Comparison of 21‐gauge and 22‐gauge aspiration needle during endobronchial ultrasound‐guided transbronchial needle aspiration
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) has typically been performed using the 22 gauge (G) dedicated TBNA needle. Recently a new 21G TBNA needle has been introduced. The efficacy of using a larger gauge biopsy needle during EBUS-TBNA has not been reported. The purpose of this study was to compare the diagnostic yield and utility of 21G and 22G needles during EBUS-TBNA. METHODS: EBUS-TBNA was performed using both 21G and 22G needles. Cytological and histological findings were recorded for each samples obtained by an independent cytologist and pathologist. The cellularity and blood contamination were evaluated in the cytological samples. The quality of the histological core was evaluated by the amount of blood clots versus the actual tissue. Each factor was compared within two slides from the two different size needles. The diagnostic yield and the differences of the cytology and histology were analysed. RESULTS: The evaluation of 45 lesions by EBUS-TBNA revealed that tumour cells were equally detected by both 21G and 22G needles. Two patients of adenocarcinoma were histologically diagnosed only by the 21G needle. Although histological structure was better preserved in five lesions collected by the 21G needle, there was more blood contamination with the 21G needle (P < 0.0001). CONCLUSIONS: There were no differences in the diagnostic yield between the 21G and 22G needles during EBUS-TBNA. The preserved histological structure of the samples obtained by the 21G needle may be useful for the diagnosis of mediastinal and hilar adenopathy of unknown aetiology which may be a challenge with the 22G 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 | 0.004 | 0.019 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".