Concordance Among National and International Obstetric Guidelines [ID 1447]
Bibliographic record
Abstract
INTRODUCTION: Recommendations for managing obstetric conditions vary across societies due to lack of strong evidence and differences in culture. This study both compares and, uniquely, quantifies the concordance of recommendations of obstetric guidelines between the United States and five other countries. METHODS: Five countries (Canada, the United Kingdom, France, Mexico, and Spain) were selected a priori for comparison. All obstetrics guidelines published by the American College of Obstetricians and Gynecologists (ACOG) from 2017 to 2023 were reviewed. Topics with published guidelines in all six countries were selected. American College of Obstetricians and Gynecologists recommendations were matched with corresponding recommendations from the five countries’ guidelines. Recommendations were categorized by guideline topic and area of care. Concordance scores for each pair of recommendations were provided by reviewers using a 0–10 scale (0=completely different; 10=exactly the same). Scores were compared by country, topic, and subtopic using the Kruskal–Wallis test with correction for multiple comparisons. RESULTS: We identified 70 ACOG guidelines, of which four topics (preterm birth, multifetal gestation, hypertensive disorders of pregnancy [HDP], and postpartum hemorrhage [PPH]) were addressed in the five selected countries’ guidelines. Concordance scores for each topic were significantly different among the countries (P<.0001). For HDP guidelines, concordance scores were significantly higher (P<.0125) for ACOG-Spain and ACOG-Mexico compared to ACOG-UK and ACOG-Canada, with similar trends in other topics. The PPH guidelines achieved the highest scores in all countries. CONCLUSIONS/IMPLICATIONS: This study provides a model for guideline concordance quantification, rather than qualitative comparison. Recommendation concordance was greater between ACOG and Spanish-speaking societies than ACOG-English- and French-speaking societies.
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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 | 0.036 | 0.171 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".