Moderators of the Effect of Preoperative Emotional Adjustment on Postoperative Depression After Surgery for Temporal Lobe Epilepsy
Bibliographic record
Abstract
PURPOSE: Other outcome measures besides seizure control must be considered when assessing the benefit of epilepsy surgery. We investigated the effect of preoperative psychosocial adjustment on postoperative depression in epilepsy patients followed up prospectively for 2 years after temporal lobectomy. METHODS: The Washington Psychosocial Seizure Inventory (WPSI) evaluated psychosocial functioning; the Centre for Epidemiological Studies Depression Scale (CES-D) measured depression. Both were completed at baseline and follow-up. RESULTS: Follow-up occurred in 39 temporal lobectomy patients at 2 years after surgery. Greatest improvement in depression scores was limited to patients with good seizure outcomes (seizure free, or marked reduction in seizure frequency), and seizure outcome was a significant predictor of postoperative depression. Despite this, preoperative scores on the emotional adjustment scale of the WPSI were most highly correlated with depression 2 years after surgery. To clarify this relation, moderated hierarchic regression suggested that good preoperative emotional adjustment (WPSI) was generally associated with less depression after surgery. Moreover, poorer preoperative adjustment combined with older age, generalized seizures, the finding of preoperative neurologic deficits, a family history of psychiatric illness, and/or a family history of seizures was related to higher depression scores 2 years after surgery. CONCLUSIONS: Depression after temporal lobectomy is dependent on a complex interaction of variables and can have a significant effect on indices of postoperative adjustment. The WPSI emotional adjustment scale may help to predict which patients are likely to be chronically depressed after surgery.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".