Neonatal Invasive Procedures Predict Pain Intensity at School Age in Children Born Very Preterm
Bibliographic record
Abstract
INTRODUCTION: Children born very preterm display altered pain thresholds. Little is known about the neonatal clinical and psychosocial factors associated with their later pain perception. OBJECTIVE: We aimed to examine whether the number of neonatal invasive procedures, adjusted for other clinical and psychosocial factors, was associated with self-ratings of pain during a blood collection procedure at school age in children born very preterm. MATERIALS AND METHODS: 56 children born very preterm (24 to 32 weeks gestational age), followed longitudinally from birth, and free of major neurodevelopmental impairments underwent a blood collection by venipuncture at age 7.5 years. The children's pain was self-reported using the Coloured Analog Scale and the Facial Affective Scale. Parents completed the Child Behavior Checklist and the State-Trait Anxiety Inventory. Pain exposure (the number of invasive procedures) and clinical factors from birth to term-equivalent age were obtained prospectively. Multiple linear regression was used to predict children's pain self-ratings from neonatal pain exposure after adjusting for neonatal clinical and concurrent psychosocial factors. RESULTS: A greater number of neonatal invasive procedures and higher parent trait-anxiety were associated with higher pain intensity ratings during venipuncture at age 7.5 years. Fewer surgeries and lower concurrent child externalizing behaviors were associated with a higher pain intensity. CONCLUSIONS: In very preterm children, exposure to neonatal pain was related to altered pain self-ratings at school age, independent of other neonatal factors. Neonatal surgeries and concurrent psychosocial factors were also associated with pain ratings.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".