Cytokine levels in neonatal necrotizing enterocolitis and long‐term growth and neurodevelopment
Bibliographic record
Abstract
OBJECTIVE: To investigate if circulating cytokines are related to growth and neurodevelopmental outcome following necrotizing enterocolitis (NEC). STUDY DESIGN: Pro-inflammatory cytokine levels were measured prospectively in 40 neonates and compared with neurodevelopmental outcome. Cytokine levels were measured at the onset of feeding intolerance (Group II, n = 17) or NEC (Group III, n = 10) and at weeks 2-3 in control infants (Group I, n = 13). Neurodevelopmental outcome was assessed at the age of 24-28 months. Data were analysed using descriptive statistics, non-parametric tests and Student t-test. RESULTS: Median birth weights (range) in groups I, II and III were 1120 (525-1564) g, 1068 (650-1937) g and 1145 (670-2833) g, and median gestational ages (range) were 28 (24-35) weeks 28 (24-35) weeks and 28 (25-37) weeks respectively. NEC occurred in 10 infants. Serum IL-6 (interleukin-6) was elevated in group III, (p = 0.03). Significant developmental delay was found in 12% of the infants in Group II and 20% of the infants in Group III, but no infant in group I. Five infants in group III with NEC (50%), had head ultrasound abnormalities. At 1 year of age, growth, weight and head circumference were significantly different in Group III, however, at two years of age, only height was significantly different, p < 0.02. Although there was wide variation, neonatal cytokine levels tended to be greater in the infants later found to have abnormal cognitive and psychomotor outcomes. CONCLUSION: This study suggests that increased serum levels of pro-inflammatory cytokines may play a role in the poor growth and neurodevelopment associated with this high-risk population.
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 | 0.001 | 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".