The Interaction Effect between Blood Stasis Constitution and Atherosclerotic Factors on Cognitive Impairment in Elderly People
Bibliographic record
Abstract
OBJECTIVE: Blood stasis (BS) constitution represents a tendency to stagnation and positively associates with the severity of atherosclerosis. In this study, we have identified the interaction effect between BS constitution and atherosclerosis on cognitive impairment in the elderly people. METHODS: Eligible elderly people ≥65 years old who attended physical examination in the Mawei community of Fuzhou city during 2015 were enrolled in this study. We explored the characteristics of Traditional Chinese Medicine (TCM) constitution and atherosclerotic factors in the normal and cognitive impairment groups and their interaction effect between participants' Minimental State Examination (MMSE) scores in the elderly people. RESULTS: The prevalence of cognitive impairment in the elderly people was 13.0%. Red blood cell (RBC), hemoglobin (HB), ankle brachial index (ABI), brachial-ankle pulse wave velocity (BaPWV), and blood stasis (BS) were significantly different between normal and cognitive impairment group (P<0.05). Logistic regression analysis indicated that RBC (odds ratio (OR)=0.530 (0.343-0.817), P=0.004), HB (OR=0.980 (0.967-0.993), P=0.003), ABI (OR=2.199(1.112-4.347), P=0.023), and blood stasis constitution (OR=1.808 (1.022-3.202), P=0.042) were correlated with cognitive impairment. The interactions of blood stasis with HB, ABI, and BaPWV significantly impacted the MMSE score (P<0.05). CONCLUSION: Elderly individuals with blood stasis may be at a higher risk of arterial stenosis and sclerosis, leading to susceptibility to 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".