Decreased Bone Turnover Markers in Children on Long‐Term Parenteral Nutrition (PN) for Intestinal Failure (IF)
Bibliographic record
Abstract
BACKGROUND: Metabolic bone disease (MBD) is a well-recognized but poorly understood complication of long-term parenteral nutrition (PN). Bone histomorphometry in adults has provided useful information but does not provide quantitative measures of bone resorption and is to invasive for children. Measurement of bone turnover markers provides an alternative less invasive approach. We therefore aimed to measure bone turnover markers in children on long-term PN for intestinal failure (IF), and to compare them to age- and gender-matched controls. METHODS: Serum concentrations of osteocalcin (OC), bone-specific alkaline phosphatase (BSAP), and c-telopeptide (CTx) were measured in IF patients treated at a multidisciplinary intestinal rehabilitation and home PN program at the Hospital for Sick Children, Toronto, Canada. Age- and gender-matched control participants were recruited for comparison. RESULTS: A total of 13 IF patients and 20 control participants were recruited. IF patients had lower serum OC and CTx concentrations when compared with controls: 42.43 ± 11.54 vs 68.39 ± 20.95 µg/L (P < .01) and 7.454 ± 2.17 vs 9.246 ± 1.92 (P < .05; mean ± SD) µg/L for OC and CTx, respectively. In a subgroup of 9 IF patients for whom BMD was available, OC and CTx concentration were negatively correlated to BMD (g/cm(2)) and BMD z score. CONCLUSION: Bone turnover markers may be useful indicators for identifying children on long-term PN at risk of MBD. Further studies are needed to validate the current results and determine the factors that influence the occurrence and evolution of MBD in children on PN.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".