Mood and Anxiety Disorders and Suicidality in Patients With Newly Diagnosed Focal Epilepsy
Bibliographic record
Abstract
Rationale and aim of the study: Mood, anxiety disorders and suicidality are more frequent in people with epilepsy than in the general population. Yet, their prevalence and the types of mood and anxiety disorders associated with suicidality at the time of the epilepsy diagnosis is not established. We sought to answer these questions in patients with newly diagnosed focal epilepsy and to assess their association with suicidal ideation and attempts. Methods: The data were derived from the Human Epilepsy Project study. A total of 347 consecutive adults aged 18 to 60 years old with newly diagnosed focal epilepsy were enrolled within 4 months of starting treatment. The types of mood and anxiety disorders were identified with the MINI International Neuropsychiatric Interview, while suicidal ideation (lifetime, current, active and passive) and suicidal attempts (lifetime, current) were established with the Columbia Suicidality Severity Rating Scale (CSSRS). Statistical analyses included T-test, Chi-square statistics and logistic regression analyses. Results: A total of 151 (43.5%) subjects had a psychiatric diagnosis; 134 (38.6%) met criteria for a mood and / or anxiety disorder and 75 (21.6%) reported suicidal ideation with or without attempts. Mood (23.6%) and anxiety (27.4%) disorders had comparable prevalence rates, while both disorders occurred together in 43 patients (12.4%). Major depressive disorders (MDD) had a slightly higher prevalence than bipolar disorders (BPD) (9.5% vs 6.9%, respectively). Explanatory variables of suicidality included MDD, BPD, panic disorders and agoraphobia, with BPD and panic disorders being the strongest variables, particularly for active suicidal ideation and suicidal attempts. Conclusions: In patients with newly diagnosed focal epilepsy, the prevalence of mood, anxiety disorders and suicidality are higher than in the general population and comparable to those of patients with established epilepsy. Their recognition at the time of the initial epilepsy evaluation is of the essence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".