Epilepsy in children with Congenital Zika Syndrome: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVES: To estimate the overall frequency of epilepsy in children with congenital Zika syndrome (CZS) and describe the profile of seizures and the response rate to anti-epileptic treatment in this group of patients. METHODS: A systematic review and meta-analysis were conducted following the Cochrane Handbook and preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. PubMed/MEDLINE, Scopus, Cochrane Library, SciELO, and LILACS were searched until June 23, 2020. Observational studies that evaluated the frequency of epilepsy in children diagnosed with CZS according to international criteria were included in the study. RESULTS: Fourteen studies evaluating 903 patients diagnosed with CZS were pooled in a meta-analysis. All studies were conducted in Brazil, with reports published between 2016 and 2020, and included children diagnosed with CSZ from 0 to 40 months of age. The overall rate of epilepsy in children diagnosed with CZS was estimated at 60% (95% confidence interval [CI] 0.51-0.68). The studies included in this review show that the frequency of epilepsy in patients with CSZ varies with age, with higher rates in older children. Epileptic spasms was the primary type of seizure observed in this group, followed by focal and generalized crisis. The response rate to anti-epileptic drugs was considerably low, ranging from 20% of seizure control in the first year and 30% in the second year. SIGNIFICANCE: Children with CZS presented a high cumulative incidence of epilepsy episodes with increased severity and a low response to anti-epileptic therapy, which is associated with the extensive damage caused by the Zika virus on the cortical structures of patients.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.034 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".