To guide or not to guide: A randomized study on the use of needle guide for chorionic villus sampling training
Bibliographic record
Abstract
INTRODUCTION: Chorionic villus sampling (CVS) is an invasive prenatal diagnostic procedure used to detect fetal genetic anomalies. CVS is increasingly replaced by noninvasive prenatal testing (NIPT). As a consequence, maintaining procedural skills among trainees has become challenging. Despite this, optimal training methods for CVS remain uncertain, particularly regarding whether techniques involving context variation, needle guides, or freehand approaches yield superior skill acquisition and performance. This randomized controlled study aimed to evaluate these training strategies, specifically focusing on skill transfer among novices in ultrasound-guided CVS. MATERIAL AND METHODS: In this randomized controlled trial, 101 ultrasound novices were allocated into three training groups: context variation, needle-guided, and freehand techniques. Participants completed a 1-h training session performing ultrasound-guided needle punctures on ballistic gel models. The context variation group alternated between needle-guided and freehand techniques with varying visual constraints. After training, each participant completed four CVS transfer tests using a CVS simulator manikin, involving two needle-guided and two freehand procedures, with differing placental positions. Blinded expert raters evaluated participant performance using a scoring system with established validity evidence. Statistical analyses included linear mixed-effect models, ANOVA, and Pearson correlation coefficients. RESULTS: There were no significant differences in overall performance scores among the three training groups (F[2, 92.0] = 0.06, p = 0.94). However, performance significantly improved during transfer tests when participants used a needle guide, irrespective of their initial training method (F[1, 266.0] = 49.5, p < 0.001). Specifically, using a needle guide significantly enhanced scores for pre-puncture ultrasound assessment (t[370] = -4.1, p < 0.001), insertion site selection (t[370] = -3.8, p < 0.001), sampling technique (t[370] = -5.8, p < 0.001), and overall procedural performance (t[370] = -5.8, p < 0.001). CONCLUSIONS: Training approaches, including needle-guided, freehand, and context variation techniques, did not differ significantly in their effect on learning ultrasound-guided CVS. However, the consistent improvement in procedural performance with needle-guided techniques suggests that incorporating needle guides into CVS training could promote safer practice for novice learners, particularly as clinical training opportunities become increasingly scarce.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".