Neonatal Inflammation and Feeding Disorders at 1 Year in Infants With Congenital Gastrointestinal Malformations
Bibliographic record
Abstract
AIM: To investigate the associations between inflammatory markers and the risk of paediatric feeding disorders (PFD) at 1 year of age in infants with congenital gastrointestinal malformations (CGMs). METHODS: Neonates with CGMs admitted to our NICU and prospectively followed up in our outpatient clinic were included. The presence of PFD was assessed at the 1-year visit using the Montreal Children's Hospital Feeding Scale (MCH-FS). Data on potential risk factors for PFD were retrospectively collected. RESULTS: Fifty-nine neonates were included. They had a median MCH-FS at 1 year of 25 [IQR = 19-37]. PFD (MCH-FS > 45) was diagnosed in 15% of cases, of which 56% were severe. The number of days with a C-reactive protein (CRP) level > 40 mg/L was significantly higher in the PFD patients. After adjusting for confounding factors, a duration of CRP > 40 mg/L remained significantly associated with PFD at 1 year (OR = 1.23, [1.02-1.47]). Similarly, the number of neonatal surgical procedures (OR = 11.4, [2.15-60.6]) was independently associated with PFD at 1 year. CONCLUSION: PFD at 1 year was observed in 15% of newborns with CGMs in our cohort. Our results suggest that sustained severe inflammation caused by surgery and its complications during the neonatal period may have long-term effects on feeding behaviour.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".