Disease Burden of Chronic Hepatitis B among Immigrants in Canada
Bibliographic record
Abstract
BACKGROUND: The prevalence of chronic hepatitis B (CHB) infection among immigrants to North America ranges from 2% to 15%, 40% of whom develop advanced liver disease. Screening for hepatitis B surface antigen is not recommended for immigrants. OBJECTIVE: To estimate the disease burden of CHB among immigrants in Canada using Markov cohort models comparing a cohort of immigrants with CHB versus a control cohort of immigrants without CHB. METHODS: Markov cohort models were used to estimate life years, quality-adjusted life years and lifetime direct medical costs (adjusted to 2008 Canadian dollars) for a cohort of immigrants with CHB living in Canada in 2006, and an age-matched control cohort of immigrants without CHB living in Canada in 2006. Parameter values were derived from the published literature. RESULTS: At the baseline estimate, the model suggested that the cohort of immigrants with CHB lost an average of 4.6 life years (corresponding to 1.5 quality-adjusted life years), had an increased average of $24,249 for lifetime direct medical costs, and had a higher lifetime risk for decompensated cirrhosis (12%), hepatocellular carcinoma (16%) and need for liver transplant (5%) when compared with the control cohort. DISCUSSION: Results of the present study showed that the socio-economic burden of CHB among immigrants living in Canada is substantial. Governments and health systems need to develop policies that promote early recognition of CHB and raise public awareness regarding hepatitis B to extend the lives of infected immigrants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".