Depresión en pacientes con epilepsia. Conceptos fisiopatológicos, clínicos y estrategias terapéuticas
Bibliographic record
Abstract
INTRODUCTION: Depression and epilepsy are highly prevalent diseases and represent a worldwide public health problem. DEVELOPMENT: A non-systematic search was performed in PubMed (MEDLINE) considering current topics in pathophysiological, clinical concepts and treatment strategies in people with epilepsy and depression. RESULTS AND CONCLUSIONS: Depression and epilepsy have a bidirectional relationship and share some pathophysiological substrates. Depression is the most common neuropsychiatric manifestation in epilepsy; screening and diagnosis are important to start a timely treatment. Antidepressant drugs does not increase the frequency of seizures, on the contrary, it is believed that antidepressants may help reducing the frequency of seizures. In addition, other antidepressant therapies such as Cognitive Behavioral Therapy and neuromodulation may be also effective for reducing the frequency of seizures. However the evidence regarding antidepressant treatment(s) in epilepsy is limited and further prospective studies are needed to better characterize the possible therapeutic strategies and develop standarized treatment guidelines.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.009 |
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; both teacher heads agree on what is shown here.
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".