Long-Term Inflammation and Glucocorticoid Therapy Impair Skeletal Modeling During Growth in Childhood Crohn Disease
Bibliographic record
Abstract
CONTEXT: Glucocorticoids and inflammation inhibit bone formation; however, the impact on skeletal modeling is unknown. OBJECTIVES: The objectives of the study were to examine changes in bone mineral density (BMD) and cortical structure after Crohn disease (CD) diagnosis and identify associations with growth, glucocorticoids, and disease activity. DESIGN/PARTICIPANTS: This was a prospective cohort study among 76 CD participants, aged 5-21 years. Tibia quantitative computed tomography trabecular BMD and cortical dimensions were obtained at diagnosis and 6 and 12 and a median of 42 months later; 51 completed the final visit. OUTCOMES: Sex, race, and age-specific Z-scores were generated for outcomes based on more than 650 reference participants, and cortical dimension Z-scores were further adjusted for tibia length. Generalized estimating equations were used to model changes in Z-scores. RESULTS: Disease activity improved over the study interval (P < .001). Trabecular BMD Z-scores improved over the first 6 months; increases were associated with improved disease activity (P < .001), younger age (P = .005), and increases in vitamin D levels (P = .02). Greater increases in tibia length were associated with greater increases in cortical area Z-scores (P < .001). Greater glucocorticoid doses and disease activity were significantly associated with failure to accrue cortical area and were more pronounced with greater linear growth (interaction P < .05). Mean (±SD) trabecular BMD (-1.0 ± 1.21) and cortical area (-0.57 ± 1.10) Z-scores at the final visit were significantly reduced. CONCLUSIONS: CD was associated with persistent deficits in trabecular BMD, although younger participants demonstrated a greater potential for recovery. In addition, greater linear growth was associated with a greater recovery of cortical dimensions, especially among participants with less glucocorticoid exposure and inflammation. These data suggest that younger age and concurrent growth provide a window of opportunity for skeletal recovery.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".