Study of cognitive function in patients with lacunar infarction associated with leukoaraiosis
Bibliographic record
Abstract
Objective To investigate the effect of different degrees of ischemic white matter lesions on the cognitive function in patients with lacunar infarction.Method One hundred twelve consecutive patients with lacunar infarction were collected.Age-related white matter changes rating scale(ARWMCRs) was used,and according to the results of ARWMCRs scores,the patients were divided into mild(n =34, 0-3 scores),moderate(n = 43,4-7 scores),and severe(n = 35,8-24 scores)groups.The national health institutes of stroke scale(NIHSS)and the modified Rankin scale(mRS)scores were used to assess the degree of neurological deficit.The mini-mental status scale(MMSE)and the Montreal Cognitive Assessment (MoCA)were used for neuropsychological tests,and event-related potential two-tone sequence auditory P300(2t-P300)wave was used for neural electrophysiological examination.The cognitive function was evaluated.The cognitive function among all groups was compared.Results ①There were significant differences in comparison of the MoCA scores among the three groups.Only the mRS score and the MMSE score in the severe group were lower than those in the mild and moderate groups.There were significant differences(P0.05).②The latency of P300 wave in the severe group was higher than that in the moder- ate and mild groups,and the latency of P300 wave in the moderate group was higher than that in the mild group.There was significant difference(P0.05).The amplitude of P300 wave in the severe group was lower than that in the moderate group and mild group.There were significant differences(P0.05). ③The ARWMCRs score in patients with white matter lesions was negatively correlated with the MMSE score,MoCA score,and amplitude of P300 wave.It was positively correlated with the latency of P300 wave and mRS score.Conclusion White matter lesions impact the cognitive function in patients with lacunar infarction.The more severe the white matter lesions,the more significant decline in cognitive function.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".