Background We investigated the effect of HIV on COVID‐19 outcomes with attention to selection bias due to differential testing and comorbidity burden. Methods This was a retrospective cohort analysis using four hierarchical outcomes: positive SARS‐CoV‐2 test, COVID‐19 hospitalization, intensive care unit (ICU) admission and hospital mortality. The effect of HIV status was assessed using traditional covariate‐adjusted, inverse probability‐weighted (IPW) analysis based on covariate distributions for testing bias (testing IPWs), HIV infection status (HIV‐IPWs) and combined models. Among people living with HIV (PWH), we evaluated whether CD4 count and HIV plasma viral load (pVL) discriminated between those who did and those who did not develop study outcomes using receiver operating characteristic analysis. Results Between March and November 2020, 63 319 people were receiving primary care services at the University of California San Diego (UCSD), of whom 4017 were PWH. The PWH had 2.1 times the odds of a positive SARS‐CoV‐2 test compared with those without HIV after weighting for potential testing bias, comorbidity burden and HIV‐IPW [95% confidence interval (CI): 1.6–2.8]. Relative to people without HIV, PWH did not have an increased rate of COVID‐19 hospitalization after controlling for comorbidities and testing bias [adjusted incidence rate ratio (aIRR) = 0.5, 95% CI: 0.1–1.4]. PWH did not have a different rate of ICU admission (aIRR = 1.08, 95% CI: 0.31–3.80) or of in‐hospital death (aIRR = 0.92, 95% CI: 0.08–10.94) in any examined model. Neither CD4 count nor pVL predicted any of the hierarchical outcomes among PWH. Conclusions People living with HIV have a higher risk of COVID‐19 diagnosis than those without HIV but the outcomes are similar in both groups.
Background We investigated the effect of HIV on COVID-19 outcomes with attention to selection bias due to differential testing and to comorbidity burden. Methods Retrospective cohort analysis using four hierarchical outcomes: positive SARS-CoV-2 test, COVID-19 hospitalization, intensive care unit (ICU) admission, and hospital mortality. The effect of HIV status was assessed using traditional covariate-adjusted, inverse probability weighted (IPW) analysis based on covariate distributions for testing bias (testing IPWs), HIV infection status (HIV IPWs), and combined models. Among PWH, we evaluated whether CD4 count and HIV plasma viral load (pVL) discriminated between those who did or did not develop study outcomes using receiver operating characteristic analysis. Results Between March and November 2020, 63,319 people were receiving primary care services at UCSD, of whom 4,017 were people living with HIV (PWH). PWH had 2.1 times the odds of a positive SARS-CoV-2 test compared to those without HIV after weighting for potential testing bias, comorbidity burden, and HIV-IPW (95% CI 1.6-2.8). Relative to persons without HIV, PWH did not have an increased rate of COVID-19 hospitalization after controlling for comorbidities and testing bias [adjusted incidence rate ratio (aIRR): 0.5, 95% CI: 0.1-1.4]. PWH had neither a different rate of ICU admission (aIRR:1.08, 95% CI; 0.31-3.80) nor in-hospital death (aIRR:0.92, 95% CI; 0.08-10.94) in any examined model. Neither CD4 count nor pVL predicted any of the hierarchical outcomes among PWH. Conclusions PWH have a higher risk of COVID-19 diagnosis but similar outcomes compared to those without HIV.
BackgroundOne in seven people living with HIV in the United States are unaware of their serostatus. Approximately 11,280 annual HIV infections (30.2%) are caused by this subset of individuals (CDC, 2017). In addition, acute HCV infections have nearly tripled since 2011, with many states seeing a dramatic increase in incidence among younger people outside the birth cohort (CDC, 2017). Because many individuals still use emergency departments (EDs) for their healthcare needs, these institutions play an increasingly important role in screening patients for HIV and HCV and linking them to medical services. Routine, opt-out testing initiatives are particularly effective at identifying new cases of HIV and HCV that could have otherwise been missed by a risk-based approach to screening.MethodsIn early May 2017, physicians and advanced practice nurses from Sutter Health’s Alta Bates Summit Medical Center (ABSMC) and a nearby outpatient HIV clinic implemented a routine HIV and HCV screening program at the hospital’s large, two-campus ED system in Oakland, CA. ED medical directors created a Nursing Standardized Procedure (NSP) to allow registered nurses (RNs) to independently order both blood tests using an automated, best practice authority (BPA) screen in the electronic health record (EHR) of any patient who met CDC-defined age criteria for testing.ResultsOf the 6,315 people screened for HIV between May 1, 2017 and March 31, 2018, 43 (0.7%) patients tested positive. Twelve (57%) of the 21 patients found to have a new HIV diagnosis also had symptomatic, acute HIV infection (AHI). All 12 patients with AHI initiated anti-retroviral therapy (ART) within five to 96 hours of their preliminary positive test result. Of the 5,820 patients screened for HCV, 424 (7.3%) were anti-HCV positive, while 185 (3.2%) patients had chronic infection. Thirty-nine percent of chronic HCV cases were among younger patients born before 1965. All patients with HIV or chronic HCV were referred to medical care at East Bay Advanced Care (EBAC).ConclusionAn automated, routine HIV-HCV testing program integrated into standard nursing workflow at a community ED resulted in the timely screening, diagnosis, and treatment of many patients with acute HIV, and identified a high prevalence of chronic HCV infections among younger patients.Disclosures R. Anson, Frontline of Communities in the United States (Gilead, Inc.): Grant Investigator, Grant recipient. C. Hall, Frontline of Communities in the United States (Gilead, Inc.): Grant Investigator, Grant recipient.
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