Initial Clinical Experience With a Flexible Peripheral 21-G Needle Device
Bibliographic record
Abstract
BACKGROUND: Bronchoscopic techniques can be used to safely sample peripheral lung nodules (PLN), and transbronchial needle aspiration (TBNA) can further increase the diagnostic yield. Current needle devices not necessarily designed for this indication have limitations. We report our initial experience with a new flexible nitinol peripheral TBNA needle specifically designed for such sampling. METHODS: Retrospective case review describing the first clinical cases performed with a commercially available 21-G peripheral TBNA device in 4 centers. RESULTS: Eleven different operators performed 40 procedures for PLNs of a mean size of 35.1 mm (±18), and located 18.8 mm (±18.8) from the pleural surface, with 50% of them being present in the upper lobes. Bronchoscopists rated the use of the needle as good or excellent for reaching the PLN in 27/30 (90%) of cases. The TBNA sample was diagnostic in 18/40 cases (45%) overall and in 18/28 (64.3%) of cases where a diagnosis on bronchoscopy was possible. No episode of pneumothorax, significant bleeding, hypoxemia, escalation of care, or other complications were noted. CONCLUSION: Our initial experience with a novel peripheral TBNA device appears safe and effective, and may offer technical advantages over other available devices. Additional studies will be required to confirm the role of this device in the approach to bronchoscopic sampling of parenchymal lung nodules.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".