Relationship Between Genetic Polymorphism and Cognitive Impairment in Patients with Acute Ischemic Stroke (APOE).
Bibliographic record
Abstract
Objective: To investigate the relationship between apolipoprotein E (ApoE) gene polymorphism and cognitive impairment (PSCI) in patients after acute ischemic stroke (AIS). Methods: A total of 150 AIS patients were treated in Chengde Central Hospital from December 2022 to December 2023 and were selected and divided into a disorder group (n=88) and a normal group (n=62) according to the presence or absence of PSCI. Clinical data of patients in the two groups were collected, ApoE genotype and allele distribution of patients in the disabled group and the normal group were detected, Montreal Cognitive Assessment and Mini-Mental State Examination scores of patients with different ApoE gene subtypes were compared, and the risk factors of PSCI after AIS were analyzed by unconditional Logistic regression. Results: The proportion of patients with acute lesions (≥3.0 cm) and the degree of carotid artery stenosis (moderate, severe, complete occlusion) in the disorder group was higher than that in the normal group, and the National Institutes of Health Stroke Scale score was higher than that in the control group, with statistical significance (P < .05). There were significant differences in the genotype and allelic distribution of ApoE between the two groups (P < .05). In both groups, the highest genotype frequency of ApoE was the ε3/3 homozygous type, which was 47.73% (in the disorder group) and 72.58% (in the normal group) respectively. In contrast, there were no significant differences in the genotype frequencies of ε2/2, ε2/3, ε2/4 and ε4/4 alleles in the two groups (P > .05). This means that in both groups of patients, the frequency of the ApoE ε3/3 genotype was the highest, while the genotype frequencies of ε2/2, ε2/3, ε2/4 and ε4/4 alleles were not significant between the two groups. difference. The distribution differences of these genotypes and alleles may be related to aspects such as disease risk and physiological function, providing valuable information for in-depth exploration of the role of ApoE in patients. The genotype frequency of ε3/3 in the disorder group was lower than that in the normal group. The frequency of the ε3/4 genotype was higher than that of the normal group, and the difference was statistically significant (P < .05). In both groups, the highest allele frequency was ε3 (68.75% in the disorder group and 83.06% in the normal group), and there was no difference in the frequency of ε2 allele between the two groups (P > .05). The frequency of the ε3 allele in the disorder group was lower than that in the normal group, and the frequency of the ε4 allele was higher than that in the normal group, the difference was statistically significant (P < .05). In the patients with cognitive impairment after AIS (disorder group), the MOCA and MMSE scores of patients with different ApoE subtypes (ε2, ε3, ε4) were compared, and the differences among the three groups were statistically significant (P < .05). The MOCA and MMSE scores in the ε4 group were lower than those in the ε2 and ε3 groups. The difference was statistically significant (P < .05). Logistic regression analysis showed that the degree of carotid artery stenosis, NIHSS score, and ApoEε4 gene were independent risk factors for PSCI in patients with AIS (P < .05). Conclusion: APOE gene polymorphism is associated with cognitive impairment in post-AIS patients, and carrying the ApoE Epsilon 4 gene may be associated with PSCI in post-AIS patients.
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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 | 0.000 | 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".