DEPRESSION, SEARCH FOR NEW CHALLENGES IN TREATMENT
Bibliographic record
Abstract
IntroductionDepression is one of the most disabling diseases of the 21st centuryEarly recovery avoids chronic symptoms.Currently the patient not only seeks an improvement of mood but also the social aspect, work, relationship and sexual areaGoals In the Hospital of Toledo (Spain), a study was carried out to check the improvements in affective, anxiety and cognitive status in patients with 3 types of antidepressants: selective serotonin reuptake inhibitors, antidepressants dual and a multimodal antidepressant (vortioxetine) MethodsOur inclusion criteria were: being over 18 years of age, diagnosis of depression or Adaptive Disorder according to DSM-V criteria, not having received antidepressant treatment in the last year, not presenting intellectual disability, signing the informed consent.The Montreal Cognitive Assessment (MOCA) scales for cognitive aspects, the Montgomery-Asberg Depression Rating Scale (MADRS) for depressive symptoms and the Hamilton scale for measuring anxiety have been used.ResultsThe data analysis was through the SPSS program the data analysis was carried out. Similar results were obtained in treatment with any of the three antidepressants in anxiety symptoms, the depressive symptoms improved more significantly with dual antidepressants and with the multimodal antidepressant and the cognition improved with the multimodal antidepressantConclusionsCurrently the treatment of depression implies a greater ambition in the recovery of all areas of life of the patient in the shortest time in the search for complete recovery.Our results indicate better functionality with dual antidepressants and vortioxetine
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".