Perinatal inflammation is associated with social and motor impairments in preterm children without severe neonatal brain injury
Bibliographic record
Abstract
OBJECTIVE: To test the association between exposure to perinatal inflammation - i.e. clinical chorioamnionitis or early-onset neonatal infection - in preterm children without severe neonatal brain injury and neurodevelopmental outcome at 30 months of corrected age (CA). DESIGN: Cross-sectional study from a French regional cohort of clinical follow-up (SEVE Network). PATIENTS: One hundred sixty-four surviving neonates without severe brain injury - namely, grade III and IV cerebral hemorrhage and cystic periventricular leukomalacia - and without late-onset neonatal inflammation exposure - namely, late-onset neonatal infection and necrotizing enterocolitis -, born at less than 33 weeks of gestational age from November 2011 to June 2015 and enrolled in the SEVE Network. MAIN OUTCOME MEASURE: Global developmental quotient (DQ) score of the revised Brunet-Lézine scale and its four indices measured by the same neuropsychologist at 30 months of CA. RESULTS: After multivariate analysis, exposure to perinatal inflammation was not found significantly associated with a modification of the global DQ score (coefficient -1.7, 95% CI -4.8 to 1.3; p = 0.26). Exposure to perinatal inflammation was associated with a decrease of the gross motor function DQ score (coefficient -6.0, 95% CI -9.9 to -2.1; p < 0.01) and a decrease of the sociability DQ score (coefficient -5.1, 95% CI -9.2 to -0.9; p = 0.02). Language and visuospatial coordination DQ scores were not affected by exposure to perinatal inflammation. CONCLUSION: Exposure to perinatal inflammation in preterm children without severe neonatal brain injury is independently associated with decreased motor and social abilities at 30 months of CA.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".