Association Between Chronic Hepatitis C Virus Infection and Myocardial Infarction Among People Living With HIV in the United States.

Hepatitis C virus (HCV) infection is common among people living with human immunodeficiency virus (PLWH). Extrahepatic manifestations of HCV, including myocardial infarction (MI), are a topic of active research. MI is classified into types, predominantly atheroembolic type 1 MI (T1MI) and supply-demand mismatch type 2 MI (T2MI). We examined the association between HCV and MI among patients in the Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems, a US multicenter clinical cohort of PLWH. MIs were centrally adjudicated and categorized by type using the Third Universal Definition of Myocardial Infarction. We estimated the association between chronic HCV (RNA+) and time to MI while adjusting for demographic characteristics, cardiovascular risk factors, clinical characteristics, and history of injecting drug use. Among 23,407 PLWH aged ≥18 years, there were 336 T1MIs and 330 T2MIs during a median of 4.7 years of follow-up between 1998 and 2016. HCV was associated with a 46% greater risk of T2MI (adjusted hazard ratio (aHR) = 1.46, 95% confidence interval (CI): 1.09, 1.97) but not T1MI (aHR = 0.87, 95% CI: 0.58, 1.29). In an exploratory cause-specific analysis of T2MI, HCV was associated with a 2-fold greater risk of T2MI attributed to sepsis (aHR = 2.01, 95% CI: 1.25, 3.24). Extrahepatic manifestations of HCV in this high-risk population are an important area for continued research

Heavy Alcohol Use Is Associated With Worse Retention in HIV Care

Poor retention in HIV care is associated with worse clinical outcomes and increased HIV transmission. We examined the relationship between self-reported alcohol use, a potentially modifiable behavior, and retention

Trajectories of Depressive Symptoms Among a Population of HIV-Infected Men and Women in Routine HIV Care in the United States

Depressive symptoms vary in severity and chronicity. We used group-based trajectory models to describe trajectories of depressive symptoms (measured using the Patient Health Questionnaire-9) and predictors of trajectory group membership among 1493 HIV-infected men (84%) and 292 HIV-infected women (16%). At baseline, 29% of women and 26% of men had depressive symptoms. Over a median of 30 months of follow-up, we identified four depressive symptom trajectories for women (labeled “low” [experienced by 56% of women], “mild/moderate” [24%], “improving” [14%], and “severe” [6%]) and five for men (“low” [61%], “mild/moderate” [14%], “rebounding” [5%], “improving” [13%], and “severe” [7%]). Baseline antidepressant prescription, panic symptoms, and prior mental health diagnoses were associated with more severe or dynamic depressive symptom trajectories. Nearly a quarter of participants experienced some depressive symptoms, highlighting the need for improved depression management. Addressing more severe or dynamic depressive symptom trajectories may require interventions that additionally address mental health comorbidities

Weight gain among treatment-naïve persons with HIV starting integrase inhibitors compared to non-nucleoside reverse transcriptase inhibitors or protease inhibitors in a large observational cohort in the United States and Canada.

IntroductionWeight gain following antiretroviral therapy (ART) initiation is common, potentially predisposing some persons with HIV (PWH) to cardio-metabolic disease. We assessed relationships between ART drug class and weight change among treatment-naïve PWH initiating ART in the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD).MethodsAdult, treatment-naïve PWH in NA-ACCORD initiating integrase strand transfer inhibitor (INSTI), protease inhibitor (PI) or non-nucleoside reverse-transcriptase inhibitor (NNRTI)-based ART on/after 1 January 2007 were followed through 31 December 2016. Multivariate linear mixed effects models estimated weight up to five years after ART initiation, adjusting for age, sex, race, cohort site, HIV acquisition mode, treatment year, and baseline weight, plasma HIV-1 RNA level and CD4+ cell count. Due to shorter follow-up for PWH receiving newer INSTI drugs, weights for specific INSTIs were estimated at two years. Secondary analyses using logistic regression and all covariates from primary analyses assessed factors associated with >10% weight gain at two and five years.ResultsAmong 22,972 participants, 87% were male, and 41% were white. 49% started NNRTI-, 31% started PI- and 20% started INSTI-based regimens (1624 raltegravir (RAL), 2085 elvitegravir (EVG) and 929 dolutegravir (DTG)). PWH starting INSTI-based regimens had mean estimated five-year weight change of +5.9kg, compared to +3.7kg for NNRTI and +5.5kg for PI. Among PWH starting INSTI drugs, mean estimated two-year weight change was +7.2kg for DTG, +5.8kg for RAL and +4.1kg for EVG. Women, persons with lower baseline CD4+ cell counts, and those initiating INSTI-based regimens had higher odds of >10% body weight increase at two years (adjusted odds ratio = 1.37, 95% confidence interval: 1.20 to 1.56 vs. NNRTI).ConclusionsPWH initiating INSTI-based regimens gained, on average, more weight compared to NNRTI-based regimens. This phenomenon may reflect heterogeneous effects of ART agents on body weight regulation that require further exploration

Development and validation of a multivariable prediction model for missed HIV health care provider visits in a large US clinical cohort

Background: Identifying individuals at high risk of missing HIV care provider visits could support proactive intervention. Previous prediction models for missed visits have not incorporated data beyond the individual level. Methods: We developed prediction models for missed visits among people with HIV (PWH) with ≥1 follow-up visit in the Center for AIDS Research Network of Integrated Clinical Systems from 2010 to 2016. Individual-level (medical record data and patient-reported outcomes), community-level (American Community Survey), HIV care site-level (standardized clinic leadership survey), and structural-level (HIV criminalization laws, Medicaid expansion, and state AIDS Drug Assistance Program budget) predictors were included. Models were developed using random forests with 10-fold cross-validation; candidate models with the highest area under the curve (AUC) were identified. Results: Data from 382 432 visits among 20 807 PWH followed for a median of 3.8 years were included; the median age was 44 years, 81% were male, 37% were Black, 15% reported injection drug use, and 57% reported male-to-male sexual contact. The highest AUC was 0.76, and the strongest predictors were at the individual level (prior visit adherence, age, CD4+ count) and community level (proportion living in poverty, unemployed, and of Black race). A simplified model, including readily accessible variables available in a web-based calculator, had a slightly lower AUC of .700. Conclusions: Prediction models validated using multilevel data had a similar AUC to previous models developed using only individual-level data. The strongest predictors were individual-level variables, particularly prior visit adherence, though community-level variables were also predictive. Absent additional data, PWH with previous missed visits should be prioritized by interventions to improve visit adherence