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
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| 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) | 0.000 | 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 it