DEVELOPMENTAL OUTCOME IN A COHORT OF INFANT LIVER TRANSPLANT RECIPIENTS
Bibliographic record
Abstract
Children with end-stage liver disease and liver transplantation (LT) during the first 12 months of life are exposed to many potential neurological insults during the most vulnerable period of brain growth. We describe the developmental outcome in infants transplanted at the University of Alberta, Stollery Children's Hospital. Methods: Infants ≤12 months of age who had a LT between 1990-2004 were registered and followed by the Complex Pediatrics Therapies Project. The children were assessed between 6 to 12 months post-LT with a neurological examination, audiology and administered the Bayley Scales of Infant Development-II (BSID-II). The BSID-II provides a Mental Development Index (MDI) which has a population normative score of 100 ± 15. Developmental delay is defined as a MDI of <70 and borderline delay 84-70. The registry also recorded potential predictive variables including age at LT, socioeconomic status (SES), diagnosis, growth and serum bilirubin and ammonia. Results: During this period, 27 grafts were transplanted into 24 recipients, with a patient survival of 21/24 (87.5%) and a graft survival of 21/27 (77.8%). Follow-up was available on 18/21 (85.7%) survivors. Etiology of the 18 children included biliary atresia n = 14 and other n = 4. The mean MDI was 77.1 ≤ 16.9 (range 109-49) with only 4 (22%) children having a MDI >85 (normal development), 9 (50%) had a MDI 84-70 (borderline delay) and 5 (28%) had a MDI <70 (developmental delay). Compared to the expected general population, prevalence of borderline delay was 3 times and developmental delay 14 times the expected rate. There was no correlation between MDI and the age at LT, SES, diagnosis, growth and pretransplant serum bilirubin and ammonia. Conclusion: End-stage liver disease and LT in infancy results in over 75% of children with borderline or developmental delay. All infants should have thorough developmental assessments to enable them to receive appropriate supports and learning environments to maximize their potential.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".