Too Hot to Handle—Quantifying Temperature Variations in the Nasal Endoscope Ocular Assembly and Light Post
Bibliographic record
Abstract
Background Nasal endoscopes have transformed and improved the safety of intranasal and transnasal surgery. The heat they can produce may, however, reach dangerous levels for surgeons. Studies have not previously assessed the temperature of the nasal endoscope light post/ocular assembly (LP/OA)—where the surgeon usually holds the endoscope. Objective This study aims to understand the effect of different nasal endoscopes, light sources, and light cords on the LP/OA temperature. Methods We measured the temperature at the LP/OA of various rigid nasal endoscopes at multiple time intervals over 30 minutes, as well as after turning off the light source and irrigating the LP/OA with 10 mL of saline. Results The highest temperature recorded was 67.37°C at the LP/OA at 30 minutes, using a new light cord, older endoscope, and 184-hour xenon light bulb. In every trial, the temperature of the LP/OA continually increased until 30 minutes when the light source was turned off. Statistically significant ( P < .001) temperature differences were seen in trials using the older xenon light sources. The light-emitting diode light source was significantly cooler with an older light cord regardless of the age of the scope ( P = .003). Conclusion Endoscope temperatures during sinus surgery may reach potentially dangerous levels at the LP/OA region. These temperatures may be sufficient to cause second-degree burns during normal usage. Factors associated with higher endoscope temperatures include longer times with the light source on and xenon light bulbs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".