Neurodevelopmental outcomes in preterm or low birth weight infants with germinal matrix-intraventricular hemorrhage: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: This meta-analysis aimed to identify the near- and long-term neurodevelopmental prognoses of preterm or low birth weight (LBW) infants with different severities of intraventricular hemorrhage (IVH). METHODS: Four databases were searched for observational studies that were qualified using the Newcastle-Ottawa Scale. RESULTS: 37 studies involving 32,370 children were included. Compared to children without IVH, children with mild IVH had higher incidences of neurodevelopmental impairment (NDI), cerebral palsy (CP), motor/cognitive delay, hearing impairment and visual impairment, as well as lower scores of the mental development index (MDI) and psychomotor development (PDI). Moreover, compared to mild IVH, severe IVH increased susceptibilities of children to NDI, motor delay, CP, hearing impairment and visual impairment, with worse performances in MDI, PDI, motor score and IQ. Mild IVH was not associated with seizures or epilepsy. CONCLUSIONS: Adverse neurodevelopmental outcomes positively associated with the occurrence and severity of IVH in preterm or LBW infants, providing evidence for counseling and further decisions regarding early therapeutic interventions. IMPACT: Adverse neurodevelopmental outcomes later in life were closely associated with the occurrence and severity of IVH in preterm or LBW infants. Our results highlight the importance to make prediction of the neurodevelopmental outcomes of children born preterm or LBW with a history of IVH, which will guide affected parents when their children need clinical interventions to reach the full potential. We emphasize the importance of identifying specific developmental delays that may exist in children with IVH, providing detailed information for the development of comprehensive intervention measures.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.048 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".