Prevalence and Correlates of HIV and Hepatitis B Virus Coinfection in Northern Alberta
Bibliographic record
Abstract
BACKGROUND: HIV and hepatitis B virus (HBV) share transmission routes, and coinfection is associated with higher morbidity and mortality. To date, no Canadian studies have examined HIV-HBV coinfection. OBJECTIVES: To examine the prevalence and correlates of HIV and HBV coinfections in Northern Alberta. METHODS: The present study was a retrospective database review of all HIV-infected (HIV+) individuals in Northern Alberta from 1982 to 2010 and a chart review of HBV surface antigen-positive individuals for whom charts were available (46.2%). RESULTS: Of 2844 HIV+ patients, 2579 (90.7%) had been tested for HBV surface antigen, and 143 (5.5%) of these were HBV coinfected. Coinfected males were primarily Caucasian (70.8%), and coinfected females were primarily black (56.4%) or Aboriginal (31.3%). Coinfected individuals were more likely to be male (88.1% versus 71.3%; P<0.001) and to have died (34.3% versus 17.9%; P<0.001). CONCLUSIONS: The prevalence of coinfection with HBV in HIV-infected patients in Northern Alberta is lower than reported in other developed nations. The pattern of coinfections in Northern Alberta likely follows immigration trends. Recognition and management may be improving with time; however, further research and additional strategies are required to enhance the prevention, identification and management of HBV infection in HIV-infected individuals.
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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 | 0.002 | 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 | 0.000 |
| 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".