Effects of Leukoaraiosis on Subsequent Cerebral Vascular Disease and Cognitive Function
Bibliographic record
Abstract
Objective To determine whether the presence of leukoaraiosis(LA) is a risk factor for subsequent cerebral vascular disease and cognitive impairment. Methods We prospectively examined 253 consecutive outpatients at Department of Neurology of Beijing Anzhen Hospital. The patients were divided into two groups: patients with leukoaraiosis(LA group) and patients without leukoaraiosis(control group). According to the scores, the patients in LA group were divided into mild, moderate and severe groups. Mini Mental State Examination(MMSE) and Montreal Cognitive Assessment(MoCA)(Beijing version) were used to assess the cognitive function. We analyzed clinical data. Patients were then followed up for the development of stroke and cognitive changes. Results In LA group, hypertension and diabetes were more common and there was significant difference between LA and control group(P =0.003 and P =0.004, respectively). The prevalence of cognitive impairment in moderate and severe LA groups was much higher than those in control group(P =0.035 and P =0.019, respectively). The incidences of cerebral infarction in mild, moderate and severe LA group were much higher than those in control group(P =0.019, P =0.024 and P =0.049, respectively). The incidences of cognitive impairment in mild, moderate and severe were much higher than those in control group(P =0.048, P =0.036 and P =0.004, respectively). There was significant difference between LA and control group for the development of cerebral infarction and cognitive impairment. Conclusion The incidence of cerebral infarction and cognitive impairment rose in senile patients with leukoaraiosis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".