Analytical Unreliability of 25 Hydroxy Vitamin D Measurements in Pre-Term Neonates
Bibliographic record
Abstract
BACKGROUND: Vitamin D supplementation is common practice for neonates and infants due to limited stores of vitamin D at birth. Although not commonly encountered, vitamin D toxicity can occur due to over-supplementation. However, toxic concentrations are often not included in method validation experiments, and assays often are not validated in the neonatal population. METHODS: We compared serial 25 hydroxy vitamin D [25(OH)D] measurements in pre-term neonates receiving 25(OH)D supplementation and identified 12 patients wherein concentrations of 25(OH)D were above 50 ng/mL (125 nM) that required additional investigations as the 25(OH)D results did not match the clinical picture. Available samples were compared across 4 immunoassay platforms (LIAISON XL, Roche Cobas e602, Abbott Alinity i, and Siemens Centaur XP) and LC-MS/MS. RESULTS: Concentrations of 25(OH)D observed on one individual immunoassay platform (LIAISON XL) fluctuated substantially between subsequent blood draws in select neonates with elevated concentrations. Serum samples from these patients showed variable agreement between LC-MS/MS and other immunoassay platforms. These fluctuations were not explained by the presence of 3-epimer-25(OH)D or 24,25(OH)2D. CONCLUSIONS: Although we were unable to identify a cause for the variable elevated results, our findings suggest that neonatal 25(OH)D measurements alone should not be used for assessment of nutritional monitoring, and that clinical correlation and other laboratory parameters including ionized calcium should be considered.
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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 | 0.017 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".