Neonatal screening for glutaryl‐CoA dehydrogenase deficiency
Bibliographic record
Abstract
Acute encephalopathic crisis in glutaryl-CoA dehydrogenase deficiency results in an unfavourable disease course and poor outcome, dominated by dystonia, feeding problems, seizures and secondary complications, and quite often leading to early death. The prerequisite for the prevention of irreversible brain damage in this disease is the detection of affected patients and initiation of treatment before the manifestation of such crisis. Apart from macrocephaly there are no signs or symptoms characteristic for this disease in presymptomatic children and, thus, they are usually missed. In some countries, implementation of extended neonatal screening programmes using electrospray ionization tandem mass spectrometry (ESI-MS/MS) allows detection of affected newborns and start of therapy before onset of neurological complications. This article summarizes recent strategies, pitfalls and shortcomings of a mass screening for glutaryl-CoA dehydrogenase deficiency using ESI-MS/MS. Furthermore, an alternative strategy, namely DNA-based neonatal screening for the Oji-Cree variant of this disease, is demonstrated. An optimization of diagnostic as well as therapeutic procedures must be achieved before GCDH deficiency unequivocally fulfills the criteria of a reliable and successful newborn screening programme.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".