Longitudinal Trajectories of Pain Sensitization Over Nine Years in People With or at Risk of Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: Pain sensitization is common in knee osteoarthritis (OA) and is associated with pain severity and functional limitations. Whether pain sensitization is induced by OA or it may be an inherent trait remains unclear. We evaluated pain sensitization trajectories and their relations to symptoms in people with or at risk of knee OA. METHODS: We used data from four study visits of the Multicenter Osteoarthritis Study over a nine-year period. We agnostically identified pain sensitization trajectory groups defined by wrist and knee pressure pain thresholds (PPTs) over nine years using group-based trajectory methods stratified by sex. We evaluated the relations of the wrist and knee PPT trajectory groups to Western Ontario and McMaster Universities Arthritis Index (WOMAC) knee pain and function at the final visit using separate linear regression models. RESULTS: ) and identified three distinct trajectory groups in both women and men: low, moderate, and high PPTs. Overall, the PPT trajectories changed minimally over time in each group. Compared to the low PPT trajectory groups (the most sensitized groups), the moderate and high PPT groups had better WOMAC pain and function at the final assessment nine years later. CONCLUSION: We identified stable but distinct pain sensitization trajectories over nine years despite likely changes in disease course and treatments over time, suggesting that individuals with knee OA may be predisposed to having different degrees of sensitization as an inherent trait, which in turn likely influences their pain experience and functional status.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".