Improvement in muscle function after 2 months of statin withdrawal is not influenced by treatment intensity in patients with statin-associated muscle symptoms
Bibliographic record
Abstract
Statin prescription intensity, defined by statin type and dose required to achieve a targeted decrease in plasma low-density lipoprotein-cholesterol (LDL-C), has been involved in statin-associated muscle symptoms (SAMS) development. This study aimed to assess whether muscle function improved differentially according to treatment intensity after two months of statin withdrawal in patients self-reporting SAMS. Patients (53.0±8.4 years [Mean±SD]) undergoing primary cardiovascular prevention were divided in two groups: low to moderate (n=49, targeted plasma LDL-C reduction <50%) and high (n=12, ≥50%). Strength, endurance, and power in extension and flexion of the dominant leg, and handgrip strength were measured using dynamometers. SAMS intensity was assessed using a 0-10 visual analog scale. After withdrawal, repeated-measures analyses showed improvements for 7/8 performance variables (+7.2 to +13.3%, all p<0.05), concomitant with a decrease in SAMS intensity (5.09 to 1.85, p<0.01), with no between-group difference. The improvement of muscle function following withdrawal was not differentiated according to treatment intensity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".