Kindergarten‐age neurocognitive, functional, and quality‐of‐life outcomes after liver transplantation at under 6 years of age
Bibliographic record
Abstract
BACKGROUND: We aimed to describe school-entry age neurocognitive, functional, and HRQL outcomes and their predictors after liver transplant done at age <6 years. METHODS: A prospective cohort of all (n = 69) children surviving liver transplant from 1999 to 2014 were assessed at age 55.4 (SD 7.2) months and 38.6 (12.4) months after transplant. Assessment included: the Wechsler Preschool and Primary Scales of Intelligence, Beery-Buktenica Developmental Test of VMI, Adaptive Behavior Assessment System caregiver-completed questionnaire, and PedsQL 4.0 Generic Core Scales. Univariate and multiple linear regression determined predictors of outcomes at P < .05. RESULTS: Neurocognitive and functional outcomes were on average within 1 SD of population norms, although shifted to the left (P ≤ .03), with more patients than expected having scores >2 (3.7-5.9 times more, P ≤ .007) SD below population norms. Total and Summary HRQL scores were statistically significantly lower than the healthy normative population (P ≤ .02) and a congenital heart disease group (P ≤ .02), but similar to children with other chronic health conditions; differences often exceeded the MCID and were lowest in the School functioning domain. There were few predictors on multiple linear regressions, and we could not confirm previous studies that suggested various inconsistent predictors of outcomes. Neurocognitive and functional outcomes scores were highly correlated with HRQL scores except for the School functioning domain, but did not fully explain them. CONCLUSIONS: Long-term follow-up of this vulnerable population is important in order to facilitate support for the patient and family, and early intervention for any difficulties identified.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".