A Comparison of Laryngospasm in "No Touch" and "Head Down Deep Extubation": A Randomized Clinical Trials
Bibliographic record
Abstract
Background: Tonsillectomy and adenotonsillectomy are simple surgical procedures that can cause laryngospasm as complications which blocks airflow causing serious issues. The laryngospasm incidence decreases in patients undergoing deep extubation. Present study aimed to compare laryngospasm in innovative method of head down deep extubation with No Touch method. Methods: Forty-two patients were enrolled in the study in (23 females and 19 males) between the ages of 5 up to 15 who were referred for tonsillectomy or adenotonsillectomy. The patients were divided into two randomized No Touch (n=21) and head down deep extubation (n=21) intervention groups according to permuted block randomization. All patients received standard general anesthesia. The first group received the no-touch extubation and the second group received head down deep extubation method. The duration of surgery, Time interval between the injection of reverse drugs and the return of spontaneous breathing (TRDRSB), time interval between anesthesia drug withdrawal and extubation (TIDWE), SPO2, incidence of laryngospasm, and cough were recorded and graded according to their severity at 0, 5, 10, 15 minutes and 2 hours after extubation, respectfully. Results: The age, weight, gender and duration of surgery, TRDRSB was not statistically different between the two groups but TIDWE showed a significant difference between groups (P<0.001). The SPO2 levels in 0, 5, 10, 15 minutes, and 2 hours after surgery were not significantly different between the “no touch” and “head down deep extubation” groups as well as the severity of coughing and laryngospasm. However, the rate of laryngospasm and cough in "No touch" group was higher than " head down deep extubation " group. Conclusion: HDDE is an innovative technique that it seems in comparison to No Touch method can reduce the incidence of laryngospasm. However, further comprehensive trials are needed to confirm these findings.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".