Anxiety and Depression in Adult First Seizure Presentations
Bibliographic record
Abstract
OBJECTIVE: To define the prevalence of psychiatric symptoms of anxiety and depression in patients at the time of their first seizure presentation to a neurologist. METHODS: Our pilot study uses a cohort approach with multimodal data (clinical, social, structural [3T magnetic resonance imaging], and functional [electroencephalogram]). We screened 105 patients referred to the Halifax First Seizure Clinic between 2014 and 2016 and 51 controls. All participants completed two screening questionnaires: Neurological Disorders Depression Inventory for Epilepsy and Generalized Anxiety Disorder 7-Item. After applying the exclusion criteria, the study population consisted of 57 patients with unprovoked first seizure and 31 controls. The prevalence of anxiety and depression was based on cutoff scores of >15 and >14 respectively. RESULTS: Unprovoked first seizure patients showed higher prevalence of depression (33%) compared with control (6%) with an odds ratio (OR) of 2.75 (95% confidence interval [CI], 0.72-10.5). There was no significant difference in the prevalence of anxiety between control subjects (9.7%) and unprovoked first seizure patients (23%). Subcategory analysis conducted after diagnosis confirmation revealed significantly increased OR of depression in patients diagnosed with new-onset epilepsy (OR, 11.6; 95% CI, 2.1-64.0) and newly diagnosed epilepsy (OR, 20.0; 95% CI,2.2-181), but not first seizure only patients (OR, 2.2; 95% CI,0.28-17.6) compared with control. CONCLUSIONS: Our study supports a bidirectional relationship between the first seizure and depression. Prevalence rate of depression increased with duration of undiagnosed epilepsy at the time of first clinical assessment.
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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 | 0.001 | 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".