Time Course of Postoperative Recovery of <i>N</i>‐Acetyl‐Aspartate in Temporal Lobe Epilepsy
Bibliographic record
Abstract
PURPOSE: To assess the time course of increases in N-acetyl-aspartate/creatine (NAA/Cr), which can be measured using proton MR spectroscopic imaging (1H-MRSI), in patients with intractable nonlesional temporal lobe epilepsy (TLE) after successful epilepsy surgery. METHODS: We performed pre- and postoperative 1H-MRSI in 16 seizure-free (SF) patients and 16 not seizure-free (NSF) TLE patients. We calculated a mixed-design analysis of variance (ANOVA) between SF and NSF groups, ipsi- and contralateral to the side of operation, and pre- and postoperative NAA/Cr measurements. We applied nonlinear regression between pre- and postoperative NAA/Cr differences and the time interval between 1H-MRSI scans to fit a negative exponential model to NAA recovery. RESULTS: Mixed-design ANOVA revealed that (a) postoperative NAA/Cr was significantly higher in SF than in NSF patients (p = 0.02) and that (b) in the SF group, postoperative NAA/Cr values were significantly higher than preoperative values (p < 0.05) and returned to the normal range in most patients. According to our nonlinear regression model, in SF patients, there was a 50% increase relative to preoperative NAA/Cr values after 5.8 months, whereas an improvement of 95% was reached after 25 months. CONCLUSIONS: Our results extend preliminary observations of postoperative NAA recovery of SF patients by characterizing the time course of recovery as an exponential function with a half-time of approximately 6 months. The reversal of neuronal metabolic dysfunction remote from the epileptic focus may underlie the clinical observation of improvement of cognitive dysfunction after successful epilepsy surgery.
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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".