Prediction of white matter lesions and subcortical atrophy for cognitive impairment in patients with ischemic stroke
Bibliographic record
Abstract
Objective To investigate the predictive role of cerebral white matter lesions (WML) and subcortical atrophy on cognitive function in patients with acute ischemic stroke (AIS) after 3 months. Methods 233 cases of AIS patients admitted to hospital continuously from September 2016 to March 2018 were enrolled and all of them underwent brain MRI.The degree of WML on FLAIR was evaluated according to the Fazekas grading standard.The linear measurement of subcortical atrophy on T1WI was carried out on the subcortical brain atrophy index, including EVANS ratio (ER), inverse cella media index (iCMI), caudate head index (CHI) and basal cistern index (BCI). Demographic, clinical and imaging data of all patients were also recorded.Mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA) were conducted at 3 months after AIS.The patients were divided into normal cognitive function (NCI) group and post stroke cognitive impairment (PSCI) group according to evaluation results of MMSE and MoCA.Multivariate logistic regression analysis was used to screen the independent risk factors of cognitive impairment. Results Univariate analysis showed that age (t=-4.233, P=0.000), sex (χ2=7.501, P=0.006), education (H=21.188, P=0.000), NHISS score (H=5.791, P=0.016), history of atrial fibrillation (χ2=6.484, P=0.011), TIA (χ2= 9.015, P=0.003), smoking history (χ2=6.943, P=0.008), Fazekas WML score (χ2=27.885, P=0.000), EVANS ratio (H=31.129, P=0.000), inverse cella media index (H=9.434, P=0.002), caudate head index (H=15.148, P=0.000), basal cistern index (t=-1.979, P=0.049) and baseline cognitive function (χ2=136.994, P=0.000) were related to cognitive impairment in patients with AIS after 3 months (P<0.05). Multivariate logistic regression analysis showed that WML score (OR=3.416, P=0.047, 95%CI: 1.017-11.482), EVANS ratio (OR=1.245, P=0.038, 95%CI: 1.012-1.531) and caudate head index (OR=1.187, P=0.040, 95%CI: 1.008-1.397) were risk factors for cognitive impairment in AIS patients after 3 months adjusting for age, education, disease severity and baseline cognitive function. Conclusion WML, EVANS ratio and caudate head index can predict short-term cognitive function in patients with AIS. Key words: White matter lesions; Subcortical atrophy; Acute ischemic stroke; Cognitive impairment
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".