Removal of the stylet from the tracheal tube: effect of lubrication
Bibliographic record
Abstract
We compared the work needed to retract a non-lubricated and a lubricated stylet from a tracheal tube over 24 h. Stylets were lubricated with sterile water, silicone fluid, lidocaine spray, lidocaine gel, MedPro(®) lubricating gel or Lacri-Lube(®). The mean (SD) work in joules needed to retract the stylet by 5 cm from the tracheal tube was recorded immediately (time 0), at 5 and 30 min and at 1, 3 and 24 h. At time 0 lubrication with sterile water (0.53 (0.09); p = 0.001), silicone fluid (0.43 (0.10); p < 0.001), lidocaine gel (0.60 (0.15); p = 0.01) and MedPro gel (0.57 (0.07); p = 0.005), were better than no lubrication (0.94 (0.28)). Where a tracheal tube is pre-loaded with a stylet for use at an indeterminate time, silicone fluid was the best choice of lubricant as it performed consistently well up to 24 h. At 24 h only silicone fluid (0.49 (0.01)) outperformed no lubrication (0.77 (0.24); p = 0.04).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".