Acceptability, feasibility, equity and resource use for prenatal screening for chlamydia and gonorrhea: A systematic review
Bibliographic record
Abstract
Background: (NG). Methods: Information sources, including MEDLINE® All, Embase and Cochrane CENTRAL (January 2003-January 2021) electronic databases were searched for studies that assessed acceptability, feasibility, equity and resource use of screening for CT or NG in pregnant persons aged ≥12 years. The Risk of Bias Assessment Tool for Non-Randomized Studies was used for quality assessment and a narrative synthesis was prepared. Results: Of the 1,386 records identified, nine observational studies (approximately 5,000 participants) and three economic evaluations met the inclusion criteria. In general, pregnant persons and healthcare providers accepted screening. Most pregnant persons and partners supported universal testing for CT. Pregnant persons preferred non-invasive sampling methods. Inequities in feasibility (accessibility to screening) exist in certain populations. Studies have shown that targeted screening can miss cases. Screening all pregnant persons for CT has net cost savings compared to no screening. Limitations include not identifying eligible literature on acceptability of prenatal screening for NG among partners of pregnant persons and some studies with increased risk populations that restrict the generalizability of the findings highlighting areas for future research. Conclusion: Prenatal screening for CT and NG is generally acceptable among pregnant persons and healthcare providers. Evidence has shown that targeted screening can miss cases. The findings were included when updating PHAC's recommendations on prenatal screening for CT and NG. This work was presented at the Society of Obstetricians and Gynaecologists of Canada's 2024 Annual Clinical and Scientific Conference in Edmonton, Alberta.
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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 | 0.046 | 0.146 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".