The levels of the adipokines adipsin and leptin are associated with knee osteoarthritis progression as assessed by MRI and incidence of total knee replacement in symptomatic osteoarthritis patients: a<i>post hoc</i>analysis
Bibliographic record
Abstract
OBJECTIVE: Limited studies have explored the association between adipokines and knee OA structural progression using quantitative MRI (qMRI), and very few have included total knee replacement (TKR) as a disease outcome. The objective of this study was to compare serum levels of five adipokines to cartilage volume loss (CVL) and investigate their predictive value for TKR. METHODS: The according-to-protocol population (n = 138) of a knee OA trial was used. Serum levels of adipsin (complement factor D), leptin, adiponectin, resistin and serpin E1, and cartilage volume were determined at baseline and 24 months with specific ELISAs and qMRI, respectively. Study knee TKR incidence up to 4 years post-trial was also assessed. RESULTS: Greater baseline values of adipsin and leptin correlated with increased CVL in the global knee and medial femur (P ⩽ 0.032) and of adipsin in the lateral compartment and femur (P ⩽ 0.028). Adiponectin showed an inverse correlation in the medial compartment and femur (P ⩽ 0.027). Resistin and serpin E1 were not associated with CVL. Multivariate analyses revealed that patients in the highest tertile at baseline of adipsin presented a greater odds ratio of CVL in the lateral compartment and femur (⩾2.87; P ⩽ 0.011), and those in the highest tertile of leptin in the medial compartment (2.78; P = 0.038). Most clinically relevant, patients in the highest tertile of adipsin or leptin at baseline had significantly greater incidence of TKR (P = 0.027). CONCLUSION: Data demonstrate that both adipsin and leptin predict greater CVL over time in the lateral and medial compartment, respectively. Importantly, this study also demonstrates that higher baseline levels of adipsin or leptin are associated with higher incidence of TKR.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".