Consequences of Succinylcholine Administration to Patients Using Statins
Bibliographic record
Abstract
BACKGROUND: Statins cause structural changes in myocytes and provoke myotoxicity, myopathy, and myalgias. Thus, patients taking statins may be especially susceptible to succinylcholine-induced muscle injury. The authors tested the hypothesis that succinylcholine increases plasma concentrations of myoglobin, potassium, and creatine kinase more in patients who take statins than in those who do not and that succinylcholine-induced postoperative muscle pain is aggravated in statin users. METHODS: Patients who took statins for at least 3 months and those who had never used statins were enrolled. General anesthesia was induced and included 1.5 mg/kg succinylcholine for intubation. The incidence and degree of fasciculation after succinylcholine administration were recorded. Blood samples were obtained before induction and 5 and 20 min and 24 h after succinylcholine administration. Patients were interviewed 2 and 24 h after surgery to determine the degree of myalgia. RESULTS: The authors enrolled 38 patients who used statins and 32 who did not. At 20 min, myoglobin was higher in statin users versus nonusers (ratio of medians 1.34 [95% CI: 1.1, 1.7], P = 0.018). Fasciculations in statin users were more intense than in nonusers (P = 0.047). However, plasma potassium and creatine kinase concentrations were similar in statin users and nonusers, as was muscle pain. CONCLUSIONS: The plasma myoglobin concentration at 20 min was significantly greater in statin users than nonusers, although the difference seems unlikely to be clinically important. The study results suggest that the effect of succinylcholine given to patients taking statins is likely to be small and probably of limited clinical consequence.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".