Predicting severe motor impairment in preterm children at age 5 years
Bibliographic record
Abstract
OBJECTIVE: To determine whether the ability to predict severe motor impairment at age 5 years improves between birth and 18 months. DESIGN: Ancillary study of the Caffeine for Apnea of Prematurity Trial. SETTING AND PATIENTS: International cohort of very low birth weight children who were assessed sequentially from birth to 5 years. OUTCOME MEASURES: Severe motor impairment was defined as a score <5th percentile on the Movement Assessment Battery of Children (MABC), or inability to complete the MABC because of cerebral palsy. Multivariable logistic regression cumulative risk models used four sets of predictor variables: early neonatal risk factors, risk factors at 36 weeks' postmenstrual age, risk factors at a corrected age of 18 months, and sociodemographic variables. A receiver operating characteristic curve (ROC) was generated for each model, and the four ROC curves were compared to determine if the addition of the new set of predictors significantly increased the area under the curve (AUC). RESULTS: Of 1469 children, 291 (19.8%) had a severe motor impairment at 5 years. The AUC increased from 0.650 soon after birth, to 0.718 (p<0.001) at 36 weeks' postmenstrual age, and to 0.797 at 18 months (p<0.001). Sociodemographic variables did not significantly improve the AUC (AUC=0.806; p=0.07). CONCLUSIONS: Prediction of severe motor impairment at 5 years of age using a cumulative risk model improves significantly from birth to 18 months of age in children with birth weights between 500 g and 1250 g. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov number NCT00182312.
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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 | 0.000 | 0.000 |
| 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".