The Burden of Pain Associated with Osteoarthritis in the Hip or Knee from the Patient’s Perspective: A Multinational Cross-Sectional Study
Bibliographic record
Abstract
INTRODUCTION: To evaluate, from the patient's perspective, the burden of pain associated with hip/knee osteoarthritis (OA) in the USA and selected European Union (EU) countries. METHODS: Data were drawn from the 2017 global Adelphi OA Disease Specific Programme™ (DSP). Patients with hip/knee OA were stratified based on pain intensity and the presence/absence of current opioid use. Outcomes included Western Ontario and McMaster Universities Osteoarthritis Index scores, functional limitations, unmet treatment needs, Charlson Comorbidity Index, relevant comorbid conditions, the 5-dimension 5-level EuroQol, and the Work Productivity and Activity Impairment Questionnaire: Specific Health Problem. Bivariate testing compared outcomes using patients with no/mild pain without opioid use as the reference group. RESULTS: The study population comprised 2170 patients (US: n = 623 [28.7%]; EU: n = 1547 [71.3%]) with knee (54.9%), hip (24.6%), or knee/hip (20.5%) OA. Mean (SD) age was 66.4 (11.2) years. Patients had no/mild pain without opioid use (39.6%), no/mild pain with opioid use (10.2%), moderate/severe pain without opioid use (30.6%), and moderate/severe pain with opioid use (19.7%). Compared with the reference group, patients with moderate/severe pain reported significantly (p < 0.05) higher functional limitations, greater use of ≥ 3 treatments and treatment dissatisfaction, reduced quality of life, and impaired work productivity and activity. The burden was highest with moderate/severe pain with opioid use. Results were generally similar in the US and EU cohorts. CONCLUSIONS: The results from this multinational cross-sectional study indicate that the impact of OA pain is multidimensional, worsened by increasing pain intensity, and may not be adequately addressed by current treatment strategies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".