HIV-Positive Injection Drug Users Who Leave the Hospital Against Medical Advice
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Leaving the hospital against medical advice has been associated with increased morbidity and readmission. Factors associated with the risk of leaving against medical advice among HIV/AIDS patients or injection drug users have not been examined in detail. OBJECTIVES: To examine the clinical and social factors associated with leaving against medical advice (AMA) from a specialized HIV/AIDS ward among patients who reported a history of injection drug use. METHODS: All patients with a history of injection drug use admitted to the HIV/AIDS ward at St. Paul's Hospital, Vancouver, British Columbia (the largest specialized HIV/AIDS hospital ward in Canada) between April 1997 and October 2000 were reviewed retrospectively. A multivariate logistic regression model utilizing a generalized estimating equation algorithm identified factors associated with leaving the hospital AMA. RESULTS: Of the 1056 hospital admissions to the HIV/AIDS ward by patients with a history of injection drug use, 263 (24.9%) resulted in leaving the hospital AMA. Independent positive predictors of leaving AMA included recent injection drug use (adjusted odds ratio [AOR] = 2.08, 95% confidence interval [CI]: 1.41-3.07) and aboriginal ethnicity (AOR = 1.55, 95% CI: 1.05-2.28). Discharge AMA was also more likely to occur on weekends (AOR = 2.27, 95% CI: 1.49-3.48) and on days when social assistance payments were issued (AOR = 2.95, 95% CI: 1.70-5.10). Factors that independently reduced the odds of hospital discharge AMA included in-hospital methadone use (AOR = 0.49, 95% CI: 0.32-0.76), social support (AOR = 0.33, 95% CI: 0.21-0.51), and older age (per 10-year increment, AOR = 0.56, 95% CI: 0.43-0.73). CONCLUSIONS: Among HIV-positive patients with a history of injection drug use, the odds of leaving the hospital AMA were reduced for subjects who received inpatient methadone treatment, were of older age, or had social supports. Addiction treatment and interventions that enhance social supports in marginalized populations at risk for hospital discharge AMA should be further explored.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it