Лечение недементных когнитивных нарушений у пациентов с артериальной гипертензией и церебральным атеросклерозом (по данным российского мультицентрового исследования «Фуэте»)
Bibliographic record
Abstract
The treatment of non dementia cognitive impairments remains a serious therapeutic problem. The article presents the results of effectiveness of dopamine agonist and presynaptic alfa-2-adrenergic receptors antagonist Pronoran in the treatment of mild and moderate cognitive impairments. One hundred and eighty nine patients (189) with non-dementia cognitive impairment caused by arterial hypertension or cerebral atherosclerosis were enrolled into the study. The patients were divided into 4 therapeutic groups (group of pronoran, pyracetam, gingko biloba and vinpocetine). Treatment efficacy was measured with Montreal cognitive assessment scale («mocatest») and McNeir memory self- assessment questionnaire. In 3 months of follow-up significant diminishing of cognitive impairments was observed in all therapeutic groups. However, in Pronoran group from the 60th day of the treatment the improvement of cognitive functions was significantly more evident than in the groups of vasoactive or metabolic 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) | 0.003 | 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".