Association of synovial fluid and urinary C2C-HUSA levels with surgical outcomes post-total knee arthroplasty
Bibliographic record
Abstract
OBJECTIVES: After total knee arthroplasty (TKA), ∼30% of knee osteoarthritis (KOA) patients show little symptomatic improvement. Earlier studies have correlated urinary (u) type 2 collagen C terminal cleavage peptide assay (C2C-HUSA), which detects a fragment of cartilage collagen breakdown, with KOA progression. This study determines whether C2C levels in urine, synovial fluid, or their ratio, are associated with post-surgical outcomes. METHODS: From a large sample of 489 subjects, diagnosed with primary KOA undergoing TKA, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and function scores were collected at baseline (time of surgery) and one-year post-TKA. Baseline urine (u) and synovial fluid (sf) were analysed using the IBEX-C2C-HUSA assay, with higher values indicating higher amounts of cartilage degradation. For urine, results were normalised to creatinine. Furthermore, subjects' changes in WOMAC scores were categorised based on percent reduction in pain or improvement in function, compared to baseline, such that >66.7%, >33.3 to ≤66.7%, and ≤33.3% denoted "strong", "moderate" and "mild/worse" responses, respectively. Associations of individual biofluid C2C-HUSA levels, or their ratio, with change in WOMAC pain and function scores up to one-year post-TKA, or category of change, were analysed by linear, logistic, or cumulative odds models. RESULTS: Higher baseline uC2C-HUSA levels or a lower ratio of baseline sfC2C-HUSA to uC2C-HUSA were associated with improvements in WOMAC pain by linear multivariable modelling [odds ratio -0.40 (95% confidence interval -0.76, -0.05) p = 0.03; 0.36 (0.01, 0.71), p = 0.04, respectively], while sfC2C-HUSA alone was not. However, lower ratios of sfC2C-HUSA to uC2C-HUSA were associated with improvements in WOMAC function [1.37 (0.18, 2.55), p = 0.02], while sfC2C-HUSA and uC2C-HUSA alone were not. Lower ratios of sfC2C-HUSA to uC2C-HUSA were also associated with an increased likelihood of a subject being categorised in a group where TKA was beneficial in both univariable [pain, 0.81 (0.68, 0.96), p = 0.02; function, 0.92 (0.85, 0.99), p = 0.035] and multivariable [pain, 0.81 (0.68, 0.97) p = 0.02; function, 0.92 (0.85, 1.00), p = 0.043] ordinal modelling, while sfC2C-HUSA and uC2C-HUSA alone were not. CONCLUSIONS: Overall, ratios of baseline sfC2C-HUSA to uC2C-HUSA, and baseline uC2C-HUSA, may play an important role in studying post-TKA surgical outcomes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".