CAIDE dementia risk score and cognitive correlates among Filipinos with mild cognitive impairment
Bibliographic record
Abstract
Abstract Background The Cardiovascular Risk Factors, Aging and Dementia (CAIDE) dementia risk score is a validated tool predicting the risk of dementia.1,2 It includes age, sex, education, blood pressure, cholesterol, body mass index (BMI), and physical inactivity, with higher scores indicating increased risk of subsequent dementia.1,2 Mild Cognitive Impairment (MCI) is a The objective is to compare the cognitive profiles of Mild Cognitive Impairment (MCI) participants with significant modifiable risk factors (CAIDE > 6) in a Filipino cohort. Method A total of 60 participants with MCI from the Filipino Multicomponent Intervention to Maintain Cognitive Performance among High Risks Population (FINOMAIN) study were included. Data on age, sex, educational level, blood pressure, cholesterol, body mass index (BMI), and physical activity were obtained. Mini Mental Status Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores were obtained. Participants were administered the Mini‐Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Alzheimer’s Disease Assessment Scale Cognitive Subscale (ADAS‐Cog). Result Forty‐four participants (73%) have significant modifiable risk factors (CAIDE > 6). Compared to participants without significant risk factors, participants with significant modifiable risk factors (CAIDE > 6) have more impaired cognition with lower MoCA scores (16 + 4 vs 19 + 3, p=0.02). MMSE was noted to be lower (25 + 3 vs 27 + 2, p=0.06); and ADAS‐Cog scores higher (13.6 + 6 vs 11.8 + 5, p=0.2), however, it was not significant. Conclusion This study shows that MCI participants with significant modifiable risk factors (CAIDE > 6) have more cognitive impairment suggesting the utility of CAIDE in the community to screen individuals at risk for dementia. Findings support the need to address modifiable risk factors to prevent cognitive deterioration. Further trials that investigate the effects of multi‐domain intervention and treatment for risk factors in improving cognition, delaying cognitive deterioration and dementia conversion.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".