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Record W4399677332 · doi:10.1093/eurjpc/zwae175.247

Impact of left ventricular ejection fraction on cognitive function in chronic heart failure: insights from key-prognostic CPET parameters

2024· article· en· W4399677332 on OpenAlexaffabout
François Besnier, Christine Gagnon, B. Bérubé, Floriane Sellier, François Vachon, Josep Iglésies, Mathieu Gayda, V. Dionne, H Benhalima, Ashwini Kumar Nigam, Martin Juneau, P L'allier, Nadia Bouabdallaoui, Jean L. Rouleau, Louis Bherer

Bibliographic record

VenueEuropean Journal of Preventive Cardiology · 2024
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsEjection fractionMedicineCardiologyCardiorespiratory fitnessStroop effectInternal medicineHeart failureMontreal Cognitive AssessmentCognitionCognitive impairmentDiseasePsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Cognitive impairment is a common comorbidity in chronic heart failure patients (CHF) that negatively affects prognosis. Previous studies reported that higher cardiorespiratory fitness (VO2peak), measured with a cardiopulmonary exercise stress test (CPET), is associated with better cognitive performance in CHF. The impact of reduced or preserved left ventricular ejection fraction (LVEF) and the cardiorespiratory parameters during exercise on cognition remain to be studied. Objectives To compare cognition in CHF patients with reduced LVEF versus those with mildly reduced or normal LVEF (R-LVEF ≤40% vs N-LVEF >40%). To examine if key-prognostic CPET parameters predict cognitive performance in each CHF subtype. Methods 68 patients with CHF (67±8 years old) performed a CPET (VO2peak, VE/VCO2 slope, Myers score. All have significant prognostic value). Cognitive assessment included global cognition (Montreal Cognitive Assessment for general cognition; MoCA), processing speed and executive function (Stroop) and memory (Rey auditory verbal learning test). LVEF was measured by echocardiography. Results Mean LVEF were 32.7±6.2% and 52.6±6.8% for R-LVEF and N-LVEF (p<0.001). Age, NYHA class, VO2peak, VE/VCO2 slope, and Myers’ CPET score were similar between groups (p>0.05). After adjusting for age, sex, and education, MoCA scores were not statistically different between groups (23.5±4.6 vs 25.3±2.9 p=0.24 respectively for R-LVEF and N-LVEF). The Stroop switching task revealed a significantly lower performance in R-LVEF vs N-LVEF (89.7±32.1s vs 74.4±16.4s, p=0.028), as well as at the fifth repetition of the verbal learning test (9.3±2.8 vs 11.1±2.2, p=0.015). A trend was observed for the immediate recall on the memory task (6.4±3.5 vs 8.3±3.1 p=0.061). Simple linear regressions showed that VO2peak (mL.kg.min) (R=0.50, p<0.001), VE/VCO2 slope (R=-0.33, p=0.024), and Myers CPET score (R=-0.43, p=0.003) significantly predicted MoCA score in R-LVEF but not in N-LVEF. VO2peak (mL.kg.min) (R= -0.47 p=0.001), VE/VCO2 slope (R= -0.37 p=0.015), and Myers’ CPET score (R= 0.32 p=0.034) predicted Stroop switching performance in R-LVEF only. Conclusion Global cognition, executive function (switching), and verbal memory (encoding) were lower in CHF with reduced LVEF versus those with mildly reduced/normal LVEF despite similar key-prognostic CPET parameters. Key-prognostic CPET parameters predicted global cognition and executive function in CHF participants with reduced LVEF. Future studies are needed to better understand cognitive deficits in CHF and potential intervention to mitigate their impact in patient’s quality of life.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.294
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.276
Teacher spread0.261 · 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 teacher head, 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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Citations2
Published2024
Admission routes2
Has abstractyes

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