Associations of Longitudinal Multiparametric MRI Findings and Clinical Outcomes in Intra-Articular Injections for Knee Osteoarthritis
Bibliographic record
Abstract
Abstract Background Osteoarthritis (OA) is a complex heterogeneous disease and degradation of the articular cartilage is the hallmark of the disease. The aim of this study was to investigate the association of pre-structural and structural features and cartilage volume/thickness with clinical outcome in knee OA patients who received intra-articular injection for one year. Methods A total of 24 patients with mild-to-moderate OA were included in this retrospective study. Patients received intra-articular injections and were assessed for one year after treatment onset using knee Magnetic resonance imaging (MRI) results. OA features were assessed semi-quantitatively using a Whole Organ Magnetic Resonance Imaging score (WORMS). Cartilage thickness and volumes of the medial femoral condyle (MFC) and medial tibial plateau (MTP) were quantified. T1ρ and T2 values for MFC cartilage were measured. Clinical outcome was measured using Korean Western Ontario and McMaster Universities (K-WOMAC) score and Knee Injury Osteoarthritis Outcomes (KOOS) score. Spearman’s rank test was used to evaluate the associations between change of imaging findings and clinical parameters. Results MTP and MFC cartilage thickness and MTP cartilage volume at baseline showed significant associations with clinical outcome. Changes in WORMS cartilage score for the medial femorotibial joint (MFTJ) and total joint were significantly correlated with clinical outcome. Conclusion Thicker baseline MFTJ cartilage and less progressive MFTJ and total joint cartilage loss were associated with favorable clinical response over 12 months in knee OA patients undergoing intra-articular injection.
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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) | 0.001 | 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".