Knee osteoarthritis patients with more subchondral cysts have altered tibial subchondral bone mineral density
Bibliographic record
Abstract
BACKGROUND: Subchondral bone cysts are a widely observed, but poorly understood, feature in patients with knee osteoarthritis (OA). Clinical quantitative computed tomography (QCT) has the potential to characterize cysts in vivo but it is unclear which specific cyst parameters (e.g., number, size) are associated with clinical signs of OA, such as disease severity or pain. The objective of this study was to use QCT-based image-processing techniques to characterize subchondral tibial cysts in patients with knee OA and to explore relationships between proximal tibial subchondral cyst parameters and subchondral bone density as well as clinical characteristics of OA (alignment, joint space narrowing (JSN), OA severity, pain) in patients with knee OA. METHODS: The preoperative knee of 42 knee arthroplasty patients was scanned using QCT. Patient characteristics were obtained, including OA severity, knee pain, JSN, and alignment. We used 3D image processing techniques to obtain cyst parameters including: cyst number, cyst number per proximal tibial volume, cyst volume per proximal tibial volume, as well as maximum and average cyst volume across the proximal tibia, as well as regional bone mineral density (BMD) excluding cysts. We used Spearman's correlation coefficients to explore associations between patient characteristics and cyst parameters. RESULTS: At both the medial and lateral compartments of the proximal tibia, greater cyst number and volume were associated with higher BMD. At the lateral region, cyst number and volume were also associated with lateral OA severity, lateral JSN, alignment and sex. Pain was not associated with any cyst parameters at any region. CONCLUSION: Cyst number and volume were associated with BMD at both the medial and lateral compartments. Lateral cyst number and volume were also associated with joint alignment, OA severity, JSN and sex. This is the first study to use clinical QCT to explore subchondral tibial cysts in patients with knee OA and provides further evidence of the relationships between subchondral cysts and clinical OA characteristics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".