Video Imaging of the Larynx Needs Careful Evaluation
Notice bibliographique
Résumé
To the Editor: We read with interest the article by Girling et al. (1) presenting video imaging as a new method to determine neuromuscular block at the larynx. We would like to make some critical comments. Movement of the bronchoscope during the period of monitoring might have an influence on the accuracy and reproducibility of the angles measured. Because the coefficient of variation in cord movement was only measured during supramaximal stimulation, it is not known what the coefficient of variation might be at another state of neuromuscular blockade, e.g., 50% blockade. Changes in cuff resting pressure of the laryngeal mask during neuromuscular blockade might change the position of the larynx. Have they made comparative measurements and how might the images and the position of the vocal cords be altered by this? Supramaximal stimuli were applied at a mean current of 74 ± 13 mA. Our own experiences suggest that this amount of current causes significant movement of the larynx and, possibly, the vocal cord angles. Girling et al. (1) calculated intra- and interobserver variability in determining vocal cord angles. Because the mean angles of these measurements are not presented, evaluation of the Bland-Altman plots is somewhat limited. Furthermore, agreement of interobserver measurements should have been compared during the onset and offset of neuromuscular blockade. Video imaging at the larynx and mechanomyography (MMG) of the hand are two fundamentally different methods of measurements. MMG measures isometric forces; video imaging measures the visual movement of the vocal cords without relation to the actual force generated. A comparable method at the hand would be to measure contraction of the adductor pollicis muscle via video imaging, e.g., determining different contraction angles. In their discussion, Girling et al. (1) state that the advantage of video imaging is direct visualization of the neuromuscular blockade versus “blind” cuff pressure measurements. We cannot agree with this statement. The main difference between this new technique and MMG or electromyography (EMG) is the subjective principle of video imaging. It cannot be concluded that video imaging, because of the mere visualization of the vocal cord movement, is superior to electromyography or cuff pressure measurements in determining neuromuscular blockade. A proper evaluation of the video imaging technique would be to compare it with one of these methods. This seems technically impossible with the cuff pressure technique but is certainly possible with IM laryngeal EMG, as recently described (2). Girling et al. (1) measured very similar onset of neuromuscular blockade after succinylcholine at the larynx and the adductor pollicis muscle. This is in concordance to a study by D’Honneur et al. (3) using EMG and in contrast to studies by Wright et al. (4) and Meistelman et al. (5) using MMG. Girling et al. (1) suggest the change in resting cuff pressure as a reason for this difference. Our own recent findings (6) using surface EMG at the larynx and the adductor pollicis muscle, however, support the findings by Wright et al. (4) and Meistelman et al. (5) and showed a significant difference in lag and onset time between larynx and adductor pollicis muscle. We suggest another explanation for these contrasting studies. Whereas in the latter studies the same technique was used to measure neuromuscular blockade at the larynx and the adductor pollicis muscle (MMG or EMG), D’Honneur et al. (3) and Girling et al. (1) have used different methods at the larynx and adductor pollicis muscle (EMG or video imaging versus MMG). Given the fact that EMG tends to measure onset times which are usually longer than MMG (7), this might well explain why no difference in onset time between larynx and adductor pollicis muscle was found by D’Honneur et al. (3) and Girling et al. (1). We conclude that video imaging seems to be an interesting research tool to measure neuromuscular blockade at the larynx but needs more evaluating to estimate its role in neuromuscular research. Thomas M. Hemmerling, MD, DEAA François Donati, MD, PhD, FRCPC
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,049 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,004 | 0,007 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,016 | 0,017 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,005 |
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 source (Gemma direct ou Codex distillé), 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 ».