Influence of early identification and therapy on long‐term outcomes in early‐onset <scp>MTHFR</scp> deficiency
Bibliographic record
Abstract
MTHFR deficiency is a severe inborn error of metabolism leading to impairment of the remethylation of homocysteine to methionine. Neonatal and early-onset patients mostly exhibit a life-threatening acute neurologic deterioration. Furthermore, data on early-onset patients' long-term outcomes are scarce. The aims of this study were (1) to study and describe the clinical and laboratory parameters of early-onset MTHFR-deficient patients (i.e., ≤3 months of age) and (2) to identify predictive factors for severe neurodevelopmental outcomes in a cohort with early and late onset MTHFR-deficient patients. To this end, we conducted a retrospective, multicentric, international cohort study on 72 patients with MTHFR deficiency from 32 international metabolic centres. Characteristics of the 32 patients with early-onset MTHFR deficiency were described at time of diagnosis and at the last follow-up visit. Logistic regression analysis was used to identify predictive factors of severe neurodevelopmental outcome in a broader set of patients with early and non-early-onset MTHFR deficiency. The majority of early-onset MTHFR-deficient patients (n = 32) exhibited neurologic symptoms (76%) and feeding difficulties (70%) at time of diagnosis. At the last follow-up visit (median follow-up time of 8.1 years), 76% of treated early-onset patients (n = 29) exhibited a severe neurodevelopmental outcome. Among the whole study population of 64 patients, pre-symptomatic diagnosis was independently associated with a significantly better neurodevelopmental outcome (adjusted OR 0.004, [0.002-0.232]; p = 0.003). This study provides evidence for benefits of pre-symptomatic diagnosis and appropriate therapeutic management, highlighting the need for systematic newborn screening for MTHFR deficiency and pre-symptomatic treatment that may improve outcome.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".