Profile and early prediction of neuromotor outcome of very low birth weight infants
Bibliographic record
Abstract
Background: Very low birth weight infants are at increased risk of developmental disorder. Early identification is necessary for planning and implementation of early intervention. Aims and Objective: To test the association of neurological examination at 40 weeks and 3 months with neuro motor outcome of VLBW infants at 24 months and to identify the perinatal and neonatal risk factors for atypical neurological outcome. Materials and Methods: It is a prospective cohort study. Consecutive 120 VLBW infants were enrolled in a single centre level III neonatal unit of a teaching hospital. Neuro motor assessment was done by Dubowitz neurological examination at 40 weeks and by Hammersmith infant neurological examination (HINE) at 3 months and 12 months at neurodevelopmental clinic. Motor assessment were performed by Alberta Infant Motor Scale (AIMS) at 6 and 12 months and by Bayley Scale of Infant & Toddler scale, (BSID) 3rd edition at 6,12 and 24 months respectively. All assessment ages were corrected for prematurity. Results: At 12 months 4.5% infants developed abnormal tone and 5.6% had motor delay. Four infants developed cerebral palsy at 24 months. Shock in neonatal period had significant association with suboptimal motor outcome at 12 months. Suboptimal HINE score at 12 months was rightly predicted at 3 months by HINE. Conclusion: Early anticipation and early identification of abnormal neuro motor outcome of VLBW infants can be used as simple and cost-effective measures for preventing long term neuro motor morbidity at resource limited countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".