Assessment of cognitive functions and related risk factors in Iranian patients with generalized epilepsy as compared to patients with non-epileptic neurological disorders
Bibliographic record
Abstract
Background: The cognitive impairment in patients with generalized epilepsy may affect their social efficiency and quality of life (QOL). The aim of this study is to determine the cognitive dysfunction and related risk factors in patients with generalized epilepsy as compared to patients with non-epileptic neurological disorders. Methods: In the present descriptive cross-sectional study, the cognitive function was assessed by Montreal Cognitive Assessment (MoCA) test in 62 patients with generalized epilepsy and also 62 patients with non-epileptic neurological diseases who referred to the Neurology Clinic, Semnan University of Medical Sciences, Semnan, Iran. The relationship between cognitive impairment and related risk factors was also investigated. The data were analyzed by SPSS software. Results: The mean score of MoCA in the patients with generalized epilepsy and the control group was 22.80 ± 4.14 and 26.48 ± 2.85, respectively (P < 0.050). The results indicated significantly lower MoCA scores in the epileptic group rather than the non-epileptic one (P < 0.001). Moreover, there was a significant relationship between MoCA score and age, education level, living place, the dose and rate of medicines, and the number of seizures in patients with epilepsy (P < 0.001). Gender and the duration of disease had no significant effects on the cognitive impairment of patients with epilepsy (P > 0.05). Conclusion: Patients with epilepsy had a significant cognitive impairment as compared to the patients with non-epileptic neurological disorders. Age, education level, living place, the dose and rate of medicines, and the number of seizures were the risk factors of cognitive impairment in the patients with epilepsy, while duration of disease and gender had no effects on the intensity of cognitive deficits.
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 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) | 0.001 | 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; 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".