Step‐by‐step diagnosis and management of the nocebo/drucebo effect in statin‐associated muscle symptoms patients: a position paper from <i>the International Lipid Expert Panel</i> (ILEP)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Statin intolerance is a clinical syndrome whereby adverse effects (AEs) associated with statin therapy [most commonly statin-associated muscle symptoms (SAMS)] result in the discontinuation of therapy and consequently increase the risk of adverse cardiovascular outcomes. However, complete statin intolerance occurs in only a small minority of treated patients (estimated prevalence of only 3-5%). Many perceived AEs are misattributed (e.g. physical musculoskeletal injury and inflammatory myopathies), and subjective symptoms occur as a result of the fact that patients expect them to do so when taking medicines (the nocebo/drucebo effect)-what might be truth even for over 50% of all patients with muscle weakness/pain. Clear guidance is necessary to enable the optimal management of plasma in real-world clinical practice in patients who experience subjective AEs. In this Position Paper of the International Lipid Expert Panel (ILEP), we present a step-by-step patient-centred approach to the identification and management of SAMS with a particular focus on strategies to prevent and manage the nocebo/drucebo effect and to improve long-term compliance with lipid-lowering therapy.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it