Correlation of anxiety and chronic pain to grade of synovitis in patients with knee osteoarthritis.
Bibliographic record
Abstract
BACKGROUND: This study was conducted with the objective of finding out the correlation between synovial inflammation measured histopathologically and subjective symptoms; anxiety and chronic pain, in knee osteoarthritis (OA). SUBJECTS AND METHODS: Thirty patients were included in the study. Ten of them were in a control group with meniscal injury, ten had early OA and 10 had late OA. Knee radiographs were graded using Kellgren-Lawrence classification. Synovial biopsies were taken during surgery or arthroscopy and synovitis score was measured by Krenns method. Anxiety was measured with Beck Anxiety Inventory and pain was taken as part of the WOMAC score (The Western Ontario and McMaster Universities Arthritis Index). RESULTS: Krenn synovitis score was determined as: no synovitis, low-grade synovitis and high-grade synovitis. Group with low-grade synovitis had significantly higher pain score than high-grade synovitis group (p=0.011). No-synovitis group had significantly lower Beck Anxiety Inventory than low-grade synovitis group (p=0.014) and high-grade synovitis (p=0.008). There are no significant differences between low-grade synovitis and high-grade synovitis in anxiety score (p=0.912). CONCLUSIONS: Chronic pain is more present in late osteoarthritis, when synovitis is less pronounced. Anxiety affects patients who suffer osteoarthritis, but it is statistically the same regarding synovitis grade, i.e. whether it is early or late 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 | 0.000 | 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) | 0.001 | 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".