A New Perspective on the Relation Between Obesity and Knee Osteoarthritis: Omentin
Bibliographic record
Abstract
OBJECTIVE: Knee osteoarthritis (KOA) is defined as a chronic degenerative joint disease. Obesity is a significant risk factor for KOA. Omentin is an adipose tissue-induced adipokine. The aim of the present study was to investigate the correlation between obesity and serum omentin levels in patients with KOA. METHODS: This study included 60 patients with KOA, 34 obese individuals (O-KOA) and 26 nonobese individuals (NO-KOA) and 40 controls, 17 obese individuals (OC) and 23 nonobese individuals (NOC) matched in terms of age, sex, and body mass index (BMI) who were recruited from the same polyclinic. Blood samples and knee radiographs were obtained from all the subjects, and clinical features, BMI, and laboratory parameters were recorded. The Kellgren-Lawrence (KL) grade and Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index were used to classify the radiographic and clinical findings, respectively. Serum omentin levels were determined using an ELISA. RESULTS: Serum omentin levels in patients were significantly lower than those in the controls (p < 0.05). When the BMI values and KL scores were considered, serum omentin levels significantly decreased in severe O-KOA versus in mild-to-moderate O-KOA. There was no statistically significant decrease in severe NO-KOA versus mild-to-moderate NO-KOA. There was a significant negative correlation between the serum omentin level and BMI and WOMAC index. All findings were supported by a receiver operating characteristic curve analysis. CONCLUSION: Serum omentin levels were inversely related to obesity and the severity of KOA. The data indicate that omentin may be a new biomarker of KOA to our knowledge and may aid the diagnosis of early-stage O-KOA, if our findings are supported by further studies involving much more samples.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".