Evaluation of Guidelines and Consensus on Ectopic Pregnancy Based by AGREE II Method
Bibliographic record
Abstract
Yiran Fu,1 Weishe Zhang,1,2 Qi Wang,1 Caihong Hu,1 Qi Li,3 Jingrui Huang1 1Department of Obstetrics, Xiangya Hospital Central South University, Changsha, People’s Republic of China; 2Hunan Engineering Research Center of Early Life Development and Disease Prevention, Changsha, People’s Republic of China; 3Reproductive Medicine Center, Xiangya Hospital Central South University, Changsha, People’s Republic of ChinaCorrespondence: Jingrui Huang, Department of Obstetrics, Xiangya Hospital Central South University, 87 Xiangya Road, Changsha, 410008, People’s Republic of China, Email jingruihuang@hotmail.com; huangjingrui@csu.edu.cnIntroduction: To evaluate the methodological quality of diagnosis and treatment guidelines/consensus related to ectopic pregnancy.Materials and methods: Use the “Appraisal of Guidelines and Research and Evaluation” (AGREE II) method to evaluate the differences among the guideline/consensus.Results: We appraised 9 clinical practice guidelines for ectopic pregnancy (9 clinical practice guidelines from 5 countries) including the United States, United Kingdom, Ireland, Canada, and China. The guidelines received the highest scores for clarity of presentation (82.72%) and lowest scores for editorial independence (30.56%). The comprehensive recommendations of the 7 guidelines were Grade B, the other 2 guidelines were Grade C.Conclusion: The overall quality of the ectopic pregnancy guidelines had room for improvement. It is recommended to supplement and improve the four fields of “independence”, “rigor”, “participants” and “application”, especially the “independence” and “application” fields.Keywords: guidelines, ectopic pregnancy, pelvic pain, AGREE II, clinical practice
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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 | 0.466 | 0.703 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.023 |
| Bibliometrics | 0.040 | 0.027 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".