A Delphi Consensus-Based Chronic Pelvic Pain Standardized Ultrasound Approach
Bibliographic record
Abstract
Objective: To develop a standardized, consensus-based international ultrasound approach on the elements that should be included in the initial ultrasound assessment of women with CPP that can be, in future, applied in clinical practice. Methods: A Delphi survey was conducted with an international panel of experts in CPP and ultrasound, selected for their clinical and scientific experience in the subject. Three rounds of questions were carried out to assess the main parameters that should be included in the ultrasound reporting template. For variables to be included in the template, a priori consensus criteria were used to reach agreement. Results: Of the 86 experts invited, 21 completed the final (third) round of the Delphi process. Experts represented North America, South America, Europe, and Australia. The final CPP ultrasound approach and reporting template established by the experts’ consensus contains 1) the assessment of the quality of the examination, 2) the necessary equipment, 3) the regions to be evaluated, and 4) elements that must be included in the exam. Conclusion: Based on consensus methodology, we propose a standardized international ultrasound approach on the elements that should be included in the initial ultrasound assessment of women with CPP. Whilst it requires validation, this tool may serve to standardize the performance of the ultrasound for the indication of CPP, enhancing the evaluation of the broad differential diagnostic and the clinical applicability.
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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 | 0.222 | 0.169 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".