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Record W4405867821 · doi:10.4103/pmrr.pmrr_38_24

Psychiatric Comorbidities in Adults with Epilepsy: A Systematic Review

2024· review· en· W4405867821 on OpenAlexaboutno aff
Arun Murugan, S Geethanjali, M. R. Jeevapriya, G Pavithra, O. V. Athira, Kasinathan Sathishkumar

Bibliographic record

VenuePreventive Medicine Research & Reviews · 2024
Typereview
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsPsychiatryAnxietyEpilepsyBipolar disorderDepression (economics)ComorbidityMedicineSpecific phobiaSystematic reviewPsychosisClinical psychologyAnxiety disorderMEDLINEMood

Abstract

fetched live from OpenAlex

Abstract Epilepsy is a chronic neurological condition that is highly predisposed to a variety of mental health problems. This systematic literature review identified original research articles that reported the prevalence of psychiatric comorbidities based on clinical assessments amongst patients with epilepsy (PWE). The included articles were published from 2000 to 2022 and focused on adults aged ≥18 years who had psychiatric diagnoses. The primary outcome was the prevalence of psychiatric comorbidities amongst PWE. A modified Newcastle–Ottawa Scale was used to assess the quality of the studies. Thirty-three articles were reviewed in full-text screening. Out of these, 15 articles that were consistent with the inclusion criteria were included in our systematic review. This protocol was registered in PROSPERO with registration ID CRD42023461739. General Anxiety Disorder and Major Depressive Disorder were the most common psychiatric comorbidities, with prevalence rates of 20.14% and 23.94%, respectively. Other reported comorbidities included post-traumatic stress disorder (8.3%), obsessive–compulsive disorder (2.9%), bipolar disorder (7.1%), psychosis (8.2%) and phobia (18.25%). These findings suggest that screening tools for depression and anxiety should be included as part of the training for epilepsy care.

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)0.017
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.379
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0150.002
Bibliometrics0.0030.007
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0010.004

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.

Opus teacher head0.146
GPT teacher head0.488
Teacher spread0.342 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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

Citations2
Published2024
Admission routes1
Has abstractyes

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