The Intubating Laryngeal Mask Airway After Induction of General Anesthesia Versus Awake Fiberoptic Intubation in Patients with Difficult Airways
Bibliographic record
Abstract
UNLABELLED: We performed the current study to compare tracheal intubation (TI) using awake fiberoptic intubation (AFOI) and TI using the intubating laryngeal mask airway (ILMA) in patients with difficult airway. Our hypothesis was that patients with difficult airways could be safely intubated after induction of anesthesia using the ILMA. After ethics approval and informed consent, 38 patients who were identified to have difficult airways were randomly assigned to AFOI or TI using the ILMA. Patients in the AFOI group had the usual sedation and airway topicalization. Patients in the ILMA group were induced with propofol for ILMA insertion and succinylcholine for TI. The first TI attempt was done blindly via the ILMA and all subsequent attempts were performed with fiberoptic guidance. All patients in the ILMA group were successfully ventilated. Successful TI was achieved in all patients in both groups. However, in 10% of the patients in the ILMA group, TI was achieved by a second anesthesiologist who was more experienced with the use of the ILMA. In a postoperative questionnaire, patients in the ILMA group were more satisfied with their method of TI (P < 0.01). The ILMA is a useful device in the management of patients with difficult airways and may be a valuable alternative to AFOI when AFOI is contraindicated or in the patient with the unanticipated difficult airway. IMPLICATIONS: The intubating laryngeal mask airway is a useful device in the management of patients with difficult airways and may be a valuable alternative to awake fiberoptic intubation (AFOI) when AFOI is contraindicated or in the patient with the unanticipated difficult airway.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".