Risk of severe acute respiratory syndrome coronavirus 2 infection among women with polycystic ovary syndrome.

OBJECTIVE: To determine whether women with polycystic ovary syndrome (PCOS) had a higher incidence of testing positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) than those without PCOS and evaluate whether PCOS diagnosis independently increased the risk of moderate or severe disease in those with positive SARS-CoV-2 test results. DESIGN: Retrospective cohort study using the National COVID Cohort Collaborative (N3C). SETTING: National COVID Cohort Collaborative. PATIENT(S): Adult nonpregnant women (age, 18-65 years) enrolled in the N3C with confirmed SARS-CoV-2 testing for any indication. Sensitivity analyses were conducted in women aged 18-49 years and who were obese (body mass index, ≥30 kg/m2). INTERVENTION(S): The exposure was PCOS as identified by the N3C clinical diagnosis codes and concept sets, which are a compilation of terms, laboratory values, and International Classification of Diseases codes for the diagnosis of PCOS. To further capture patients with the symptoms of PCOS, we also included those who had concept sets for both hirsutism and irregular menses. MAIN OUTCOME MEASURE(S): Odds of testing positive for SARS-CoV-2 and odds of moderate or severe coronavirus disease 2019 (COVID-19) in the PCOS cohort compared with those in the non-PCOS cohort. RESULT(S): Of the 2,089,913 women included in our study, 39,459 had PCOS. In the overall cohort, the adjusted odds ratio (aOR) of SARS-CoV-2 positivity was 0.98 (95% confidence interval [CI], 0.97-0.98) in women with PCOS compared to women without PCOS. The aORs of disease severity were as follows: mild disease, 1.02 (95% CI, 1.01-1.03); moderate disease, 0.99 (95% CI, 0.98-1.00); and severe disease, 0.99 (95% CI, 0.99-1.00). There was no difference in COVID-19-related mortality (aOR, 1.00; 95% CI, 0.99-1.00). These findings were similar in the reproductive-age and obese reproductive-age cohorts. CONCLUSION(S): Women with PCOS had a similar likelihood of testing positive for SARS-CoV-2. Among those who tested positive, they were no more likely to have moderate or severe COVID-19 than the non-PCOS cohort. Polycystic ovary syndrome is a chronic condition associated with several comorbidities, including cardiovascular disease and mental health issues. Although these comorbidities are also associated with COVID-19 morbidity, our findings suggest that the comorbidities themselves, rather than PCOS, drive the risk of disease severity.

A medication-wide association study (MWAS) on repurposed drugs for COVID-19 with Pre-pandemic prescription medication exposure and pregnancy outcomes.

Information on effects of medication therapies during pregnancy is lacking as pregnant patients are often excluded from clinical trials. This retrospective study explores the potential of using electronic health record (EHR) data to inform safety profiles of repurposed COVID medication therapies on pregnancy outcomes using pre-COVID data. We conducted a medication-wide association study (MWAS) on prescription medication exposures during pregnancy and the risk of cesarean section, preterm birth, and stillbirth, using EHR data between 2010-2017 on deliveries at PennMedicine. Repurposed drugs studied for treatment of COVID-19 were extracted from ClinicalTrials.gov (n = 138). We adjusted for known comorbidities diagnosed within 2 years prior to birth. Using previously developed medication mapping and delivery-identification algorithms, we identified medication exposure in 2,830 of a total 63,334 deliveries; from 138 trials, we found 31 medications prescribed and included in our cohort. We found 21 (68%) of the 31 medications were not positively associated with increased risk of the outcomes examined. With caution, these medications warrant potential for inclusion of pregnant individuals in future studies, while drugs found to be associated with pregnancy outcomes require further investigation. MWAS facilitates hypothesis-driven evaluation of drug safety across all prescription medications, revealing potential drug candidates for further research.

Ideas for how informaticians can get involved with COVID-19 research

[...]there is a possibility that some of the observed genetic differences may be artifacts of this process. [...]the well-known CCR5-delta32 allele has a variation that protects individuals who have been exposed to the Human Immunodeficiency Virus (HIV);they are protected from developing AIDS (Acquired Immunodeficiency Syndrome) [10]. Because of this, researchers are gearing up to study the genomes of COVID-19 positive patients in comparison to controls (COVID-19-negative patients). Capacity and resource management tools can generate projects based on regional infection counts and current patient admissions to estimate the number of patients that will require hospitalization, intensive care unit beds, medications, and mechanical ventilation. Informaticians can support these efforts by 1) educating patients and care providers about data science resources and electronic health record (EHR) platforms for building point-of-care solutions, 2) joining the open-source community efforts to develop these technologies, and 3) volunteering with the information services divisions within their healthcare organizations to deploy telehealth tools and engage in patient management projects.