Hospital Readmissions Among Persons With Human Immunodeficiency Virus in the United States and Canada, 2005-2018: A Collaboration of Cohort Studies
Bibliographic record
Abstract
Background. Hospital readmission trends for persons with human immunodeficiency virus (PWH) in North America in the context of policy changes, improved antiretroviral therapy (ART), and aging are not well-known. We examined readmissions during 2005–2018 among adult PWH in NA-ACCORD. Methods. Linear risk regression estimated calendar trends in 30-day readmissions, adjusted for demographics, CD4 count, AIDS history, virologic suppression (<400 copies/mL), and cohort. Results. We examined 20 189 hospitalizations among 8823 PWH (73% cisgender men, 38% White, 38% Black). PWH hospitalized in 2018 versus 2005 had higher median age (54 vs 44 years), CD4 count (469 vs 274 cells/μL), and virologic suppression (83% vs 49%). Unadjusted 30-day readmissions decreased from 20.1% (95% confidence interval [CI], 17.9%–22.3%) in 2005 to 16.3% (95% CI, 14.1%–18.5%) in 2018. Absolute annual trends were −0.34% (95% CI, −.48% to −.19%) in unadjusted and −0.19% (95% CI, −.35% to −.02%) in adjusted analyses. By index hospitalization reason, there were significant adjusted decreases only for cardiovascular and psychiatric hospitalizations. Readmission reason was most frequently in the same diagnostic category as the index hospitalization. Conclusions. Readmissions decreased over 2005–2018 but remained higher than the general population’s. Significant decreases after adjusting for CD4 count and virologic suppression suggest that factors alongside improved ART contributed to lower readmissions. Efforts are needed to further prevent readmissions in PWH
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".