Metabolic bone markers can be related to preserved insulin secretion in children with newly diagnosed type 1 diabetes
Bibliographic record
Abstract
INTRODUCTION: Type 1 diabetes (T1D) may be associated with numerous complications including bone metabolism disorders. The aim of the study was to evaluate the bone metabolism markers twice in children with a newly diagnosed T1D and after an average of seven months of its duration in relation to parameters of the clinical course of diabetes. MATERIAL AND METHODS: In 100 T1D patients and 52 control subjects, the following bone turnover markers were evaluated: osteocalcin - OC, osteoprotegerin - OPG, sRANKL, and deoxypyridoline in urine - DPD and DXA examination was also performed. RESULTS: Lower OC concentration at T1D onset in comparison to controls (p < 0.001) and its increase during follow-up (p < 0.001) was ob-served. The OPG concentration was elevated at T1D onset as compared to the control group (p = 0.024) and decreased thereafter (p < 0.001). The s-RANKL level increased during follow-up (p < 0.001) and was lower than in controls (p < 0.001). Urine DPD con-centration also increased during follow-up in the T1D patient group (p < 0.001) and was higher in comparison to the control group (p = 0.021). BMD-TBLH was higher in the control group as compared to patients both at T1D onset (p = 0.025) and in follow-up ob-servation (p = 0.034). Moreover, OPG correlated positively with glycated haemoglobin (HbA1c) (p = 0.004) and negatively with fasting C-peptide level (p = 0.046) and BMI Z-score (p = 0.003), whereas s-RANKL correlated positively with both fasting (p < 0.001) and stimulated C-peptide levels (p < 0.001). CONCLUSIONS: Bone metabolism disorders observed at T1D onset in children and modified after reaching the metabolic control of the disease seem to be most strongly associated with preserved insulin secretion.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".