Motor skills as early indicators for cognitive development in preterm infants with very low birth weight
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Preterm babies born with very low birth weight (VLBW, birth weight <1500 g) have inferior long-term neurodevelopmental outcomes to term babies. This study aimed to identify early predictive neurodevelopmental factors for future cognitive outcomes that could serve as indicators for early intervention strategies. METHODS: This longitudinal cohort study enrolled 146 VLBW preterm infants, identified between 2011 and 2020. Each child underwent four neurodevelopmental assessments (at ages 6,12, 24, and 60 months) using the Bayley-III and Wechsler Preschool and Primary Scale of Intelligence-IV examinations. Correlation and linear regression analyses were performed to determine the correlation between early neurodevelopmental status and late cognitive outcomes. We concurrently considered neonatal medical complications and socioeconomic variables as risk factors to develop a prediction model of cognitive outcomes at five years old. RESULTS: A total of 146 VLBW children, born with a mean weight of 1090.4 ± 229.6 g and a mean gestational age of 28.2 ± 2.0 weeks, were evaluated. At 6 months of age, motor outcome was the only factor that exhibited a significant correlation with cognitive development at 5 years of age (p < 0.01, r = 0.242). The strength of the correlation between motor and cognitive function increased with age, reaching greater significance at 12 and 24 months (p < 0.001, r = 0.409 and 0.472, respectively). The linear regression model demonstrated that neonatal medical conditions and Bayley motor score at six months old predicted 26% of the variance in the Full-Scale Intelligence Quotient (FSIQ) at five years old. CONCLUSION: The results of the present study show that motor function was the earliest and persistent predictor of FSIQ. This underscores the importance of prioritizing motor development in interventions as early as six months of age, which could substantially advance the timing of early intervention programs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it