Cognitive impairment in patient with lacunar infarct and white matter lesion
Bibliographic record
Abstract
Objective To investigate the features and its risk factors for cognitive impairment in patients with lacunar infarct （LI） and white matter lesion （WML）.Methods The inpatients with LI and WML aged 65 to 75 years old were enrolled. Their demographic and clinical data were collected. LI and WML were diagnosed by magnetic resonance imaging （MRI）. Montreal Cognitive Assessment Scale （MoCA） was used to evaluate cognitive function. Self-Rating Depression Scale and Hamilton Anxiety Scale were used to exclude patients with depression and anxiety. The patients were divided into either a cognitive impairment group or a normal cognitive function group. The demographic and clinical data of both groups were compared. Multivariate logistic regression analysis was used to analyze and determine the indenendent riskfactors for cognitive impairment. The characteristics of cognitive impairment of LI and WML were compared. Results A total of 130 patients with LI or WML were enrolled, 92 of them had cognitive impairment, and 38 had normal cognitive function; 85 had LI, and 45 had WML; 53 were males and 77 were females. Univariate analysis showed that years of education in the cognitive impairment group （7.54 ±4. 65 years vs. 11.29 ±3.17 years; t =4. 286, P =0. 001） was significantly lower than that of the normal cognitive function group, while the constituent ratios of hypertension （54. 6% vs. 16.2% ;X2 =4. 477, P = 0. 018）, hyperlipidemia （53. 1% vs. 16.2% ;X2 =5. 263; P =0. 044）, diabetes mellitus （46. 9% vs. 10.8% ; X2 =3. 827, P =0. 017）, as well as LI （43.8% vs. 21.5% ;X2 =3. 928, P =0. 015） and WML （26. 9% vs. 7.7% ;X2 =4. 072, P =0. 009） were significantly higher than those of the normal cognitive function group. Multivariate logistic regression analysis showed that years of education （odds ratio [ OR], 1. 305, 95% confidence interval [ CI] 1. 104 -7. 975; P =0. 001）, diabetes mellitus （OR 1. 328, 95% CI 1. 292 -3. 422; P =0. 015）, hypertension （OR 1. 978, 95% CI 1. 034 -5. 443; P =0. 028, LI （OR 1. 224, 95% CI 1. 004 - 2. 007; P=0. 013）, and WML （OR 1. 489, 95% CI 1. 202 -3. 778; P=0. 010） were the independent risk factors for cognitive impairment. The total MoCA score （21.61 ± 5.33 vs. 19. 19 ± 7.07; t = 1. 841, P = 0. 038） and cube copy （0.43 ± 0. 50 vs. O. 31 ± 0. 47; t = 1. 104, P = 0. 010）, clock drawing test （2.53 -± 0. 89 vs. 2.04 ± 1.22; t =2. 229, P =0. 008）, letters identification （0. 85 ±0. 36 vs. O. 62 ±0. 50; t =2. 585, P = =0. 000）, and 100 minus 7 consecutively （2. 62 ±0. 79 vs. 2. 19 ±1.17; t =2. 113; P =0. 001） of the WML group were significantly lower than those of the LI group. Conclusions The patients with LI and WML often had cognitive impairment, and the cognitive impairment in patients with WML was more serious. Years of education, hypertension and diabetes were the independent risk factors for cognitive impairment in patients with LI and WML. Visuospatial executive function and attention damage in patients with WML were severer than those of the patients with LI. Key words: Stroke, Lacunar; Leukoencephalopathies; Cognition Disorders; Magnetic ResonanceImaging; Risk Factors
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".