Association between Apoϵ4 allele and cardiometabolic and social risk factors with cognitive impairment in elderly population from Bogota
Bibliographic record
Abstract
Being an ϵ4 carrier in the Apoϵ gene has been suggested as a modifying factor for the interaction between cardio-metabolic, social risk factors, and the development of cognitive impairment. Objective: The main objective of this study was to assess the existence of such interaction in a sample of Bogota's elderly population. Methods: A cross-sectional study was conducted with 1,263 subjects older than 50 years. Each participant was diagnosed by consensus, after neuropsychological and neuropsychiatric evaluations, under a diagnosis of normal cognition, mild cognitive impairment (MCI) according to Petersen's criteria, or dementia according to DSM-IV criteria. Apoϵ was typified and an analysis of MoCA test was performed in each group carrying or not ϵ4 allele. Results: Our study showed that 75% were women with a median age of 68 years (interquartile range 62-74 years) and a median schooling for 6 years (interquartile range 4-12 years). Dementia was related to low education level of ≤5 years OR=11.20 (95%CI 4.99-25.12), high blood pressure (HBP) OR=1.45 (95%CI 1.03-2.05), and age over 70 years OR=7.68 (95%CI 3.49-16.90), independently of being or not an ϵ4 allele carrier. Diabetic subjects with dementia carrying ϵ4 allele showed a tendency to exhibit lower scores on the MoCA test, when compared with noncarriers' diabetic subjects with dementia. Conclusions: The presence of ϵ4 allele does not modify the relationship between cognitive impairment and the different cardio-metabolic and social risk factors, except in diabetic subjects ϵ4 carriers with dementia who showed a tendency to exhibit lower scores of the MoCA test, when compared with noncarriers' diabetic subjects with dementia.
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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 | 0.001 |
| 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) | 0.001 | 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".