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Enregistrement W2057917074 · doi:10.1097/aln.0000000000000499

Lung Ultrasonography for the Detection of Anesthesia-induced Lung Atelectasis

2014· letter· en· W2057917074 sur OpenAlexafffundabout
Martin Girard, Vincent Généreux, Audrey Monastesse

Notice bibliographique

RevueAnesthesiology · 2014
Typeletter
Langueen
DomaineMedicine
ThématiqueUltrasound in Clinical Applications
Établissements canadiensCentre Hospitalier de l’Université de Montréal
Organismes subventionnairesUniversité de Montréal
Mots-clésAtelectasisMedicineLungUltrasoundMechanical ventilationRadiologyPathologyAnesthesiaInternal medicine

Résumé

récupéré en direct d'OpenAlex

We have read with great interest the article by Acosta et al.1 exploring the use of lung ultrasound as a mean to detect intraoperative atelectasis. However, despite their statement to the contrary, the occurrence of B lines in the setting of atelectasis has already been described by others. Although B lines were initially thought to originate from the interaction of the ultrasound beam with thickened subpleural interlobular septa found in alveolar-interstitial pathologies,2 recent work has challenged this hypothesis. In an elegant series of experiments, Soldati et al.3–5 have shown that B lines are observed when the ultrasound beam interacts at the pleural surface with lung tissue of a specific density. Although this can occur with the replacement of subpleural air by an ultrasound-conductive substance (e.g., water, pus, blood, and fibrous tissue), the withdrawal of air (e.g., resorption atelectasis) will also lead to the genesis of B lines. Demonstrating this last point, in an ex vivo animal model of graded atelectasis, B lines were observed in increasing numbers with increasing atelectasis. Pathologic examination of the excised lungs showed diffusely compressed alveoli mixed with sporadic areas of normally expanded distal air spaces.5The study by Acosta et al. comes at an interesting moment. The recent publication of two randomized controlled trials6,7 exploring the impact of intraoperative mechanical ventilation parameters on postoperative pulmonary complications has generated much interest.8 Although some have linked the negative results of the PROVHILO (PROtective Ventilation using HIgh versus LOw positive end-expiratory pressure) trial to a lack of regular recruitment maneuvers and a positive end-expiratory pressure set too high,9 others blame the use of inappropriately high tidal volumes in the control group for the positive results in the IMPROVE (Intraoperative PROtective VEntilation) trial.10 In the absence of imagery supporting claims of atelectasis or overdistention, the culprits usually blamed for the development of postoperative pulmonary complications, it is unlikely this question will be resolved before more data becomes available. Interestingly, recent anesthesiology literature has demonstrated the advantage of hemodynamic optimization11 championing the concept that individualization is preferable to a “one size fits all” approach. Likewise, individualization of mechanical ventilation parameters might be an interesting avenue to explore if we wish to decrease the occurrence of postoperative respiratory complications. This hypothesis is supported by spiral computed tomography studies reporting significant interpatient variability in the amount of atelectasis induced by general anesthesia.12,13 Therefore, we believe that bedside monitoring to detect lung atelectasis or overdistention is needed. Although magnetic resonance imaging and computed tomography fulfill this requirement, they cannot be used in an intraoperative setting except in specially designed operating rooms and could not realistically be repeated throughout a procedure. Because lung ultrasonography can be performed at the bedside and is devoid of any ionizing radiation, the present study by Acosta et al., although interesting in and of itself, is an important milestone toward establishing lung ultrasonography as a tool to optimize intraoperative mechanical ventilation parameters. Other investigators have described loss of aeration scales that have allowed the study of the therapeutic effects of antibiotics in ventilator-associated pneumonia,14 the effect of different levels of positive end-expiratory pressure in patients with acute respiratory distress syndrome on lung reexpansion15 and the detection of patients likely to fail extubation after a successful spontaneous breathing trial.16 Although not developed specifically for the diagnosis and monitoring of anesthesia-induced atelectasis, the use of these scales would have been an interesting addition to the study by Acosta et al. Whether to optimize intraoperative mechanical ventilation parameters or to assist anesthesiologists in the care of hypoxemic patients, lung ultrasonography is likely to have a bright future in our operating rooms.Supported by Grant of the Fondation 2013, Fondation d’anesthésiologie et réanimation du Québec; Grant of the Fonds de développement 2014, Département d’anesthésiologie, Université de Montréal.The authors declare no competing interests.

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)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,208
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0020,001
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 Opus0,037
Tête enseignante GPT0,317
Écart entre enseignants0,280 · 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

Citations9
Publié2014
Routes d'admission3
Résumé présentoui

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