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COMPREHENSIVE ASSESSMENT OF THE PREVALENCE OF DEMENTIA AFTER STROKE

2022· article· ru· W4285987772 on OpenAlexaboutno aff
З.Б. Абдрахманова, Н.З. Шапамбаев, Б.Т. Сейтханова, Г.А. Байжанова, Л.Н. Магай

Bibliographic record

VenueFarmaciâ Kazahstana · 2022
Typearticle
Languageru
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentDementiaCognitionStroke (engine)Cognitive impairmentMedicinePhysical therapyRehabilitationPhysical medicine and rehabilitationPsychologyGerontologyPsychiatryInternal medicineDisease

Abstract

fetched live from OpenAlex

В качестве причины осложнений у больных, перенесших Инсульт, обращено внимание на деменции. Причин переливания крови в головной мозг или дефицита крови много. В статье представлены тесты, проводимые с целью выявления повреждения когнитивных функций ранним признаком деменции (шкала MMSE, Монреальская когнитивная шкала (MoCA)). Оценка их эффективности, чувствительности и преимущества. Цель: Оценка распространенности постинсультной деменции по шкалам MMSE, Монреальская когнитивная (MoCA). Результаты: В исследовании приняли участие 255 респондентов, из них мужчины составили 54,2%, женщины-45,8%. Встречаемость когнитивных расстройств с диагнозами i63.3, I61.0, G45.8, I 60.1 по МКБ-10 инсульта оценивали 100 больных по шкале MMSE и 155 больных по Монреальской когнитивной шкале (MoCA). В этом исследовании было установлено, что определение деменции в раннем этапе наиболее эффективна этим шкалам. Заключение: При осмотре больного когнитивные нарушения первого проявления инсульта существенно не учитываются при обследовании больного. Это, в свою очередь, негативно сказывается на проведении лечебно-оздоровительных мероприятий, снижает прогностические возможности реабилитационного процесса. Поэтому необходимым компонентом комплексного обследования пациента с инсультом должно быть определение тяжести когнитивного дефицита. As a cause of complications in Stroke patients, attention is drawn to dementia. There are many reasons for blood transfusion to the brain or blood deficiency. The article presents tests conducted to identify damage to cognitive functions by an early sign of dementia (MMSE scale, Montreal Cognitive Scale (MoCA)). Evaluation of their effectiveness, sensitivity and advantages. Objective: Assessment of the prevalence of post-stroke dementia according to MMSE scales, Montreal Cognitive (MoCA). Results: 255 respondents took part in the study, of which 54.2% were men and 45.8% were women. The incidence of cognitive disorders with diagnoses i63.3, I61.0, G45.8, I 60.1 according to ICD10 stroke was assessed in 100 patients on the MMSE scale and 155 patients on the Montreal Cognitive Scale (MoCA). In this study it was found that the definition of dementia at an early stage is most effective for these scales. Сonclusions: When examining a patient, cognitive impairments of the first manifestation of stroke are not significantly taken into account when examining a patient. This, in turn, has a negative impact on the conduct of therapeutic and recreational activities, reduces the prognostic possibilities of the rehabilitation process. Therefore, a necessary component of a comprehensive examination of a stroke patient should be to determine the severity of cognitive deficits.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.300
Teacher spread0.269 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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