Utility of EEG Activation Procedures in Epilepsy: A Population-Based Study
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Bibliographic record
Abstract
PURPOSE: No previous population-based study has addressed the contribution of activation procedures to the yield of epileptiform abnormalities on serial EEGs. We assessed yield of activation-related epileptiform abnormalities and predictors of finding an activation-related abnormality with multiple EEGs in a population-based study of newly diagnosed epilepsy. METHODS: We used the resources of the Rochester Epidemiology Project to identify 449 residents of Rochester, Minnesota with a diagnosis of newly diagnosed epilepsy at age 1 year or older, between 1960 and 1994, who had at least one EEG. Information on all activation procedures (i.e., sleep, hyperventilation, and photic activation) and seizure/epilepsy characteristics was obtained by comprehensive review of medical records. RESULTS: At the first EEG, the yield of epileptiform abnormalities was greatest for individuals 1 to 19 years of age at diagnosis, for each activation procedure. The yield in patients aged 1 to 19 versus ≥20 years was 21.6% versus 10.3% for sleep, 6.5% versus 3.3% for photic stimulation, and 10.3% versus 5% for hyperventilation. Among young people (aged 1-19 years), sleep was associated with an increased likelihood of finding an activation-related abnormality on any EEG. The likelihood of finding an activation-related abnormality on any EEG was decreased for postnatal symptomatic and for unknown etiology. CONCLUSIONS: Among activation procedures, sleep showed the highest yield of epileptiform abnormalities. There was a low yield for photic stimulation and hyperventilation. Within each activation procedure, younger age at diagnosis had the greatest yield. Sleep is the most effective activation procedure, especially in younger patients, and should be performed when possible.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it