Clinical experience of the use of agomelatine in the treatment of patients with depression and chronic brain ischemia
Bibliographic record
Abstract
OBJECTIVE: To study the efficacy and tolerability of agomelatine (valdoxan) in treatment of mild depressive states in patients with chronic brain ischemia (CBI). MATERIAL AND METHODS: The study comprised 33 patients (23 women, 10 men, average age 54.5 years), including 12 people (36.4%) with CBI, stage I, and 21 (63.6%) with CBI, stage II. All patients had a single depressive episode of mild severity. Diagnosis of affective and cognitive impairment was carried out using clinical and neuropsychological methods (the Hamilton Depression Rating Scale (HDRS-17), the Hospital Anxiety and Depression Scale (HADS), the night sleep questionnaire developed by A.M. Vein, the Mini-mental state examination (MMSE), the modified Mini-Cog method, the Montreal Cognitive Assessment Scale (MoCA), the Clinical Global Impression scale (CGI-S, CGI-I) to assess the degree and dynamics of the disease, the Patient Global Impression (PGI) scale. The survey had been performed after 2,4 and 8 weeks of treatment. Agomelatine (valdoxan) was used 1 time per day in the evening in a dose of 25 mg (1 tablet). RESULTS AND CONCLUSION: Agomelatine improved sleep from the second week of treatment, reduced anxiety symptoms after six weeks and depressive symptoms after eight weeks. The improvement of cognitive functions was noted as well. No side-effects was observed. The results revealed the high antidepressive activity of the drug in treatment of mild depressive states in patients with chronic brain ischemia, the balanced spectrum of effects on anxiety, depression, insomnia, the positive effect on cognitive functions that allows to recommend agomelatine in treatment of patients with CBI.
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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 | 0.001 | 0.003 |
| 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) | 0.001 | 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".