, 30% (<italic>n</italic> = 146) were female, and 25% (<italic>n</italic> = 124) included both sexes. Ratios of male-only to female-only case reports varied by physiological system. The majority of case reports had male first (61%, <italic>n</italic> = 302) and last (70%, <italic>n</italic> = 340) authors. Case reports with male last authors were more likely to describe male patients [<italic>X</italic><sup>2</sup> (2, <italic>n</italic> = 465) = 6.6, <italic>p</italic> = 0.037], while case reports with female last authors were more likely to include patients of both sexes [OR = 1.918 (95% CI = 1.163–3.16)]. Despite a limited sample size, these data reflect emerging research on sex-differences in the physiological presentation and impact of Covid-19 and parallel large-scale trends in authorship patterns. Ultimately, this work highlights potential biases in the dissemination of clinical information via case reports and underscores the inextricable influences of sex and gender biases within biomedicine.</p>