The Influence of Social Determinants on Receiving Outpatient Treatment with Monoclonal Antibodies, Disease Risk, and Effectiveness for COVID-19.

BACKGROUND: Limited research has studied the influence of social determinants of health (SDoH) on the receipt, disease risk, and subsequent effectiveness of neutralizing monoclonal antibodies (nMAbs) for outpatient treatment of COVID-19. OBJECTIVE: To examine the influence of SDoH variables on receiving nMAb treatments and the risk of a poor COVID-19 outcome, as well as nMAb treatment effectiveness across SDoH subgroups. DESIGN: Retrospective observational study utilizing electronic health record data from four health systems. SDoH variables analyzed included race, ethnicity, insurance, marital status, Area Deprivation Index, and population density. PARTICIPANTS: COVID-19 patients who met at least one emergency use authorization criterion for nMAb treatment. MAIN MEASURE: We used binary logistic regression to examine the influence of SDoH variables on receiving nMAb treatments and risk of a poor outcome from COVID-19 and marginal structural models to study treatment effectiveness. RESULTS: The study population included 25,241 (15.1%) nMAb-treated and 141,942 (84.9%) non-treated patients. Black or African American patients were less likely to receive treatment than white non-Hispanic patients (adjusted odds ratio (OR) = 0.86; 95% CI = 0.82-0.91). Patients who were on Medicaid, divorced or widowed, living in rural areas, or living in areas with the highest Area Deprivation Index (most vulnerable) had lower odds of receiving nMAb treatment, but a higher risk of a poor outcome. For example, compared to patients on private insurance, Medicaid patients had 0.89 (95% CI = 0.84-0.93) times the odds of receiving nMAb treatment, but 1.18 (95% CI = 1.13-1.24) times the odds of a poor COVID-19 outcome. Age, comorbidities, and COVID-19 vaccination status had a stronger influence on risk of a poor outcome than SDoH variables. nMAb treatment benefited all SDoH subgroups with lower rates of 14-day hospitalization and 30-day mortality. CONCLUSION: Disparities existed in receiving nMAbs within SDoH subgroups despite the benefit of treatment across subgroups.

Neutralizing Monoclonal Antibody Use and COVID-19 Infection Outcomes.

Importance: Evidence on the effectiveness and safety of COVID-19 therapies across a diverse population with varied risk factors is needed to inform clinical practice. Objective: To assess the safety of neutralizing monoclonal antibodies (nMAbs) for the treatment of COVID-19 and their association with adverse outcomes. Design, Setting, and Participants: This retrospective cohort study included 167 183 patients from a consortium of 4 health care systems based in California, Minnesota, Texas, and Utah. The study included nonhospitalized patients 12 years and older with a positive COVID-19 laboratory test collected between November 9, 2020, and January 31, 2022, who met at least 1 emergency use authorization criterion for risk of a poor outcome. Exposure: Four nMAb products (bamlanivimab, bamlanivimab-etesevimab, casirivimab-imdevimab, and sotrovimab) administered in the outpatient setting. Main Outcomes and Measures: Clinical and SARS-CoV-2 genomic sequence data and propensity-adjusted marginal structural models were used to assess the association between treatment with nMAbs and 4 outcomes: all-cause emergency department (ED) visits, hospitalization, death, and a composite of hospitalization or death within 14 days and 30 days of the index date (defined as the date of the first positive COVID-19 test or the date of referral). Patient index dates were categorized into 4 variant epochs: pre-Delta (November 9, 2020, to June 30, 2021), Delta (July 1 to November 30, 2021), Delta and Omicron BA.1 (December 1 to 31, 2021), and Omicron BA.1 (January 1 to 31, 2022). Results: Among 167 183 patients, the mean (SD) age was 47.0 (18.5) years; 95 669 patients (57.2%) were female at birth, 139 379 (83.4%) were White, and 138 900 (83.1%) were non-Hispanic. A total of 25 241 patients received treatment with nMAbs. Treatment with nMAbs was associated with lower odds of ED visits within 14 days (odds ratio [OR], 0.76; 95% CI, 0.68-0.85), hospitalization within 14 days (OR, 0.52; 95% CI, 0.45-0.59), and death within 30 days (OR, 0.14; 95% CI, 0.10-0.20). The association between nMAbs and reduced risk of hospitalization was stronger in unvaccinated patients (14-day hospitalization: OR, 0.51; 95% CI, 0.44-0.59), and the associations with hospitalization and death were stronger in immunocompromised patients (hospitalization within 14 days: OR, 0.31 [95% CI, 0.24-0.41]; death within 30 days: OR, 0.13 [95% CI, 0.06-0.27]). The strength of associations of nMAbs increased incrementally among patients with a greater probability of poor outcomes; for example, the ORs for hospitalization within 14 days were 0.58 (95% CI, 0.48-0.72) among those in the third (moderate) risk stratum and 0.41 (95% CI, 0.32-0.53) among those in the fifth (highest) risk stratum. The association of nMAb treatment with reduced risk of hospitalizations within 14 days was strongest during the Delta variant epoch (OR, 0.37; 95% CI, 0.31-0.43) but not during the Omicron BA.1 epoch (OR, 1.29; 95% CI, 0.68-2.47). These findings were corroborated in the subset of patients with viral genomic data. Treatment with nMAbs was associated with a significant mortality benefit in all variant epochs (pre-Delta: OR, 0.16 [95% CI, 0.08-0.33]; Delta: OR, 0.14 [95% CI, 0.09-0.22]; Delta and Omicron BA.1: OR, 0.10 [95% CI, 0.03-0.35]; and Omicron BA.1: OR, 0.13 [95% CI, 0.02-0.93]). Potential adverse drug events were identified in 38 treated patients (0.2%). Conclusions and Relevance: In this study, nMAb treatment for COVID-19 was safe and associated with reductions in ED visits, hospitalization, and death, although it was not associated with reduced risk of hospitalization during the Omicron BA.1 epoch. These findings suggest that targeted risk stratification strategies may help optimize future nMAb treatment decisions.

A Queue-Based Monte Carlo Analysis to Support Decision Making for Implementation of an Emergency Department Fast Track.

Emergency departments (EDs) are seeking ways to utilize existing resources more efficiently as they face rising numbers of patient visits. This study explored the impact on patient wait times and nursing resource demand from the addition of a fast track, or separate unit for low-acuity patients, in the ED using a queue-based Monte Carlo simulation in MATLAB. The model integrated principles of queueing theory and expanded the discrete event simulation to account for time-based arrival rates. Additionally, the ED occupancy and nursing resource demand were modeled and analyzed using the Emergency Severity Index (ESI) levels of patients, rather than the number of beds in the department. Simulation results indicated that the addition of a separate fast track with an additional nurse reduced overall median wait times by 35.8 ± 2.2 percent and reduced average nursing resource demand in the main ED during hours of operation. This novel modeling approach may be easily disseminated and informs hospital decision-makers of the impact of implementing a fast track or similar system on both patient wait times and acuity-based nursing resource demand.

A comparison of DNA profiling techniques for monitoring nutrient impact on microbial community composition during bioremediation of petroleum-contaminated soils.

Amplicon length heterogeneity PCR (LH-PCR) and terminal restriction fragment length polymorphisms (TRFLP) were used to monitor the impact that nutrient amendments had on microbial community dynamics and structural diversity during bioremediation of petroleum-contaminated soils. Slurried soils contaminated with petroleum hydrocarbons were treated in airlift bench-scale bioreactors and were either amended with optimal inorganic nutrients or left unamended. Direct DNA extraction and PCR amplification of whole eubacterial community DNA were performed with universal primers that bracketed the first two or three hypervariable regions of the 16S rDNA gene sequences. The LH-PCR method profiled a more diverse microbial community than did the TRFLP method. The LH-PCR method also tracked differences between the communities due to nutrient amendments. An in silico database search for bacterial genera with amplicon lengths represented in the community fingerprints was performed. It was possible to qualitatively identify different groups in the microbial community based on the amplicon length variations. A similar "virtual" search was performed for the TRFLP fragments using the web-based TAP-TRFLP program. Cloning and sequencing of the PCR products confirmed the in silico database matches. The application of the LH-PCR method as a monitoring tool for bioremediation could greatly enhance and extend the current understanding of the microbial community dynamics during the biodegradation of environmental contaminants.