Corrected head circumference centiles as a possible predictor of developmental performance in high-risk neonatal intensive care unit survivors
Bibliographic record
Abstract
The aim of this study was to evaluate the predictive value of corrected head circumference (HC) centiles at 2 years of age with respect to developmental performance in a series of high-risk neonatal intensive care unit (NICU) survivors with microcephaly. The study used a retrospective review of the clinical files of children seen in a clinic devoted to the follow-up of all high-risk survivors of a hospital's level III NICU. All children with microcephaly (occipital-frontal circumference below the 2nd centile for sex) at 2 years of age were identified. The HC obtained at 2 years was corrected to the ages for which the absolute HC corresponded to either the 50th or 2nd centile for the child's sex. Of 312 high-risk patients followed, 38 (12.2%) were microcephalic. Fifteen performed below the 50th age-corrected HC centile (severe developmental delay), 12 performed between the 50th and 2nd age-corrected HC centile (moderate developmental delay), and 11 performed above the 2nd age-corrected HC centile (mild developmental delay). The absolute value of HC measurement was not a predictor of developmental performance. Of all clinical factors evaluated, only coexisting epilepsy was found to be a significant predictor of less than the 50th age-corrected HC centile developmental performance (chi2=6.134, p=0.01). We conclude that in a high-risk population, the presence of microcephaly implies developmental impairment, though neither the absolute HC measurement nor the corrected HC centile is predictive. Coexisting epilepsy in this context appears to worsen developmental outcome.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".