Neonatal Hypocalcemic Convulsions Secondary to Vitamin D Deficiency
Bibliographic record
Abstract
Vitamin D deficiency is a major public health issue affecting large proportions of the population. Therefore, maternal vitamin D deficiency is not uncommon. Infants born to mothers who are deficient in vitamin D are at risk of developing vitamin D deficiency and hypocalcaemia. We reported here a case of neonatal hypocalcaemic seizures secondary to vitamin D deficiency. A 25-day old, full term male infant presented two episodes of generalized seizures. Laboratory investigations in blood, revealed low calcium level at 5.5 mg/dl, elevated phosphatemia level at 9.6 mg/dl and high parathormone (PTH) level at 133.4 pg/ml. Unfortunately 25 hydroxy vitamin D assay was not available in the infant but it was low in the mother at 12.9 ng/ml. The infant was commenced on vitamin D and calcium supplements during some weeks which allowed normalization of calcium levels. After several months of treatment cessation, the infant was doing well, and his development was according to his chronological. His calcium, phosphatemia and PTH levels were within normal ranges without any treatment. Hypocalcemia in this infant was presumably due to vitamin D deficiency as other causes were unlikely. Neonatal hypocalcaemic seizures are a rare presentation of vitamin D deficiency. This case could have been preventable had the mother been given vitamin D supplementation during pregnancy and early lactation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".