Longitudinal assessment (1995–2003) of hospitalizations of HIV‐infected patients within a geographical population in Canada
Bibliographic record
Abstract
OBJECTIVES: To determine the frequency of and reasons for hospitalization of adult HIV-infected patients compared with the general population. METHODS: Length of stay, primary/secondary diagnoses and discharge status were reviewed for all HIV-infected patients admitted to Calgary-area hospitals between 1995 and 2003. Admissions were classified as HIV- or non-HIV-related using International Classification of Diseases, 9th and 10th revisions (ICD-9/10) codes and confirmed by chart review. Summary comparative data on admissions for the general population were obtained from the regional administrative database. RESULTS: HIV-infected adults were hospitalized more than twice as frequently, experienced longer stays (median length 5 vs 3 days, respectively) and had higher in-hospital mortality rates (9.1 vs 1.3 per 100 admissions, respectively) than the general population (P < 0.01). Hospitalizations of HIV-infected patients declined by 58% from 1995 to 2003. Patients newly diagnosed with HIV infection accounted for 15% of all HIV-related hospitalizations. HIV-related admissions for known HIV-infected patients decreased from 12 per 100 patient-years-followed in 1995 to 3 per 100 patient-years-followed in 2003. Low CD4 counts, AIDS, and no current use of highly active antiretroviral therapy (HAART) were strongly correlated with hospitalizations (P < 0.01). Non-HIV-related hospitalizations for HIV-infected patients increased by 42% and were associated with comorbidities (e.g. substance use and psychological disorders). CONCLUSION: Despite the reduction in HIV-related hospitalizations following the introduction of HAART, all-cause hospitalization rates have increased and have started to erode this benefit.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".