Association of aberrant resting heart rates with dementia risk across the life‐course by a longitudinal multilevel analysis
Bibliographic record
Abstract
BACKGROUND: The underlying causes of dementia often emerge decades before clinical symptoms appear, with risks accumulating throughout the life-course. However, younger adults are always neglected in dementia research. Failing to address the risk of dementias in younger adults will most likely lead to a cascading effect on brain health that persists through mid-life to late life. Resting heart rate (RHR), a key determinant of cardiovascular health and perfusion, remains insufficiently understood its life-course relationship with Alzheimer's disease (AD). METHODS: We analyzed data from the National Alzheimer's Coordinating Center (NACC) across three age groups: young adults (18-50 years), mid-life (51-64 years), and older adults (65 years). We adopted multi-level logistic regression analysis to examine the longitudinal association between RHR and dementia while controlling for potential confounders, and the E-value approach was applied to estimate robustness of this effect. RESULTS: After adjusting for potential confounders, in young adults, RHR < 60 bpm was associated with increased dementia risk. Among older adults, RHR > 100 bpm was linked to a higher risk of developing dementia (OR = 1.38, 95% CI: 1.09 - 2.11). The corresponding E-values for both young and older adult groups were 1.63 and 1.26 respectively, indicating that unaccounted for confounding variables with small-to-moderate sized is required to account for an away effect. CONCLUSION: Both low and high RHR are significant risk factors for dementia in specific age groups. These findings highlight the importance of monitoring RHR as part of dementia prevention strategies.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".