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Record W2617989231 · doi:10.2146/ajhp160714

Coenzyme Q10 supplementation in the management of statin-associated myalgia

2017· review· en· W2617989231 on OpenAlexaff
Jason Tan, Arden R. Barry

Bibliographic record

VenueAmerican Journal of Health-System Pharmacy · 2017
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsmyalgiaMedicineEzetimibeMyopathyStatinNiacinAdverse effectInternal medicineMuscle crampMuscle weaknessSimvastatinWeaknessStroke (engine)Physical therapySurgery

Abstract

fetched live from OpenAlex

Statins are indicated for use as first-line therapy in the prevention of major adverse cardiovascular events (e.g., myocardial infarction, stroke) in patients with or at risk for cardiovascular disease.1 However, muscle-related adverse effects, including myopathy, often limit the use of statins in practice. Myopathy is a general term that encompasses myalgia (muscle pain), muscle weakness, and cramps.2 Statin-associated myalgia (SAM) has occurred in 0.1–5.0% of patients in randomized controlled trials (RCTs) of statins; those figures likely represent an underestimation of SAM frequency due to the studies’ exclusion of patients with a history of SAM or intolerant to statins during the run-in phase.3,–5 Symptoms of SAM often include muscle pain, aches, weakness, and cramps, which may or may not correspond to an elevation in serum levels of creatine kinase (CK). In practice, SAM is often managed by lowering the dosage of the suspected offending drug, switching agents, or using alternate dosing strategies (e.g., every-other-day or once-weekly dosing).6 Persistence in prescribing of different statins and statin doses is recommended due to the relative lack of evidence of cardiovascular benefit with other lipid-lowering agents (e.g., ezetimibe, fibrates, niacin).1

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.938
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.102
GPT teacher head0.450
Teacher spread0.348 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations7
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Health-System PharmacySame topicLipoproteins and Cardiovascular HealthFrench-language works237,207