Risk Factors Associated With Inpatient Hospital Utilization in HIV-Positive Individuals and Relationship to HIV Care Engagement
Bibliographic record
Abstract
BACKGROUND: Prompt linkage to HIV primary care may reduce the need for inpatient hospitalization. METHODS: Retrospective cohort study of South Carolina HIV-infected individuals diagnosed from January 1986 to December 2006 who utilized 62 inpatient facilities from (January 2007 to June 2010). Suboptimal primary care engagement was defined as <2 reports of a CD4T-cell count or viral load value to surveillance in each calendar year from January 2007 to June 2010. Multivariable logistic regression explored associations of HIV primary care engagement with inpatient hospitalization after accounting for sociodemographic characteristics and disease stage. Poisson and negative binominal regression examined primary care engagement, sociodemographic characteristics, and disease stage on frequency of inpatient hospitalization and total inpatient days. RESULTS: Individuals presenting to the hospital with an AIDS-defining illness had greater risk of suboptimal HIV primary care engagement [adjusted odds ratio (aOR) = 1.58; 95% confidence interval (CI): 1.23 to 2.04] more inpatient hospitalizations (incidence rate ratio [IRR] = 1.74; 95% CI: 1.65 to 1.83) and inpatient days (IRR = 2.17; 95%CI: 2.00 to 2.36). Blacks demonstrated greater suboptimal care risk (aOR = 1.61; 95% CI: 1.15 to 2.25), more inpatient visits (IRR = 1.09; 95% CI: 1.01 to 1.17), and inpatient days (IRR = 1.21; 95% CI: 1.09 to 1.34). Medicare protected against suboptimal primary care engagement (aOR = 0.66; 95% CI: 0.46 to 0.95) but was associated with more hospitalizations (IRR = 1.09; 95% CI: 1.01 to 1.18). AIDS disease stage was associated with decreased suboptimal care risk (AIDS ≤ 1 year, aOR = 0.05; 95% CI: 0.02 to 0.12; AIDS > 1 year, aOR = 0.11; 95% CI: 0.06 to 0.20) but more hospitalizations (AIDS ≤1 year, IRR = 1.12; 95% CI: 1.04 to 1.21; AIDS > 1 year, IRR = 1.12; 95% CI: 1.04 to 1.21) and inpatient days (AIDS ≤ 1 year, IRR = 1.22; 95% CI: 1.08 to 1.37; AIDS >1 year, IRR = 1.35; 95% CI: 1.21 to 1.50). CONCLUSIONS: Disease stage, race, and insurance status strongly influence HIV primary care engagement and inpatient hospitalization. Admissions may be related to general medical conditions, substance abuse, or antiretroviral therapy.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".