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Record W3147702125

Relationship between cognitive impairment and cerebrovascular stenosis in patients with subcortical infarction

2015· article· en· W3147702125 on OpenAlexaboutno aff
Zhou Kai-g

Bibliographic record

VenueAcademic Journal of Second Military Medical University · 2015
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStenosisCardiologyInternal medicineMagnetic resonance angiographyCerebral infarctionMiddle cerebral arteryAngiographyRadiologyMagnetic resonance imagingIschemia
DOInot available

Abstract

fetched live from OpenAlex

Objective To investigate the intracranial vascular lesions in patients with subcortical infarction-induced vascular cognitive impairment(VCI),and to investigate the etiology and mechanisms of VCI.Methods Inpatients with subcortical infarction in our hospital were enrolled in this study from Nov.2012 to Feb.2014,with those unable to complete the cognitive evaluation eliminated.According to the diagnostic criteria of VCI the patients were divided into two groups:49with cognitive impairment(VCI group)and 42 without cognitive impairment(NVCI group).The clinical data,physical examinations,laboratory tests,and the Montreal Cognitive Assessment(MoCA)scale scores were collected.Cerebral blood vessels were assessed by CT angiography or magnetic resonance angiography(MRA).Results The results showed that,according to TOAST classification,VCI group had 24(48.98%)patients with large artery atherosclerosis(LAA)and NVCI group had 22(52.38%),showing no significant difference between the two groups.CTA or MRA indicated that 37(75.51%)patients in VCI group had vascular stenosis,with 75.25% of the 37 patients having intracranial vascular stenosis and 28.71%with middle cerebral artery stenosis.Patients with single cerebral artery stenosis accounted for 18.37% and those with the multiple artery stenosis accounted for 57.14%.CTA or MRA indicated that 34(80.95%)patients in NVCI group had vascular stenosis,with 60% having intracranial vascular stenosis,including 32% with middle cerebral artery stenosis,26.19% with single cerebral artery stenosis,and 54.76% with the multiple artery stenosis,with the latter two data being significantly different from the VCI group(P0.05).In VCI group,the number of intracranial vascular stenosis branches ranged 0-6,with a mean of(1.51±1.67),and a negative relation was found between numbers of stenosis arteries and MoCA scores in patients of VCI group(rs=-0.283,P0.05).Conclusion Different from the common causes of small blood vessels,LAA is the most common etiology of subcortical VCI,which implied that exploring the LAA causes of small lesions is crucial for the prevention of VCI in Chinese patients.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.234
Teacher spread0.217 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2015
Admission routes1
Has abstractyes

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