Analysis of cognitive dysfunction in patients with silent cerebral infarction
Bibliographic record
Abstract
Objective To study in depth the relationship between silent cerebral infarction(SCI)and cognitive dysfunction.Methods In gender,age,blood sugar,blood kidney function,blood lipid,blood pressure,EKG performance,with or without carotid plaque,Mini-Mental State Examination(MMSE) score value and Montreal Cognitive Assessment(MoCA) score value,all statistical analyses for 44 cases of hypertensive patients in Shanghai area were performed using SPSS 13.0.Results Demographic and laboratory parameters were similar between the SCI and non-SCI groups(P0.05).However,the presence of carotid artery plaques was significantly more common in the SCI group(15/26) than the non-SCI group(3/18)(P0.05).Meanwhile,the MoCA score value and the MMSE score decreased of the patients before and after 9 months between two groups were obviously different(P0.05).In addition,multiple logistic regression analysis showed that both blood urea nitrogen and carotid plaque were independent risk factors of SCI.Also,the occurrence of SCI was related to MMSE score value after 9 months follow-up and the MoCA score value.Conclusion SCI may cause cognitive dysfunction,which is especially more obvious during follow-up.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".