School performance in children at the time of new-onset seizures and at long-term follow-up: A retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: School-performance difficulties (SPD) are common in children with epilepsy. The objectives of this study were to determine if the rate of SPD in children with seizures change from seizure-onset to follow-up and differ from children with psychiatric disorders. METHODS: School-aged children who required an initial electroencephalography (EEG) test in 2016 were reviewed and separated into two groups based on the presence or absence of seizures. Developmental delay and SPD were compared between groups at initial assessment and SPD was assessed after 2-4 years of follow-up. Analysis was also performed on a sub-set of patients with psychiatric disorders. RESULTS: At baseline, the rate of SPD was similar between the seizure (n = 146) and non-seizure (n = 332) groups [26% vs. 27%]. At follow-up, the seizure (n = 119) group had a significantly higher rate of SPD than the non-seizure (n = 215) group (54% vs. 43%). There was no difference in the rate of SPD between the seizure (n = 119) and psychiatric (n = 69) groups at baseline (31% vs. 43%) or follow-up (54% vs. 55%). CONCLUSION: Over time, children with recurrent seizures experience more SPD than children without seizures, but similar SPD to children with psychiatric disorders.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".