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The Relationship Between Cardiorespiratory Fitness, Autonomic Nervous System And Cognition In Coronary Artery Disease Patients

2024· article· en· W4402556585 on OpenAlexaffabout
Florent Besnier, Sarah Clavet, Mathieu Gayda, Josep Iglésies, Christine Gagnon, Martin Juneau, Anil Nigam, François Simard, Philippe L. L’Allier, Louis Bherer

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2024
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsCardiorespiratory fitnessAutonomic nervous systemCoronary artery diseaseDiseaseCognitionMedicineCardiologyInternal medicineNeurosciencePhysical medicine and rehabilitationPsychologyHeart rateBlood pressure

Abstract

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INTRODUCTION: Coronary artery disease (CAD) is associated with low cardiorespiratory fitness, cognitive impairment and altered autonomic nervous system (ANS) function. The relationship between VO2max, cognition and the ANS remains poorly studied in people with CAD. PURPOSE: We investigated cognitive performances and cardiac autonomic measures in CAD patients with low, middle and high VO2max. We hypothesize that compared to lower fit CAD patients, higher fit patients will show better ANS adaptation to orthostatic stress, and that ANS response (ΔLF/HF ratio) would correlate with better cognition. METHODS: 47 individuals with CAD performed a cardiopulmonary exercise test and neuropsychological tests (MOCA, working memory, processing speed, executive functions). Responses to orthostatic stress were analyzed with heart rate variability (5 min in a supine position followed by 5 min in a standing position). Participants were divided into tertiles based on their VO2max. RESULTS: mean VO2max was 17.6 ± 1.9 vs 22.2 ± 1.8 vs 29.2 ± 4.2 mL.kg.min respectively for lower fit, medium fit and higher fit CAD patients (p < 0.001). Responses to orthostatic stress were significantly lower in lower fit compared to medium and higher fit patients for ΔLF/HF ratio (0.02 ± 1.7 vs 1.8 ± 2.9 vs 2.5 ± 3.1; p = 0.035), ΔLFn.u. (-3.4 ± 18.2 vs 16.1 ± 22.6 vs 19.9 ± 21.1; p = 0.006), ΔHFn.u. (1.76 ± 21.5 vs -18.3 ± 25.2 vs -22.3 ± 22.2; p = 0.013) and ΔParasympathetic Nervous System index (-0.75 ± 0.50 vs -1.17 ± 0.60 vs -1.10 ± 0.52; p = 0.044). Cognitive parameters were not statistically different between groups. After normalization for age, sex, and weight, patients with a VO2max ≤90% predicted values had significantly lower scores on the MOCA and verbal memory compared to those with a VO2max >90% predicted values: 25.8 ± 2.0 vs 27.5 ± 1.8 p = 0.004 and -0.27 ± 0.8 vs 0.21 ± 0.99 p = 0.048, respectively for MOCA and verbal memory. Only the Baevsky’s stress index measured in supine position was negatively correlated with verbal memory (R = -0.32, p = 0.036). CONCLUSION: In patients with CAD, lower VO2max is associated with altered autonomic responses to orthostatic stress. Lower fit patients have lower cognitive scores for MOCA and verbal memory, compared to higher fit patients. This underscores the potential impact of fitness levels on ANS and cognitive functions in CAD. Mirella and Lino Saputo Research Chair in Cardiovascular Diseases and the Prevention of Cognitive Decline from Université de Montréal at the Montreal Heart Institute. FB is financially supported by a fellowship from the Fonds de Recherche du Québec – Santé (FRQ-S).

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)0.000
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.317
Teacher spread0.289 · 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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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