Association between U.S. State AIDS Drug Assistance Program (ADAP) Features and HIV Antiretroviral Therapy Initiation, 2001–2009
Bibliographic record
Abstract
BackgroundU.S. state AIDS Drug Assistance Programs (ADAPs) are federally funded to provide antiretroviral therapy (ART) as the payer of last resort to eligible persons with HIV infection. States differ regarding their financial contributions to and ways of implementing these programs, and it remains unclear how this interstate variability affects HIV treatment outcomes.MethodsWe analyzed data from HIV-infected individuals who were clinically-eligible for ART between 2001 and 2009 (i.e., a first reported CD4+ <350 cells/uL or AIDS-defining illness) from 14 U.S. cohorts of the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD). Using propensity score matching and Cox regression, we assessed ART initiation (within 6 months following eligibility) and virologic suppression (within 1 year) based on differences in two state ADAP features: the amount of state funding in annual ADAP budgets and the implementation of waiting lists. We performed an a priori subgroup analysis in persons with a history of injection drug use (IDU).ResultsAmong 8,874 persons, 56% initiated ART within six months following eligibility. Persons living in states with no additional state contribution to the ADAP budget initiated ART on a less timely basis (hazard ratio [HR] 0.73, 95% CI 0.60–0.88). Living in a state with an ADAP waiting list was not associated with less timely initiation (HR 1.12, 95% CI 0.87–1.45). Neither additional state contributions nor waiting lists were significantly associated with virologic suppression. Persons with an IDU history initiated ART on a less timely basis (HR 0.67, 95% CI 0.47–0.95).ConclusionsWe found that living in states that did not contribute additionally to the ADAP budget was associated with delayed ART initiation when treatment was clinically indicated. Given the changing healthcare environment, continued assessment of the role of ADAPs and their features that facilitate prompt treatment is needed.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".