Diabetes Is Associated With Increased Hand Pain in Erosive Hand Osteoarthritis: Data From a Population‐Based Study
Bibliographic record
Abstract
OBJECTIVE: To explore factors related to hand pain in persons with radiographic hand osteoarthritis (OA). METHODS: Persons in the Musculoskeletal Pain in Ullensaker Study with radiographic hand OA (≥1 joint with Kellgren/Lawrence grade ≥2) were included (n = 530). We examined the cross-sectional association between possible explanatory variables and hand pain in the entire sample and in 2 hand OA phenotypes (erosive versus nonerosive) using structural equation analyses. Outcome variables were the Australian/Canadian Hand Osteoarthritis Index (AUSCAN; range 0-20) and number of tender finger joints upon palpation (NTJ; range 0-30). RESULTS: The mean age was 65 years (40-79 years) and 375 participants were women (71%). Diabetes mellitus, female sex, lower education status, familial OA, infrequent alcohol drinking, widespread pain, poor mental health, and higher number of finger joints with ultrasound-detected synovitis and radiographic OA were related to more hand pain in the entire sample. Stratified analyses showed that diabetes mellitus was strongly associated with AUSCAN pain (B-unstandardized coefficient = 3.81 [95% confidence interval (95% CI) 2.27, 5.35]) and NTJ (B-unstandardized coefficient = 4.16 [95% CI 2.01, 6.31]) in erosive hand OA only. In nonerosive OA, lower education status, having familial OA, and poor mental health were associated with hand OA pain. Widespread pain was associated with both outcomes in both phenotypes. CONCLUSION: Structural and inflammatory OA changes as well as demographic factors, psychosocial factors, and diabetes mellitus were associated with pain in hand OA. The strong association between diabetes mellitus and pain in erosive hand OA should be further explored.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".