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Effects of comprehensive training on mild cognitive impairment in patients with stroke

2014· article· en· W3029476286 on OpenAlexaboutno aff
Huixiang Yang

Bibliographic record

VenueZhonghua xingwei yixue yu naokexue zazhi · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentBarthel indexCognitive impairmentIntervention (counseling)CognitionPhysical therapyMedicineStroke (engine)Cognitive trainingCognitive InterventionQuality of life (healthcare)Activities of daily livingPsychologyPhysical medicine and rehabilitationPsychiatryNursing

Abstract

fetched live from OpenAlex

Objective To explore the comprehensive training effects of mild cognitive impairment(MCI) in patients with cerebral apoplexy. Methods Selected 70 cases of cerebral apoplexy patients with MCI were randomly divided into control group(n=35) and intervention group(n=35). The patients in control group maintained the original treatment and nursing, and the comprehensive training was used in intervention group. Before and after the intervention Montreal cognitive assessment scale (MoCA), daily life ability Barthel index (MBI) were used to evaluate the change of MCI patients. Results After training, the score of MBI in the intervention group(55.71±5.08) was significantly higher than that of before training (52.59±5.62) and the control group(53.65±5.78). After training, the score of MoCA in the intervention group(23.37±2.40)was significantly higher than that of before training (21.77±2.53)and the control group(21.73±2.43). Conclusion Comprehensive training can improve cognitive function in patients with cerebral apoplexy, ease the burden on society and the family, and improve the quality of life. Key words: Stroke; Mild cognitive impairment; Comprehensive training

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 score0.369
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.235
Teacher spread0.215 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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