MétaCan
Menu
Back to cohort
Record W2081727499 · doi:10.1159/000081055

Frequency and Risk Factors of Vascular Cognitive Impairment Three Months after Ischemic Stroke in China: The Chongqing Stroke Study

2004· article· en· W2081727499 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNeuroepidemiology · 2004
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsStroke (engine)MedicineCognitionLogistic regressionMontreal Cognitive AssessmentOdds ratioAtrial fibrillationCognitive declineCognitive impairmentDementiaPhysical therapyInternal medicinePsychiatryDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Frequency of poststroke cognitive impairment is high in western countries, and the risk factors of poststroke cognitive impairment have not been fully understood yet. We sought to examine the frequency and risk factors of cognitive impairment after ischemic stroke in a large stroke cohort of China. METHODS: A total of 434 consecutive patients with ischemic stroke were enrolled. The cognitive status before and 3 months after stroke was evaluated using the Informant Questionnaire on Cognitive Decline in the Elderly and the Mini-Mental State Examination, respectively. Poststroke cognitive impairment was defined as cognitive impairment with concomitant stroke, stroke-related cognitive impairment was defined as cognitive impairment developing after index stroke, and cognitive impairment after first-ever stroke was defined as cognitive impairment developing after first-ever stroke. Logistic regression analysis was used to find the risk factors of cognitive impairment after stroke. RESULTS: (1) Frequency of poststroke cognitive impairment was 37.1%, that of stroke-related cognitive impairment was 32.2%, and that of cognitive impairment after first-ever stroke was 29.6%. (2) The patients with cognitive impairment more often had older age, low educational level, atrial fibrillation, prior stroke, everyday drinking, left carotid territory infarction, multiple lesions, embolism, and dysphasia. (3) The factors associated with poststroke cognitive impairment in logistic regression analysis were age (OR 1.215, 95% CI 1.163-1.268), low educational level (OR 2.023, 95% CI 1.171-3.494), prior stroke (OR 5.130, 95% CI 2.875-9.157), everyday drinking (OR 2.013, 95% CI 1.123-3.607), dysphasia (OR 3.994, 95% CI 1.749-9.120), and left carotid territory infarction (OR 2.685, 95% CI 1.595-4.521). CONCLUSIONS: Cognitive impairment is common 3 months after ischemic stroke in Chinese people. Risk factors for poststroke cognitive impairment include age, low educational level, everyday drinking, prior stroke, dysphasia, and left carotid territory infarction.

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.

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)0.001
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 score0.004
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.014
GPT teacher head0.268
Teacher spread0.254 · 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