Comparison of the Baska <sup>®</sup> mask with the single‐use laryngeal mask airway in low‐risk female patients undergoing ambulatory surgery
Bibliographic record
Abstract
We compared the Baska(®) mask with the single-use classic laryngeal mask airway (cLMA) in 150 females at low risk for difficult tracheal intubation in a randomised, controlled clinical trial. We found that median (IQR [range]) seal pressure was significantly higher with the Baska mask compared with the cLMA (40 (34-40 [16-40]) vs 22 (18-25 [14-40]) cmH2O, respectively, p < 0.001), indicating a better seal. In contrast, the first time success rate for insertion of the Baska mask was lower than that seen with the cLMA (52/71 (73%) vs 77/99 (98%), respectively, p < 0.001). There were no differences in overall device insertion success rates (78/79 (99%) vs 68/71 (96%), respectively, p = 0.54). The Baska mask proved more difficult to insert, requiring more insertion attempts, taking longer to insert and had higher median (IQR [range]) insertion difficulty scores (1.6 (0.8-2.2 [0.1-5.6]) vs 0.5 (0.3-1.4 [0.1-4.0]), respectively, p < 0.001). There was also an increased rate of minor blood staining of the Baska mask after removal, but there were no differences in other complication rates, such as laryngospasm, or in the severity of throat discomfort. In conclusion, in clinical situations where the seal with the glottic aperture takes priority over ease of insertion, the Baska mask may provide a useful alternative to the cLMA.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".