Ergonomics in Endoscopic Sinus Surgery: Systematic Review of the Literature
Bibliographic record
Abstract
OBJECTIVE: To conduct a systematic review of reports on the ergonomic posture of the surgeon during endoscopic sinus surgery. STUDY DESIGN: Literature review. METHODS: Systematic review of the French- and English-language literature using PubMed from January 1970 to March 2004. Articles were divided into four categories: visualization through an endoscope or a videoendoscope, monitor position, sitting or standing position, and arm support. RESULTS: Endoscopic sinus surgery with direct vision through the endoscope is associated with faulty neck positioning and does not appear to bring any advantages in terms of surgical performance compared with vision via a video monitor. Low back pain and lower extremity complaints are commonly associated with the standing position. Spinal flexion seems more harmful than a straight posture. The preferred viewing angle for video monitors is a few degrees below the horizontal gaze line. An arm support can be beneficial because it is associated with minimization of neck, shoulder, and lumbar stress. CONCLUSION: We recommend (1) visualization via a television monitor instead of direct vision through an endoscope, (2) positioning the screen in direct axis with the surgeon's body and a few degrees below the horizontal line of gaze, (3) surgery in the seated position instead of the standing position, and (4) the use of an elbow support for the arm holding the endoscope.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".