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Enregistrement W2985030720 · doi:10.1111/anae.14882

Redefining endpoints with apnoeic oxygenation in pregnancy – better the devil you know than the devil you don't?

2019· letter· en· W2985030720 sur OpenAlexaff
W. Shippam, Roanne Preston, J. Douglas, Anthony Chau

Notice bibliographique

RevueAnaesthesia · 2019
Typeletter
Langueen
DomaineMedicine
ThématiqueAirway Management and Intubation Techniques
Établissements canadiensB.C. Women's Hospital & Health Centre
Organismes subventionnairesnon disponible
Mots-clésOxygenationMedicineTidal volumeAnesthesiaFraction of inspired oxygenOxygenVentilation (architecture)Respiratory systemInternal medicineMechanical ventilationChemistry

Résumé

récupéré en direct d'OpenAlex

We thank Tanna and Saha 1 for their interest in our study and for raising a thought-provoking discussion about the potential for lowering end-tidal oxygen fraction endpoint in obstetric patients when using high-flow nasal oxygenation. The current recommended pre-oxygenation target of end-tidal oxygen fraction ≥ 0.9 pre-dates the advancement of high-flow nasal oxygenation 2. This specific value originated from the idea that it is desirable to reduce the risk of hypoxia by providing a reservoir of 95% oxygen assuming an obligatory 5% alveolar carbon dioxide, which corresponds to an end-tidal oxygen fraction of 0.9 according to an earlier study by Berry et al. 3. In our study, after 3 min of tidal volume breathing, there were significantly fewer numbers of parturients who were able to achieve the pre-oxygenation target of an end-tidal oxygen fraction ≥ 0.9 in the high-flow nasal oxygenation group compared with the standard flow rate facemask group (47% vs. 85%, respectively). If we had used a lower target of end-tidal oxygen fraction ≥ 0.8 as a primary endpoint, the high-flow nasal oxygenation group would have achieved a substantially greater proportion above the threshold (88% high-flow nasal oxygenation vs. 95% facemask), altering the conclusion of the study 4. Our findings, along with a number of associated studies, have consistently found that not all pregnant women can achieve end-tidal oxygen fraction ≥ 0.9 after 3 min of pre-oxygenation 5, 6. In fact, Chiron et al. reported that even with standard facemask pre-oxygenation, 25% of third trimester healthy pregnant women could not attain the target of end-tidal oxygen fraction ≥ 0.9 following 3 min of tidal volume breathing or eight deep breaths 5. As such, we agree with Tanna and Saha that the threshold of end-tidal oxygen fraction ≥ 0.9 should be re-examined. Indeed, reducing the endpoint of pre-oxygenation would mean a potentially shortened time to delivery of the fetus. Also, using a simple theoretical model, the additional loss in safe apnoea time by lowering the threshold of end-tidal oxygen fraction from 0.9 to 0.8 may not be clinically significant, especially when arterial desaturation rate can be slowed by apnoeic oxygenation (Table 1). However, just as it is difficult to justify the strict need for end-tidal oxygen fraction ≥ 0.9, the paucity of compelling evidence demonstrating reliability of apnoeic oxygenation in obstetric patients makes it just as difficult to challenge the status quo and adopt a lower endpoint. 1. FRC oxygen (ml) a. at FETO2 0.8 = 1536 ml b. at FETO2 0.9 = 1728 ml 2. Rate of oxygen consumption (VO2) at rest = 3.56 ml.kg.min−1 in the thirrd trimester 10 = 284 ml.min−1 Apnoeic time (FRC/VO2) a. at FETO2 80 = 5.4 min b. at FETO2 90 = 6.1 min 3. VO2 in labour in the third trimester = 4.28 ml.kg.min−1 10 = 342 ml.min−1 Apnoeic time (FRC/VO2) a. at FETO2 80 = 4.5 min b. at FETO2 90 = 5.1 min 4. Maximum VO2 in average non-athletic pregnant woman = 27 ml.kg.min−1 11 = 2160 ml.min−1 Apnoeic time (FRC/VO2) a. at FETO2 80 = 42.7 s b. at FETO2 90 = 48 s Using a lower target of end-tidal oxygen fraction may be reasoned if apnoeic oxygenation can consistently maintain the oxygen reservoir following induction of general anaesthesia for obstetric patients; however, the success of this technique relies on a number of ideal conditions to be met. The benefit of apnoeic diffusion oxygenation is highly dependent on airway patency; yet, even with the most careful of pre-assessment, it is impossible to predict which patient may not have the patent airway necessary to support apnoeic diffusion 7. Additionally, an early non-obstetric study by Fraioli et al. 8 demonstrated that apnoeic oxygenation is less effective in patients with a low predicted functional residual capacity to body weight ratio. Although the results are difficult to generalise to obstetric patients, this study highlights the possibility that apnoeic oxygenation may not be as effective in individuals with altered respiratory physiology and thus the need to further affirm its role in pregnancy. We need to better understand how we could identify parturients who would not benefit from apnoeic oxygenation. Studying apnoeic oxygenation in pregnancy is ethically and practically difficult. Most parturients who receive general anaesthesia are higher risk parturients who have lower physiological reserves and are often not included in research studies. However, we believe time should be dedicated to investigate how to conduct apnoeic oxygenation effectively in the parturient and factors associated with its ineffectiveness, as difficult as that may be. Results from ongoing high-flow nasal oxygenation studies may offer further useful insights and information to guide this discussion, but until then, many obstetric anaesthetists would likely practice with the devil they know 9. Much more convincing data would be necessary before advocating the lowering of a safety margin that has persisted for decades.

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.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,164
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,017
Tête enseignante GPT0,241
Écart entre enseignants0,224 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2019
Routes d'admission1
Résumé présentoui

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