Decreased plasma Aβ levels were not associated with post‐stroke cognitive impairment
Bibliographic record
Abstract
Abstract Background It has been reported that stroke promotes the deposition of Aβ in the brain, which may be associated with post‐stroke cognitive impairment. Considering plasma Aβ is closely related to Aβ deposition in the brain, in the present study, we investigated the relationship between plasma Aβ levels and cognitive dysfunction after stroke. Method A total of 138 patients of acute ischemic stroke (within 2 weeks of onset) who were hospitalized in the Neurology Department of the first affiliated hospital of Xi 'an Jiaotong University and 138 age‐matched controls were enrolled between Jan1, 2017, and Oct 30, 2018. The Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) was used to assess the pre‐existing cognitive status. A validated Chinese version of the Mini‐Mental State Examination was used to assess cognition. Fasting venous blood was taken in the morning and plasma Aβ42, Aβ40, sLRP1, and sRAGE levels were measured by ELISA. The relationship between plasma Aβ and cognitive impairment was analyzed using logistic regression analysis. Result Among acute ischemic stroke 138 patients, 37 patients met the criteria for cognitive impairment, the incidence of cognitive impairment was 26.81%. Plasma Aβ42, sLRP‐1 and Aβ42/Aβ40 ratio were decreased in the acute ischemic stroke group. While plasma Aβ40, Aβ42, sLRP‐1, sRAGE levels and Aβ42/Aβ40 ratio had no significant difference between cognitive impairment group and the normal cognitive group. The multivariate analysis showed that plasma Aβ40, Aβ42, sLRP‐1, sRAGE levels and Aβ42/Aβ40 ratio were not associated with post‐stroke cognitive impairment. Conclusion Plasma Aβ42, sLRP‐1 and Aβ42/Aβ40 ratio were decreased after acute ischemic stroke, however, the levels of plasma Aβ and transports were not associated with post‐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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".