Treatment response variations to a single large bolus of enteral cholecalciferol in vitamin D deficient critically Ill children: Metabolomic insights for precision nutrition
Bibliographic record
Abstract
Vitamin D deficiency (VDD) is prevalent globally and in pediatric intensive care units, where it represents a modifiable risk factor that may impact patient recovery during hospitalization. Herein, we performed a retrospective analysis of serum samples from a phase-II randomized placebo-controlled trial involving a single large bolus of 10,000 IU/kg vitamin D3 ingested by critically ill children with VDD (25-OH-D < 50 nmol/L). Targeted and untargeted methods were used to comprehensively measure 6 vitamin D metabolites, 239 lipids, 68 polar metabolites, and 4 electrolytes using a multi-step data workflow for compound authentication. Complementary statistical methods classified circulating metabolites/lipids associated with vitamin D repletion following high-dose vitamin D3 intake (n = 20) versus placebo (n = 11) comprising an optional standard of care maintenance dose (< 1000 IU/day). There was a striking increase in median serum concentrations of 25-OH-D3 (4.7-fold), 3-epi-25-OH-D3 (24-fold) and their C3-epimer ratio (6.7-fold) in treated patients on day 3, whereas serum vitamin D3 peaked on day 1 (128-fold) unlike placebo. Treatment response differences were attributed to D3 bioavailability and C3-epimerase activity without evidence of hypercalcemia. For the first time, we report the detection of circulating 3-epi-D3 that was strongly correlated with vitamin D3 uptake (r = 0.898). Metabolomic studies revealed that vitamin D sufficiency (serum 25-OH-D >75 nmol/L) coincided with lower circulating levels of 3-methylhistidine, cystine, S-methylcysteine, uric acid, and two lysophosphatidylcholines 7 days after treatment. Rapid correction of VDD was associated with indicators of lower oxidative stress, inflammation, and muscle protein turn-over that may contribute clinical benefits in high-risk critically ill children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".