Predictors of Hand Contracture in Early Systemic Sclerosis and the Effect on Function: A Prospective Study of the GENISOS Cohort
Bibliographic record
Abstract
OBJECTIVE: To identify baseline features that predict progression of hand contractures and to assess the effect of contractures on functional status in the prospective GENISOS cohort. METHODS: Rate of decline in hand extension, as an indicator of hand contracture, was the primary outcome. We assessed longitudinal hand extension measurements, modified Health Assessment Questionnaire (MHAQ) score, Medical Outcomes Study Short Form-36 (SF-36) physical function score, and demographic, clinical, and serological variables. Subjects with ≥ 2 hand measurements at least 6 months apart were included. RESULTS: A total of 1087 hand measurements for 219 patients were available over an average of 8.1 ± 4.8 years. Hand extension decreased on average by 0.11 cm/year. Antitopoisomerase I antibody (ATA) positivity and higher modified Rodnan Skin Score (mRSS) were predictive of faster decline in hand extension (p = 0.009 and p = 0.046, respectively). In a subgroup analysis of 62 patients with ≤ 2 years from SSc onset, ATA and diffuse disease type were associated with faster decline in hand extension; anticentromere positivity was associated with slower rate of decline. Although the rate of decline in patients with disease duration ≤ 2 years was numerically higher, the difference was not statistically significant. Hand extension continued to decline in a linear fashion over time and was inversely related to overall functional status. CONCLUSION: ATA was predictive of contracture development in both early disease (≤ 2 yrs) and in the overall cohort. Hand extension declined linearly over time and was inversely associated with MHAQ and SF-36 scores. ATA positivity and higher baseline mRSS were predictive of faster decline in hand extension.
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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) | 0.001 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".