Long-Term Effects of Preterm Birth on Children’s Brain Structure: An Analysis of the Adolescent Brain Cognitive Development (ABCD) Study
Bibliographic record
Abstract
Abstract Approximately 10% of births are preterm [PTB; <37 weeks gestational age (GA)], which confers risk for cognitive, behavioral, and mental health challenges. Using the large and relatively diverse (i.e., designed to reflect sociodemographic variation in the United States population) Adolescent Brain Cognitive Development Study (ABCD Study), we characterized the impact of PTB on brain structure in middle-late childhood (9–10 years). The ABCD sample covers the GA spectrum, and the large sample size (∼11,500) permits consideration of how associations between PTB and brain structure are impacted by GA, sex, birthweight, and analytic choices such as controlling for total brain size. We found a pattern of relative cortical thinning in temporoparietal and dorsal prefrontal regions and thickening of medial prefrontal and occipital regions in PTB compared with children born full term (≥37 weeks GA). This pattern was apparent when controlling for mean thickness and when considering moderate (>32 and <37 weeks GA) and very PTB (≤32 weeks GA) separately, relative to full term birth. Surface area (SA) and subcortical volumes showed reductions in PTB children that were largely attenuated when controlling for brain size. Effects on cortical thickness (CT) and surface area were partially mediated by birthweight. Although boys are at increased risk for adverse outcomes following PTB, there was limited evidence of sex differences of PTB effects. Finally, cortical thickness effects estimated in a “discovery” sample (N = 7528) predicted GA in a holdout “replication” sample (N = 2139). Our findings help to clarify the effects of PTB on brain structure into late childhood across the GA spectrum.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".