Video Imaging of the Larynx Needs Careful Evaluation
Bibliographic record
Abstract
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
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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 | 0.005 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.016 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".