Impact of Neonatal Thyroid Hormone Insufficiency and Medical Morbidity on Infant Neurodevelopment and Attention Following Preterm Birth
Bibliographic record
Abstract
BACKGROUND: Infants born preterm are at risk of both transiently reduced thyroid hormone levels and impaired neurocognitive development, including attention deficits. The objective of this study was to examine the effects of reduced thyroid hormone levels on general neurodevelopment and attention at 3 months corrected age. METHODS: Sixty-four infants born 24 to 35 weeks gestation were stratified into four gestational age groups: Group A, 23-26 weeks (n = 10); Group B, 27-29 weeks (n = 23); Group C, 30-32 weeks (n = 20); Group D, 33-35 weeks (n = 11). Controls were 33 healthy infants born full-term (Group E). In preterm only, free thyroxine (FT(4)), triiodothyronine (T(3)), and thyrotropin (TSH) were measured at 2 and 4 weeks of life and at 40 weeks postconceptional age. At 3 months corrected age, all infants were assessed with the Bayley Scales of Infant Development-Second Edition (BSID-II), from which both mental development index (MDI) and psychomotor development index (PDI) scores and four indices of attention were derived: sustained attention, selective attention, attention shift, and total attention. RESULTS: Gestational age-stratified preterm groups differed significantly in T(3) and FT(4) levels at 2 and 4 weeks of life in infants born less than 27 weeks gestation. Preterm infants overall scored significantly below full-term on BSID-II MDI and PDI, selective, sustained, and total attention scales. In the preterm group, FT(4) levels were positively associated with PDI and selective, sustained, and total attention. CONCLUSIONS: Reduced levels of thyroid hormone in the neonatal period in preterm infants are associated with a reduced neurocognitive outcome in the attention domain at 3 months corrected age.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".