Seroprevalence of hepatitis B in previously undiagnosed patients: A community screening study
Bibliographic record
Abstract
BACKGROUND: Forty percent of hepatitis B carriers have no knowledge of their diagnosis. A prior study in British Columbia suggested high rates of hepatitis B among immigrants. The authors undertook a large-scale screening study to validate these rates. METHODS: Attendees at Asian health fairs without knowledge of their hepatitis B status participated. They completed a questionnaire, and blood was drawn for HBV serologies. Active HBV was defined as HBV surface antigen positive. RESULTS: Of 2,726 patients, 1,704 (62.5%) were female and 1,022 (37.5%) male. Mean age was 62.7 (SD 22.1) years, and mean time of residing in Canada was 27.5 (SD 15.3) years. Most patients originated from China (1,042 patients, 38.2%) and Hong Kong (871, 31.2%). Fifty-six patients tested positive (seroprevalence rate 2.05%, 95% CI 1.52%–2.59%). Most seropositive patients were from China (28 patients, 50.0%). Mean time of residence in Canada for seropositive patients (23.8 [SD 2.1] y) was less than seronegative patients (27.6 [SD 0.3] y) ( p = 0.06). There was a trend towards association of seropositivity with time of residence in Canada (OR 0.98, 95% CI 0.96–1.00, p = 0.09). 8 (14.3%) seropositive patients did not have family doctors, compared with 128 (4.8%) seronegative patients. Lack of a family doctor was strongly associated with seropositivity (OR 3.31, 95% CI 1.32–7.25, χ2 = 10.42, p = 0.001). INTERPRETATION: The authors have shown that high risk immigrant populations may have seroprevalence rates as high as 2,700 per 100,000. Lack of a family physician was associated with seropositivity. These results should be used to design improved outreach programs.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".