Evaluation of an Emergency Prevention Program for Mother to Child Transmission of HIV in British Columbia
Bibliographic record
Abstract
INTRODUCTION: The objective of this study was to evaluate a province-wide program designed to identify HIV infection accurately and to prevent mother to child transmission among high-risk pregnant women of unknown serostatus. METHODS: Between 2000 and 2007, 347 high-risk women were identified through the Prevention of Mother to Child Transmission (PMTCT) program implemented in 27 hospitals across British Columbia. Rates of HIV transmission and details of the implementation of prophylaxis kits were assessed. RESULTS: Of the 346 high-risk mother-infant pairs identified and included in the provincial program, 35.4% of the mothers and 95.7% of infants received antiretroviral therapy for prevention of vertical transmission. Of 309 pairs who subsequently underwent HIV testing, five mothers were found to be HIV positive, an infection rate of 16.2/1000 in this cohort; the overall rate in BC is 0.68/1000 births. One of the five infants born to an HIV positive mother was infected with HIV. DISCUSSION: The program was successful in identifying a subgroup of pregnant women at increased risk of HIV infection; however, mother to child transmission occurred in one of five cases (20%). To reduce the risk of mother to child HIV transmission in BC to the lowest possible level, additional strategies such as increasing uptake of prenatal screening and point-of-care testing in labour and delivery may need to be explored.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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".