Racial and Ethnic Differences in Hospital Admissions of Emergency Department COVID-19 Patients.

BACKGROUND: Several studies have found that among patients testing positive for COVID-19 within a health care system, non-Hispanic Black and Hispanic patients are more likely than non-Hispanic White patients to be hospitalized. However, previous studies have looked at odds of being admitted using all positive tests in the system and not only those seeking care in the emergency department (ED). OBJECTIVE: This study examined racial/ethnic differences in COVID-19 hospitalizations and intensive care unit (ICU) admissions among patients seeking care for COVID-19 in the ED. RESEARCH DESIGN: Electronic health records (n=7549) were collected from COVID-19 confirmed patients that visited an ED of an urban health care system in the Chicago area between March 2020 and February 2021. RESULTS: After adjusting for possible confounders, White patients had 2.2 times the odds of being admitted to the hospital and 1.5 times the odds of being admitted to the ICU than Black patients. There were no observed differences between White and Hispanic patients. CONCLUSIONS: White patients were more likely than Black patients to be hospitalized after presenting to the ED with COVID-19 and more likely to be admitted directly to the ICU. This finding may be due to racial/ethnic differences in severity of disease upon ED presentation, racial and ethnic differences in access to COVID-19 primary care and/or implicit bias impacting clinical decision-making.

The Impact of Language on Hospital Outcomes for COVID-19 Patients: A Study of Non-English Speaking Hispanic Patients.

BACKGROUND: The COVID-19 pandemic has highlighted and exacerbated health inequities, as demonstrated by the disproportionate rates of infection, hospitalization, and death in marginalized racial and ethnic communities. Although non-English speaking (NES) patients have substantially higher rates of COVID-19 positivity than other groups, research has not yet examined primary language, as determined by the use of interpreter services, and hospital outcomes for patients with COVID-19. METHODS: Data were collected from 1,770 patients with COVID-19 admitted to an urban academic health medical center in the Chicago, Illinois area from March 2020 to April 2021. Patients were categorized as non-Hispanic White, non-Hispanic Black, NES Hispanic, and English-speaking (ES) Hispanic using NES as a proxy for English language proficiency. Multivariable logistic regression was used to compare the predicted probability for each outcome (i.e., ICU admission, intubation, and in-hospital death) by race/ethnicity. RESULTS: After adjusting for possible confounders, NES Hispanic patients had the highest predicted probability of ICU admission (p-value < 0.05). Regarding intubation and in-hospital death, NES Hispanic patients had the highest probability, although statistical significance was inconclusive, compared to White, Black, and ES Hispanic patients. CONCLUSIONS: Race and ethnicity, socioeconomic status, and language have demonstrated disparities in health outcomes. This study provides evidence for heterogeneity within the Hispanic population based on language proficiency that may potentially further contribute to disparities in COVID-19-related health outcomes within marginalized communities.

Regulatory approval characteristics of antimicrobial versus non-antimicrobial products, 1984-2018: an evaluation of Food and Drug Administration flexibilities.

Antimicrobial resistance is of growing concern. To encourage development of new treatments, some commentators have suggested regulators exercise increased flexibility on the clinical evidence required for approval. We examined all 1065 new drugs and biologics approved by the US Food and Drug Administration between 1984 and 2018 and recorded each drug's use of the Orphan Drug Act, fast-track, priority review, accelerated approval, and breakthrough therapy programmes, as well as dates of investigational new drug application, new drug application, and new drug approval, which were used to calculate clinical development and review times. There were 178 (17%) antimicrobial products, which were more likely than non-antimicrobial products to benefit from priority review (103 [58%] of 178 vs 402 [45%] of 887, p=0·0023), fast-track designation (58 [37%] of 157 vs 151 [19%] of 814], p<0·001), and accelerated approval (23 [18%] of 129 vs 67 [9%] of 711, p=0·0046), and less likely to have Orphan Drug Act designation (25 [14%] of 178 vs 267 [30%] of 887, p<0·0001). Median time from investigational new drug application to approval was shorter for antimicrobial than for non-antimicrobial drugs (5·9 years [IQR 4·6-7·3] vs 7·6 years [IQR 5·7-10·2], p<0·001). Except for Orphan Drug Act status, expedited clinical testing and review programmes have been used at least as frequently for antimicrobial products as for non-antimicrobial drugs. No evidence supported claims that antimicrobial progress through the regulatory approval process in the USA is more time-consuming than non-antimicrobial development.

Determining Which of Several Simultaneously Administered Vaccines Increase Risk of an Adverse Event.

INTRODUCTION: Childhood immunization schedules often involve multiple vaccinations per visit. When increased risk of an adverse event is observed after simultaneous (same-day) vaccinations, it can be difficult to ascertain which triggered the adverse event. This methods paper discusses a systematic process to determine which of the simultaneously administered vaccine(s) are most likely to have caused an observed increase in risk of an adverse event. METHODS: We use an example from the literature where excess risk of seizure was observed 1 day after vaccination, but same-day vaccination patterns made it difficult to discern which vaccine(s) may trigger the adverse event. We illustrate the systematic identification process using a simulation that retained the observed pattern of simultaneous vaccination in an empirical cohort of vaccinated children. We simulated "true" effects for diphtheria-tetanus-acellular pertussis (DTaP) and pneumococcal conjugate (PCV) on risk of seizure the day after vaccination. We varied the independent and interactive effects of vaccines (on the multiplicative scale). After applying the process to simulated data, we evaluated risk of seizure 1 day after vaccination in the empirical cohort. RESULTS: In all simulations, we were able to determine which vaccines contributed to excess risk. In the empirical data, we narrowed the association with seizure from all vaccines in the schedule to three likely candidates, DTaP, PCV, and/or Haemophilus influenzae type B (HiB) (p < 0.01, attributable risk when all three were administered together: five per 100,000). Disentangling their associations with seizure would require a larger sample or more variation in the combinations administered. When none of these three were administered, no excess risk was observed. CONCLUSION: The process outlined could provide valuable information on the magnitude of potential risk from individual and simultaneousvaccinations. Associations should be further investigated with independent data as well as biologically based, statistically independent hypotheses.