Endobronchial Ultrasound-guided Transbronchial Needle Aspiration With a 19-G Needle Device
Bibliographic record
Abstract
BACKGROUND: Endobronchial ultrasound (EBUS)-guided transbronchial needle aspiration is a well-established first-line minimally invasive modality for mediastinal lymph node sampling. Although results are excellent overall, the technique underperforms in certain situations. We aimed to describe our results using a new 19-G EBUS-guided transbronchial needle aspiration device to determine safety and feasibility of this approach. METHODS: We completed a retrospective chart review of all cases performed to the time of data analysis at each of 3 study sites. RESULTS: A total of 165 procedures were performed with a total of 297 individual lymph nodes or lesions sampled with the 19-G device by 10 bronchoscopists. Relatively large targets were selected for sampling with the device (mean lymph node size: 20.4 mm; lung lesions: 33.5 mm). A specific diagnosis was obtained in 77.3% of cases with an additional 13.6% of cases with benign lymphocytes, for a procedural adequacy rate of 90.9%. Procedure sample adequacy was 88.6% in suspected malignant cases, 91.0% in suspected sarcoidosis/lymphadenopathy cases, and 85.7% of cases with suspected lymphoma. On a per-node basis, a specific diagnosis was noted in 191/280 (68.2%) of samples, with an additional 61 showing benign lymphocytes for a per-node sample adequacy rate of 90%. One case (0.6%) of intraprocedure bleeding was noted. CONCLUSIONS: A new flexible 19-G EBUS needle was successfully and safely applied in a large patient cohort for sampling of lung and enlarged mediastinal lesions with high diagnostic rates across clinical indications.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".