P.073 Diagnostic utility of specific abnormal EEG patterns in children
Bibliographic record
Abstract
Background: CTS and PPR are common EEG findings that are classically associated with CECTS and GGE respectively. PPD and sleep spindles are physiologic phenomenon that occur in respond to intermittent photic stimulation and sleep respectively. Methods: We reviewed EEG studies with CTS, PPR, asymmetric PPD, or asymmetric sleep spindles. For CTS, we determined sensitivity, specificity, PPV and NPV for a diagnosis of CECTS. For PPR, we determined the same diagnostic outcome measures for a diagnosis of GGE or JME. For each of asymmetric PPD and asymmetric sleep spindles, we determined the same diagnostic outcome measures for the presence of a structural abnormality on brain MRI. Results: CTS had 83% specificity and 75% PPV in children with normal neurological examination. PPR had high specificity of 92% and NPV 92% for GGE; for JME, PPR also had high sensitivity (92%). Asymmetric PPD had low sensitivity for structural brain abnormalities (17%), with specificity 80%. In contrast, asymmetric sleep spindles had higher sensitivity and specificity, 44% and 97%, respectively. Conclusions: CTS are seen with CECTS and other conditions. PPR is highly indicative of a GGE, though may be seen other conditions. Relative attenuation of sleep spindles is a more reliable indicator of structural brain malformation than asymmetric PPD.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.004 | 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".