Outpatient ambulatory EEG as an option for epilepsy surgery evaluation instead of inpatient EEG telemetry
Bibliographic record
Abstract
Outpatient ambulatory EEG is more cost-effective than inpatient EEG telemetry and may provide adequate seizure localization in a presurgical evaluation. A 51-year-old right-handed male had been unable to work or drive since the age of 35 due to intractable partial onset epilepsy. A 72-hour outpatient ambulatory EEG recorded 18 seizures from the right temporal region. No epileptiform activity was seen in the left hemisphere. Magnetic resonance imaging showed right mesial temporal sclerosis as well as an area of encephalomalacia at the medial inferior right temporal lobe. Neuropsychological assessment found that the patient was a good neurosurgery candidate. At this point, the patient was considered to be a candidate for a right temporal lobectomy. A standard right temporal lobectomy was performed. The patient has been seizure-free for 10 months after the surgery. Follow-up EEGs show no epileptiform activity. The patient is preparing to go back to work, and his driver's license was reinstated 9 months postsurgery. Neuropsychological reassessment is pending, but no apparent change in cognition has been noticed by the patient or his family. Cases with a high congruence between diagnostic imaging and the EEG abnormalities identified in the portable EEG may provide enough information regarding seizure frequency and localization to eliminate the need for inpatient EEG telemetry in the evaluation of patients for epilepsy surgery. We believe that the use of aEEG in preoperative planning should be restricted to cases of TLE and to patients with a high frequency of seizures.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".