Altered subchondral bone mineral density in painful knee osteoarthritis without cysts: a comparative analysis of lateral and medial regions
Bibliographic record
Abstract
OBJECTIVES: This study aims to elucidate the mechanisms underlying pain generation and progression in knee osteoarthritis (KOA) by investigating alterations in proximal tibial subchondral bone mineral density (BMD) among individuals experiencing painful KOA without subchondral cysts, utilizing three-dimensional (3D) bone densitometry. METHODS: A prospective, single-center data collection was conducted at the 960th Hospital of the Joint Logistics Support Force of the PLA. We employed a 3D bone densitometry technique to assess BMD in specific regions. Knee pain was evaluated using the Western Ontario and McMaster Universities Arthritis Index (WOMAC). Based on WOMAC scores, the knees of each patient were categorized into a moderate-severe pain group and a mild pain group. We explored the correlation between BMD and pain and analyzed differences among various pain subgroups. RESULTS: Computed tomography (CT) imaging of 84 knees from 42 patients revealed a significant association between BMD and pain. The moderate-to-severe pain group exhibited higher BMD in the lateral compartment compared to the mild pain group. Statistically significant differences were observed in 0-2.5 mm lateral-posterior, 2.5-5.0 mm lateral-anterior, 5.0-7.5 mm medial-posterior, and 7.5-10.0 mm lateral-posterior. CONCLUSIONS: The altered subchondral bone density of the proximal tibia may play a pivotal role in the pathogenesis of KOA-related pain in patients.
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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 | 0.000 |
| 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) | 0.002 | 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".