Statin-Induced Rhabdomyolysis: A Comprehensive Review of Case Reports
Bibliographic record
Abstract
PURPOSE: To identify case reports of statin-induced rhabdomyolysis and summarize common predisposing factors, symptoms, diagnostic findings, functional outcomes, characteristics, treatment, and rehabilitation. METHOD: MEDLINE, CINAHL, SCOPUS, and PEDro databases were searched (1990-2013) for relevant case reports using the search terms "Statins," "Rhabdomyolysis," "Myalgia," "Muscle damage," "Muscle injury," and "Myopathy." Relevance (based on title and abstract) was assessed by one investigator; two investigators independently reviewed the relevant articles to determine inclusion in the review. RESULTS: A total of 112 cases met the inclusion criteria. The majority were in men (70%) and people over 45 years of age (mean 64 [SD 14] years). Simvastatin was the most commonly reported statin (n=55); the majority of cases reported the use of concomitant medications such as fibrates (n=25). Weakness (n=65) and muscle pain (n=64) were the most common symptoms. In 19 cases, the patient was referred to rehabilitation, but the case reports do not include descriptions of the treatment. CONCLUSION: Statin-induced rhabdomyolysis was more commonly reported when statins were used in conjunction with other drugs, which potentiated its effect. Research is needed to identify the role of exercise and rehabilitation following statin-induced rhabdomyoloysis since muscle damage may be severe and may have long-term effects on muscle function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".