Consensus‐based recommendations for the diagnosis and treatment of anxiety and depression in children and adolescents with epilepsy: A report from the Psychiatric Pediatric Issues Task Force of the International League Against Epilepsy
Bibliographic record
Abstract
The Psychiatric Pediatric Issues Task Force of the International League Against Epilepsy (ILAE) aimed to develop recommendations for the diagnosis and treatment of anxiety and depression in children and adolescents with epilepsy. The Task Force conducted a systematic review and identified two studies that assessed the accuracy of four screening measures for depression and anxiety symptoms compared with a psychiatric interview. Nine studies met the eligibility criteria for treatment of anxiety and depressive disorders or symptoms. The risk of bias and certainty of evidence were assessed. The evidence generated by this review followed by consensus where evidence was missing generated 47 recommendations. Those with a high level of agreement (≥80%) are summarized. Diagnosis: (1) Universal screening for anxiety and depression is recommended. Closer surveillance is recommended for children after 12 years, at higher risk (e.g., suicide-related behavior), with subthreshold symptoms, and experiencing seizure worsening or therapeutic modifications. (2) Multiple sources of ascertainment and a formal screening are recommended. Clinical interviews are recommended whenever possible. The healthcare provider must always explain that symptom recognition is essential to optimize treatment outcomes and reduce morbidity. (3) Questioning about the relationship between symptoms of anxiety or depression with seizure worsening/control and behavioral adverse effects of antiseizure medications is recommended. Treatment: (1) An individualized treatment plan is recommended. (2) For mild depression, active monitoring must be considered. (3) Referral to a mental health care provider must be considered for moderate to severe depression and anxiety. (4) Clinical care pathways must be developed. (5) Psychosocial interventions must be tailored and age-appropriate. (6) Healthcare providers must monitor children with epilepsy who are prescribed antidepressants, considering symptoms and functioning that may not improve simultaneously. (7) Caregiver education is essential to ensure treatment adherence. (8) A shared-care model involving all healthcare providers is recommended for children and adolescents with epilepsy and mental health disorders. We identified clinical decisions in the management of depression and anxiety that lack solid evidence and provide consensus-based guidance to address the care of children and adolescents with epilepsy.
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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 | 0.086 | 0.192 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.021 |
| Bibliometrics | 0.017 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.014 | 0.007 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".