P.111 Investigation of clinical features, EEG findings, and brain imaging in psychiatric patients with epilepsy at Razi Psychiatric Hospital
Bibliographic record
Abstract
Background: This study aimed to assess the clinical features, Electroencephalography (EEG) findings, and brain imaging results in psychiatric patients diagnosed with epilepsy at Razi Psychiatric Hospital. Methods: This retrospective descriptive-analytical study was carried out on patients with epilepsy and psychiatric disorders admitted to Razi Psychiatric Hospital over two years. A total of 94 patient files seizure and epilepsy comorbidity, recorded in the hospital’s health information system (HIS), were reviewed. Data collection involved a demographic checklist and an epilepsy scale; the latter, developed by DiIorio, Colleen, et al., encompassed personal characteristics, mental disorders, epilepsy, and seizures. The Kruskal-Wallis and MannWhitney non-parametric tests were utilized to compare the mean scores of variables, with SPSS software, version 21 facilitating the analysis Results: Out of 94 patients with seizure and epilepsy, 9.6% had focal seizure, 26.6% had generalized epilepsy, 36.1% had focal-generalized seizure, and 26.8% had unknown seizure. About 12% had a structural etiology, while the remaining 88% had an etiology that remained unidentified. Conclusions: The findings indicate that epilepsy, affecting individuals from adolescence through to old age, can lead to psychiatric disorders. For many patients, the etiology of their condition remains elusive, and EEG findings and brain imaging appear normal in the majority of cases
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".