Current practice for awake fibreoptic intubation – asking the right questions
Notice bibliographique
Résumé
We would like to thank Drs. Murphy and Howes for their thoughtful editorial, which accompanied our recent study of awake fibreoptic intubation (AFOI) practice 1, 2, and for recognising the training opportunities that our institution provides. However, rather than alluding to unanswered questions in our data, we are concerned that they have applied conjecture and inference to ask the wrong questions about AFOI. Murphy and Howes assert that ‘placing particular emphasis on any individual component … risks losing sight of the bigger picture’. Just as pilots emphasise training on the most critical phases of flight, so too must clinicians. Efforts must be made to train for complex, procedural skills as well as considering the important, but non-specific, ‘bigger picture’. The question is – how can we excel at all components of the airway management pathway? The simple answer is self-evident in our data: training. Murphy and Howes cite an editorial 3 written by one of our authors. Our prospective study (rather than audit, as there are no accepted standards) has demonstrated that AFOI is associated with low morbidity and a high success rate, particularly when appropriate training is undertaken. Although we do not state that AFOI should be the ‘gold standard’, our data clearly highlights that AFOI has a valuable role to play in the management of the difficult airway. Had Drs. Murphy and Howes put Ahmad and Bailey's editorial into context 3, they would have understood that training is recommended for AFOI, and when not undertaken, AFOI should be considered a specialist skill. Performed by appropriately trained and competent clinicians, the utility of a technique that has been part of anaesthetic practice for 50 years is difficult to refute. The question here, then, is: who should train in AFOI? We thank the authors for contextualising our prospective data with retrospective results collected in the USA 4 and Canada 5. Retrospective data points can be under-reported, and the low complication rates reported by Joseph et al. 4 could be an inaccurate representation of their true incidence. Moreover, the comparable complication rates provided by Law et al. 5 might also be under-reported. It would be interesting to know what prospective data from North America shows. Comparing our results with data from unsedated, healthy course delegates (a self-selected group of subjects) is misleading 6. The immediate complication rate in healthy volunteers was greater than we found in comorbid patients with complex airway pathology (19.5% vs. 11% respectively), and so the co-administration of sedation does not necessarily correlate with increased risk. Interestingly, the Difficult Airway Society has recently commissioned national guidelines on the performance of AFOI. Whether sedation will be recommended as standard practice remains to be seen. The question that needs answering here is: does sedation increase or decrease the safety of performing AFOI? We agree that there is insufficient evidence recommending high-flow nasal oxygen (HFNO) for all AFOIs. Murphy and Howes infer our data do not demonstrate that HFNO increases safety, and point to an interesting study showing that HFNO increases the time to intubation during rapid sequence induction (RSI) without increasing desaturation rates, despite the primary aim of RSI being to rapidly secure the airway 7. We believe that this data mirrors ours; despite increased sedation, we found no difference in the rates of desaturation. This is a positive finding for HFNO techniques, and should be viewed as improving the evidence-base for administering HFNO, but requires further research.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».