Time Flow Study to Assess Opportunities to Improve Efficiency in Endoscopic Tympanoplasty
Bibliographic record
Abstract
BACKGROUND: To characterize the workflow during transcanal totally endoscopic tympanoplasty by recording the time and instrumentation used for different steps in the procedure. This analysis aims to identify aspects of instrumentation and surgical technique that could be modified to improve surgical efficiency. METHODS: Thirty-one endoscopic tympanoplasty procedures were observed at a single academic center. Patient age ranged from 2.7 to 17.8 years. The procedure was separated into distinct steps. The duration in minutes and the instruments used were recorded by an independent observer. RESULTS: Raising the tympanomeatal flap (median 9.82 minutes) and positioning the graft and replacing the flap (median 9.13 minutes) took significantly longer than all other steps (P < .05, Wilcoxon method). Teaching a trainee significantly increased step duration by a total of 32.8 minutes (P < .05, Wilcoxon method). There was no correlation between age of the patient, side of the ear, surgical technique, or graft type, and duration of surgery. Suction instruments with a functional tip (dissector or knife tip) were most commonly used to dissect and maneuver soft tissue while maintaining the surgical field clear of blood. CONCLUSION: As elevation of the tympanomeatal flap and graft placement are the most time-consuming steps in endoscopic tympanoplasty, especially for surgical trainees, surgical efficiency could most dramatically be enhanced by modification of instrumentation or technique to facilitate these steps. Modification of simpler steps such as hair trimming and ear canal packing have less potential for shortening surgical duration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".