Genome-wide sequencing in acutely ill infants: genomic medicine’s critical application?
Bibliographic record
Abstract
Diagnostic genome-wide sequencing (exome or genome sequencing and data analysis for high-penetrance disease-causing variants) in acutely ill infants appears to be clinically useful, but the value of this diagnostic test should be rigorously demonstrated before it is accepted as a standard of care. This white paper was developed by the Paediatric Task Team of the Global Alliance for Genomics and Health's Regulatory and Ethics Work Stream to address the question of how we can determine the clinical value of genome-wide sequencing in infants in an intensive care setting. After reviewing available clinical and ethics literature on this question, we conclude that evaluating diagnostic genome-wide sequencing as a comprehensive scan for major genetic disease (rather than as a large panel of single-gene tests) provides a practical approach to assessing its clinical value in acutely ill infants. Comparing the clinical value of diagnostic genome-wide sequencing to chromosomal microarray analysis, the current evidence-based standard of care, per case of serious genetic disease diagnosed provides a practical means of assessing clinical value. Scientifically rigorous studies of this kind are needed to determine if clinical genome-wide sequencing should be established as a standard of care supported by healthcare systems and insurers for diagnosis of genetic disease in seriously ill newborn infants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".