The Changing Demographics of Women Living with HIV/AIDS in Southern Alberta from 1982 to 2006
Bibliographic record
Abstract
INTRODUCTION: Women account for a growing proportion of HIV infections in Canada. This has implications with respect to prevention, diagnosis and treatment. OBJECTIVE: To describe the female population presenting for HIV care in southern Alberta and to examine the impact of opt-out pregnancy screening. METHODS: A retrospective review of demographic and clinical characteristics of all patients presenting to the Southern Alberta HIV Clinic (SAC) care program from 1982 to 2006, was performed. RESULTS: The proportion of newly diagnosed patients who were female increased from 7.5% before 1998 to 21.5% after 1998. Women were more likely to be from vulnerable populations, such as intravenous drug users (31.3% versus 13.7%, P<0.001), aboriginals/Métis (21.5% versus 8.7%, P<0.001), blacks (28.9% versus 4.9%, P<0.001) and immigrants (36.6% versus 14.7%, P<0.001). Heterosexual intercourse was the main risk factor for HIV acquisition (43.7%). Women were less likely than men to have requested HIV testing (20.9% versus 37.8%, P<0.001). Opt-out pregnancy screening accounted for 12.7% of HIV-positive tests in women, following its introduction in 1998. Of the women diagnosed by pregnancy screening, 62.1% were from HIV-endemic countries. There was an association between reason for testing and CD4 count at presentation; women who requested their HIV test had higher median CD4 counts than those diagnosed because of illness (478 cells/mL, interquartile range [IQR]=370 cells/mL versus 174 cells/mL, IQR=328 cells/mL, P<0.001) or pregnancy screening (478 cells/mL, IQR=370 cells/mL versus 271 cells/mL, IQR=256 cells/mL, P=0.001). CONCLUSIONS: Women were less likely than men to have requested HIV testing and were more likely to be diagnosed by population-based screening methods. Women, especially vulnerable groups, account for a growing number and proportion of newly diagnosed HIV infections in Alberta. The implications of expanded screening in this population merit further consideration.
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".