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Record W4389575126 · doi:10.33920/med-01-2311-07

Features of cognitive impairment and anxiety-depressive disorders in patients in the acute period of stroke

2023· article· en· W4389575126 on OpenAlexaboutno aff
Е. Н. Кабаева, A. G. Gushchina, S. A. Krylova, N. V. Nozdryukhina, А. А. Pozdnyakov

Bibliographic record

VenueVestnik nevrologii psihiatrii i nejrohirurgii (Bulletin of Neurology Psychiatry and Neurosurgery) · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaAnxietyStroke (engine)MedicineMontreal Cognitive AssessmentDepression (economics)ComorbidityCognitionBeck Depression InventoryPhysical therapyDiseasePsychiatryPsychologyInternal medicine

Abstract

fetched live from OpenAlex

Introduction. Cognitive impairment after a stroke remains one of the leading causes of disability. Despite the introduction of new methods of treatment, diagnosis, and prevention of acute vascular diseases, more than 50 % of patients experience cognitive disorders after a stroke, a third of which reach a severe degree of dementia. The purpose of the study is to identify and assess risk factors for the development of cognitive impairment disorders in patients after a stroke and evaluate the impact of anxiety and depressive phenomena on their course. Materials and methods. The combined retro-prospective study included 40 patients with mild stroke according to the NIHSS. The diagnosis of stroke in all subjects was verified based on the results of MSCT of the brain. All patients underwent a comprehensive clinical and laboratory monitoring: a general examination; an assessment of neurological and functional status; an assessment of cognitive functions and mental status by MMSE scale and the Frontal Assessment Battery; an assessment of anxiety-depressive disorders by the Spielberger State-Trait Anxiety Inventory, the Beck Depression Inventory, and the Hamilton Rating Scale. The influence of individual risk factors on the development of cognitive impairment was evaluated. Results. More than 80 % of the patients with mild stroke in the acute period experienced a decrease in cognitive functions, while 62 % of the subjects showed signs of frontal dementia of varying severity. In the presence of high comorbidity with forms of the circulatory system pathologies (hypertension, diabetes, atrial fibrillation, coronary heart disease), there was a high frequency of both frontal dementia (in 87 % of the patients), and a decrease in cognitive functions on the MMSE scale (67 % of cases). All patients were diagnosed with depression, and half of them — with severe depression. 80 % of the patients with severe depression had severe cognitive changes on the MMSE scale, and 75 % had severe frontal dysfunction. Conclusion. Thus, high vascular comorbidity and the presence of anxiety and depressive disorders are significant risk factors for the development of cognitive impairment after a stroke. In this regard, measures aimed at their timely detection, treatment, and correction will make it possible to effectively reduce the incidence of post-stroke cognitive impairment, which, in turn, will improve the quality of life not only for the patients themselves but also for their relatives.

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)0.001
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 score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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