CROI 2024 Abstract eBook

Abstract eBook

Poster Abstracts

Methods: We conducted a cross-sectional secondary analysis of HIV care data from the Lubombo and Manzini regions. We used data from adult ART clients with a baseline and one-year VL result from October 2021 to September 2022 from the client management information system (CMIS). Data included clients' sociodemographic and clinical information. Clients with VL <1000 were suppressed, and VL ≥50 were suppressed but detectable. Viral load was categorized into <50, 50-200, 201-500, 501-999 and ≥1000. We analyzed the data using descriptive, comparative, and multivariate logistic regression analysis reporting adjusted odds ratios (AOR). Results: Of 66,145 PLHIV in the database, 63,547 (96%) had a suppressed viral load. Most clients (N=43,394; 65.6%) were from the Manzini region, and 57,547 (87%) were on a Dolutegravir-based ART regimen. Median age was 39 (IQR: 32, 48); 43,879 (66.3%) were females, and the median duration on ART was six years (IQR: 4, 10). Of 2598 with a high viral load (HVL) (VL≥1000) at baseline, 1,550 (59.8%) had follow-up VL data; 1,117 (72%) were suppressed, and 433 (28%) remained unsuppressed. Amongst clients with suppressed baseline VL (n=63,547), 34,757 (54.7%) had follow-up VL data; 33,879 (97.5%) remained suppressed and 878 (2.5%) had HVL. Comparison of clients with HVL at follow up with baseline categories of VL indicates a linear increase in the proportion of clients with HVL (Figure 1). Baseline predictors of HVL at follow-up were age <15 (AOR 2.0; 95%CI: 1.46,2.74; p<0.001), 15-24 (AOR 2.72; 95%CI:2.17,3.40; P<0.001), 25-34 (AOR 1.62;95% CI: 1.33, 1.99;p<0.001) compared to ≥45 years; males (AOR 1.15; 95%CI:1.01,1.31; p=0.029) compared to females; baseline viral load 50-200 (AOR 3.52; 95%CI:2.65,4.67; p<0.001), VL=201-500 (AOR 7.22; 95%CI: 5.1, 10.3; p<0.001), VL=501-999 (AOR 11.4; 95%CI: 6.9, 18.8; p<0.001), ≥1000 (AOR 13.1; 95%CI: 11.4, 15.1; p=0.001) compared to baseline VL<50. Conclusion: Any detectable VL is a risk for virological failure.This requires strategies that support and strengthen stepped-up adherence counselling for all clients with a detectable VL to limit progression to virological failure and for contextualized care for males and PLHIV aged <35 years. 1037 HIV Data Informed Care: Using Routine Data to Identify Persons At Risk of Developing Viremia Thomas Martin 1 , Ravi Goyal 1 , Gordon Honerkamp Smith 2 , Alan Wells 1 , Samantha Tweeten 3 , Diana Corona-Mata 4 , Susan J. Little 1 1 University of California San Diego, San Diego, CA, USA, 2 University of California San Diego, La Jolla, CA, USA, 3 San Diego Department of Public Health, San Diego, CA, USA, 4 Hospital Universitario Reina Sofia, Cordoba, Spain Background: Identifying persons with HIV (PWH) at increased risk of developing unsuppressed viral load or falling out of care could lead to improved resource allocation and improve the focus of public health data to-care activities. We sought to evaluate factors associated with developing unsuppressed viral load in San Diego County, California using routinely reported HIV data. Methods: Data were obtained from the Enhanced HIV/AIDS Reporting System (eHARS) for PWH who were diagnosed or resided in San Diego County. The analysis was limited to individuals whose diagnosis date was known and occurred after May 2017 (based on eHARS data availability) and had attained viral suppression (VL200 copies/ml after attaining viral suppression. Survival curves for each group were estimated separately using the Kaplan-Meier estimator and compared using log-rank tests. To compare viral load testing patterns between the rebound and no rebound group, we used Wilcoxon rank sum tests. Results: Between June 2017 and December 2021, 1840 persons were diagnosed with HIV and achieved viral suppression. From these participants there was a total of 12,222 viral load measurements included in the analysis. Among these individuals, 244 (13.3%) subsequently developed an unsuppressed viral load (>200 copies/ml). Factors associated with an increased rate of unsuppressed

viremia included younger age at diagnosis (p=0.013), Black race or Hispanic ethnicity (p=0.04), female birth sex (p=0.04), persons with any history of injection drug use (IDU, p=0.003), men who have sex with men (MSM) who also report IDU, and a later HIV stage at diagnosis (p=<0.001). Viral load testing pattern analysis indicated that among persons with at least 1 year of follow up, less frequent testing (p=<0.001) and lower variance in testing interval (p=0.002) were associated with developing unsuppressed viral load. Conclusion: Multiple demographic, HIV associated factors, and viral load testing patterns were associated with an increased risk of developing unsuppressed HIV viral load. These variables may be considered as part of a risk score to identify individuals before they develop unsuppressed viremia. Prospective evaluation is needed to determine if such a score could lead to greater clinical and social support services to prevent viral load rebound. The figure, table, or graphic for this abstract has been removed. 1038 Longitudinal Viral Load Clustering for People With HIV Using Functional Principal Component Analysis Jiayang Xiao , Yunqing Ma, Xueying Yang, Bankole Olatosi, Xiaoming Li, Jiajia Zhang University of South Carolina at Columbia, Columbia, SC, USA Background: While multiple indicators like viral suppression (VS) and viral rebound (VR) exist for monitoring HIV viral load (VL), research on continuous VL clustering is limited. By characterizing people with HIV (PWH) into distinct groups, stratified long-term risks of virological failure can be assessed. Therefore, this study aims to use functional data clustering to identify continuous VL patterns and characterize each cluster by demographics, comorbidities, social behaviors, CD4 count, and antiretroviral therapy (ART) history. Methods: We analyzed adult PWH diagnosed from 2005 to 2020 in South Carolina with a 5-year minimum follow-up from the first VS to the last VL test. Functional principal component analysis (FPCA) was used to categorize PWH to clusters based on sparse VL test. ANOVA were used to test the difference in VL characteristics, demographics, comorbidities, social behaviors, and longitudinal CD4 count during the follow-up period of each cluster. Subgroup analyses were conducted among PWH with ART, examining the ART patterns within each cluster, including initial, most recent, most frequently used ART, and any regimen switches. Results: A total of 5,916 PWH were grouped into four clusters: long-term VS group (Cluster 1, 17.3%), short-term VS group (Cluster 2, 29.8%), suboptimal VS group (Cluster 3, 28.3%), and viral failure group (Cluster 4, 24.9%). In Cluster 1 with an average of 11-year follow-up, PWH displayed sustained VS (95.3%), lower mean CD4 count (28.1%), most NRTI+NNRTI in first and last 3 months (72.8% and 64.0%), and less regimen switches (32.0%). Results for Cluster 2 were similar except for shorter follow-up (6 years), more comorbidities (31.4%), and higher max CD4 count (48.4%). In Cluster 3, PWH were mostly under 30 years old (44.8%) and Black (77.2%), with relatively lower mean VL (92.9%), lower number of VR (18.4%), higher maximum CD4 count (47.6%), and were mostly prescribed with NRTI+NNRTI in first 3 months (50.9%). In Cluster 4, demographics were similar to Cluster 3, while PWH had higher mean VL (40.6%), lower mean CD4 count (31.4%), received most PI+NRTI (32.4%) in the first 3 months, and switched the regimen more frequently (55.2%). Conclusion: The findings highlight the value of continuous clustering in understanding the distinct viral profiles of PWH. By identifying distinct clusters varied in VL patterns, demographics, substance use, comorbidities, CD4 count, and ART, we emphasize the importance of tailored treatment and insights for targeted interventions.

Poster Abstracts

CROI 2024 333