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Abstract 15951: Psychosocial Wellbeing Does Not Affect Muscle Pain and Quality of Life During Atorvastatin Treatment

2015· article· en· W4231830762 on OpenAlexaboutno aff
Amanda L. Zaleski, Beth A. Taylor, Linda S. Pescatello, Gregory A. Panza, Jeffrey A. Capizzi, Adam Grimaldi, C Michael White

Bibliographic record

VenueCirculation · 2015
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsnot available
Fundersnot available
KeywordsBrief Pain InventoryMedicineAtorvastatinBeck Depression InventoryDepression (economics)Quality of life (healthcare)PlaceboPsychosocialPhysical therapyInternal medicineMcGill Pain QuestionnaireStatinChronic painAnxietyPsychiatryVisual analogue scaleAlternative medicine

Abstract

fetched live from OpenAlex

Introduction: HMG-CoA reductase inhibitors (statins) are generally well-tolerated, although muscle weakness and pain have been reported in ~10% of statin users. However, many self-reported muscle side effects are non-specific. As mental health influences self-perception of pain, we sought to assess the effect of baseline well-being and depression on self-reported muscle pain and quality of life (QOL) after 6 months of atorvastatin (ATORVA) 80 mg/d or placebo in healthy, statin-naïve adults. Hypothesis: We hypothesized that lower levels of well-being and higher levels of depression would result in higher self-reported pain that interferes with QOL after statin therapy. Methods: The Psychological General Well-Being Index (Well-Being; n=82) and Beck Depression Inventory (Depression; n=55) were administered at baseline in subjects (aged 59.5+1.2 yrs) from STOMP (Effect of Statins on Skeletal Muscle Performance; Clinical Trials #NCT00609063). Muscle pain (Short-Form McGill Pain Questionnaire [SF-MPG]) and pain that interferes with QOL (Brief Pain Inventory [BPI]), were also measured before and after drug treatment. Results: At baseline, there were no group differences in Well-Being, Depression, or pain measures between groups (ps ≥0.05). Baseline Well-Being correlated with baseline BPI pain severity (r=-0.309, p<0.01) and BPI pain interference with QOL (r=-0.271, p<0.05); including both affective and activity subcomponents (ps<0.05). Baseline Depression correlated with baseline pain (r=0.313, p<0.05). Pain severity and interference with QOL scores were not different between statin users and controls after 6 mo of ATORVA (ps≥0.05). Baseline Well-Being and Depression were not significant predictors of pain after 6 mo of ATORVA (ps≥0.05 for overall effects and interactions). Conclusions: Lower levels of psychosocial well-being and higher levels of depression are associated with greater non-specific muscle pain, however, they are not associated with statin-associated muscle side effects or QOL after 6 mo of ATORVA in otherwise healthy adults. Trial Registration: NCT00609063

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.069
GPT teacher head0.347
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2015
Admission routes1
Has abstractyes

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