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Record W2039957669 · doi:10.1542/peds.110.3.570

Does Parenchymal Brain Injury Affect Biobehavioral Pain Responses in Very Low Birth Weight Infants at 32 Weeks’ Postconceptional Age?

2002· article· en· W2039957669 on OpenAlexaff
Tim F. Oberlander, Ruth E. Grunau, Colleen Fitzgerald, Michael F. Whitfield

Bibliographic record

VenuePEDIATRICS · 2002
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsChildren’s Health Research InstituteChildren's & Women's Health Centre of British ColumbiaBC Research (Canada)University of British Columbia
Fundersnot available
KeywordsMedicineGestational ageIntraventricular hemorrhageBirth weightPeriventricular leukomalaciaLow birth weightPediatricsAnesthesiaPregnancy

Abstract

fetched live from OpenAlex

OBJECTIVE: Children with neurologic impairments have shown diminished pain response compared with control subjects; however, it remains unclear what mechanisms underlie this response or when it develops. If this were also true with premature infants who undergo neonatal intensive care, then infants with parenchymal brain injury (PBI) would be at increased risk of underrecognition and undertreatment of procedural pain. The purpose of this study was to determine whether infants with PBI display altered responses to acute procedural pain at 32 weeks' postconceptional age (PCA), compared with control subjects. METHODS: We compared responses to blood collection by heel lance at 32 weeks' PCA in 12 very low birth weight infants (mean [range] birth weight: 876 g [630-1240 g]; gestational age: 26.3 weeks (24-28 weeks) who had sustained PBI in the neonatal period, with 12 control subjects matched for gestational age at birth and gender (838 g [625-990 g]; 26.3 weeks [24-28 weeks[) who had normal neonatal brain imaging. PBI was defined as cerebral parenchymal infarction (grade 4 intraventricular hemorrhage) or cystic periventricular leukomalacia on serial cranial ultrasound scans conducted in the neonatal period. Biobehavioral responses to pain were measured using facial activity (Neonatal Facial Coding System) and measures of heart rate (HR) variability (low-frequency [LF] power [0.04-0.15], high-frequency [HF] power [0.15-0.8 Hz], and LF/HF ratio) as a measure of cardiac autonomic modulation. Neurodevelopmental follow-up was undertaken at 18 months. RESULTS: The infants with PBI had significantly higher illness severity scores at day 1 compared with day 3 (Score of Neonatal Acute Physiology II: 32.1 vs 19.8) but similar previous pain experiences (109 vs 115) and total morphine exposure (0.29 vs 0.30 mg/kg). Both groups of children mounted similar responses to heel lance at 32 weeks' PCA with no difference in facial response or HR variability. Mean HR and facial action scores increased from baseline to the lance, whereas LF, HF, and the LF/HF ratio decreased significantly. No group differences were found. The only statistically significant difference between groups was that infants with PBI had more tongue protrusion at lance. Neurodevelopmental follow-up showed 8 of 11 toddlers with PBI had cerebral palsy compared with 0% of control toddlers. Psychomotor Developmental Index score on the Bayley Scales of Infant Development II was significantly lower in the PBI group. Five of 11 toddlers with PBI had Mental Developmental Index score <2 standard deviations below mean compared with 0% of the control toddlers. CONCLUSION: Contrary to expectations, we did not find any evidence of an altered pain response pattern in infants with proven brain injury in the neonatal period. Although most infants with PBI developed cerebral palsy, these findings suggest that cerebral injury predominantly to the central white matter leaves brainstem responses intact in the neonatal period. Furthermore, it seems that the injured brain of the preterm infant has not yet expressed the identifiable differences in pain display and the functional impairment observed at later ages.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.020
GPT teacher head0.287
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations71
Published2002
Admission routes1
Has abstractyes

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