Memory outcome after temporal lobe epilepsy surgery: corticoamygdalohippocampectomy versus selective amygdalohippocampectomy
Bibliographic record
Abstract
OBJECT: The aim of this study was to compare IQ and memory outcomes at the 1-year follow-up in patients with medically refractory mesial temporal lobe epilepsy (MTLE) due to hippocampal sclerosis. All patients were treated using a corticoamygdalohippocampectomy (CAH) or a selective amygdalohippocampectomy (SelAH). METHODS: The data of 256 patients who underwent surgery for MTLE were retrospectively evaluated. One hundred twenty-three patients underwent a CAH (63 [right side] and 60 [left side]), and 133 underwent an SelAH (61 [right side] and 72 [left side]). A comprehensive neuropsychological test battery was assessed before and 1 year after surgery, and the results were compared between the surgical procedures. Furthermore, seizure outcome was compared using the Engel classification scheme. RESULTS: At 1-year follow-up, there was no statistically significant difference between the surgical approaches with respect to seizure outcome. Overall, IQ scores showed improvement, but verbal IQ decreased after left SelAH. Verbal memory impairment was seen after left-sided resections especially in cases of SelAH, and nonverbal memory decreased after right-sided resection, especially for CAH. Left-sided resections produced some improvement in nonverbal memory. Older age at surgery, longer duration of seizures, greater seizure frequency before surgery, and poor seizure control after surgery were associated with poorer memory. CONCLUSIONS: Both CAH and SelAH can lead to several cognitive impairments depending on the side of the surgery. The authors suggest that the optimal type of surgical approach should be decided on a case-by-case basis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".