Safety and efficacy of three‐dimensional versus two‐dimensional endoscopy in otolaryngology surgery and training: A systematic review
Bibliographic record
Abstract
OBJECTIVE: Three-dimensional (3D) endoscopy has been developed to provide depth perception to allow for improved visualisation during otolaryngology surgery. We conducted a systematic review to determine the surgical safety and efficacy of 3D endoscopy in comparison to two-dimensional (2D) endoscopy in performing otolaryngology procedures, and the role of 3D endoscopy as a training tool for novice otolaryngology surgeons. METHODS: Primary studies were identified through MEDLINE, Embase and Web of Science databases, which were searched for articles published through June 2022 that compared the outcomes of 2D and 3D endoscopy in otolaryngology surgical procedures or otolaryngology-relevant simulations. Candidate articles were independently reviewed by two authors. RESULTS: A total of 18 full-text articles met inclusion criteria for this study. In clinical trials (n = 8 studies, 362 subjects), there were no significant differences in performance time, intraoperative or postoperative complications with 3D endoscopes when compared to 2D. In simulation studies (n = 10 studies, 336 participants), 3D endoscopes demonstrated a decreased error rate (n = 5 studies) and shorter performance time (n = 3 studies). Studies also reported improved depth perception (n = 14 studies) and visualisation preference (n = 5 studies) with 3D over 2D systems. The 3D systems were found to have a shorter learning curve and better manoeuvrability among novice surgeons. CONCLUSION: 3D endoscopy showed equivalent safety and efficacy compared to 2D endoscopy in otolaryngology surgery. The improved depth perception and performance for novices using 3D endoscopes suggests the technology may be superior to 2D endoscopes as a training tool for otolaryngology surgeons.
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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 | 0.011 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".