Emotional functioning: Long‐term outcomes after pediatric epilepsy surgery
Bibliographic record
Abstract
OBJECTIVE: Children with epilepsy are at a high risk for developing symptoms of anxiety and depression. By improving seizure control, epilepsy surgery has the potential to improve patients' anxiety and depression symptoms. Few studies have assessed the long-term outcomes of anxiety and depressive symptoms after pediatric epilepsy surgery while using an appropriate control group. This study examined anxiety and depressive symptoms 4-11 years after surgery in surgical patients and in a control group of nonsurgical patients with pediatric-onset epilepsy. METHODS: Seventy-three surgical patients with a mean age of 19.87 (standard deviation [SD] 4.46, range 10.08-28.50) and 40 nonsurgical controls with a mean age of 20.31 (SD 4.01, range 12.08-27.25) completed the study measures. Patients completed the Child Depression Inventory II/Beck Depression Inventory II and State Trait Anxiety Inventory for Children/State Trait Anxiety Inventory and parents completed the Child Behavior Checklist/Adult Behavior Checklist to assess the patients' anxiety and depressive symptoms. Baseline measurements of affective symptoms (Child Behavior Checklist) were retrieved from the patients' medical records. RESULTS: Patient-reported affective functioning was obtained at the follow-up visit only. Patient-reported depressive symptoms and state and trait anxiety were similar for both groups. Based on parent reports at follow-up, patients with seizures were found to have significantly more depressive problems and anxious/depressed symptoms, and marginally more withdrawn symptoms relative to patients without seizures. SIGNIFICANCE: Seizure status was related to the presence of affective symptoms, irrespective of whether the patient had undergone surgery. In addition, parents and not patients reported the presence of anxiety and depressive symptoms, which indicates the importance of obtaining multiple informants to assess affective symptomatology.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".