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Correlation between collateral circulation and cognitive impairment in patients with acute ischemic stroke

2018· article· en· W3030598705 on OpenAlexaboutno aff
Yang Qian-jin, Chen Rongzhi

Bibliographic record

VenueInt J Cerebrovasc Dis · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCollateral circulationMedicineInternal medicineStroke (engine)CardiologyNeurologyCollateralLogistic regressionStenosisPsychiatryFinance

Abstract

fetched live from OpenAlex

Objective To investigate the risk factors for cognitive impairment and their correlation with collateral circulation in patients with acute ischemic stroke. Methods From January 2016 to December 2017, patients with acute ischemic stroke admitted to the Department of Neurology, Jiangmen People's Hospital were enrolled. According to their status of collateral circulation, they were divided into either good collateral circulation group or poor collateral circulation group. According to the Montreal cognitive score, they were divided into cognitive impairment group and non-cognitive impairment group. Multivariate logistic regression analysis identified the independent risk factors for cognitive impairment in patients with acute ischemic stroke. Results A total of 225 patients were enrolled, including 106 females (47.1%) and 119 males (52.9%), aged 47-87 years, average 66.96±9.65 years. The average baseline score of the National Institutes of Health Stroke Scale was 4.5±2.1. Ninety-seven patients (43.1%) had cognitive impairment; 79 had obvious stenosis or occlusion at the intracranial and extracranial segments of cerebral arteries; 148 (65.8%) had good collateral circulation, and 77 (34.2%) had poor collateral circulation. The proportions of patients with atherosclerotic stroke (P=0.033) and cognitive impairment (P=0.041) in the good collateral circulation group were significantly higher than those in the poor collateral circulation group. There were significant differences in the proportions of patients with large-artery atherosclerotic stroke (P=0.007), anterior circulation stroke (P=0.018), collateral dysfunction (P=0.041), as well as baseline systolic blood pressure (P=0.006), baseline diastolic blood pressure (P=0.013), low-density lipoprotein cholesterol (P=0.021), and homocysteine (P=0.024) between the cognitive impairment group and the non-cognitive impairment group. Multivariate logistic regression analysis showed that baseline systolic blood pressure (odds ratio[OR] 1.007, 95% confidence interval[CI] 1.001-1.012; P=0.036), and large-artery atherosclerotic stroke (OR 2.650, 95% CI 1.490-4.714; P=0.001) were independently positively correlated with cognitive impairment, while the status of collateral circulation was not an independent risk factor for cognitive impairment (P=0.073). Conclusions The status of collateral circulation was associated with cognitive impairment in patients with acute ischemic stroke, but it was not an independent risk factor. Key words: Stroke; Brain Ischemia; Cognition Disorders; Collateral Circulation; Cerebrovascular Circulation; Risk Factors

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.236
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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