Neonatal hyperinsulinism—broadening the differential diagnosis
Bibliographic record
Abstract
The patient is a 12-month-old late preterm (36 + 6 weeks) female born to a 32-year-old, G2P1 mother. The father’s ancestral background is mixed: East Indian and African, and the mother’s is Caucasian. At birth, baby was admitted to the NICU for respiratory distress. Birth weight was 3,330 g (86th centile), length was 47 cm (43rd centile), and head circumference was 35.5 cm (97th centile). She had multiple dysmorphisms, including low set ears, flattened nasal bridge, coarse facial features (Figures 1 and 2), deep hand creases, and severe pectus excavatum causing right ventricular compression and right ventricular outlet obstruction. Hypoglycemia was noted at 2 hours of life and persisted for four days, requiring an intravenous 10% dextrose infusion. No critical sample was obtained as hypoglycemia resolved. Severe laryngomalacia and gastroesophageal reflux were diagnosed. Genetics was consulted and microarray was unremarkable. On admission for overnight oximetry pending supraglottoplasty repair at 3 months of age, she was incidentally found to be hypoglycemic, with blood glucose levels of 1.8 mmol/L. She required a continuous glucose infusion to maintain normoglycemia. A critical sample obtained when the patient was hypoglycemic demonstrated inappropriately elevated levels of insulin 40 pmol/L, consistent with hyper-insulinemic hypoglycemia.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".