P3.197 Uptake and Case Detection of Prenatal Screening of Maternal Syphilis, HIV and Hepatitis C, in British Columbia, Canada, 2007–2011
Bibliographic record
Abstract
Background In British Columbia (BC), Canada, (pop 4.6 million), prenatal screening for rubella, syphilis, and HIV is routinely recommended while hepatitis C (HCV) screening is based on risk criteria. We determined testing uptake and case detection rates at prenatal screening for these important perinatally transmissible pathogens. Methods We identified prenatal specimens for women aged 16–45 years between 2007–11 from the BC Public Health Reference Microbiology Laboratory and calculated the proportion of unique women screened for rubella, syphilis, HIV, and HCV per calendar year. Records were linked to laboratory surveillance data, permitting inclusion of prior testing history for HIV and HCV, to determine if detected cases were newly diagnosed at screening (new diagnoses/100,000) or a previously identified case. HIV and HCV prevalence were defined as all new and prior diagnoses among screened women (prevalence/100,000). Results Of the 233,203 women who underwent one or more prenatal screening in the study period, 96.9% were screened for rubella, 93.3% for syphilis, 93.8% for HIV, and 21.5% for HCV. Over 5 years, syphilis, HIV, and HCV screening increased by 4.4%, 4.3%, and 8.3%, respectively. The overall syphilis diagnosis rate was 15.4/100,000 and decreased over the study period. For HIV, the overall new diagnosis rate and prevalence was 5.1 and 45.9/100,000 respectively; for HCV the corresponding values were 82.8 and 551.5/100,000. The new diagnosis rates for HIV and HCV decreased over the study period while there were no significant changes in prevalence. Conclusion In BC, prenatal screening for syphilis and HIV is high and improving annually with declining diagnosis rates. Previous research in BC suggests HCV prevalence in pregnant women in BC is underestimated based on risk-based screening. The low HCV screening rates and high prevalence observed in our study corroborates the need to consider broader prenatal HCV screening.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".