Antiepileptic drugs and sexual dysfunction in patients with epilepsy
Bibliographic record
Abstract
Introduction Epilepsy is a common disease that is mostly treated with antiepileptic drugs (AEDs). The sexual dysfunction (SD) side effects related to the use of AEDs have not received sufficient attention. Objectives The aims of this study were to assess the prevalence of SD and to study the role played by the AEDs among patients with epilepsy. Methods A cross-sectional and analytic study was conducted from September to December 2023, among patients with epilepsy follow up in the neurology outpatients of the University Hospital in Gabes (Tunisia), received AEDs, married for at least six months and sexually active. We collected the therapeutics data including type and number of prescribed AEDs and medication adherence, using pre-established form. SD was measured using the Arizona Sexual Experience Scale (ASEX) questionnaire. Results Forty-five patients were enrolled (68.9% male and 31.1% female). The average age was 46.76 years (SD=12.39). The majority of patients had a low socio-economic status (64.4%). Carbamazepine and phenobarbital were the most commonly AEDs prescribed (57.8% and 53.3% respectively), especially as monotherapy (62.3%). Poor medication adherence was observed in 13 patients (28.9%). The frequency of SD among patients, based on ASEX questionnaire, was 44.4%. The factors associated with SD included carbamazepine and phenobarbital prescription (p=0.036 and p=0.045 respectively), double or multiple drug therapies (p=0.006) and poor medication adherence (p=0.033). Conclusions SD is very common in patients with epilepsy. This seems to be related to AEDs such as using of carbamazepine and phenobarbital, polytherapy and poor medication adherence. Disclosure of Interest None Declared
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 | 0.000 | 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".