Tactile Fade Detection with Hand or Wrist Stimulation Using Train-of-Four, Double-Burst Stimulation, 50-Hertz Tetanus, 100-Hertz Tetanus, and Acceleromyography
Bibliographic record
Abstract
In Brief Residual neuromuscular blockade can be evaluated using acceleromyography, tactile assessment of train-of-four (TOF), double-burst stimulation (DBS), 50-Hz tetanus, or 100-Hz tetanus. Nerve stimulation can be at the hand or the wrist. We compared all these tests at both sites of stimulation. Rocuronium was given to 32 patients under sevoflurane anesthesia. The mechanomyographic adductor pollicis TOF ratio was measured at one extremity. In the other, stimulation was at the hand or the wrist, by random allocation, and the acceleromyographic TOF ratio was measured. During recovery, a blinded observer estimated tactile fade. The TOF fade became undetectable when mechanomyographic TOF ratio was (mean ± sd) 0.31 ± 0.15. For DBS, this threshold was 0.76 ± 0.11. For 50-Hz tetanus, it was 0.31 ± 0.15. For 100-Hz tetanus, it was 0.88 ± 0.18, with a range of 0.14–1.00. These tactile responses were the same for hand and wrist stimulation. When acceleromyographic TOF ratio reached 1.0, the mechanomyographic TOF ratio was 0.89 ± 0.06. With stimulation in the hand, acceleromyographic TOF ratio >1.0 was less frequent than at the wrist. To exclude residual paralysis, TOF, DBS, and 50-Hz tetanus are inadequate, 100-Hz tetanus is unreliable, and acceleromyography performs best. IMPLICATIONS: To detect residual neuromuscular blockade, tactile evaluation of 50-Hz tetanic, train-of-four (TOF), or double-burst fade lacks sensitivity. Fade after a 100-Hz tetanus is unreliable. An acceleromyographic TOF ratio of 1.0 is recommended to exclude residual paralysis. Stimulation at the hand and the wrist yields similar results for tactile evaluation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".