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Cognitive impairment in patients with minor stroke/TIA: a follow-up study

2017· article· en· W3031252073 on OpenAlexaboutno aff
Shenzhe Dong, Ping Chen, Yanguo Xu, Tao Liu, Renliang Zhao

Bibliographic record

VenueInt J Cerebrovasc Dis · 2017
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentMedicineStroke (engine)Internal medicineMinor strokeCognitionLogistic regressionCognitive impairmentDiseasePsychiatry

Abstract

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Objective To investigate the changes of cognitive impairment with disease progression in patients with minor stroke/transient ischemic attack (TIA). Methods Consecutive patients with minor stroke/TIA were enrolled prospectively. Montreal Cognitive Assessment (MoCA) was used to conduct the cognitive function assessment within 7 d of the onset (baseline), at 1 and 3 months, respectively. Compared with the baseline, the total scores of MoCA in patients increased by ≥2 at 3 months were cognitive function improvement and increased <2 were no cognitive function improvement. Multivariate logistic regression analysis was applied to identify the independent risk factors for no cognitive improvement. Results A total of 112 patients with minor stroke/TIA were enrolled in the study, including 63 patients (56.2%) with TIA and 49 (43.8%) with minor stroke. At baseline, 1 month, and 3 months, 77 (68.8%), 72 (64.3%) and 60 (53.6%) patients had cognitive impairment. At 3 months after the onset, the cognitive function of 25 patients (22.3%) were improved, in which 19 (76.0%) and 6 (24.0%) patients had TIA/minor stroke respectively; 87 (77.7%) did not have any improvement. Compared with the improvement group, the level of education was significantly lower (3.29±3.48 years vs. 5.63±4.26 years; t=2.814, P=0.006), the level of glycosylated hemoglobin was significantly higher (6.35%±1.26% vs. 7.21%±1.26%; t=-3.088, P=0.003) in the no improvement group, and the proportions of patients with minor stroke (49.4% vs. 24.0%; χ2=5.101, P=0.024), hypertension (52.9% vs. 24.0%; χ2=6.509, P=0.011), hyperlipidemia (51.7% vs. 24.0%; χ2=6.019, P=0.014), diabetes (41.4% vs. 16.0%; χ2=5.448, P=0.020), and coronary heart disease (32.2% vs.8.0%; χ2=5.792, P=0.016) were significantly higher. Multivariate logistic regression analysis showed that the level of education (odds ratio [OR] 1.364, 95% confidence interval [CI] 1.059-1.756; P=0.016), atrial fibrillation (OR 2.509, 95% CI 1.020-6.167; P=0.045), and higher glycosylated hemoglobin level (OR 1.586, 95% CI 1.021-2.034; P=0.030) were the independent risk factors for no cognitive function improvement at 3 months after the onset of minor stroke/TIA. As time went on, the MoCA score and visual spatial execution, memory, abstract and directional scores were increased significantly (P<0.001), while there were no significant differences in naming, attention, and language scores. Conclusions About 2/3 patients with minor stroke/TIA had cognitive impairment, and as time went on, they were improved. The lower education level, atrial fibrillation and higher baseline glycated hemoglobin were the independent risk factors for affecting no cognitive impairment improvement after monor stroke/TIA. Key words: Stroke; Brain Ischemia; Ischemic Attack, Transient; Cognition Disorders

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 score0.027
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)0.0010.000

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 head0.010
GPT teacher head0.257
Teacher spread0.247 · 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
Published2017
Admission routes1
Has abstractyes

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