Relationship between antiepileptic drugs and biological markers affecting long-term cardiovascular function in children and adolescents.
Bibliographic record
Abstract
BACKGROUND: Epilepsy is a neurological disorder, relatively common in the paediatric population. These children are often treated with antiepileptic drugs (AEDs) for several years. The consequence of such long-term exposure may lead to variations in plasma homocysteine and serum lipoprotein concentrations. OBJECTIVE(S): To review the cardiovascular effects of anticonvulsant therapy and their use in childhood epilepsy with special reference to homocysteine and lipoprotein. METHODS: A literature search was conducted on PubMed (1966-May 2009) and MEDLINE (1966-May 2009). Key terms included antiepileptic drugs, epilepsy, homocysteine, cardiovascular events, and children. RESULTS: Certain AEDs including carbamazepine, phenobarbital, phenytoin and valproic acid, as well as the presence of a homozygous 5-methylenetetrahydrofolate reductase polymorphism in the genotype, are potential causes of elevation in plasma homocysteine and serum lipoprotein concentrations. CONCLUSIONS: Persistent elevation in these biochemical markers has shown to be associated with the development of long-term sequelae such as cardiovascular diseases, prompting concerns about the long-term implications of chronic AED use in children and cardiovascular risk. Further research is needed to assess the relationship between specific chronic AED use, homocysteine and lipoprotein concentrations, the influence of genotype, as well as the risk of long-term sequelae in the paediatric population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".