Vitamin D Deficiency and Insufficiency in 2 Independent Cohorts of Patients with Systemic Sclerosis
Bibliographic record
Abstract
OBJECTIVE: To investigate 25-OH vitamin D concentrations in 2 independent systemic sclerosis (SSc) populations from France and Italy. METHODS: We studied 156 consecutive SSc patients comparable for demographic characteristics: 90 from Northern France and 66 from Southern Italy. 25-OH vitamin D, intact parathyroid hormone, and serum total calcium and phosphorus were measured in all patients. Vitamin D concentrations < 30 ng/ml were considered insufficiency, while values < 10 ng/ml were classified as deficiency. RESULTS: Vitamin D insufficiency and deficiency rates were very high and comparable between the 2 populations: 74/90 (82%) versus 57/66 (86%) for insufficiency and 29/90 (32%) versus 15/66 (23%) for deficiency, respectively, in the French and Italian patients. They were not influenced by vitamin D supplementation, which was not statistically different in the 2 groups. In the combined populations, a significant negative correlation was found between low vitamin D levels and European Disease Activity Score (p = 0.04, r = -0.17) and an even more significant correlation was found with acute-phase reactants (p = 0.004, r = -0.23 for erythrocyte sedimentation rate), and low levels of vitamin D were associated with the systolic pulmonary artery pressure (sPAP) estimated by echocardiography (p = 0.004). In multivariate analysis, vitamin D deficiency was associated with sPAP (p = 0.02). CONCLUSION: Vitamin D deficiency was very common in the 2 SSc populations, independent of geographic origin and vitamin D supplementation. This suggests that common vitamin D supplementation does not correct the deficiency in SSc patients, and that a higher dose is probably needed, especially in those with high inflammatory activity or severe disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".