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Record W4380876875 · doi:10.1002/alz.064226

Heart rate variability is associated with global cognition and cognitive impairment: Results from the einstein aging study

2023· article· en· W4380876875 on OpenAlexaboutno aff
Carol A. Derby, Jiyue Qin, Grace Liu, Sharath Koorathota, Cuiling Wang, Richard P. Sloan

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsnot available
Fundersnot available
KeywordsHeart rate variabilityCognitionDementiaMontreal Cognitive AssessmentMedicineAudiologyLogistic regressionCognitive impairmentPsychologyGerontologyCardiologyInternal medicineHeart ratePsychiatryBlood pressure

Abstract

fetched live from OpenAlex

Abstract Background The role of autonomic function in cognitive impairment is unclear. Heart rate variability (HRV) provides a feasible, non‐invasive measure of cardiac autonomic control. We examined whether HRV is associated with global cognition and cognitive impairment using 7‐day ambulatory ECG assessments in the Einstein Aging Study. Method Analyses included 84 participants free of dementia (mean age 78.1 (± 5.2) years; 82% female; 39% non‐Hispanic White, 44% non‐Hispanic Black, mean education 14.7 (± 3.3 years)). Participants wore a small, single lead ECG device continuously over 7 days. Power spectral analyses were applied to determine HRV over 5‐minute epochs in the high (0.15‐0.40 Hz, hfHRV) and low (0.04‐0.15 Hz, lfHRV) frequency bands, and values were log transformed. Demographics, comorbidities, and cognition were assessed during clinic visits. Two tests per domain evaluated memory, executive function, language, visuo‐spatial and attention with impairment defined as performance ≥ 1.5 SD below the age, sex, education standardized norm on at least one test. Global cognition was assessed using the MoCA, and Mild Cognitive Impairment (MCI) was defined using Jak‐Bondi criteria. Associations of HRV with cognition were examined using logistic (MCI, domain specific impairment) and linear (MoCA) regression adjusting for age, sex, race/ethnicity and education, diabetes, and hypertension. Result Mean MoCA score was 24 (SD 3.5), 21 (25%) had MCI and impairment was identified in 25% (memory), 28.6% (executive function), 21.4% (attention), 17.9% (language) and 27.4% (visuospatial). Both hfHRV and lfHRV were inversely associated with MCI (OR per 1 SD increase in log HRV: 0.47, p = 0.02 for hfHRV and 0.42, p = 0.01 for lfHRV) and with memory impairment (OR per 1 SD increase in log HRV: 0.52, p = 0.03 for hfHRV and 0.43, p = 0.01 for lfHRV). Higher hfHRV and lfHRV were each associated with better MoCA score (β for 1 SD increase in log HRV: 0.65, p = 0.046 for hfHRV; 0.80, p = 0.02). Conclusion Whether HRV is associated with cognitive impairment remains unclear, particularly the role of hfHRV, indicative of parasympathetic control. Findings suggest that hfHRV is related to cognitive performance and impairment. Results for lfHRV also suggest joint effects of the sympathetic and parasympathetic systems.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.282
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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