Bibliographic record
Abstract
Abstract The long-term effects of infant pain are complex, and vary depending on how early in life the exposure occurs, due to differences in developmental maturity of specific systems underway. Changes to later pain sensitivity reflect multiple factors such as age at pain stimulation, extent of tissue damage, type of noxious insult, intensity, and duration. In both full-term and preterm infants exposed to hospitalization, sequelae of early pain are confounded by parental separation and quality of pain treatment. Neonates born very preterm are outside the protective uterine environment, with repeated exposure to pain occurring during fetal life. Especially for infants born in the late second trimester, the cascade of autonomic, hormonal, and inflammatory responses to procedures may induce excitotoxicity with widespread effects on the brain. Quantitative advanced imaging techniques have revealed that neonatal pain in very preterm infants is associated with altered brain development during the neonatal period and beyond. Recent studies now provide evidence of pathways reflecting mechanisms that may underlie the emerging association between cumulative procedural pain exposure and neurodevelopment and behavior in children born very preterm. Owing to immaturity of the central nervous system, repetitive pain in very preterm neonates contributes to alterations in multiple aspects of development. Importantly, there is strong evidence that parental caregiving to reduce pain and stress in preterm infants in the Neonatal Intensive Care Unit (NICU) may prevent adverse effects, and sensitive parenting after NICU discharge may help ameliorate potential long-term effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".