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Record W4410701079 · doi:10.1016/j.chest.2025.05.020

Ultrathin Bronchoscopy With Radial Endobronchial Ultrasound and Rapid On-Site Evaluation for the Diagnosis of Peripheral Pulmonary Lesions

2025· article· en· W4410701079 on OpenAlexaff
Erik Vakil, Marc Fortin, Anne V. Gonzalez, Laïla Samy, Alex Chee, Elaine Dumoulin, Marie Dvorakova, Christopher A. Hergott, Moosa Khalil, Noël Lampron, Paul MacEachern, Simon Martel, Benjamin Shieh, Mathieu Simon, Thibaud Soumagne, Tatjana Terzić, Alain Tremblay

Bibliographic record

VenueCHEST Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsUniversité LavalUniversité de MontréalMcGill University Health CentreUniversity of Calgary
Fundersnot available
KeywordsMedicineBronchoscopyEndobronchial ultrasoundPeripheralRandomized controlled trialRadiologyUltrasoundNuclear medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The routine use of CT imaging and lung cancer screening has increased the identification of peripheral pulmonary lesions (PPLs). Sampling may be needed for some nodules. Many new technologies are available to improve the diagnostic performance of bronchoscopy for the sampling of PPLs, but few comparative trials exist. The objective of this study was to compare the diagnostic performance of bronchoscopy with radial endobronchial ultrasound (rEBUS) using an ultrathin bronchoscope (BF-MP190F; Olympus) with a non-ultrathin bronchoscope and to compare the diagnostic performance of bronchoscopy with and without rapid on-site evaluation (ROSE). RESEARCH QUESTION: Does diagnostic performance differ between ultrathin and non-ultrathin bronchoscopes with rEBUS, and what impact does ROSE have on diagnostic performance of rEBUS? STUDY DESIGN AND METHODS: This pragmatic, multicenter, 2 × 2 factorial, randomized controlled trial involved adult patients with PPLs (mean diameter < 5 cm) and radiographic stage N0 disease referred for bronchoscopy. The study was powered to detect a 20% improvement in the primary outcome of difference in diagnostic yield (DY) between ultrathin and non-ultrathin bronchoscopes and between procedures with and without ROSE. Secondary outcomes included sensitivity for malignancy, complications, and procedure duration. RESULTS: Of 215 patients assessed, 186 patients were randomized and 181 patients were analyzed. Malignancy prevalence was 84%. No significant differences in DY or sensitivity for malignancy were found between non-ultrathin and ultrathin bronchoscopes: 65.6% vs 58.2% (difference, -7.3%; P = .36) and 84.3% vs 74.3% (difference, -10.0%; P = .21), respectively. Similarly, no significant differences were observed with or without ROSE: 60.4% vs 63.5% (difference, -3.1%; P = .76) and 80.3% vs 78.3% (difference, 2.0%; P = .83), respectively. INTERPRETATION: We could not identify a difference in DY or sensitivity for malignancy for the diagnosis of PPLs between an ultrathin bronchoscope and a non-ultrathin bronchoscope and between ROSE and no ROSE. The study was underpowered to detect smaller but potentially clinically meaningful differences. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov; No.: NCT03809169; URL: www. CLINICALTRIALS: gov.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.024
GPT teacher head0.314
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractno

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