Neuropsychological Outcome in Early School Age Children with Intestinal Failure
Bibliographic record
Abstract
Purpose: Evaluation of neurocognitive function in children with intestinal failure (IF) is critical to optimize long-term outcomes. Recent research suggests that early cognitive abilities are delayed in this population, although later developmental outcomes are unknown. We examined the neuropsychological outcomes of children with IF at early school-age. Methods: Prospective single center neuropsychological assessments of children in an intestinal rehabilitation program between 2012–2016. Transplant recipients were excluded. Assessments included measures of general intellect (WPPSI-IV, WISC-IV/V), academics (WIAT-II/III), learning and memory (CMS, CVLT-C), language (PPVT-4, EVT-2), visual-motor integration (Beery VMI) and fine-motor dexterity (Purdue Pegboard). DSM-IV or V criteria was used to diagnose learning disability (LD), intellectual disability (ID), and/or attention deficit hyperactivity disorder (ADHD). Age-normed scores were correlated with social and medical variables. Results: Sample included 28 children (15 males), age 5–8 years, with the following etiologies: necrotizing enterocolitis (NEC) (8), gastroschisis (6), atresia (5), volvulus (4), Hirschsprung’s disease (3), and other (2). 17/28 (61%) were premature (<37 weeks gestational age (GA)) Overall, intellectual functioning was within the low end of normal range (mean Full Scale IQ=89, range: 53–123). 13/28 children (46%) received diagnoses: 8 LD, 3 ID, 2 combined LD and ADHD. Total number of septic episodes in the first year of life (median 2, range 0–7) was significantly correlated with lower scores on most measures, while having a sibling at home was a positive predictor (Table 1). Using linear regression to adjust for GA, total first-year septic episodes remains a significant predictor (p<.05) of working memory, visual-motor and visual memory scores, with a trend for predicting intellectual functioning (p=.067). Additional risk factors significantly correlated with lower scores on ≥2 cognitive functions include: length of hospitalization in first year of life, NEC diagnosis, gestational age, birth weight, and sustained conjugated bilirubin.FigureConclusion: Early school-age assessment is important for children with IF, as they are at high risk of learning/attention issues. Medically effective treatment of septic episodes within the first year of life is critical for improving long-term cognitive outcomes. Certain social factors (e.g. sibling at home) are linked with positive outcomes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".