0881 Impact of Statin Withdrawal on Sleep Quality
Bibliographic record
Abstract
Abstract Introduction Statins are benchmark lipid-lowering drugs, reducing blood cholesterol by controlling its synthesis. There are side effects linked to statins use, including statin-associated muscle symptoms (SAMS). These symptoms typically include myalgia, stiffness, weakness, fatigue and/or cramps. SAMS can lead to a reduction in muscle performance, as well as an altered health-related quality of life. Nevertheless, the potential effects of SAMS on sleep remains poorly documented. The objective of this exploratory work was to assess if measures of sleep disturbances and its consequences improve after drug withdrawal in SAMS self-reporters. Methods Patients (5 men [M] / 3 women [W], 44.8±6.3 yrs.) in a primary cardiovascular prevention cohort composed two groups: statin users with (SAMS, 2M/2W) or without symptoms (No SAMS, 3M/1W). All patients were required to have a low cardiovascular risk over ten years (i.e. Framingham Risk Score < 10%) and were using different types and doses of statins for more than two months. Sleep was measured objectively by actigraphy and subjectively using the Epworth Sleepiness Scale (ESS) and the Pittsburgh Sleep Quality Index (PSQI). Finally, a 10-point visual analog scale (VAS) was used to self-assess the intensity of SAMS, specifically at night. Measures were taken before and after two months of statins withdrawal. Results After withdrawal, we observed an improvement of objective sleep quality in the SAMS group (sleep efficiency: +3.79%, effect size [ES]: 0.33 [small effect]; wake after sleep onset: -15.6%, ES: -0.30 [small effect]; number of awakenings after sleep onset: -12.7%, ES: -0.45 [small effect]), concurrent with a decrease of subjective perception of SAMS intensity at night (VAS, from 4.5 to 1.0, ES: -0.79 [moderate effect]). A decrease of subjective daytime sleepiness (ESS, from 11.3 to 8.3, ES: -0.45 [small effect]) and an increase of subjective sleep quality (PSQI, from 7.66 to 6.33, ES: -0.31 [small effect]) were also seen in this group. On the other hand, the No SAMS group showed no change after drug withdrawal for any of the different objective and subjective sleep parameters (ES: -0.08 to 0.15 [trivial effects]). Conclusion Our preliminary data suggest that SAMS are associated with sleep disturbances and impaired sleep quality. Support (if any)
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.005 | 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".