Associations of ischemic heart disease with brain glymphatic MRI indices and risk of Alzheimer's disease
Bibliographic record
Abstract
BACKGROUND: The impact of ischemic heart disease (IHD) on the brain glymphatic MRI indices and risk of Alzheimer's disease (AD) remains largely unclear. This study aimed to investigate the associations between IHD, brain glymphatic MRI indices and risk of AD. METHODS: A total of 1385 non-dementia subjects (55.2 % male, mean age 73.53) were included. Diffusivity along the perivascular space (DTI-ALPS), free water (FW) and choroid plexus volume were used to reflect glymphatic function. The associations of IHD with MRI derived glymphatic indices, PET amyloid, tau and cognitive performance were explored by multiple regression analysis. IHD were tested as predictors of clinical progression using cox proportional hazards modeling. The mediation effect of MRI derived glymphatic indices on the relationship between IHD and cognitive changes was investigated. RESULTS: Individuals with IHD exhibited glymphatic dysfunction revealed by lower DTI-ALPS (p = 0.035), higher FW (p < 0.001), and higher choroid plexus volume (p = 0.019). IHD had poorer cognitive performance in MMSE (p = 0.022), ADNI-MEM (p = 0.001) and ADNI-MF (p = 0.006), and more amyloid deposition (p = 0.007). IHD had a higher diagnostic conversion risk (HR = 1.321, 95 % CI = 1.003-1.741). IHD was associated with longitudinal cognitive decline in all cognitive tests (p < 0.05 for all) and FW (β = 0.012, 95 % CI 0.001, 0.023, p = 0.038). FW demonstrated an indirect effect (β = -0.0009, 95 % CI: -0.0034, -0.0001) and mediated 13.85 % effect for the relationship between IHD and ADNI-EF decline. CONCLUSION: IHD is independently associated with AD risk, and brain glymphatic dysfunction may partially mediate this relationship.
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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 | 0.000 |
| 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".