Cardiovascular risk factors, aging, and incidence of dementia (CAIDE) risk score and its association with cognitive performance and volumetric brain measures in mild cognitive impairment
Bibliographic record
Abstract
Background: The Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) composite score is a promising measure connecting vascular health to cognitive decline; However, its association with brain imaging findings remains underexplored. This study aimed to evaluate the predictive value of the associations between CAIDE and structural brain measures in individuals with mild cognitive impairment (MCI). Methods: Participants (n = 226) aged 55-90 years with available CAIDE scores and white matter hyperintensity (WMH) measurements and a diagnosis of amnestic MCI were included. Regression models were used to evaluate the association between CAIDE score and neuropsychiatric and imaging findings. Results: Higher CAIDE scores were significantly correlated with lower MMSE scores (r = -0.22, p = 0.001) and higher CDR-SB (r = 0.34, p < 0.001) and ADAS-Cog 11 scores (r = 0.38, p < 0.001). CAIDE scores were significantly positively related to total cerebrum (β = 0.319), gray matter (β = 0.337), and hippocampal volumes (β = 0.250, all p < 0.001). ROC analysis demonstrated that total gray matter (AUC = 0.70) and total brain (AUC = 0.69) were more accurate predictors of dementia risk compared to WMH volume (AUC = 0.52). Conclusion: Higher CAIDE dementia risk scores were linked to poorer cognitive performance but showed limited association with WMH burden in individuals with MCI. Gray matter and hippocampal volumes were stronger correlates of dementia risk than WMH volume and CAIDE-related risk may be better captured by cortical and hippocampal structural changes rather than white matter disease.
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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 | 0.003 |
| 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 | 0.001 |
| 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".