Consensus on Training and Assessment of Competence in Performing Chorionic Villus Sampling and Amniocentesis: An International Delphi Survey
Bibliographic record
Abstract
INTRODUCTION: The aim of this study was to obtain expert consensus on the content of a curriculum for learning chorionic villus sampling (CVS) and amniocentesis (AC) and the items of an assessment tool to evaluate CVS and AC competence. METHODS: We used a 3-round iterative Delphi process. A steering committee supervised all processes. Seven international collaborators were identified to expand the breadth of the study internationally. The collaborators invited fetal medicine experts to participate as panelists. In the first round, the panelists suggested content for a CVS/AC curriculum and an assessment tool. The steering committee organized and condensed the suggested items and presented them to the panelists in round 2. In the second round, the panelists rated and commented on the suggested items. The results were processed by the steering committee and presented to the panelists in the third round, where final consensus was obtained. Consensus was defined as support by more than 80% of the panelists for an item. RESULTS: Eighty-six experts agreed to participate in the study. The panelists represented 16 countries across 4 continents. The final list of curricular content included 12 theoretical and practical items. The final assessment tool included 11 items, systematically divided into 5 categories: pre-procedure, procedure, post-procedure, nontechnical skills, and overall performance. These items were provided with behavioral scale anchors to rate performance, and an entrustment scale was used for the final overall assessment. CONCLUSION: We established consensus among international fetal medicine experts on content to be included in a CVS/AC curriculum and on an assessment tool to evaluate CVS/AC skills. These results are important to help transition current training and assessment methods from a time- and volume-based approach to a competency-based approach which is a key step in improving patient safety and outcomes for the 2 most common invasive procedures in fetal medicine.
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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 | 0.117 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".