Psychiatric comorbidity in people with epilepsy in Ethiopia: Systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Psychiatric comorbidity is a double burden among people with epilepsy. Since people with epilepsy are more vulnerable to psychiatric illnesses. So, the implementation of an appropriate intervention to minimize the double burden of comorbidity is very important. Therefore, this systematic review and meta-analysis aimed to assess the prevalence and associated factors of psychiatric comorbidity among people with epilepsy in Ethiopia. METHODS: This systematic review and meta-analysis followed the Preferred Reporting Item Review and Meta-analysis (PRISMA) guideline. Searching databases were PubMed, PsycINFO, Web of Science, Cochrane Library, Google Scholar, and HINARI.The quality of the included articles was assessed using the Newcastle-Ottawa Scale (NOS). The pooled meta-logistic regression was computed to estimate the pooled prevalence and the risk factors with a 95% CI. RESULTS: The pooled prevalence of psychiatric comorbidity in people with epilepsy was 34.69 % (95 % CI: 29.27, 40.10). Frequent seizures (POR = 2.94: 95 % CI: 1.08, 8.00) and a history of divorce (POR = 2.00: 95 % CI: 1.09, 3.81) were associated factors of psychiatric comorbidity in people with epilepsy. CONCLUSIONS: This systematic review and meta-analysis revealed that the pooled prevalence of psychiatric comorbidity among people with epilepsy was found to be higher compared with the general population. Therefore, among people with epilepsy, parallel psychiatric evaluation is very important along with neurological evaluation.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.003 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".