Screening Electroencephalograms in Autism Spectrum Disorders: Evidence-Based Guideline
Bibliographic record
Abstract
The purpose of this study was to establish guidelines for the use of screening electroencephalograms (EEGs) in autism spectrum disorders to identify subclinical epileptiform activity. MEDLINE and EMBASE were searched for relevant articles. The evidence was reviewed using the methodology of the Canadian Task Force on Preventive Health Care. A priori criteria were established for article selection and for grading the quality and strength of the evidence. Seizures are common, occurring in 20 to 30% of patients based on the majority of studies. Epileptiform EEG abnormalities are present in 10.3% to 72.4% of patients and subclinical abnormalities in 6.1% to 31%. Evidence for the effectiveness of anticonvulsants and corticosteroids in reducing seizures and/or autistic symptoms is based primarily on case series and case reports, with only one published randomized trial. There is currently insufficient evidence to recommend for or against the use of screening EEGs in autistic patients. Given the frequency of seizure disorders in this patient population, a high index of clinical suspicion should be maintained for subtle symptoms of seizures.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".