Development of a management protocol for internal carotid artery injury during endoscopic surgery: A modified Delphi method and single-center multidisciplinary working group
Bibliographic record
Abstract
BACKGROUND: Intra-operative internal carotid artery (ICA) injury during transnasal endoscopic surgery is a potentially catastrophic event. Such an injury is life-threatening in the immediate setting, with a reported peri-operative mortality rate of 10%. Nasal packing, muscle patches, direct vessel closure, and endovascular techniques have been described as useful strategies for managing ICA bleeds. The objective of this study was to develop a formalized management protocol for intra-operative ICA injury through engagement with a multi-disciplinary panel. METHODS: A modified Delphi method including literature review, iterative rounds of stakeholder feedback, and expert panel discussions was used to develop a management protocol for ICA injury during transnasal endoscopic surgery. The 10-person multi-disciplinary panel included otolaryngologists, neurosurgeons, interventional neuroradiologists, anesthesiologists, and operating room nursing staff. RESULTS: After three rounds of stakeholder engagement with the expert panel, consensus was reached on important elements to include within the protocol. The protocol was divided in three categories: Alert, Control, and Transfer. 'Alert' focusses on early communication with anesthesia and nursing staff. 'Control' focusses on techniques to expose the injury and obtain hemostasis or adequate tamponade. Lastly, 'Transfer' describes the process of contacting neuro-interventional radiology and safely transferring the patient. A one-page handout of the protocol was developed for placement in operating theatres. CONCLUSION: Due to the life-threatening nature of ICA injury, it is imperative that endoscopic sinus and skull base surgeons are prepared to manage this complication. Using a modified Delphi method with a multidisciplinary expert panel, a protocol for management of intra-operative ICA injury was developed.
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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 | 0.227 | 0.172 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".