Resting Heart Rate and Cognitive Decline: A Meta-Analysis of Prospective Cohort Studies
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Several previous meta-analyses have identified an association between cognitive decline and heart rate variability, which reflects autonomic nerve activity. This systematic review and meta-analysis investigated the impact of increased resting heart rate (RHR) on the incidence of cognitive decline, including dementia. METHODS: The PubMed, Embase, and PsycInfo databases were searched for relevant prospective cohort studies published before April 18, 2022. A methodological quality assessment of the included studies was conducted using the Newcastle-Ottawa Scale. Summary estimates of the incidence of cognitive decline, including dementia, were generated using a random-effects model. Potential publication bias was evaluated using Begg's funnel plots and Egger's regression tests. RESULTS: The meta-analysis included 7 prospective cohort studies comprising 53,621 participants. A weak significant association was observed between RHR and the risk of cognitive decline, although the analysis indicated high heterogeneity among the studies (relative risk=1.18, 95% confidence interval=1.04-1.33, I²=82.5%). Significant associations were determined between RHR and all combined types of dementia except for Alzheimer's disease and mild cognitive impairment. There was also a dose-response association between increased RHR and cognitive decline. The meta-estimate of the cognitive decline risk associated with a 10 beat-per-minute increase in RHR was 1.06, and it was 1.10 for dementia. CONCLUSIONS: This study found that a higher RHR was associated with an increased cognitive decline risk. Due to study limitations such as publication bias and high heterogeneity, additional studies are required to validate this finding. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration number CRD42021282912.
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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 | 0.025 | 0.049 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.063 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".