O15 Does knee pain or radiographic osteoarthritis better predict future muscle outcomes? Findings from the Hertfordshire Cohort Study
Bibliographic record
Abstract
Disclosures: N.R. Fuggle: None. L. Westbury: None. K. Jameson: None. M. Edwards: None. C. Cooper: None. E. Dennison: None. Background: Sarcopenia is defined according to accelerated loss of muscle mass, strength and function and is associated with significantly increased morbidity and mortality. Osteoarthritis is the most common joint condition and can be defined clinically (through symptoms and signs) or radiologically. We investigated whether knee pain or radiologic osteoarthritis was predictive of future sarcopenic muscle outcomes in the Hertfordshire Cohort Study (comprised of UK community-dwelling older adults). Methods: We recruited 435 older adults (221 males and 214 females). At baseline, knee pain was defined as a Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) knee pain score of ≥ 1 and radiographic osteoarthritis via plain radiography with a Kellgren and Lawrence score ≥2. At follow-up grip strength was assessed using JAMAR dynamometry and muscle function via gait speed. Whole-body dual X-ray absorptiometry (DXA) was used to derive percentage lean mass. Linear regression was used to assess the relationship between knee pain and/or radiographic osteoarthritis and grip strength, gait speed and percentage lean mass in models unadjusted and adjusted for anthropometric and lifestyle factors. Results: The mean age of participants was 64.9 years (SD 2.7) at baseline and follow-up was approximately 11 years. There were no significant sex differences in the prevalence of radiographic osteoarthritis (men 90 (40.7%), women 84 (39.3%)), knee pain (men 103 (49.8%), women 111 (56.1%)) or the combination of radiographic osteoarthritis and knee pain (men 54 (41.5%), women 54 (46.6%)). The following are from fully-adjusted analyses. Knee pain was significantly predictive of lower percentage lean mass (-0.58 z-score (-0.79, -0.36), p < 0.001) and grip strength (-0.19 z-score (-0.38, -0.00), p = 0.50). Radiographic knee osteoarthritis was also significantly associated with lower percentage lean mass (-0.27 z-score (-0.50, -0.04, p = 0.021) and grip strength (-0.39 z-score (-0.58, -0.21), p < 0.001). The combination of radiographic osteoarthritis and knee pain was associated with lower percentage lean mass (-0.75 z-score (-1.03, -0.48), p < 0.001), grip strength (-0.48 z-score (-0.72, -0.23), p < 0.001) and a reduction in gait speed (-0.26 z-score (-0.50,-0.02), p < 0.04). Conclusion: We observed that the occurrence of knee pain predicted lower future muscle mass, radiographic osteoarthritis predicted lower future muscle mass and strength and the combination (knee pain and radiographic osteoarthritis) predicted lower future muscle mass, strength and function. These findings suggest that those individuals with co-existent evidence of knee pain and radiographic osteoarthritis are at particular risk of adverse muscle outcomes and, if our results are replicated elsewhere, these individuals should be targeted with interventions to ameliorate this decline in muscle mass, strength and function.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".