MétaCan
Menu
Back to cohort
Record W6906496435 · doi:10.17605/osf.io/wm2x8

Association of Depression and Anxiety with Epilepsy and Seizure Outcomes: Protocol of A Pooled Study-level Analysis of cohort studies

2023· article· en· W6906496435 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2023
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyFunnel plotEpilepsyDepression (economics)Meta-analysisPublication biasCohort

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.030
GPT teacher head0.351
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueOSF Preprints (OSF Preprints)Same topicEpilepsy research and treatmentFrench-language works237,207