Risk factors of vascular cognitive impairment in patients after stroke at early stage
Bibliographic record
Abstract
Objective To analyze the risk factors of vascular cognitive impairment in patients after stroke at early stage,Methods Three hundred patients with stroke at early stage were chosen in our study; their age,gender,levels of blood pressure,lipids and HbA1c,homocysteine (Hcy),and high-sensitivity C-reactive protein (HS-CRP),atrial fibrillation,smoking,drinking and lesion sites were detected.Based on the scores in Montreal Cognitive Scale 30 d after the onset,statistical analysis was performed on the above factors.Results Univariate analysis showed that age,atrial fibrillation,levels of HbA1c and blood pressure,lesion sites,HS-CRP level,and Hcy level were significantly associated with the vascular cognitive impairment.Further logistic regression analysis indicated that levels of HbA1c and blood pressure,and lesion sites,and HS-CRP and Hcy levels were the independent risk factors (OR=1.489,P=0.021,95％CI:1.054～1.956; OR=1.134,P=0.027,95％CI:1.011～1.130; OR=3.124,P=0.028,95％CI:1.167～3.012; OR=2.476,P=0.029,95％CI:1.897～2.245; OR=2.132,P=0.032,95％CI:1.097～2.323).Conclusion Levels of HbA1c and blood pressure,and lesion sites,and HS-CRP and Hcy levels can serve as the predictive indexes of vascular cognitive impairment in patients after stroke at early stage. Key words: Stroke; Vascular cognitive impairment; Risk factor
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".