Neonatal procedural pain exposure predicts lower cortisol and behavioral reactivity in preterm infants in the NICU
Bibliographic record
Abstract
Data from animal models indicate that neonatal stress or pain can permanently alter subsequent behavioral and/or physiological reactivity to stressors. However, cumulative effects of pain related to acute procedures in the neonatal intensive care unit (NICU) on later stress and/or pain reactivity has received limited attention. The objective of this study is to examine relationships between prior neonatal pain exposure (number of skin breaking procedures), and subsequent stress and pain reactivity in preterm infants in the NICU. Eighty-seven preterm infants were studied at 32 (±1 weeks) postconceptional age (PCA). Infants who received analgesia or sedation in the 72 h prior to each study, or any postnatal dexamethasone, were excluded. Outcomes were infant responses to two different stressors studied on separate days in a repeated measures randomized crossover design: (1) plasma cortisol to stress of a fixed series of nursing procedures; (2) behavioral (Neonatal Facial Coding System; NFCS) and cardiac reactivity to pain of blood collection. Among infants born ≤28 weeks gestational age (GA), but not 29–32 weeks GA, higher cumulative neonatal procedural pain exposure was related to lower cortisol response to stress and to lower facial (but not autonomic) reactivity to pain, at 32 weeks PCA, independent of early illness severity and morphine exposure since birth. Repeated neonatal procedural pain exposure among neurodevelopmentally immature preterm infants was associated with down-regulation of the hypothalamic–pituitary–adrenal axis, which was not counteracted with morphine. Differential effects of early pain on development of behavioral, physiologic and hormonal systems warrant further investigation.
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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 | 0.003 |
| 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 | 0.001 |
| 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".