Randomized controlled trial comparing stylet‐free endoscopic ultrasound‐guided fine‐needle aspiration with 22‐G and 25‐G needles
Bibliographic record
Abstract
BACKGROUND AND AIM: Previous studies comparing endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) results with different gauge needles have all been carried out with the stylet in place and show no clear advantage to the larger 22-G needle. Similar data for stylet-free EUS-FNA (SF-EUS-FNA) are unavailable. The aim of the present study was to determine whether diagnostic yield and specimen adequacy is superior with the 22-G needle as compared to the 25-G needle. METHODS: All patients ≥ 18 years referred for solid-lesion EUS-FNA were eligible. Patients with suspected diagnosis of lymphoma, gastrointestinal stromal tumor, sarcoidosis, significant coagulopathy (international normalized ratio > 1.5 or platelets < 50000/mm(3)), use of clopidogrel within 7 days of EUS, and pregnancy were excluded. The two needles were compared regarding diagnostic yield, sample adequacy, bloodiness, ease of puncture, visibility, number of passes, failures, and complications. RESULTS: One hundred and twenty consecutive patients were included and 126 lesions were sampled. Sensitivity, specificity, positive predictive value and negative predictive value for the 22-G SF-EUS-FNA were 83%, 100%, 100% and 56%, respectively, and for the 25-G SF-EUS-FNA were 88.8%, 100%, 100% and 76.5%, respectively (P=NS). There were no significant differences between the 22-G and the 25-G FNA needles in sample adequacy, bloodiness, ease of puncture, FNA failure, visibility, number of passes and complications; and no significant differences between either needle were found in relation to lesion site. CONCLUSION: For SF-EUS-FNA, the larger 22-G needle offers no advantage over the smaller 25-G needle.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| 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".