P.030 Hippocampal deep brain stimulation provides drastic relief for intractable seizures
Bibliographic record
Abstract
Background: Deep brain stimulation (DBS) is the application of electrical currents via depth electrodes to regulate neuronal activity. DBS has been shown as a productive intervention for seizure control in patients with drug-resistance. This case had both a failed response to antiepileptic drugs (AEDs) and a temporal lobectomy. Methods: This case details the evolution of epilepsy in a 29-year-old female with seizures since the age of around 10. The patient has been followed for 6 months to monitor the treatment effects. No medication changes were made post-procedure. Results: The patient experienced a seizure frequency of 2-5 events per month. The patient had a right temporal lobectomy at age 12, which led to only 3 years in remission. The events are complex partial seizures characterized by unresponsive staring, lip smacking, hand automatisms and confusion. The patient failed 7 AEDs. Intracranial recording showed the most frequent activity coming from the left anterior and posterior hippocampus. Two depth electrodes were implanted accordingly. Stimulation began in September 2016 and the patient has since had only 2 seizures. Conclusions: Deep brain stimulation provides extensive relief for this case of intractable epilepsy. The patient’s level of awareness, mood, and quality of life all improved significantly in response to treatment.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.005 | 0.001 |
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".