MétaCan
Menu
Back to cohort
Record W1206347719

Лечение недементных когнитивных нарушений у пациентов с артериальной гипертензией и церебральным атеросклерозом (по данным российского мультицентрового исследования «Фуэте»)

2012· paratext· ru· W1206347719 on OpenAlexaboutno aff
Н Н Яхно, В. В. Захаров, Я. Страчунская, Б. Вeльмейкин, В. Житкова, Л. А. Иванова, В. Курушина, В. Похабов, А. Свиркунова

Bibliographic record

VenueThe Neurological Journal · 2012
Typeparatext
Languageru
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaMedicineCognitionVinpocetineAgonistAdrenergic agonistEffects of sleep deprivation on cognitive performanceInternal medicinePsychologyPsychiatryPharmacologyReceptor
DOInot available

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0010.003
Science and technology studies0.0070.005
Scholarly communication0.0030.001
Open science0.0100.004
Research integrity0.0040.018
Insufficient payload (model declined to judge)0.0390.043

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.

Opus teacher head0.069
GPT teacher head0.302
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueThe Neurological JournalSame topicNeurological Disorders and TreatmentsFrench-language works237,207