Neonatal amygdala volumes, procedural pain and the association with social-emotional development in children born very preterm
Bibliographic record
Abstract
Abstract Very preterm birth is associated with later social-emotional impairments, which may result from enhanced vulnerability of the limbic system during this period of heightened susceptibility in early life. In a prospective cohort study, neonates born very preterm (< 30 weeks’ gestation) underwent MRI scanning at term-equivalent age (TEA) and clinical data were collected. Procedural pain was operationalized as the number of skin breaking procedures. Amygdala volumes were automatically extracted. The Strengths and Difficulties questionnaire was used to assess social-emotional outcomes at 5 years of age. General Linear Models were employed to examine the association between neonatal amygdala volumes and social-emotional outcomes, with the timing of procedural pain exposure employed as a moderator in subsequent models. 42 preterm infants were recruited. Larger right amygdala volumes at TEA were associated with impaired prosocial behaviour. Procedural pain was found to moderate the relationship between right amygdala volumes and conduct problems, such that early or late skin breaking procedures experienced within the first few weeks of life strengthened this association. Examination of sensitive windows when the developing brain may be most vulnerable to the adverse effects of procedural pain may inform pain management practices to improve social-emotional outcomes in this population.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".