P300 event-related potentials in people with epilepsy: clinico-neurophysiologic study
Bibliographic record
Abstract
Abstract Background There is increasing evidence that prolonged or recurrent seizures can cause or exacerbate cognitive impairment (CI) in memory, attention, orientation, and visuospatial and abstraction disabilities, all of which can jeopardize educational progress and achievement throughout life. The objectives of our study are to assess the cognitive functions in people with epilepsy (PwE) using P300 event-related potentials (ERPs), and correlate each P300 components with six explanatory variables (epilepsy type, seizure type, NHS3 score- seizure severity, disease duration, age at first seizure, and the number of anticonvulsant medications). Methods One hundred and two PwE [52 with focal epilepsy and 50 with generalized epilepsy, as classified by the International League Against Epilepsy in 2017]. They underwent electroencephalography (EEG) and P300. The Montreal Cognitive Assessment (MoCA) scale was used to assess baseline cognitive functions. Results Epileptic patients showed significant latency prolongation and amplitude reduction of P300 as compared to non-epileptic population. Longer P300 latency and lower amplitude were seen in patients with abnormal EEG records. P300 latency was longer in patients using poly-therapy. P300 components correlated well with age at presentation and disease duration but not with NHS3. According to epilepsy type, 50.98% of PwE had focal epilepsy and 49.02% had generalized epilepsy, 85.29% of them had abnormal EEG recording. Considering seizure type, 47.06% had a generalized tonic–clonic seizure, 38.24% had a focal to bilateral tonic–clonic seizure, 20.59% had a myoclonic seizure, 12.75% had a focal with impaired awareness seizure, 3.92% had a focal aware seizure, and 2.94% had an absence seizure. Seventy-seven PwE had one type of seizure, while 25 had more than one type of seizure. The NHS3 score was higher in those with a single seizure type than in those with multiple seizure types. Conclusion All seizure types had an abnormal P300 component, indicating cognitive function deficits. P300 may be a promising objective method for assessing cognitive function in PwE. The number of antiepileptic drugs used, the presence of EEG abnormalities, the age at presentation, and the duration of the disease are the factors that best correlate with cognitive impairment (CI).
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".