ArticleBMJ open2025
Simulation-based training intervention using artificial intelligence to improve clinical bronchoscopy performance: a pre-postintervention study.
Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Recent advances in artificial intelligence across interventional pulmonology: a narrative review.Journal of thoracic disease · 2026Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesDoes a simulation-based training intervention with an artificial intelligence (AI) navigation system improve their clinical bronchoscopy performance? And can the AIs outcome measures be used to evaluate clinical performance?
designPre-postintervention study.
settingOdense University Hospital of Southern Denmark, pulmonary endoscopy suite.
participantsNine bronchoscopists (4 experienced, >500 bronchoscopies and 5 intermediates, 10-500 bronchoscopies). PRIMARY OUTCOME MEASURES: Diagnostic completeness (DC), structured progress (SP), procedure time (PT) and procedure efficiency (DC/PT).
resultsThe primary outcome measures showed no statistically significant difference between the pre- and postintervention bronchoscopies DC: 53% versus 59%, p=0.16, SP: 29% versus 32%, p=0.35 and PT: 219 s versus 181 s, p=0.22. The experienced outperformed the intermediates regarding DC: 73% versus 43%, p<0.001, SP: 47% versus 13%, p<0.001 and procedure efficiency: 533 s/full inspection versus 274 s/full inspection, p<0.001 but not on PT: 189 s versus 208 s, p=0.53).
conclusionsDC, SP and PT showed no statistically significant difference after a simulation-based training intervention. DC, SP and procedure efficiency differentiated between experienced and intermediate bronchoscopists and can be used to evaluate clinical bronchoscopy performance.
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