IMPACT OF EPILEPSY DEVELOPMENT ON COGNITIVE FUNCTION IN STROKE SURVIVORS: A RETROSPECTIVE COHORT ANALYSIS.
Bibliographic record
Abstract
BACKGROUND: Epilepsy frequently occurs as a neurological complication post-stroke, substantially impacting survivors' quality of life and prognoses. However, the precise incidence and cognitive consequences of post-stroke epilepsy remain underexplored. Understanding these aspects is critical for informing clinical management strategies. METHODS: This retrospective cohort study aimed to investigate the incidence of epilepsy and its cognitive implications among 74 stroke survivors treated at the Regional Hospital of Berat from 2020 to 2023. Participants were assessed for epilepsy development during a three-year follow-up period, with relevant demographic and clinical data collected. Cognitive function was evaluated using standardized tests, including the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Logistic regression analysis identified factors associated with post-stroke epilepsy, while repeated measures ANOVA assessed cognitive changes over time. RESULTS: During the follow-up period, 21.6% of stroke survivors developed epilepsy, with an average age of onset at 61.5 years and a median time from stroke to epilepsy diagnosis of 8.5 months. Logistic regression identified older age at stroke onset (p=0.012), hemorrhagic stroke subtype (p=0.024), prior stroke history (p=0.004), and cortical involvement (p=0.047) as independent predictors of epilepsy development. Stroke survivors with epilepsy exhibited significantly poorer cognitive performance across memory, attention, executive function, and processing speed domains compared to those without epilepsy. Over time, the epilepsy group experienced a significant decline in MMSE scores from 25.6 to 22.1 (p<0.001) and MoCA scores from 20.4 to 17.6 (p<0.001), while non-epilepsy group scores remained relatively stable. A significant interaction effect between epilepsy status and time (p<0.001) highlighted the cognitive decline associated with epilepsy onset. CONCLUSION: The study underscores the critical importance of early identification and management of epilepsy in stroke survivors to mitigate cognitive decline. Understanding the risk factors for post-stroke epilepsy and its cognitive consequences can guide targeted interventions aimed at preserving cognitive function and enhancing the overall well-being of stroke survivors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".