Incidence of post-stroke cognitive impairment in patients with first-ever ischemic stroke: a multicenter cross-sectional study in China
Bibliographic record
Abstract
Background: Post-stroke cognitive impairment (PSCI) is a common sequela after stroke. China has a large population of stroke survivors, but a large-scale survey on the incidence and risk factors for PSCI has not been undertaken. We aimed to calculate the incidence and risk factors for vascular cognitive symptoms among first-ever stroke survivors in China through a multicenter cross-sectional study. Methods: From May 1, 2019 to November 30, 2019, patients with a clinical diagnosis of first-ever ischemic stroke were recruited from 563 hospitalized-based stroke center networks in 30 provinces of China. Cognitive impairment was measured by 5-min National Institute of Neurological Disease and Stroke-Canadian Stroke Network (NINDS-CSN) at 3-6 months after the indexed stroke. Stepwise multivariate regression and stratified analysis were performed to assess the association between PSCI and demographic variables. Findings: A total of 24,055 first-ever ischemic stroke patients were enrolled, with an average age of 70.25 ± 9.88 years. The incidence of PSCI as per the 5-min NINDS-CSN was 78.7%. Age ≥75 years old (OR: 1.887, 95%CI: 1.391-2.559), western regional residence (OR: 1.620, 95%CI: 1.411-1.860) and lower education level were associated with increased PSCI risk. Hypertension might be related to non-PSCI (OR: 0.832, 95%CI: 0.779-0.888). For patients under 45 years old, unemployment was an independent risk factor for PSCI (OR: 6.097, 95%CI: 1.385-26.830). For patients who were residents of the southern region (OR: 1.490, 95%CI: 1.185-1.873) and non-manual workers (OR: 2.122, 95%CI: 1.188-3.792), diabetes was related to PSCI. Interpretation: PSCI is common in Chinese patients with first-ever stroke, and many risk factors are related to the occurrence of PSCI. Funding: The Beijing Hospitals Authority Youth Program (No. QMS20200801); Youth Program of the National Natural Science Foundation of China (No. 81801142); the Key Project of Science and Technology Development of China Railway Corporation (No. K2019Z005); The Capital Health Research and Development of Special (No. 2020-2-2014); Science and Technology Innovation 2030-Major Project (No. 2021ZD0201806).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".