Neurodevelopmental Outcome and Treatment Efficacy of Benzoate and Dextromethorphan in Siblings with Attenuated Nonketotic Hyperglycinemia
Bibliographic record
Abstract
OBJECTIVE: To evaluate the impact of sodium benzoate and dextromethorphan treatment on patients with the attenuated form of nonketotic hyperglycinemia. STUDY DESIGN: Families were recruited with 2 siblings both affected with attenuated nonketotic hyperglycinemia. Genetic mutations were expressed to identify residual activity. The outcome on developmental progress and seizures was compared between the first child diagnosed and treated late with the second child diagnosed at birth and treated aggressively from the newborn period using dextromethorphan and benzoate at dosing sufficient to normalize plasma glycine levels. Both siblings were evaluated with similar standardized neurodevelopmental measures. RESULTS: In each sibling set, the second sibling treated from the neonatal period achieved earlier and more developmental milestones, and had a higher developmental quotient. In 3 of the 4 sibling pairs, the younger sibling had no seizures whereas the first child had a seizure disorder. The adaptive behavior subdomains of socialization and daily living skills improved more than motor skills and communication. CONCLUSIONS: Early treatment with dextromethorphan and sodium benzoate sufficient to normalize plasma glycine levels is effective at improving outcome if used in children with attenuated disease with mutations providing residual activity and when started from the neonatal period.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".