A Neuromuscular Approach to Statin-Related Myotoxicity
Bibliographic record
Abstract
Approximately 95% of statin-treated patients tolerate this form of cholesterol management without any adverse effects. However, given their efficacy in reducing low density lipoproteins and cardiovascular events large numbers of patients are selected for statin therapy. Therefore muscle complications are, in fact, quite common. Limited understanding of the underlying pathophysiology has hampered physicians' ability to identify patients at risk for developing statin myotoxicity. A growing number of published case reports/series have implicated statins in the exacerbation of both acquired and genetic myopathies. A clinical management algorithm is presented which outlines a variety of co-morbidities which can potentiate the adverse effects of statins on muscle. In addition, a rational approach to the selection of those patients most likely to benefit from skeletal muscle biopsy is discussed. Ongoing work will define the extent to which statin-intolerant patients represent carriers of recessive metabolic myopathies or pre-symptomatic acquired myopathies. The expanding importance of pharmacogenomics will undoubtedly be realized in the field of statin myopathy research within the next few years. Such critical information is needed to establish more definitive management and diagnostic 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".