Patient Attrition Between the Emergency Department and Clinic Among Individuals Presenting for HIV Nonoccupational Postexposure Prophylaxis
Bibliographic record
Abstract
BACKGROUND: Nonoccupational postexposure prophylaxis (nPEP) is recommended after a sexual or parenteral exposure to human immunodeficiency virus (HIV). Patients frequently seek care in an emergency department (ED) after an exposure and are usually referred to an HIV clinic for further management. There have been few data on determinants of attrition after presentation to EDs for nPEP. METHODS: From July 2010 to June 2011, we prospectively recorded all referrals to nPEP programs from 2 large EDs at 2 academic medical centers in Boston, Massachusetts. Data were recorded on patient demographics, nature of potential HIV exposures, referrals to and attendance at HIV clinics, and reported completion of 28 days of antiretroviral therapy (ART). Multivariable logistic regression was used to evaluate risk factors for (1) patient attrition between the ED and HIV clinic follow-up and (2) documented completion of ART. RESULTS: Of 180 individuals who were referred to clinic follow-up for nPEP care from the ED, 98 (54.4%) attended a first nPEP clinic visit and 43 (23.9%) had documented completion of a 28-day course of ART. Multivariable analysis revealed older age (adjusted odds ratio [aOR], 0.96; 95% confidence interval [CI], .93-.99) and self-payment (aOR, 0.32; 95% CI, .11-.97) were significant predictors for failing to attend an initial HIV clinic appointment. Women were less likely than men to complete a 28-day ART regimen (aOR, 0.34; 95% CI, .15-.79). CONCLUSIONS: Commonly used nPEP delivery models may not be effective for all patients who present with nonoccupational exposures to HIV. Interventions are needed to improve rates of follow-up and completion of nPEP to reduce the risk of preventable HIV infections.
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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 | 0.002 | 0.010 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".