Long-acting injectable (LAI) cabotegravir/rilpivirine (CAB/RPV) provides an effective treatment option for people with HIV (PWH). Studies suggest that PWH on LAI CAB/RPV may experience isolated episodes of transient viremia (HIV RNA > 20 copies/mL) defined as virologic blips (VB). The risk factors for VB in PWH receiving LAI CAB/RPV are limited. We aimed to describe a cohort of PWH on LAI CAB/RPV and evaluate risk factors and time to VB following LAI CAB/RPV initiation. We obtained DC Cohort data from PWH who initiated LAI CAB/RPV prior to July 2023 and used Kaplan-Meier curves and Cox proportional hazards models to evaluate the association between participant demographics, HIV clinical factors, and time to VB. Among 98 PWH who initiated LAI CAB/RPV, 9 (9.2%) experienced at least one VB (median HIV RNA = 50 copies/mL; ranges 30-12,000 copies/mL) during a median follow-up period of five months (IQR: 2-10). The median CD4 count among PWH was 754 cells/µL (IQR: 598, 980) at the time of LAI CAB/RPV initiation. Having a high CD4 (≥ 500 cells/μL) at LAI CAB/RPV initiation was significantly associated with a lower hazard for VB when compared to baseline CD4 < 200 cells/µL [hazard ratios (HR): 0.15 [95% confidence intervals (CI): 0.03, 0.77]; aHR: 0.07 (95% CI: 0.01, 0.50); log-rank p = .026]. No other characteristics were significantly associated with time to VB, and no participants experienced virologic failure. Considerations for baseline CD4 may be important when initiating a patient on LAI CAB/RPV, and future studies will help evaluate the VB occurrence and associated factors among PWH.

Objective: Evaluate potential risk factors for severe coronavirus disease 2019 (COVID-19) among health care workers (HCWs) at the University of Virginia Medical Center in Charlottesville, Virginia. Methods: We conducted a retrospective manual chart review of data from HCWs who were diagnosed with COVID-19 from March 2020 to March 2021. Using data from patient medical histories, we ascertained risk factors for COVID-19–related emergency department encounter, hospitalization, or death. Results: We had 634 patients in total, and 9.8% had a severe COVID-19–related outcome. A history of deep vein thrombosis/pulmonary embolism/stroke (odds ratio, 19.6; 95% confidence interval, 5.11 to 94.7), as well as asthma, chronic lung disease, diabetes, or current immunocompromised status, was associated with increased adjusted odds of COVID-19–related emergency department encounter/hospitalization/death. Conclusions: A preexisting history of deep vein thrombosis/pulmonary embolism/stroke is a novel risk factor for poor COVID-19 outcomes among a cohort of HCWs.

The high proportion of people with HIV (PWH) in the 2022–2023 mpox outbreak has raised questions surrounding the association between HIV and mpox. The objectives of this study were to evaluate the association between engagement in HIV-associated healthcare and mpox diagnosis, as well as to characterize cases of mpox among PWH. The DC Cohort is a longitudinal cohort of PWH in Washington, DC. We conducted a 5:1 (controls:cases) nested case-cohort study on male participants, matching age and care site. Cases were participants with an identified mpox diagnosis. Conditional logistic regression was used to assess the impact of indicators of engagement in HIV-associated healthcare on mpox diagnosis. We identified 70 cases of mpox in DC Cohort participants randomly matched to 323 controls, for a total of 393 participants included in the analysis. Study participants were primarily non-Hispanic Black (72.3%) with a median age of 41 (IQR: 36, 50). There was no association between engagement in care and mpox diagnosis; however, low CD4 was associated with increased odds of mpox diagnosis (aOR: 4.60 (95% CI: 1.23, 17.11)). Among a cohort of PWH, engagement in care was not associated with mpox diagnosis, suggesting that the overrepresentation of PWH among mpox cases is not due to surveillance bias.

Objectives: There is a high prevalence of internalized stigma among people with HIV (PWH) and it is possible that factors associated with stigma differ by gender. Therefore, we evaluated whether gender is an effect modifier of the association between covariates and internalized stigma among 694 PWH. Methods: Linear regression with interaction terms between covariates and gender was used to evaluate significant associations and test for interactions. Results: We found a 10-year increase in age was associated with lower stigma among women (β (95% CI): −0.20 (−0.30, −0.10)) but not among men (β = 0). Generalized anxiety disorder (GAD) was associated with higher stigma (GAD & GAD-squared β (95% CI): 0.12 (0.08, 0.187), −0.004 (−0.006, −0.001)) and an increased time since HIV diagnosis was associated with lower stigma (β (95% CI): −0.20 (−0.30, −0.10)). Conclusions: Gender-specific interventions should be developed to account for the differences in the association between age and stigma across genders.

Background: The validated Screening Tool of Older People’s Prescriptions (STOPP) identifies potentially inappropriate prescribing (PIP)—treatments where potential risk outweighs potential benefit. STOPP is particularly important for people aging with HIV and comorbidities, since PIP may exacerbate symptoms and decrease adherence. Methods: We analyzed data from the DC Cohort, a longitudinal cohort of people with HIV (PWH). We applied STOPP criteria to identify PIP among DC Cohort participants aged ≥ 50 years who completed a Patient Reported Outcomes (PROs) survey. All medications prescribed in the 2 years prior to PROs survey completion were considered. Negative binomial models were used to evaluate factors associated with PIP and structural equation modeling was used to evaluate whether symptom burden mediates the relationship between PIP and quality of life. Results: Of 1048 eligible DC Cohort participants, 486 (46%) had at least one PIP. The most common systems implicated were musculoskeletal (23%), analgesic drugs (16%), and the central nervous system (13%). Age, race/ethnicity, HIV transmission factor, social determinants of health, and type of HIV care site were significantly associated with number of PIP in the crude models. In the multivariable model with just demographic variables, the association between age (aIRR: 1.03 (95% CI: 1.02, 1.04)), intravenous drug use (aIRR: 1.68 (95% CI: 1.20, 2.35)), White, non-Hispanic race (aIRR: 0.67 (95% CI: 0.50, 0.92)), site type (aIRR: 0.75 (95% CI: 0.62, 0.92)), and the expected number of PIPs remained significant. In the fully adjusted multivariable model with demographics and SDOH, the association between age, intravenous drug use, White, non-Hispanic race, and expected number of PIPs remained significant. Statistical evidence that symptom burden mediates the relationship between PIP and each of the QOL dimensions was present. Conclusions: Future interventions should work to decrease PIP among these high-risk groups, especially for PIP associated with increased symptom burden.