CROI 2025 Abstract eBook

Abstract eBook

Poster Abstracts

Methods: This retrospective cohort study utilized the National COVID Cohort Collaborative (N3C), a longitudinal EHR repository. We analyzed 2-year mortality among patients infected with SARS-CoV-2 between April 2020 and June 2022, with follow-up until June 2024. Patients were categorized into urban, urban-adjacent rural (UAR), and nonurban-adjacent rural (NAR) groups based on residential ZIP codes using Rural-Urban Commuting Area codes. Mortality differences were assessed using Kaplan-Meier analysis and weighted multivariable Cox regression, adjusting for demographic differences and background risk, including obesity, hypertension, substance use, tobacco use, individual comorbid conditions included in the Charlson Comorbidity Index, COVID-19 vaccination status, residential social vulnerability (independent of rural residency using the CDC’s Social Vulnerability Index), U.S. Census Division, and SARS-CoV-2 variant-dominant strain at the time of infection. Results: Among 2,658,202 SARS-CoV-2-infected patients, Kaplan-Meier curves revealed a significant association between rurality and 2-year mortality post infection ( p <0.001). Cox regression exhibited higher mortality among rural residents at 1-, 3-, 12-, and 24-months post-infection ( Figure 1 ). Compared to urban dwellers, the adjusted hazard ratios for 2-year mortality for UAR and NAR were 1.27 (1.25-1.28) and 1.31 (1.30-1.32). Conclusions: We demonstrated that rural dwellers have significantly higher mortality than urban dwellers after SARS-CoV-2 infection, and this worse prognosis persists for at least 2 years, with an approximate 27% increased risk of 2-year all-cause mortality risk for rural-dwelling patients following COVID-19, even after adjusting for background risk and demographic differences. The COVID-19-exacerbated rural mortality penalty persists beyond the immediate acute period after infection, highlighting a need for continued public health prioritization of rural communities. The figure, table, or graphic for this abstract has been removed. HIV Infection and Long COVID: A RECOVER Program, EHR-Based Cohort Study Kellie L. Hawkins 1 , Dima Dandachi 2 , Colby Lewis 3 , M. Daniel Brannock 4 , Zoe Verzani 3 , Saajjad Abedian 3 , Sohrab Jaferian 5 , Shannon Wuller 6 , Jennifer Truong 6 , Margot Gage Witvliet 7 , Kristen Marks 3 , Edward M. Gardner 8 , Ighovwerha Ofotokun 9 , Roy M. Gulick 3 , Kristine M. Erlandson 10 , for the RECOVER Consortium 1 Public Health Institute at Denver Health, Denver, CO, USA, 2 University of Missouri, Columbia, MO, USA, 3 Weill Cornell Medicine, New York, NY, USA, 4 RTI International, Berkeley, CA, USA, 5 University of Rochester Medical Center, Rochester, NY, USA, 6 New York University Langone Medical Center, New York, NY, USA, 7 Lamar University, Beaumont, TX, USA, 8 Denver Health Medical Center, Denver, CO, USA, 9 Emory University, Atlanta, GA, USA, 10 University of Colorado Anschutz Medical Campus, Aurora, CO, USA Background: Studies show that people with HIV (PWH) may be prone to post-acute sequela of SARS-CoV-2 infection (PASC), or Long COVID (LC). We investigated the association between HIV status and LC utilizing the National Patient-Centered Clinical Research Network (PCORnet) and the NCATS National COVID Cohort Collaborative (N3C) databases. Methods: PCORnet and N3C cohorts were queried from 1/1/2018 to 4/30/2024, limited to age ≥21 with COVID (ICD10 diagnosis codes, positive test, use of nirmatrelvir/ritonavir), and stratified by HIV status and sex at birth. Covariates included age, race, COVID severity (hospitalization), variant, pre-pandemic health utilization, and Charlson Comorbidity Index (CCI) score. Uni/multivariable models compared LC development after COVID diagnosis by HIV status. Odds ratios (OR) of LC defined based on the ICD10 code or computable phenotype (CP, symptoms post COVID) in relation to HIV status for each cohort are presented. CP was distinct in PCORnet and N3C. Results: PCORnet included 11,964 with and 1,357,932 without HIV and N3C 23,931 with and 3,288,424 without HIV. In both cohorts, PWH were more likely to be male, identify as Hispanic or Black, have higher CCI score (irrespective of HIV), and higher pre-pandemic healthcare utilization compared to people without HIV. There were more patients in both cohorts assigned long COVID using the computable phenotype than ICD10 code (19 vs. 1.7% in PCORnet and 8.1 vs. 1.4% in N3C). By computable phenotype, a small increased odds of developing long COVID was seen among people with compared to without HIV in both cohorts (PCORnet adjusted OR 1.09 [CI 1.04-1.14] and N3C adjusted OR 1.18 [CI 1.13-1.23]). By ICD10, there was no association between long COVID and HIV in either cohort (adjusted OR 1.01 [CI 0.88-1.16] and 1.07 [CI 0.97-1.18]), respectively.

Conclusions: Data from two large cohorts support an increased risk of long COVID development in people with HIV, and highlights challenges and possible disparities in recognizing and diagnosing long COVID.

919

Putting the PASC Score to the Test: Clinical vs Statistical Accuracy in Long COVID Alba M. Azola 1 , Leah H. Rubin 2 , Rebecca E. Easter 3 , Rebecca Veenhuis 1 , Hannah Parker 1 , Christina Della Penna 1 , Holly Schultz 1 , Isabel Santiuste 1 1 The Johns Hopkins University School of Medicine, Baltimore, MD, USA, 2 The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, 3 The Johns Hopkins University, Baltimore, MD, USA Background: Long COVID (LC) is a mass disabling event affecting millions worldwide. Given the broad definitions and lack of biomarkers, there is an urgent need for diagnostic tools to identify those affected. Here we aimed to validate the RECOVER Post-Acute Sequelae of SARS-CoV-2 Infection (PASC) Score in a cohort of SARS-CoV-2 infected patients with LC and fully recovered individuals while iteratively improving the tool’s sensitivity and specificity. Methods: Participants included 100 LC patients from LC clinics in Baltimore, MD between August 2023 and July 2024 who met the National Academy of Medicine(NAM) 2024 LC definition, and 18 SARS-CoV-2 infected but fully recovered individuals. LC participants were required to have least one neuropsychiatric symptom (e.g., brain fog). Exclusion criteria included history of psychosis, recent substance misuse(nicotine, cannabis excluded), and lack of English proficiency. Participants completed comprehensive surveys and questionnaires assessing symptoms based on the methods of the PASC score publication. Using the NAM 2024 LC definition as the ‘true’ condition, we compared evaluation metrics for the REVOVER PASC score cutoff(PASC Total >12) as well as comparing the presence of individual, pairs, and triplets of symptoms. Evaluation metrics(e.g., sensitivity, specificity, F1) were calculated based on these classifications for the overall PASC score and symptom combinations. Results: The LC cohort(n=100) had a mean age of 47.7 years, was predominantly female(73%), White(78%), and well-educated(76% >16 years). Controls(n=18) had similar demographic characteristics. LC diagnosis and PASC scores were significantly associated(χ 2 =44.72, P <0.001). The PASC score showed excellent specificity(100%) and positive predictive value(PPV; 100%) albeit limited sensitivity(80%), missing approximately 20% of the patients with LC. The negative predictive value(NPV) was 47.37%, indicating that only 47% of those who tested negatively via PASC score did not have LC. When examining whether combinations of symptoms performed better than the total PASC score cutoff, we found that the presence of loss of smell/taste, post-exertional malaise, or brain fog demonstrated 93% sensitivity, 100% specificity, and PPV, 72% NPV, and an F1 score of 0.964. Conclusions: Validation of the RECOVER PASC supports its utility and highlights the need for ongoing refinement of the LC definition. We call for national efforts to create and validate a readily implementable clinical tool for LC diagnosis.

Poster Abstracts

918

CROI 2025 287