A Prospective, Multicenter Evaluation of Safety and Diagnostic Outcomes With Robotic-Assisted Bronchoscopy
Bibliographic record
Abstract
BACKGROUND: It remains challenging to safely and reliably biopsy peripheral pulmonary lesions (PPLs). Robotic-assisted bronchoscopy (RAB) is gaining adoption for navigation to PPLs. However, evidence from large studies remains limited. RESEARCH QUESTION: What is the clinical safety, navigational success, and diagnostic yield of RAB for biopsy of PPLs in a broad range of patients in a real-world setting? STUDY DESIGN AND METHODS: This multicenter, prospective, single-arm study enrolled patients aged > 21 years with 8- to 50-mm lung lesions requiring bronchoscopic diagnosis. The primary end point was the incidence of the following device- or procedure-related events: (1) pneumothorax requiring intervention; (2) bleeding requiring intervention; or (3) respiratory failure. Secondary end points included individual components of the primary end point, procedure time, pneumothoraces, radial probe endobronchial ultrasound confirmation, conversion to an alternative biopsy procedure, complications, and diagnostic yield. RESULTS: Among 715 patients at 21 sites, 679 met study criteria and underwent RAB (mean age 68.7 years; 55.4% female; 86.5% White; 77.5% with current/past tobacco use). Mean (range) lesion size was 20.9 (7.0-63.0) mm; median (interquartile range) distance from the pleural surface was 5 (0-16) mm. Most lesions were solid (n = 587 [86.6%]) and within the outer two-thirds of the lung (n = 593 [87.5%]). The primary end point was observed in 26 (3.8%) patients (19 pneumothorax, 7 bleeding, and 0 respiratory failure). Users reported that RAB reached the lesion in 670 (98.7%) of 679 cases, and lesion location was confirmed with radial probe endobronchial ultrasound in 607 (91.7%) of 662 cases; sampling through the bronchoscope was performed in 675 (99.4%) of 679 cases. Prevalence of malignancy was 64.1% through 12 months. Adjudicated diagnostic yield was 61.6% when calculated with the American Thoracic Society/American College of Chest Physicians (CHEST) definition for strict reporting criteria. Sensitivity for malignancy was 78.8%. INTERPRETATION: This multicenter prospective study of RAB-to our knowledge, the largest to date-showed that RAB-guided sampling of PPLs is safe and compares favorably to results from sizable non-robotic bronchoscopy studies. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov; No.: NCT04182815; URL: www. CLINICALTRIALS: gov.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".