Preterm births: Can neonatal pain alter the development of endogenous gating systems?
Bibliographic record
Abstract
Prematurity is known to affect the development of various neurophysiological systems, including the maturation of pain and cardiac circuits. The purpose of this study was to see if numerous painful interventions, experienced soon after birth, affect counterirritation-induced analgesia (triggered using the cold pressor test) later in life. A total of 26 children, between the ages of 7 and 11 participated in the study. Children were divided into three groups, according to their birth status (i.e., term-born, born preterm and exposed to numerous painful interventions, or born preterm and exposed to few painful interventions). Primary outcome measures were heat pain thresholds, heat sensitivity scores, and cardiac reactivity. Results showed that preterm children and term-born children had comparable pain thresholds. Exposure to conditioning cold stimulation significantly increased heart rate and significantly decreased the thermal pain sensitivity of term-born children. These physiological reactions were also observed among preterm children who were only exposed to a few painful interventions at birth. Changes in heart rate and pain sensitivity in response to conditioning cold stimulation were not observed in preterm children that had been exposed to numerous painful procedures during the neonatal period. These results suggest that early pain does not lead to enhanced pain sensitivity when premature babies become children, but that their endogenous pain modulatory mechanisms are not as well developed as those of children not exposed to noxious insult at birth. Greater frequency of painful procedures also dampened the rise in heart rate normally observed when experimental pain is experienced.
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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 | 0.000 |
| 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".