Emergency department utilization by people living with HIV released from jail in the US South
Bibliographic record
Abstract
BACKGROUND: Incarceration is disruptive to HIV care, often resulting in poor retention in care for people living with HIV (PLWH) after jail release. This gap in HIV care might result in potentially preventable emergency department (ED) utilization. We analyzed demographic, incarceration, socioeconomic and clinical data for PLWH released from the Dallas County Jail to the community (1450 incarcerations, 1155 unique individuals) between January 2011 and November 2013. RESULTS: The study population consisted of predominantly men (77%), with a mean age of 39 years, 67% were black and 14% were Hispanic; half of the releasees visited the ED at least once during the first-year post-jail. In adjusted analyses, female gender, family awareness of HIV status, serious mental illness, and late engagement to HIV care were significantly associated with higher ED utilization. Compared to the general Dallas population, PLWH released from jail had a 5-fold higher proportion of ED visits classified as related to substance use or mental health. CONCLUSIONS: Further efforts are needed to improve the transition from incarceration to community-based HIV care, substance use disorder treatment and mental health services, and to directly address re-engagement in HIV care for out-of-care PLWH who visit the ED.
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.
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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".