Systematic analysis of adverse reactions associated with dantrolene treatment: From clinical features to molecular mechanisms
Bibliographic record
Abstract
Dantrolene, 1st synthesized in 1967, is widely used for treating malignant hyperthermia (MH), neuroleptic malignant syndrome, and spasticity. However, comprehensive analysis of its adverse effects and underlying mechanisms remains limited. This study aims to analyze dantrolene-associated adverse events (AEs) using pharmacovigilance databases, with particular focus on subgroup analysis comparing MH versus non-MH patients, and investigate their underlying molecular mechanisms. We analyzed AEs from 3 pharmacovigilance databases (U.S. Food and Drug Administration Adverse Event Reporting System [2004-2024], Japanese Adverse Drug Event Report [2004-2023], Canada Vigilance Adverse Reaction Online Database [1991-2019]) and conducted differential gene expression analysis using GEO datasets (GSE184769, GSE227229). Signal detection employed disproportionality analysis using reporting odds ratio (ROR), proportional reporting ratio, Bayesian confidence propagation neural network, and Empirical Bayesian Geometric Mean indices. Analysis revealed significant respiratory and musculoskeletal AEs. Respiratory failure was consistently reported across databases (ROR: 29.33-46.29), while musculoskeletal complications included rhabdomyolysis (ROR: 14.05) and compartment syndrome (ROR: 80.52). MH patients showed increased risks of muscular weakness (ROR: 19.00), respiratory failure (ROR: 5.48), and pulmonary edema (ROR: 22.18). Molecular analysis identified IL6 and ALB as key mediators of respiratory effects, while Adgrl1 and Adgrl2 emerged as crucial regulators of muscle function. Our study quantified differential dantrolene susceptibility, revealing significantly higher AE risks in MH versus non-MH patients: muscular weakness (ROR: 19.00), respiratory failure (ROR: 5.48), and pulmonary edema (ROR: 22.18). Molecular analysis demonstrated that mutant ryanodine receptor 1 channels amplify IL6/ALB-mediated respiratory effects and disrupt Adgrl1/2-regulated muscle function, establishing the mechanistic basis for MH patient vulnerability and supporting MH-specific dosing strategies.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".