Quantitative Train-of-Four Monitoring Using the TetraGraph™ to Evaluate Rocuronium Requirements During Renal Transplantation in a Pediatric Patient
Bibliographic record
Abstract
The pharmacokinetics of neuromuscular blocking agents (NMBAs) may be altered in patients with renal insufficiency or failure, including alterations in the volume of distribution or elimination of the primary drug and its metabolites. In this patient population, monitoring of the end-organ effects of NMBAs may be useful to guide initial and subsequent dosing, as well as reversal of neuromuscular blockade. Train-of-four (TOF) monitoring remains the most commonly used technique to monitor the end-organ effect of NMBAs and the neuromuscular junction. Here we present the use of an electromyography (EMG)-based TOF monitor in a 9-year-old boy with end-stage renal disease during intraoperative anesthetic care for renal transplantation. The perioperative management of such patients, including dosing of NMBAs and use of neuromuscular blockade monitoring, is discussed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".