Prevalence of Congenital Disorders of Glycosylation in Childhood Epilepsy and Effects of Anti-Epileptic Drugs on the Transferrin Isoelectric Focusing Test
Bibliographic record
Abstract
INTRODUCTION: Childhood epilepsy is one of the most common neurological problems. The transferrin isoelectric focusing (TIEF) test is a screening test for congenital disorders of glycosylation (CDG). We identified abnormal TIEF test in children with epilepsy in our epilepsy genetics clinic. To determine if an abnormal TIEF test is associated with anti-epileptic medications or abnormal liver functions, we performed a retrospective cohort study. METHODS: This study was performed between January 2012 and March 2020. Electronic patient charts were reviewed. Standard non-parametric statistical tests were applied using R statistical software. Fischer's exact test was used for comparisons. RESULTS: = 1). We report 51 different genetic diseases in 84 patients. Two groups, (1) abnormal TIEF test; (2) normal TIEF test, showed statistically significant differences for abnormal liver functions and for valproic acid treatment. CONCLUSION: The TIEF test guided CDG diagnosis in 2.9% of the patients. Due to the high prevalence of CDG (4.4%) in childhood epilepsy, the TIEF test might be included into the diagnostic investigations to allow earlier and cost-effective diagnosis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".