Prenatal hepatitis C screening, diagnoses, and follow-up testing in British Columbia, 2008–2019
Bibliographic record
Abstract
OBJECTIVE: Current guidelines in British Columbia recommend prenatal screening for hepatitis C antibodies (anti-HCV) if risk factors are present. We aimed to estimate frequency of prenatal anti-HCV testing, new diagnoses, repeated and follow-up testing among BC women. METHODS: BC Centre for Disease Control Public Health Laboratory data estimated the number of BC women (assigned female at birth or unknown sex) aged 13-49 who received routine prenatal serological screening (HIV, hepatitis B, syphilis and rubella) from 2008-2019. Anti-HCV tests ordered the same day as routine prenatal screens were considered prenatal anti-HCV tests. Assessment of follow-up was based on HCV RNA and/or genotype testing within one year of new prenatal anti-HCV diagnoses. RESULTS: In 2019, 55,202 routine prenatal screens were carried out for 50,392 BC women. Prenatal anti-HCV tests increased significantly, from 19.6% (9,704/49,515) in 2008 to 54.6% (27,516/50,392) in 2019 (p<0.001). New prenatal anti-HCV diagnoses (HCV positive diagnoses at first test or seroconversions) declined from 14.3% in 2008 to 10.1% in 2019. The proportion of women with new prenatal anti-HCV diagnoses that were a result of a first HCV test declined from 0.3% (29/9,701) in 2008 to 0.03% (8/27,500) in 2019. For women known to be anti-HCV positive at the time of prenatal screening, the proportion who had a prenatal anti-HCV test increased from 35.6% in 2008 to 50.8% in 2019. CONCLUSION: Prenatal anti-HCV testing increased substantially over the study period. However, new HCV diagnoses remained relatively stable, suggesting that a considerable proportion of BC women with low or no risk are being screened as part of prenatal care. The vast majority of women with new HCV diagnoses receive appropriate follow-up HCV RNA and genotype testing, which may indicate interest in HCV treatment. These findings contribute to the discussion around potential for prenatal anti-HCV screening in an effort to eliminate HCV.
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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 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.000 | 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".