The viral hepatitis B care cascade: A population‐based comparison of immigrant groups
Bibliographic record
Abstract
BACKGROUND AND AIMS: The global burden of viral hepatitis B is substantial, and monitoring infections across the care cascade is important for elimination efforts. There is little information on care disparities by immigration status, and we aimed to quantify disease burden among immigrant subgroups. APPROACH AND RESULTS: In this population-based, retrospective cohort study, we used linked laboratory and health administrative records to describe the HBV care cascade in five distinct stages: (1) lifetime prevalence; (2) diagnosis; (3) engagement with care; (4) treatment initiation; and (5) treatment continuation. Infections were identified based on at least one reactive antigen or nucleic acid test, and lifetime prevalence was estimated as the sum of diagnosed and estimated undiagnosed cases. Care cascades were compared between long-term residents and immigrant groups, including subgroups born in hepatitis B endemic countries. Stratified analyses and multivariable Poisson regression were used to identify drivers for cascade progression. Between January 1997 and December 2014, 2,014,470 persons were included, 50,475 with infections, of whom 30,118 were engaged with care, 11,450 initiated treatment, and 6554 continued treatment >1 year. Lifetime prevalence was estimated as 163,309 (1.34%) overall, 115,722 (3.42%) among all immigrants, and 50,876 (9.37%) among those from highly endemic countries. Compared to long-term residents, immigrants were more likely to be diagnosed (adjusted rate ratio [aRR], 4.55; 95% CI, 4.46, 4.63), engaged with care (aRR, 1.07; 95% CI, 1.04, 1.09), and initiate treatment (aRR, 1.09; 95% CI, 1.03, 1.16). CONCLUSIONS: In conclusion, immigrants fared well compared to long-term residents along the care cascade, having higher rates of diagnosis and slightly better measures in subsequent cascade stages, although intensified screening efforts and better strategies to facilitate linkage to care are still needed.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".