Transient neonatal hyperinsulinism: early predictors of duration
Bibliographic record
Abstract
Abstract Objectives Hyperinsulinism is the most common cause of recurrent hypoglycemia in infants, with transient and permanent forms. Currently, there are no effective tools to predict severity and time to resolution in infants with transient hyperinsulinism (tHI). Therefore, our objective was to assess whether early glucose trends predict disease duration in tHI. Methods A retrospective, pilot cohort of infants admitted with tHI was phenotyped for clinical and laboratory parameters. Blood glucose (BG) values were collected from the first documented hypoglycemia for 120 h (five days). Results In 27 neonates with tHI, the presence of fetal distress (p=0.001) and higher mean daily BG (p=0.035) were associated with shorter time to resolution of hypoglycemia. In a further sensitivity analysis that grouped the cohort by the presence or absence of fetal distress, we found that in neonates without fetal distress, lower mean daily glucose was associated with longer disease duration (R2=0.53, p=0.01). Conclusions Our pilot data suggests that predictors for disease duration of tHI may be elicited in the first week of life, and that tHI associated with fetal distress may represent a distinct clinical entity with a shorter time course.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".