Resident Use of EEG Cap System to Rule Out Nonconvulsive Status Epilepticus
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Nonconvulsive status epilepticus (NCSE) requires an EEG for diagnosis and in many centers access may be limited. The authors aimed to test whether neurology residents can be trained to use and interpret full-montage EEGs using an EEG cap electrode system to detect NCSE while on-call. METHODS: Neurology residents were trained to interpret EEG recordings using the American Clinical Neurophysiology Society critical care EEG terminology. Residents who achieved a score of 70% or higher in the American Clinical Neurophysiology Society certification test and attended a training session were eligible to use the EEG cap on-call with patients suspected of having NCSE. Residents' experience and interpretation of observed EEG patterns were evaluated using a questionnaire. Each EEG recording was independently reviewed by three epilepsy specialists to determine the interpretability of each study and whether the residents correctly identified the EEG patterns. RESULTS: Sixteen residents undertook the training and 12 (75%) achieved a score of 70% or higher on the certification test. Seven of these residents performed 14 EEG cap studies between August 2017 and May 2018. The percent agreement between residents and electroencephalographers was 78.6% for EEG interpretability and 57.1% for description of EEG pattern. Residents did not miss any malignant patterns concerning for NCSE, which accounted for 1 of 14 EEGs but "overcalled" patterns as malignant in 3 of 14 recordings. CONCLUSIONS: This study suggests that neurology residents can be taught to perform and interpret EEGs using a cap system to monitor for NCSE. Additional training will help improve EEG interpretation and sensitivity.
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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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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