The high cost of medical care for patients who present late (CD4<200 cells/μL) with HIV infection
Bibliographic record
Abstract
OBJECTIVE: To compare the direct costs of medical care in the year following HIV diagnosis for patients who present with a CD4 count <200 cells/microL ('late presenters') and those who present with a CD4 count >200 cells/microL ('early presenters'). METHODS: Direct costs (i.e. drugs, laboratory tests, outpatient care, in-patient care, and home care) for the 12 months following HIV diagnosis, sociodemographic data and clinical data were collected for all patients presenting for HIV care in Southern Alberta, Canada between April 1996 and April 2001. Mean costs are presented as costs in 2001 Canadian dollars. RESULTS: Thirty-nine per cent of 241 patients presented with a CD4 count <200 cells/microL. The mean costs for late presenters were more than twice as high as those for early presenters (i.e. $18,448 vs. $8455, respectively). Late presenters were more likely to be older, male and black, and to have a risk activity of men having sex with men (MSM) or heterosexual contact (P<0.05). However, the large difference in mean costs cannot be attributed to differences in characteristics. When characteristics were statistically held constant, the estimated excess cost of late presentation was almost unaffected, at $9723 (z=5.6). Repeating the analysis using disaggregated costing categories suggested that the difference in total costs was largely attributable to differences in HIV-related hospital care costs, which were 15 times higher for late presenters. CONCLUSIONS: Direct care costs in the year following HIV diagnosis were more than 200% higher for patients who presented late. This difference could not be attributed to differences in patient characteristics. Most costs were attributable to HIV-related hospital care costs and the immediate initiation of antiretroviral therapy. While early diagnosis in those at risk for HIV remains medically important, the short-term economic impact is also substantial.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".