ABSTRACT
Background. Therapeutic vaccination following SARS-CoV-2 infection might stimulate anti-viral immunity and improve patient outcomes. We investigated, amongst previously unvaccinated patients, whether vaccination with the Pfizer, Moderna, or Johnson & Johnson vaccines within 14 days of a positive SARS-CoV-2 test affected 30-day patient outcomes. Methods. Using a deidentified national electronic health record dataset (Optum, Inc.), we identified previously unvaccinated patients who tested positive forCOVID-19 between 12/11/2020 and 12/19/2021. Among this cohort, 1,909 patients received a first vaccine dose within 14 days (vaccinated) while 446,309 did not receive a first dose of vaccine within 30 days of their first positive test (unvaccinated). We performed 1:1 propensity score matching based on age, gender, race, ethnicity, region, BMI, insurance, and comorbidities from the Charlson Comorbidity Index. Next, we compared odds of severe outcomes within 30 days between vaccinated and unvaccinated groups using a partial proportional odds model with the following ordinal severity outcome: no hospitalization, hospitalization, ICU stay, or death (Stata version 17.0, alpha = 0.05). Results. 1,909 vaccinated patients were propensity score-matched to 1,909 unvaccinated patients. The final matched cohort was statistically indistinguishable (p > 0.05) for all metrics used in propensity score calculation. This matched cohort (n = 3,818) was 58.6% female, 67.7% white, 12.6% Hispanic, and 56.4% commercially insured, with a mean age of 50.6 years and a similar comorbidity profile. A partial proportional odds model showed that unvaccinated patients were at increased risk for hospitalization and higher ordered outcomes (OR = 1.19, 95% CI: 1.02-1.39), ICU stay and higher ordered outcomes (OR 1.63, 95% CI: 1.21-2.20), and death (OR 4.57, 95% CI: 2.50-8.37). Conclusion. Among previously unvaccinated patients, those who received a first dose vaccine within 14 days of a positive COVID-19 test were less likely to experience hospitalization, ICU stay, or death compared to matched peers who did not receive a first dose in the acute phase of infection. The sample size of patients vaccinated during the acute phase is limited, so further studies are indicated to evaluate the safety and efficacy of this practice.
ABSTRACT
Background. As the risk for concomitant COVID-19 infection in people living with HIV (PLHIV) remains largely unknown, we explored a large national database to identify risk factors for COVID-19 infection among PLHIV. Methods. Using the COVID-19 OPTUM de-identified national multicenter database, we identified 29,393 PLHIV with either a positive HIV test or documented HIV ICD9/10 codes. Using a multiple logistic regression model, we compared risk factors among PLHIV, who tested positive for COVID-19 (5,134) and those who tested negative (24,259) from January 20, 2020, to January 20, 2022. We then compared secondary outcomes including hospitalization, Intensive Care Unit (ICU) stay, and death within 30 days of test among the 2 cohorts, adjusting for COVID-19 positivity and covariates. We adjusted all models for the following covariates: age, gender, race, ethnicity, U.S. region, insurance type, adjusted Charlson Comorbidity Index (CCI), Body Mass Index (BMI), and smoking status. Results. Among PLHIV, factors associated with higher odds for acquiring COVID-19 (Figure 1) included lower age (compared to age group 18-49, age groups 50-64 and >65 were associated with odds ratios (OR) of 0.8 and 0.75, P= 0.001), female gender (compared to males, OR 1.06, P= 0.07), Hispanic White ethnicity/race (OR 2.75, P=0.001),Asian (OR 1.35, P=0.04), and AfricanAmerican (OR1.23, P=0.001) [compared to non-Hispanic White], living in the U.S. South (compared to the Northeast, OR 2.18, P= 0.001), being uninsured (compared to commercial insurance, OR 1.46, P= 0.001), higher CCI (OR 1.025, P= 0.001), higher BMI category (compared to having BMI< 30, Obesity category 1 or 2,OR 1.2 and obesity category 3,OR1.34, P=0.001), and noncurrent smoking status (compared to current smoker, OR 1.46, P= 0.001). Compared to PLHIV who tested negative for COVID-19, PLHIV who tested positive, had an OR 1.01 for hospitalization (P = 0.79), 1.03 for ICU stay (P=0.73), and 1.47 for death (P=0.001). Conclusion. Our study found that among PLHIV, being Hispanic, living in the South, lacking insurance, having higher BMI, and higher CCI scores were associated with increased odds of testing positive for COVID-19. PLHIV who tested positive for COVID-19 had higher odds of death. (Figure Presented).
ABSTRACT
Background. The percentage of children infected with COVID-19 has outpaced that of adults. As children >5 years are now eligible to receive vaccines, it is necessary to understand the effect of vaccination in the context of demographic characteristics, clinical factors, and variants on pediatric COVID-19 illness severity. Methods. Weconducted a descriptive study of patients<=18 years fromthe Optum COVID-19 electronic health record dataset. Patients were included if positive for COVID-19 by polymerase chain reaction or antigen testing for the first time from 3/ 12/2020 to 1/20/2022. We compare race and ethnicity, age, gender, US region of residence, vaccination status, body mass index (BMI), pediatric comorbidity index (PCI) (Sun, Am. J. Epidemiol. 2021), and predominant variant (by time and region) with 2-tailed t-test, multi-category chi-square test, and odds ratios (R version 4.1.2;alpha = 0.05). PCI is a validated comorbidity index predicting hospitalization in pediatric patients. Results. Of all pediatric patients in our dataset, 165,468 (13.2%) tested positive for COVID-19. 3,087 (1.9%) were hospitalized, 1,417 (0.9%) were admitted to the ICU, 1545 (0.9%) received respiratory support, and 31 (0.02%) died, comparable to AAP-reported hospitalization and mortality rates in US children. Patients with severe outcomes were more likely to be younger, non-Caucasian, from the US South, unvaccinated, and have a higher PCI (Figure 1). Excluding non-severe outcomes, rates of death and ICU admission were higher in 0-4-year-olds compared to 5-11 or 12- 18-year-olds (Figure 2). All patients receiving at least one dose of the vaccine survived. The odds ratio of a severe outcome is 0.11 (95% CI 0.07-0.16) in fully vaccinated patients compared to unvaccinated patients. The odds ratio of a severe outcome is 0.55 (95% CI 0.49-0.63) in partially vaccinated patients compared to unvaccinated patients. Demographic and clinical characteristics of pediatric patients with COVID-19 Conclusion. In this large population, incidence rate of severe outcomes from COVID-19 in pediatric patients was higher among non-Caucasian patients, living in the South, with underlying comorbid illness, and those not yet eligible for vaccination. These findings reinforce the need for a vaccine for younger patients and targeted vaccine outreach to racial and ethnic minorities and children with chronic conditions. (Figure Presented).
ABSTRACT
Study Objectives: The novel coronavirus (SARS-CoV-2) pandemic placed unprecedented strain on the supply of personal protective equipment (PPE) in health care settings, particularly the emergency department (ED). Innovative strategies were needed for PPE conservation. Our ED deployed electronic PPE (ePPE) - a telehealth approach to conduct medical screening exams (MSEs) of COVID-19-suspected patients. As part of our plan to scale this intervention, we sought to evaluate provider perceptions of ePPE-based MSEs. Methods: We conducted a qualitative analysis at Vanderbilt University Medical Center in Nashville, TN. Emergency clinicians were identified through use of structured ePPE documentation elements in the EHR. Patients who received ePPE-based MSEs included English-speaking adults with fever or respiratory symptoms (inclusion criteria: age < 50;SpO2 > 94%;RR < 20;HR < 110;no cardiovascular, respiratory, or immunosuppressive history). We invited providers to participate in semi-structured video interviews (Zoom, San Jose, CA). A Likert scale between 1 [Not at all effective] and 5 [Extremely effective] was used to gauge perceived ePPE effectiveness. We recorded and transcribed interviews, subsequently extracting then encoding notable excerpts using Dedoose (SocioCultural Research Consultants, Los Angeles, CA). Thematic analysis was performed using intervention characteristics from the Consolidated Framework for Implementation Research (CFIR): intervention source, evidence strength and quality, relative advantage, adaptability, trialability, complexity, design quality and packaging, and cost. Results: We identified 18 clinicians who documented ePPE use. On review, 2 never used ePPE and 5 only supervised other clinicians who used ePPE. Of the remaining 11, we interviewed 7 attending physicians and 1 physician assistant between 5/15/20 and 6/5/20. Providers gave ePPE a mean effectiveness score of 4.2 (SD 0.53). Identified advantages included improved patient and provider safety, PPE conservation, and improved patient-provider communication. The primary perceived limitation was inability to auscultate the lungs. While noting the risk of missed alternate diagnoses (eg, heart failure), providers asserted that video-based history-taking and respiratory exam sufficed for low-acuity patients and that auscultation’s absence was unlikely to change management. Beyond MSEs, providers used ePPE for patient reassessment and counseling, as well as to facilitate supervision. Many emphasized ePPE’s flexibility: “If I do pick up on a few things…I can always, sort of, abandon [ePPE] and go in and do my exam.” Barriers to use included potential for negative patient perceptions, poor audio quality, difficulty incorporating an interpreter, and workflow challenges related to staff coordination. Clinicians revealed that many ePPE encounters were not fully documented, suggesting ePPE use may be underrepresented in this study. Conclusion: In this trial implementation of ePPE, we found that ED clinicians perceived ePPE as an effective and useful technique for MSEs of COVID-19-suspected patients. The benefits largely outweighed the disadvantages, particularly in the low-acuity population. Our study may have been limited by early adoption from clinicians favorable to such technology, and future work should examine perceptions among clinicians with varying degrees of technology comfort.