Breast Arterial Calcification Is Not Associated with Mild Cognitive Impairment or Incident All-Cause Dementia Among Postmenopausal Women: The MINERVA Study
Bibliographic record
Abstract
Background: Since vascular risk factors are implicated in cognitive decline, and breast arterial calcification (BAC) is related to vascular risk, we postulated that BAC may be associated with cognitive impairment and dementia. Methods: We used a multiethnic cohort of 3,913 asymptomatic women 60–79 years of age recruited after mammography screening at a large health plan in 2012–2015. A BAC mass score (mg) was derived from digital mammograms. Cognitive function was measured at baseline using the Montreal Cognitive Assessment (MoCA) and incident all-cause dementia (n = 49 events; median follow-up = 5.6 years) were ascertained with validated ICD-9 and ICD-10 codes. We used cross-sectional linear regression of MoCA scores on BAC, then multinomial logistic regression predicting mild cognitive impairment not progressing to dementia and incident all-cause dementia and, finally, Cox regression of incident all-cause dementia. Results: No association by linear regression was found between MoCA scores and BAC presence in unadjusted or adjusted analysis. Women with severe (upper tertile) BAC had a MoCA score lower by 0.58 points (standard error [SE] = 0.18) relative to women with no BAC. However, this difference disappeared after multivariate adjustment. No significant associations were found in multinomial logistic regression for either BAC presence or gradation in unadjusted or adjusted analysis. No significant associations were found between BAC presence with incident all-cause dementia (fully adjusted hazard ratio = 0.74; 95% confidence interval: 0.39–1.39). Likewise, no significant association with incident all-cause dementia was noted for BAC gradation. Conclusions: Our results do not support the hypothesis that BAC presence or gradation may contribute to cognitive impairment or development of all-cause dementia.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".