Associations between fluorescence optical imaging and magnetic resonance imaging and symptoms in hand osteoarthritis
Bibliographic record
Abstract
OBJECTIVES: To investigate whether Fluorescence Optical Imaging (FOI) enhancement and MRI-defined synovitis are associated with pain and physical function in hand OA patients. METHODS: Bilateral FOI scans and MRI of the dominant hand were available for 221 patients. Finger joints were examined for tenderness on palpation. Pain in individual finger joints during the last 24 h and last 6 weeks and hand pain intensity by the Australian/Canadian hand index and Numeric Rating Scale were self-reported. On joint level, we applied logistic regression with generalized estimating equations to examine whether FOI enhancement and MRI-defined synovitis were associated with pain in the same joint. On subject level, we applied linear regression to assess whether FOI and MRI sum scores were associated with pain intensity and physical function. RESULTS: Metacarpophalangeal and thumb base joints were excluded from analyses due to little/no FOI enhancement. Finger joints with FOI enhancement on the composite image had higher odds (95% CI) of pain during the last 6 weeks [grade 1: 1.4 (1.2-1.6); grade 2-3: 2.1 (1.7-2.6)]. Similar results were found for joint pain during the last 24 h and joint tenderness in fingers. Numerically stronger associations were found between MRI-defined synovitis and finger joint pain/tenderness. FOI and MRI sum scores demonstrated no/weak associations with hand pain and physical function. CONCLUSION: FOI enhancement and MRI-defined synovitis were associated with pain in the same finger joint. None of the imaging modalities demonstrated consistent associations with pain, stiffness and physical function on subject level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 | 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".