Do we really need sugammadex as an antagonist of muscle relaxants in anesthesia?
Bibliographic record
Abstract
PURPOSE OF REVIEW: Sugammadex is a selective relaxant-binding agent that is designed to encapsulate rocuronium and chemically similar steroidal muscle relaxants such as vecuronium. This review summarizes recent information on the use of sugammadex in clinical practice. RECENT FINDINGS: The main advantages of sugammadex when compared with conventional anticholinesterase agents are a much faster recovery time and its unique ability to reverse rapidly and efficiently, for the first time, deep levels of neuromuscular blockade. However, there is paucity of evidence-based studies on the benefit of deep neuromuscular block, and then routine administration of sugammadex to reverse any level of block, for example, during laparoscopic surgery. It appears that reduction of costs depends mainly on organizational factors. Finally it must be remembered that sugammadex only works with steroidal nondepolarizing muscle relaxants; therefore neostigmine should not be withdrawn because it is the only reversal agent effective against atracurium or cisatracurium. SUMMARY: Sugammadex offers a significantly faster and more predictable recovery profile than neostigmine. It is now possible to reverse rapidly and efficiently any level of neuromuscular blockade and to avoid the risk of adverse events because of residual paralysis such as critical respiratory events during recovery from anesthesia.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".