The burden of genetic disease among hospitalized children in Newfoundland
Bibliographic record
Abstract
Background: The Newfoundland and Labrador (NL) population is enriched for certain genetic diseases due to genetic drift and founder effects. Five previous studies have examined the amount of genetic disease among children admitted to a single pediatric hospital. The frequency of strongly genetic disorders (chromosomal and Mendelian disorders) ranged from 4 to ~11%, and all the hospitals served admixed populations. We conducted a similar study, hypothesizing that the amount of genetic disease among hospitalized NL children might be higher than in the previously published studies. Objectives: We determined the genetic content of 4,144 consecutive hospitalizations to Newfoundland and Labrador's only pediatric hospital. By reviewing the discharge summary, each admission was retrospectively classified into one of 11 genetic content groups. We also compared the utilization of hospital resources by children with strongly genetic versus minimally genetic conditions. Finally, we determined the appropriateness of referrals for genetic services. -- Results: Out of 4,144 children, 8.3% had a strongly genetic disease (342 patients with a Mendelian or chromosomal syndrome). Another ~25% (1,033 patients) had a moderately genetic disease and 67% (2,769 cases) were classified as minimally genetic. Children in the strongly genetic group had a mean length of stay (8.01 d) that was significantly longer than the non-genetic group (3.99 d), with more cumulative surgeries and cumulative hospital days. Children with single-gene disorders were at risk for prolonged lengths of stay (> 7 days). Of 3,281 unique admissions, 1 in 4 children with a diagnosis that is an indication for genetic consultation failed to be referred. The largest deficit occurred for children with mental retardation and for those with birth defects that have a significant genetic component. -- Conclusions: The proportion of admitted children with chromosomal and Mendelian disorders was comparable to previous studies, so that even though certain genetic diseases are overrepresented in NL, this is not reflected among hospitalized children. Our dataset may be enriched for children with high heritability multifactorial diseases (including diabetes and asthma), but comparison with earlier studies is complicated by differences in classification schemes and/or by the fact that the incidence of some of these diseases has increased over the past three decades.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".