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Experience with citicoline in patients with post-stroke cognitive impairment

2020· article· en· W3080651700 on OpenAlexaboutno aff
А Н Боголепова, С. Г. Бурд, А. В. Лебедева, Е. А. Коваленко

Bibliographic record

VenueNeurology neuropsychiatry Psychosomatics · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCiticolineAnxietyCognitionStroke (engine)Depression (economics)Montreal Cognitive AssessmentAdverse effectMedicineCognitive impairmentCognitive declinePsychiatryInternal medicinePsychologyAnesthesiaDementiaDisease

Abstract

fetched live from OpenAlex

Objective : to investigate the efficacy and safety of citicoline (Ceresil ® Canon) in patients with post-stroke cognitive impairment. Patients and methods . Examinations were made in 33 patients aged 45 years and older who had experienced primary ischemic hemispheric stroke with complaints of a decline in memory or other cognitive functions. The cognitive status was assessed using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). The presence of anxiety-depressive spectrum disorders was determined on the Hospital Anxiety and Depression Scale. All the patients received citicoline (Ceresil ® Canon) oral solution at a dose of 1000 mg/day for 3 months. Results and discussion . Citicoline administration showed a statistically significant reduction in the severity of cognitive impairment (p<0.001). The time course of positive changes in the cognitive status of patients was reflected by an increase in the median score on the MMSE from 26 [25; 27.5] to 28 [26.5; 29] and on MoCA from 23 [21; 25] to 25 [22; 26]. There was a decline in the number of patients with anxiety-depressive disorders. No adverse events or side effects were found in the patients. Conclusion . The findings suggest that citicoline (Ceresil ® Canon) produced as an oral solution is well tolerated and improves cognitive functions and affective sphere in patients in the recovery period of ischemic stroke.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.237
Teacher spread0.224 · 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; a candidate call from one teacher head, not a consensus.

Study designObservational
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

Citations4
Published2020
Admission routes1
Has abstractyes

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