The CADEUS study: burden of nonsteroidal anti‐inflammatory drug (NSAID) utilization for musculoskeletal disorders in blue collar workers
Bibliographic record
Abstract
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • To our knowledge, no study has ever described the intensity of nonsteroidal anti‐inflammatory drug (NSAID) utilization in an employed population by occupation. • As the use of NSAIDs carries a well‐known risk of adverse effects, this risk adds to the burden of musculoskeletal disorders in employed populations. • Information on utilization of NSAIDs in this context will help to better characterize and prevent this risk. WHAT THIS STUDY ADDS • In spite of a previous history of dyspepsia, blue collar workers had the highest rate of chronic and continuous utilization of nonselective NSAIDs. • No clustering of cyclooxygenase‐2 selective NSAID utilization according to a previous history of dyspepsia was observed among blue collar workers. • The association between chronicity of NSAID utilization and occupation was independent of medical indication for the prescription and other lifestyle factors. AIM The aim of this study was to compare patterns of utilization of NSAIDs for musculoskeletal disorders (MSD) by occupation in a general employed population. METHODS This was a secondary analysis of the CADEUS cohort study on 5651 actively employed patients, who submitted at least one claim for the reimbursement of a NSAID dispensation for a MSD between August 2003 and July 2004, in the French National Healthcare Insurance database. Questionnaires were sent to prescribing physicians to obtain diagnoses and the medical history, and to patients for their occupation, height and weight and smoking status. Multivariate logistic regression was used to study the determinants of a heavy use of NSAIDs defined as ‘over four dispensations in one year with less than two months between any two’. RESULTS Factors associated with heavy use of NSAIDs were age (Odds ratio (OR): 1.8 (ten years), 95% confidence interval (CI): 1.6–1.9), osteoarthritis (versus back pain) (OR: 1.8, 95% CI: 1.5–2.1), body mass index (superior to 30) (OR: 1.8, 95% CI: 1.5–2.2), and occupation (blue collar versus white collar workers) (OR: 1.4, 95% CI: 1.2–1.6). Blue collar workers also had a 20% higher prevalence of 5‐year history of dyspepsia. No difference was observed between sexes or in the use of COX‐2 selective inhibitors between occupations. CONCLUSION Factors associated with occupational constraints that contribute to the severity of MSDs, may explain the heavier use of NSAIDs among blue collar workers in spite of a concurrent and past medical history of adverse reactions to this type of medication.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".