Neonatal Hypoglycaemia and Visual Development: A Review
Bibliographic record
Abstract
BACKGROUND: Many newborn babies experience low blood glucose concentrations, a condition referred to as neonatal hypoglycaemia (NH). The effect of NH on visual development in infancy and childhood is of interest because the occipital lobes, which include the primary visual cortex and a number of extrastriate visual areas, may be particularly susceptible to NH-induced injury. In addition, a number of case series have suggested that NH can affect eye and optic nerve development. OBJECTIVE: To review the existing literature concerning the effect of NH on the visual system. METHODS: A PubMed, Embase, Medline, and Google Scholar literature search was conducted using prespecified MeSH terms. RESULTS: The literature reviewed revealed no clear evidence for an effect of NH on the development of the eye and optic nerve. Furthermore, occipital and occipital-parietal lobe injuries following NH often occurred in conjunction with comorbid conditions and were not clearly linked to subsequent visual dysfunction, possibly due to difficulties in measuring vision in young children and a lack of studies at older ages. A recent, large-scale, prospective study of NH outcomes at 2 years of age found no effect of mild-to-moderate NH on visual development. CONCLUSION: The effect of NH on visual development is unclear. It is currently unknown whether NH affects visual function in mid-to-late childhood when many visual functions reach adult levels.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".