Predicting long-term neurodevelopmental outcomes for children born very preterm: a systematic review
Bibliographic record
Abstract
CONTEXT: Children born very preterm (<32 weeks' gestation) have increased risk of neurodevelopmental difficulties compared with those born at term. While various neonatal exposures have been linked with later developmental challenges, identifying those at risk of difficulties later in childhood remains a challenge but is essential for targeting early intervention and counselling families. OBJECTIVE: To systematically review and synthesise the evidence regarding early medical and environmental factors for neurodevelopmental impairment, cognitive, motor and behavioural outcomes for children born very preterm. DESIGN: Ovid MEDLINE, Embase and PubMed were searched for articles between 1 January 1990 and 29 April 2024 reporting on a representative, prospective geographical, network-based or multisite cohorts of children born <32 weeks' gestation. MAIN OUTCOME MEASURES: Neurodevelopmental impairment, cognitive, motor and emotional-behavioural functioning in children aged 36 months to 18 years. Data were extracted and reported descriptively due to heterogeneity in study measures. RESULTS: From 18 012 records, 29 studies from 16 cohorts were included. Brain injury, bronchopulmonary dysplasia, male sex and lower socioeconomic status were the most consistent predictors of neurodevelopmental impairment, IQ, working memory, cerebral palsy, fine motor skills and some behavioural measures. Emotional problems were generally not associated with neonatal variables investigated to date. CONCLUSION: Numerous factors are independently associated with childhood outcomes after being born very preterm, with specific predictors varying across domains of functioning and limited available evidence for some predictor-outcome combinations. Knowledge of these factors may assist in targeting those at highest risk for closer surveillance and early intervention.PROSPERO registration numberCRD42022368957.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".