Correlation of Circulating Dickkopf-1 Level with Sonographic Findings and Radiographic Grading in Primary Knee Osteoarthritis
Bibliographic record
Abstract
Background: Osteoarthritis (OA) is a frequently complex joint disease that involves all joint components, including cartilage degeneration and new bone development. Dickkopf-1 (Dkk-1) regulates bone growth and repair in OA. The purpose of this study is to determine Dkk-1 blood levels in individuals with primary knee joint OA, as well as their associations with disease progression and severity. Methods: This study included 45 individuals with primary OA of the knee and 45 healthy participants. Demographic data, body mass index, Visual Analog Scale, and Western Ontario and McMaster Universities Arthritis questionnaire scores were gathered. On radiography, the Kellgren and Lawrence score was acquired. The knee joint ultrasonography results were documented. The blood level of Dkk-1 was determined using the enzyme-linked immunosorbent assay method. Results: < 0.001). Dkk-1 serum levels were significantly lower in individuals with ultrasonographic knee effusion (median = 3.2, interquartile range [IQR] = 3.1-4.16) than in those without effusion (median = 4.79, IQR = 4.04-5.09). Furthermore, there was a strong correlation between Dkk-1 levels and ultrasonographically measured femoral cartilage thickness. Conclusion: Dkk-1 is an interesting radiological indicator associated with degenerative articular joint disease. It may have a crucial function in slowing the process of degeneration in knee OA and reflecting the disease's radiographic and clinical severity.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".