Diffusion of Newer HIV Prevention Innovations: Variable Practices of Frontline Infectious Diseases Physicians
Bibliographic record
Abstract
BACKGROUND: US Public Health Service guidelines recommend early initiation of antiretroviral treatment (ART) for human immunodeficiency virus infection (HIV)-infected patients and preexposure prophylaxis (PrEP) as a prevention option for persons at risk for HIV acquisition. Before issuance of these guidelines, few clinicians reported prescribing early ART or PrEP. METHODS: The Emerging Infections Network, a national network of infectious diseases physicians in the United States and Canada, was surveyed in September 2014 to assess practices of adult HIV-care providers with early ART, PrEP, and other guideline-recommended HIV prevention methods. RESULTS: Almost half of the 1191 active members invited (48.1%) participated; 415 (72.4%) were HIV-care providers. Most providers (86.5%) indicated that they typically recommended ART initiation at diagnosis, irrespective of CD4(+) cell count. However, for patients with a CD4(+) cell count >500/µL, clinicians would defer ART if patients did not feel ready to initiate ART (94.7%) or had uncontrolled substance abuse (66.0%). Many providers had counseled HIV-infected patients about PrEP for partners (59.0%) or offered visits for partners to discuss PrEP (40.7%), and 31.8% had prescribed PrEP. Clinicians who deferred ART were less likely to endorse and engage in aspects of PrEP provision. CONCLUSIONS: Concordant with guidelines, most infectious diseases physicians recommend early ART, and many have experience with aspects of PrEP provision, suggesting recent evolution of clinician practices. Providers who defer ART are also cautious about PrEP. Interventions that help physicians motivate patients to initiate ART and identify missed opportunities to provide PrEP could enhance HIV prevention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".