Correlation between grading of MRI-determined thickness of knee synovitis and knee joint function and pain scores in end-stage osteoarthritis
Bibliographic record
Abstract
Objective To investigate if MRI findings of the thickness of synovitis could be used as criteria for the indications of knee replacement. Methods Thirty-one patients with end-stage knee osteoarthritis (OA) were selected and received the following examinations: (1) noninvasive MRI evaluation for grading the synovial thickness of the investigated sites (i.e., medial and lateral parapatellar recesses, and medial and lateral suprapatellar pouches; synovitis was categorized into grade zero to three on the basis of the thickness); (2) determination of knee-joint pain scores (visual analogue scale, VAS score) and functional scores Western Ontario and McMaster Univerisities Osteoarthrifis index, WOMAC) before total knee arthroplasty (TKA). Pearson’s linear test or Spearman rank test was used to analyze the correlation between synovial thickness and WOMAC OA index, and VAS score. Results Statistical analysis revealed no significant differences in MRI synovial thickening grade across the different regions of the knee.No correlation existed between the grades of MRI-determined thickness for synovitis and knee joint function scores with pain score (rs=0.17, P>0.05; rs=0.32, P >0.05), as well as no correlation existed between the different regions of the knee and the above factors respectively. Conclusion The grade of MRI-determined thickness of synovitis shows no correlation with the subjective scores in the patients with end-stage knee OA, thus the grades of MRI-determined thickness cannot be used as criteria for knee joint replacement indications, and further study on the relation among MRI, VAS and WOMAC scores is still warranted. Key words: Osteoarthritis; Magnetic resonance imaging; Synovial membrane; Visual analog scale
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".