Indices of Resective Surgery Effectiveness for Intractable Nonlesional Focal Epilepsy
Bibliographic record
Abstract
Among 70 patients with intractable focal epilepsy and no specific lesion, as determined by both MRI (magnetic resonance imaging) and histopathology, outcome after resective surgery was polarized: 26 (37%) became seizure free (SF), and 27 (39%) were not helped. Eighteen (42%) of 43 standard temporal resections rendered patients SF, somewhat more than eight (30%) of 27 other procedures. To seek reliable prognostic factors, the subsequent correlative data compared features of the 26 SF patients with those of the 27 not helped. Although ictal semiology guided the site of surgical resection, it and other aspects of seizure and neurologic history failed to predict surgical outcome. However, two aspects of preoperative scalp EEGs correlated with SF outcomes: (a) among 25 patients in whom >50% of clinical seizures arose from the later resected lobe and no other origins, 18 (72%) became SF compared with seven (28%) of 25 with other ictal profiles; (b) 13 (93%) of 14 temporal lobe patients whose interictal and ictal EEGs lacked features indicative of multifocal epileptogenesis became SF compared with five (33%) of 15 with such components. The considered need for subdural (SD) EEG reduced SF outcome from 18 (90%) of 20 patients without SD to eight (24%) of 33 with SD; this likely reflected an insufficient congruity of ictal semiology and interictal and ictal scalp EEG for localizing epileptogenesis. Within this SD group, >50% of clinical seizure origins from a later resected lobe increased SF outcome somewhat: from two (14%) of 14 without this attribute to six (40%) of 15 with it; 100% of such origins increased SF outcome from two (12%) of 16 to six (46%) of 13.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| 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 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".