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A Unified Methodological Framework for Vestibular Schwannoma Research
Published on: June 20, 2017
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Generating Operative Workflows for Vestibular Schwannoma Resection: A Two-Stage Delphi's Consensus in Collaboration
Hugo Layard Horsfall1,2, Danyal Z Khan1,2, Justin Collins3
1Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom.
Journal of Neurological Surgery. Part B, Skull Base
|September 6, 2023
Summary
This study codifies the translabyrinthine approach for vestibular schwannoma resection into five phases and 57 steps. This operative workflow aids surgical training and understanding of variations in vestibular schwannoma surgery.
Area of Science:
- Neurosurgery
- Skull Base Surgery
- Otolaryngology
Background:
- Operative workflows systematically categorize surgical procedures.
- Understanding surgical variation is crucial for education and training.
- This study focuses on the translabyrinthine approach for vestibular schwannoma resection.
Purpose of the Study:
- To present a codified operative workflow for the translabyrinthine approach to vestibular schwannoma resection.
- To establish a standardized framework for surgical education and analysis.
- To provide a foundation for future research in vestibular schwannoma surgery.
Main Methods:
- A mixed-method consensus process involving literature review and Delphi consensus.
- Collaboration with the British Skull Base Society (BSBS).
- Multiple rounds of Delphi consensus until data saturation and over 90% agreement.
Main Results:
- Seventeen experienced skull base surgeons participated.
- A 100% response rate was achieved across Delphi rounds.
- The translabyrinthine approach was codified into five phases and 57 unique steps.
Conclusions:
- A national, consensus-derived operative workflow for the translabyrinthine approach to vestibular schwannomas is presented.
- The workflow includes operative steps, instruments, technique errors, and event errors.
- This codified approach serves as foundational research for AI applications and comparative surgical studies.
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