Psychiatric outcomes after temporal lobe surgery in patients with temporal lobe epilepsy and comorbid psychiatric illness: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The currently available evidence is unclear in regard to psychiatric outcomes of temporal lobe epilepsy (TLE) in patients with comorbid psychiatric disorders (PD). AIM: To identify and synthesize psychiatric outcomes in patients with TLE and comorbid psychiatric illnesses before and after TLE surgery. METHODS: Studies were included if participants were adults and/or children with temporal epilepsy and comorbid psychiatric illness. Surgical interventions included focal resection (e.g., lobectomy, selective amygdalohippocampectomy) or stereotactic laser ablation. Included studies reported on pre- and post- surgery data of comorbid psychiatric illness (e.g., mood and anxiety disorders, depression, psychosis, adjustment disorders, non-epileptic seizures, and personality disorders). RESULTS: Ten studies were included in the review. The proportion of patients achieving PD resolution or improvements after surgery varied widely between studies, ranging from 15 % to 57 % at the reported follow-up time. Three studies reported on PD symptom worsening after surgery, with considerable variations of patient proportions across studies. Meta-analysis suggests that 43 % of patients demonstrated improvement and 33 % of patients showed a worsening in psychiatric scores across all studies. Preliminary data from three studies suggest that seizure control may be associated with favourable psychiatric outcomes. CONCLUSION: A considerable proportion of reported TLE patients with comorbid psychiatric illnesses have improvement in their psychiatric symptoms after temporal lobe epilepsy surgery. There is scarcity of detailed outcome reporting including symptom scores, and to date, predictive factors for favourable vs unfavourable outcomes in this patient population are not clear. Further research on the topic is warranted.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.028 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".