Cambios de osteoprotegerina en saliva y suero de pacientes con osteoartritis de rodilla
Bibliographic record
Abstract
El alcance de este estudio fue evaluar los niveles de osteoprotegerina (OPG) salival y sérica en la osteoartritis de rodilla (OA). Los niveles de OPG en suero y saliva de 30 OA y 30 controles sanos emparejados en este estudio transversal se evaluaron mediante ELISA. El dolor de rodilla fue evaluado por The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Los datos se analizaron mediante la prueba t de Student, la prueba de correlación de Spearman y receiver operating characteristic (ROC). El nivel medio de OPG en suero, pero no en saliva fue menor en la artrosis de rodilla que en el grupo sano. WOMAC se correlacionó negativamente con la OPG sérica (r = −0,501; p = 0,000). El valor de corte de OPG sérico fue de 237,5 pg/mL para el diagnóstico de OA de rodilla. Como la OPG sérica fue más baja en la artrosis de rodilla y se correlacionó negativamente con WOMAC, parece que la detección de OPG en suero, pero no en la saliva puede ser un marcador probable para el diagnóstico de artrosis de rodilla. La osteoprotegerina disminuye en la osteoartritis de rodilla. The scope of this study was to assess salivary and serum osteoprotegerin (OPG) levels in knee osteoarthritis (OA). Serum and saliva OPG levels of 30 knee OA and 30 matched healthy controls in this cross-sectional study was assessed by ELISA. Knee pain was assessed by WOMAC. Data were analyzed by Student's t-test, Spearman correlation test and ROC. The mean serum but not saliva OPG level was lower in knee OA than that of the healthy group. WOMAC negatively correlated with serum OPG (r = −0.501; P = 0.000). The serum OPG cutoff value was 237.5 pg/ml for the diagnosis of knee OA. As serum OPG was lower in knee OA and negatively correlated with WOMAC, it seems that detection of OPG in serum but not in saliva may be a probable marker to the diagnosis of knee OA. Osteoprotegerin decreases in knee osteoarthritis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".