Skeletal Muscle Metabolic Dysfunction in Patients With Malignant Hyperthermia Susceptibility
Bibliographic record
Abstract
BACKGROUND: Malignant hyperthermia (MH), a pharmacogenetic disorder of skeletal muscle, presents with a potentially lethal hypermetabolic reaction to certain anesthetics. However, some MH-susceptible patients experience muscle weakness, fatigue, and exercise intolerance in the absence of anesthetic triggers. The objective of this exploratory study was to elucidate the pathophysiology of exercise intolerance in patients tested positive for MH with the caffeine-halothane contracture test. To this end, we used phosphorus magnetic resonance spectroscopy, blood oxygen level-dependent functional magnetic resonance imaging (MRI), and traditional exercise testing to compare skeletal muscle metabolism in MH-positive patients and healthy controls. METHODS: Skeletal muscle metabolism was assessed using phosphorus magnetic resonance spectroscopy and blood oxygen level-dependent functional MRI in 29 MH-positive patients and 20 healthy controls. Traditional measures of physical capacity were employed to measure aerobic capacity, anaerobic capacity, and muscle strength. RESULTS: During 30- and 60-second exercise, MH-positive patients had significantly lower ATP production via the oxidative pathway compared to healthy controls. MH-positive patients also had a longer recovery time with blood oxygen level-dependent functional MRI compared to healthy controls. Exercise testing revealed lower aerobic and anaerobic capacity in MH-positive patients compared to healthy controls. CONCLUSIONS: Results of this exploratory study suggest that MH-positive patients have impaired aerobic metabolism compared to healthy individuals. This could explain the exercise intolerance exhibited in MH-susceptible patient population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".