Time Between Viral Loads for People With HIV During the COVID-19 Pandemic

Background: During the COVID-19 pandemic, patients experienced significant care disruptions, including lab monitoring. We investigated changes in the time between viral load (VL) checks for people with HIV associated with the pandemic. Methods: This was an observational analysis of VLs of people with HIV in routine care at a large subspecialty clinic. At pandemic onset, the clinic temporarily closed its onsite laboratory. The exposure was time period (time-varying): pre-pandemic (January 1st 2019-March 15th, 2020);pandemic lab-closed (March 16th-July 12th, 2020);and pandemic lab-open (July 13th-December 31st, 2020). We estimated time from an index VL to a subsequent VL, stratified by whether the index VL was suppressed (<= 200 copies/mL). We also calculated cumulative incidence of a non-suppressed VL following a suppressed index VL, and of re-suppression following a loss of viral suppression. Results: Compared to pre-pandemic, hazard ratios for next VL check were: 0.34 (95% CI: 0.30, 0.37, lab-closed) and 0.73 (CI: 0.68, 0.78, lab-open) for suppressed patients;0.56 (CI: 0.42, 0.79, lab-closed) and 0.92 (95% CI: 0.76, 1.10, lab-open) for non-suppressed patients. The 12-month cumulative incidence of loss of suppression was the same in the pandemic lab-open (4%) and pre-pandemic period (4%). The hazard of re-suppression following loss of suppression was lower during the pandemic lab-open versus the pre-pandemic period (hazard ratio: 0.68, 95% CI: 0.50, 0.92). Conclusions: Early pandemic restrictions and lab closure significantly delayed VL monitoring. Once the lab re-opened, non-suppressed patients resumed normal monitoring. Suppressed patients still had a delay, but no significant loss of suppression.

COVID-19 and the HIV CARE CONTINUUM in C3PNO COHORTS

Background: The COVID-19 pandemic disrupted the normal delivery of HIV care, altered social support networks, and caused economic insecurity. People with HIV (PWH) are vulnerable to such disruptions, particularly if they have a history of substance use. We describe engagement in care and adherence to antiretroviral therapy (ART) for PWH during the pandemic. Methods: From May 2020 to February 2021, 773 PWH enrolled in 6 existing cohorts completed 1495 surveys about substance use and engagement in HIV care during the COVID-19 pandemic. We described the prevalence and correlates of having missed a visit with an HIV provider in the past month and having missed a dose of ART in the past week. Results: Thirteen percent of people missed an HIV visit in the past month. Missing a visit was associated with unstable housing, food insecurity, anxiety, low resiliency, disruptions to mental health care, and substance use including cigarette smoking, hazardous alcohol use, cocaine, and cannabis use. Nineteen percent of people reported missing at least one dose of ART in the week prior to their survey. Missing a dose of ART was associated with being a man, low resiliency, disruptions to mental health care, cigarette smoking, hazardous alcohol use, cocaine, and cannabis use, and experiencing disruptions to substance use treatment. Conclusion: Social determinants of health, substance use, and disruptions to mental health and substance use treatment were associated with poorer engagement in HIV care. Close attention to continuity of care during times of social disruption is especially critical for PWH.

COVID-19 cases & hospitalizations in a US multisite cohort of people with HIV

Background: COVID-19 outcomes among people with HIV (PWH) remain inconclusive. We characterized all cases of COVID-19 identified in a long-term multi-site cohort of PWH, as well as factors associated with increasing severity of COVID-19 during the early months of the COVID-19 pandemic. Methods: We examined all PWH with SARS-CoV-2 infection and COVID-19 disease identified from laboratory testing data (RT-PCR, antigen test results) and ICD-10 codes March-July 2020 from seven sites in the CFAR Network of Integrated Clinical Systems (CNICS) cohort. Cases were verified by medical record review. We evaluated predictors of increased disease severity, indicated by hospitalization. Relative risks were estimated using Poisson regression, adjusted for clinical and demographic characteristics using disease risk scores. Results: Among 13,862 PWH in care (20% female, median age 52 (IQR 40-59), 58% Black or Hispanic race/ethnicity), 198 COVID-19 cases were detected during the study period. A higher proportion of PWH with COVID-19 were female (27%), Black or Hispanic (76%), and had BMI ≥30 (45%). No significant differences in CD4+ count (current or lowest) were seen between PWH with and without COVID-19. We found evidence suggesting more unstable housing among COVID-19 cases compared to non-cases (14% vs. 9%). Among PWH with COVID-19, 38 (19%) were hospitalized, 10 (5%) required intensive care, 8 (4%) received invasive mechanical ventilation, and 4 (2%) died. Hospitalization among PWH with COVID-19 was associated with: CD4+ count ≤350 (aRR 1.77;95% CI 1.05, 2.98);age ≥60 (aRR 2.0;95%CI 1.13, 3.54);pre-existing kidney disease with eGFR <60 (aRR 1.76;95% CI 0.99, 3.13);and BMI ≥30 (aRR 1.96;95% CI 1.02, 3.78) (Table). Conclusion: The population frequency of COVID-19 detected in PWH was 1.4%, likely an underestimate of the true frequency of SARS-CoV-2 infection and COVID-19 disease due to evolving testing availability and access over time. A higher proportion of PWH with COVID-19 were Black or Hispanic, in excess of the overrepresentation of people of color with HIV compared to the general population. PWH with decreased eGFR, low CD4+ count, and obesity had greater risk of more severe COVID-19 disease. Our results highlight disparities in risk of COVID-19 acquisition among PWH in the US and indicate additional vigilance in screening and monitoring of COVID-19 among PWH with these characteristics. The expected accrual of additional COVID-19 cases will allow more precise evaluation of the impact of comorbidities. (Figure Presented).

Visit completion during the telemedicine transition in early months of the pandemic

Background: Prior to the COVID-19 pandemic, evidence on telemedicine use in people with HIV was limited. In response to the pandemic, telemedicine was widely adopted. On March 16th, 2020, the John G. Bartlett Specialty Practice converted from exclusively in-person visits to mostly telemedicine visits. We studied the impact of this transition on visit completion. Methods: We conducted separate analyses of patients in the Johns Hopkins HIV Clinical Cohort scheduled for visits in the 14 weeks before and in the 14 weeks after the transition. For each 14-week period, we calculated the percentage of people who completed at least one visit. We calculated odds ratios (OR) for having completed ≥1 visit, associated with demographic and clinical factors in each period. Results: Pre-transition and post-transition characteristics of the study sample were: 1,580 vs 1,598 patients, 61% vs. 63% male, 80% vs. 78% black, 56 vs. 57 median age, 92% vs. 92% viral suppression, and 25% vs. 24% people with a history of injection drug use (IDU) by chart review. Pre-transition, 79% of patients completed ≥1 visit. Post-transition, 1,315 patients (82%) were scheduled for telemedicine visits and 283 were scheduled for in-person visits. Visit completion in the post-transition period was 84%, overall. Visit completion for telemedicine visits was 98%. Telemedicine visits were conducted 70% by phone, 30% by video. A History of IDU was associated with lower odds of visit completion, pre-transition OR=0.84 [95% confidence interval (CI):0.64,1.11], post-transition OR=0.74 [CI:0.55,0.99]. Substance use in recent years was associated with lower odds of visit completion post-transition: heroin use OR=0.39 [CI:0.24,0.62] and cocaine use OR=0.57 [CI:0.37,0.86]. OR for visit completion associated with tobacco use pre-transition was 0.64 [CI:0.50,0.82] and post-transition was 0.86 [CI:0.66,1.14]. Age 60+ was associated with higher odds of visit completion pre-transition (OR=1.67 [CI:1.16,2.41]) but not posttransition (OR=0.87 [CI:0.57,1.35]). Conclusion: Moving to telemedicine visits during the pandemic provided access to services, with a higher proportion of patients completing ≥1 visit, but many patients were only able to complete a telemedicine visit by phone. The impact of expanding access to telemedicine on probability of visit completion and possibly differential access by subsets of the population should be explored more once data for longer time periods are available, as should the long-term impact on other clinical outcomes.