Minimal Illumination for Direct Laryngoscopy and Intubation in Different Ambient Light Settings
Bibliographic record
Abstract
OBJECTIVES: This study sought to investigate the minimal laryngoscope illumination required for proper laryngoscopy and intubation in different ambient light settings as determined by paramedics. METHODS: Paramedics qualified to intubate patients in the field were recruited to intubate a cadaver embalmed with a minimal fixation technique designed to maintain tissue integrity. All paramedic participants intubated the cadaver under three different ambient light settings representing possible out-of-hospital settings: an outdoor night setting, an indoor setting, and an outdoor day setting. Paramedics were asked to determine the minimal illumination required for intubation of the cadaver under each of these settings. RESULTS: Twenty-three paramedics participated in the study. The mean (+/-SD) minimal illumination required for intubation was 39.1 (+/-35.4) lux at the night setting, 92.5 (+/-57.3) lux at the indoor setting, and 209.7 (+/-117.4) lux at the day setting. There was a statistically significant difference in minimal illumination required between each of the three light settings (p < 0.0001). CONCLUSIONS: Minimal illumination requirements in the out-of-hospital setting may be lower than previously recommended. Ambient light intensity affects this minimal illumination requirement, with brighter ambient light conditions necessitating more laryngoscope light output. Further studies assessing out-of-hospital laryngoscope illumination should consider ambient light conditions.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".