ArticleThe Journal of thoracic and cardiovascular surgery2025
Characterizing a learning curve for robotic-assisted bronchoscopy: Analysis of skills acquisition in a high-volume academic center.
Article in The Journal of thoracic and cardiovascular surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Robotic-assisted transbronchial biopsy versus computed tomography-guided transthoracic needle biopsy for peripheral pulmonary lesions: a systematic review and meta-analysis of direct comparative studies.Journal of robotic surgery · 2026Pooled it
- Diagnostic performance and safety for robotic-assisted bronchoscopy in pulmonary nodules: a systematic review and meta-analysis.International journal of surgery (London, England) · 2025Pooled it
- Shape-sensing robotic-assisted bronchoscopy (ss-RAB) for peripheral pulmonary nodules: learning curve and diagnostic performance from an initial multicenter experience in China.Respiratory research · 2026Trial
- Predicting Diagnostic Success and Procedural Efficiency in Robotic Bronchoscopy Using Machine Learning.Diseases (Basel, Switzerland) · 2026Article
- Robotic-assisted bronchoscopy-guided cryobiopsy for the diagnosis of ground-glass opacity-predominant peripheral pulmonary nodules.Respiratory research · 2026Article
- Learning curve, safety and diagnostic yield of the GalaxyJournal of thoracic disease · 2026Article
- Fast Track Pathway for Lung Cancer: The Integration of ION Robotic-Assisted Bronchoscopy With Robotic Thoracic Surgical Resection.Surgical innovation · 2026Article
- Learning Shape-Sensing Robotic-Assisted Bronchoscopy after Mastering Advanced Image-Guided Navigation Bronchoscopy.Respiration; international review of thoracic diseases · 2026Article
- Multimodal innovations and clinical applications of Robotic-assisted bronchoscopy in pulmonary nodule diagnosis: a review of recent advances.BMC pulmonary medicine · 2025Review
- Can we rely on intraoperative bronchoscopic biopsies for surgical decision making? 78 single anesthetic robotic bronchoscopy to anatomic resections.JTCVS open · 2025Article
- Cone beam computed tomography for navigational bronchoscopy.Journal of thoracic disease · 2025Review
- Protocol for robotic-assisted bronchoscopy versus electromagnetic navigation bronchoscopy for the diagnosis of peripheral pulmonary nodules: a randomized trial (ARTICULAtE study).Journal of thoracic disease · 2025Article
- Robotic-assisted bronchoscopy-advancing lung cancer management.Frontiers in surgery · 2025Review
- Unlocking the depths: the evolution of robotic-assisted bronchoscopy.Frontiers in oncology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
objectiveShape-sensing robotic-assisted bronchoscopy is an emerging technology for the sampling of pulmonary lesions. We seek to characterize the shape-sensing robotic-assisted bronchoscopy learning curve at an academic center.
methodsShape-sensing robotic-assisted bronchoscopy procedures performed by 9 proceduralists at a single institution were analyzed. Cumulative sum analyses were performed to examine diagnostic sampling and procedure time over each operator's first 50 cases, with the acceptable yield threshold set to 73%.
resultsDuring the study period, 442 patients underwent sampling of 551 lesions. Each operator sampled 61 lesions (interquartile range, 60-63 lesions). Lesion size was 1.90 cm (interquartile range, 1.33-2.80 cm). The median procedure time for single-target cases decreased from 62 minutes during the first 10 cases to 39 minutes after case 40 (P < .001). The overall diagnostic yield was 72% (range, 58%-83%). Six of 9 operators achieved proficiency over the study period. An aggregated cumulative sum analysis of those who achieved competency demonstrated a steep improvement between lesions 1 and 21 and crossing of the competency threshold by lesion 25. Temporal analysis of yield-related lesion characteristics demonstrated that at approximately lesion 20, more challenging lesions were increasingly targeted, as evidenced by smaller target size, higher rates of unfavorable radial endobronchial ultrasound views, and a negative bronchus sign.
conclusionsSkills acquisition in shape-sensing robotic-assisted bronchoscopy is variable. Approximately half of proceduralists become facile with the technology within 25 lesions. After the initial learning phase, operators increasingly target lesions with more challenging features. Overall, these findings can inform certification and competency standards and provide new users with expectations related to performance over time.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.