A systematic review and quantitative analysis of neurocognitive outcomes in children with four chronic illnesses
Bibliographic record
Abstract
BACKGROUND: Concern has been expressed that infants and children exposed to uneventful surgery and anesthesia may incur neurological injury that becomes manifest in poor scholastic performance or future learning difficulties. A recent meta-analysis of seven clinical studies examined the relationship between learning or behavior difficulties and pediatric exposure to anesthesia/surgery and reported an odds ratio of 1.4; however, the level of association and causal factors remain unclear. The purpose of our study is to provide context to the pediatric anesthesia neurotoxicity question by reviewing the evidence linking four childhood illnesses with neurocognitive development. In the present review, we have sought to quantify the magnitude of the impact of chronic illness on neurocognitive development through a systematic review of publications that report the developmental trajectory of patients with four childhood diseases: cystic fibrosis (CF), hemophilia A, end-stage renal disease (ESRD) and end-stage liver disease (ESLD). METHODS: Studies were identified by searching the electronic databases OVID MEDLINE and Pubmed and scanning reference lists of articles by two authors. Limits were applied to the English language and to humans. We used the following search terms: CF, hemophilia A, ESRD, ESLD in combination with academic performance, educational status, educational measurement, learning, achievement, developmental delay, learning disabilities, intellectual disabilities, behavioral disorders, intelligence quotient (IQ), cognition, school problems, absenteeism, school attendance, anxiety, learning regression, or developmental regression. The search strategy was reviewed independently by all four authors. Eligibility assessment was performed independently in an unblinded standardized manner by two authors who chose relevant articles from the overall search results by scanning the titles and abstracts of articles and from the references within citations. The full-text publications were reviewed by all four authors. All pertinent data related to the objectives were collected and independently reviewed by two authors. The data were summarized in the form reported in the studies. When possible, reported data were submitted to analysis with the Mantel-Haenszel method using a random effects model. Analyses were performed using the Review Manager computer program. RESULTS: In the studies retrieved, the main outcomes were measures of intellectual or cognitive characteristics, as exemplified by the Wechsler battery of tests. Reporting of measures of achievement (for example, GPA) was rare. Children with CF and hemophilia A did not appear disadvantaged by their disease as general intelligence levels were comparable with the general population norms. In children with ESRD, mean IQ reported during dialysis improved after transplantation. Although they improved relative to their pretransplantation cognitive functioning, children with ESLD who received transplants are approximately eight IQ points below the population norm. CONCLUSIONS: Overall, the results suggest that the burden of chronic childhood illness, by itself, does not impair cognitive development in children with hemophilia A and CF. Children with ESRD and ESLD, despite optimal management, show a mild cognitive deficit compared with the population norm. Given the impact of these four specific chronic illnesses on neurocognitive outcome in children and the improvement in IQ post-transplant in both ESRD and ESLD, the results suggest that the effect of an uncontrolled confounding illness on neurocognitive development is small.
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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 | 0.019 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.020 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".