Cognitive and academic outcomes of large‐for‐gestational‐age babies born at early term: A systematic review and meta‐analysis
Bibliographic record
Abstract
INTRODUCTION: gestational weeks) in large-for-gestational-age infants may reduce perinatal risks such as shoulder dystocia, but it may also increase the long-term risks of reduced cognitive abilities. This systematic review aimed to evaluate the cognitive and academic outcomes of large-for-gestational-age children born early term vs full term (combined or independent exposures). MATERIAL AND METHODS: The protocol was registered in the PROSPERO database under the registration no. CRD42024528626. Five databases were searched from their inception until March 27, 2024, without language restrictions. Studies reporting childhood cognitive or academic outcomes after early term or large-for-gestational-age births were included. Two reviewers independently screened the selected studies. One reviewer extracted the data, and the other double-checked the data. The risk of bias was assessed using the Newcastle-Ottawa Quality Assessment Scale. In addition to narrative synthesis, meta-analyses were conducted where possible. RESULTS: Of the 2505 identified articles, no study investigated early-term delivery in large-for-gestational-age babies. Seventy-six studies involving 11 460 016 children investigated the effects of either early-term delivery or large-for-gestational-age. Children born at 37 weeks of gestation (standard mean difference, -0.13; 95% confidence interval, -0.21 to -0.05), but not at 38 weeks (standard mean difference, -0.04; 95% confidence interval, -0.08 to 0.002), had lower cognitive scores than those born at 40 weeks. Large-for-gestational-age children had slightly higher cognitive scores than appropriate-for-gestational-age children (standard mean difference, 0.06; 95% confidence interval, 0.01-0.11). Similar results were obtained using the outcomes of either cognitive impairment or academic performance. CONCLUSIONS: No study has investigated the combined effect of early-term delivery on cognitive scores in large-for-gestational-age babies. Early-term delivery may have a very small detrimental effect on cognitive scores, whereas being large for gestational age may have a very small benefit. However, evidence from randomized controlled trials or observational studies is required.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.023 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".