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.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".