Phenotypes of osteoarthritis-related knee pain and their transition over time: data from the osteoarthritis initiative
Bibliographic record
Abstract
BACKGROUND: Identification of knee osteoarthritis (OA) pain phenotypes, their transition patterns, and risk factors for worse phenotypes, may guide prognosis and targeted treatment; however, few studies have described them. We aimed to investigate different pain phenotypes, their transition patterns, and potential risk factors for worse pain phenotypes. METHODS: Utilizing data from the Osteoarthritis Initiative (OAI), pain severity was assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale. We identified the activity-related pain phenotypes and estimated the transition probabilities of pain phenotypes from baseline to the 24-month using latent transition analysis. We examined the risk factors at baseline with the 24-month pain phenotypes and the transition of pain phenotypes. RESULTS: In 4796 participants, we identified four distinct knee pain phenotypes at both baseline and 24-month follow-up: no pain, mild pain during activity (Mild P-A), mild pain during both rest and activity (Mild P-R-A), and moderate pain during both rest and activity (Mod P-R-A). 82.9% knees with no pain at baseline stayed the same at 24-month follow-up, 17.1% progressed to worse pain phenotypes. Among "Mild P-A" at baseline, 32.0% converted to no-pain, 12.8% progressed to "Mild P-R-A", and 53.2% remained. Approximately 46.1% of "Mild P-R-A" and 54.5% of "Mod P-R-A" at baseline experienced remission by 24-month. Female, non-whites, participants with higher depression score, higher body mass index (BMI), higher Kellgren and Lawrence (KL) grade, and knee injury history were more likely to be in the worse pain phenotypes, while participants aged 65 years or older and with higher education were less likely to be in worse pain phenotypes at 24-month follow-up visit. Risk factors for greater transition probability to worse pain phenotypes at 24-month included being female, non-whites, participants with higher depression score, higher BMI, and higher KL grade. CONCLUSIONS: We identified four distinct knee pain phenotypes. While the pain phenotypes remained stable in the majority of knees over 24 months period, substantial proportion of knees switched to different pain phenotypes. Several socio-demographics as well as radiographic lesions at baseline are associated with worse pain phenotypes at 24-month follow-up visit and transition of pain phenotypes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".