Association of Depression and Anxiety with Epilepsy and Seizure Outcomes: Protocol of A Pooled Study-level Analysis of cohort studies
Bibliographic record
Abstract
BACKGROUND/ INTRODUCTION: Depression and anxiety disorders are serious mental disorders that are common among adults of all ages around the world. It has been reported people with depression and anxiety disorders will have a high risk of developing neurological conditions, including seizure disorders and epilepsy. Moreover, people with depression and anxiety disorders will have different clinical outcomes compared with control population. However, the associations between depression or anxiety disorders and epilepsy or seizure outcomes are controversial. Therefore, the aim of this study is to establish the associations between these psychological disorders and epilepsy or seizure outcomes. Methods Three eletronic databases including Pubmed, EMBASE and Cochrane Library will be systematically searched from inception through March 2023 to determine relevant cohort studies investigating the associations between depression or anxiety disorders and epilepsy or seizure outcomes. Two independent review authors will extract data from eligible studies using predesigned standardized data extraction sheets. The results will be crosschecked separately the two authors. A third author will adjudicate discrepancies. Quality assessment will be performed using the Newcastle-Ottawa quality assessment scale (NOS) tool. Pooled risk estimates (RRs or HRs with their 95% CI) will be calculated using the DerSimonian-Laird random-effects model. If between-study heterogeneity is identified, we will undertake subgroup analysis or meta-regression to investigate the possible sources of heterogeneity (participants, exposure, outcome and study design) stratified by multiple study characteristics. Potential publication bias will be detected by inspection of funnel plot asymmetry, combined with the Egger linear regression approach (Egger’s test) and the Begg rank correlation test (Begg’s test). DISCUSSION: This pooled analysis will evaluate the association of depression or anxiety and epilepsy or seizure outcomes, providing high-level evidence regarding the early identification and prevention of epilepsy or seisure with its outcomes. Key words Depression; Anxiety; Epilepsy; Seizure; Outcomes; Pooled analysis; Cohort studies
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".