Effect of epileptiform discharges and hippocampal volume on cognitive dysfunction following clipping of ruptured aneurysms in the anterior circulation
Bibliographic record
Abstract
Introduction Cognitive dysfunction after aneurysmal subarachnoid hemorrhage (aSAH) remains unclear due to various neurological impairments. This study aimed to evaluate the changes in hippocampal volume, cognitive function, and interictal epileptiform discharges after clipping in patients with aSAH of anterior circulation. Methods Patients with modified Rankin Scale scores of 0–3 points who underwent clipping were evaluated. Aneurysmal locations were classified as middle cerebral artery (MCA), internal carotid artery (ICA), and anterior cerebral artery (ACA). Surgery was performed using the transsylvian approach or interhemispheric approach. Hippocampal volume measurement, neuropsychological assessments, and interictal electroencephalogram evaluations were performed postoperatively at the subacute phase. Epileptiform discharges were assessed using the spike index (SI). Results We included 60 patients (23 men, 37 women; median age, 57.4 years). Aneurysmal locations were found in the MCA, ICA, and ACA in 23, 19, and 18 patients, respectively. The postoperative hippocampal volume was significantly reduced on the clipping approach side in the MCA and ICA groups (MCA, p < .001; ICA, p < .001). There was no correlation between hippocampal volume and cognitive function. A significant difference was noted in elevated SI on the approach side of the MCA (p < .001), ICA (p < .001), and ACA (p < .001) in the transsylvian approach group. The elevated SI on the left approach side showed significant differences in some neuropsychological assessments (performance intellectual quotient, p = .028; perceptual organization, p = .045; working memory, p = .003). Discussion Cognitive dysfunction in the subacute phase after clipping for aSAH was not correlated with hippocampal volume reduction but was correlated with interictal epileptiform discharges.
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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) | 0.001 | 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 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".