The Assessment of Sore Throat Following Nasotracheal Intubation
Bibliographic record
Abstract
In Response: We strongly disagree with the assertion that utilization of a postoperative analgesic protocol would have enhanced the interpretability of our results.1 One of the most important strengths of randomized clinical trials is that known and unknown determinants of outcome can be controlled.2,3 Since our trial was randomized, and all postoperative care (including pain management) was performed by clinicians effectively blinded to group allocation, there should be no systematic bias with respect to postoperative analgesic needs. On average, the analgesic requirements for a patient in the GlideScope® videolaryngoscopy group should be the same as the analgesic requirements for a patient in the direct laryngoscopy group, as their surgical procedures and all other factors determining postoperative analgesic needs should be equally and randomly distributed between the two groups. This obviates the need for any analgesia protocols, and it means that, as long as a type I error did not occur,4 any difference in the incidence of sore throat postoperatively can be ascribed solely to the intervention studied (i.e., GlideScope® videolaryngoscopy versus direct laryngoscopy). We do agree that the prespecified secondary outcome of moderate or severe sore throat incidence would ideally have been adjudicated by a fully blinded assessor. However, significant attention was devoted to this issue by requiring the assessor to adhere to a written script on the data collection sheet,5 minimizing the chance that investigator bias would influence this outcome. Philip M. Jones, MD Timothy P. Turkstra, MD Department of Anesthesia and Perioperative Medicine London Health Sciences Centre—University Hospital London, Ontario, Canada [email protected]
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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 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".