Guidelines for the Management of Vasa Previa
Bibliographic record
Abstract
OBJECTIVES: To describe the etiology of vasa previa and the risk factors and associated condition, to identify the various clinical presentations of vasa previa, to describe the ultrasound tools used in its diagnosis, and to describe the management of vasa previa. OUTCOMES: Reduction of perinatal mortality, short-term neonatal morbidity, long-term infant morbidity, and short-term and long-term maternal morbidity and mortality. EVIDENCE: Published literature on randomized trials prospective cohort studies, and selected retrospective cohort studies was retrieved through searches of PubMed or Medline, CINAHL, and the Cochrane Library, using appropriate controlled vocabulary (e.g., selected epidemiological studies comparing delivery by Caesarean section with vaginal delivery studies comparing outcomes when vasa previa is diagnosed antenatally vs.intrapartum) and key words (e.g. vasa previa). Results were restricted to systematic reviews, randomized control trials/controlled clinical trials, and observational studies. Searches were updated on a regular basis and incorporated into the guideline to October 1, 2008. Grey (unpublished) literature was identified through searching the websites of health technology assessment and health technology assessment-related agencies,clinical practice guideline collections, clinical trial registries, and from national and international medical specialty societies. VALUES: The evidence collected was reviewed by the Diagnostic Imaging Committee and the Maternal Fetal Medicine Committee of the Society of Obstetricians and Gynaecologists of Canada (SOGC) and quantified using the evaluation of evidence guidelines developed by the Canadian Task Force on Preventive Health Care. BENEFITS, HARMS, AND COSTS: The benefit expected from this guideline is facilitation of optimal and uniform care for pregnancies complicated by vasa previa. SPONSORS: The Society of Obstetricians and Gynaecologists of Canada.
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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 | 0.013 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 0.011 |
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".