Long term type 1 diabetes is associated with hand pain, disability and stiffness but not with structural hand osteoarthritis features – The Dialong hand study
Bibliographic record
Abstract
OBJECTIVE: To explore whether having long-term type 1 diabetes (>45 years) is associated with a higher prevalence of radiographic hand OA, erosive hand OA and increased hand pain, disability and stiffness. METHODS: In total N = 96 persons with type 1 diabetes diagnosed before 1970 were included (mean [SD] age: 62.2 [7.4], mean [SD] HbA1c: 7.43 [0.80] and N = 49 [51%] men). Regular measurements of their HbA1c were obtained till 2015. We included N = 69 healthy controls without any diabetes (mean [SD] age: 63.0 [7.0], mean [SD] HbA1c: 5.41 [0.32], N = 29 [42%] men). The groups were compared for radiographic hand OA (Kellgren-Lawrence grade ≥2 in ≥1 joint) and erosive hand OA (central erosions in ≥1 joint), Australian/Canadian index (AUSCAN) for hand pain, disability and stiffness using regression analyses adjusted for age, sex, educational level and waist circumference. RESULTS: We found no associations between having long term type 1 diabetes and more prevalent radiographic hand OA (OR = 0.83, 95% CI = 0.38-1.81). We found a trend towards higher prevalence of erosive hand OA in diabetes patients (OR = 2.96, 95% CI = 0.82-10.64). Strong and consistent associations were observed between long term type 1 diabetes and increased hand pain (B = 2.78, 95% CI = 1.65-3.91), disability (B = 5.30, 95% CI = 3.48-7.12) and stiffness (B = 2.00, 95% CI = 1.33-2.67). These associations were particularly strong for women and participants below the median age of 61 years. CONCLUSION: Long-term type 1 diabetes was not associated with radiographic hand OA, but was strongly associated with hand pain, disability and stiffness. The association between diabetes and erosive hand OA warrants further investigation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".