Intraoperative Cuff Pressure Measurements of Endotracheal Tubes in the Operating Theater
Bibliographic record
Abstract
Abstract Background: Endotracheal tube (ETT) intracuff pressure (P INTRACUFF ) monitoring is not a mandatory part of daily anesthetic practice in many countries. Correct P INTRACUFF is required to ensure adequate ventilation, to prevent aspiration, and to avoid complications. The aim of this study was to objectively measure the P INTRACUFF in ETTs among patients from an Australian tertiary hospital to define the range of P INTRACUFF values seen in a setting without the use of routine objective monitoring. Patients and Methods: A prospective single-center audit of P INTRACUFF of 268 elective and emergency surgical patients undergoing general anesthesia with an ETT was performed. P INTRACUFF values were measured with a calibrated cuff manometer following the induction of anesthesia. Patient characteristics were compared between three patient groups of measured P INTRACUFF values: 20 cmH 2 O, 20–30 cmH 2 O, and >30 cmH 2 O. Results: To estimate the P INTRACUFF , only the auditory method was used among 66.0% of the patients, the tactile method was used in 18.3%, and the remainder used both or other methods. Following induction of anesthesia, the mean P INTRACUFF was 31.0 cmH 2 O (±standard deviation 16.4). The P INTRACUFF was <20 cmH 2 O for 54 patients (20.1%), and it exceeded 30 cmH 2 O for 103 patients (38.4%). Patients with a P INTRACUFF >30 cmH 2 O had a marginally higher body mass index (BMI) compared to patients with a P INTRACUFF <30 cmH 2 O ( P = 0.002). Patients with higher BMIs and smaller ETTs had higher cuff pressures. Conclusion: This study demonstrates that replacing subjective estimation methods with mandatory cuff pressure measurement can ensure that normal values are achieved during anesthesia.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".