HIV-infected individuals who use alcohol and other drugs, and virologic suppression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
People living with HIV (PLWH) on antiretroviral therapy (ART) who use substances were examined to (a) describe those with virologic control and (b) determine which substance use-factors are associated with lack of virologic control. Participants were adult PLWH taking ART with either past 12-month DSM-IV substance dependence or past 30-day alcohol or illicit drug use. Substance use factors included number of DSM-IV alcohol or drug dependence criteria and past 30-day specific substance use. Associations with HIV viral load (HVL) (<200 vs. ≥200 copies/mL) were tested using logistic regression models. Multivariable analyses adjusted for age, sex, homelessness and anxiety or depression. Participants (n = 202) were median age 50 years, 66% male, 51% African American and 75% self-reported ≥90% past 30-day ART adherence. Though HVL suppression (HVL <200 copies/mL) was achieved in 78% (158/202), past 30-day substance use was common among this group: 77% cigarette use; 51% heavy alcohol use; 50% marijuana; 27% cocaine; 16% heroin; and 15% illicit prescription opioid use. After adjusting for covariates, specific substance use was not associated with a detectable HVL, however number of past 12-month DSM-IV drug dependence criteria was (adjusted odds ratio = 1.23 for each additional criterion, 95% CI: 1.04-1.46). Three-quarters of a substance-using cohort of PLWH receiving ART had virologic control and ≥90% ART adherence. Substance dependence criteria (particularly drug dependence), not specifically substance use, were associated with lack of virologic control. Optimal HIV outcomes can be achieved by individuals who use alcohol or drugs and addressing symptoms of substance dependence may improve HIV-related outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it