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Record W4386084732 · doi:10.57187/smw.2023.40109

Association of chocolate consumption with neurological and cardiovascular outcomes in atrial fibrillation: data from two Swiss atrial fibrillation cohort studies (Swiss-AF and BEAT-AF)

2023· article· en· W4386084732 on OpenAlexaff
Annina Stauber, Andreas Müller, Nikki Rommers, Stefanie Aeschbacher, Nicolas Rodondi, Leo H. Bonati, Raban Jeger, David J. Kurz, Claudia Liedtke, Peter Ammann, Marcello Di Valentino, P Chocano, Richard Kobza, Michael Kühne, David Conen, Stefan Osswald, Alain Bernheim

Bibliographic record

VenueSwiss Medical Weekly · 2023
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsMedicineAtrial fibrillationNeurocognitiveCohortInternal medicineCardiologyLogistic regressionPopulationProportional hazards modelCohort studyMagnetic resonance imagingCognitionRadiologyPsychiatry

Abstract

fetched live from OpenAlex

AIM: To assess the associations of chocolate consumption with neurocognitive function, brain lesions on magnetic resonance imaging (MRI), and cardiovascular outcome in patients with atrial fibrillation (AF). METHODS: We analysed data from patients of two prospective multicentre Swiss atrial fibrillation cohort studies (Swiss-AF) and (BEAT-AF). Assessments of MRI findings and neurocognitive function were performed only in the Swiss-AF population (in 1727 of 2415 patients [71.5%] with a complete data set), as patients enrolled in BEAT-AF were not systematically evaluated for these outcomes. Otherwise, the two cohorts had an equivalent set of clinical assessments. Clinical outcome analysis was performed in 3931 patients of both cohorts. Chocolate consumption was assessed by questionnaire. Patients were categorised as no/low chocolate consumption (No/Low-Ch) ≤1 servings/week, moderate chocolate consumption (Mod-Ch) >1-6 servings/week, and high chocolate consumption (High-Ch) >6 servings/week, respectively. Brain lesions were evaluated by MRI. Assessment of cognitive function was performed by neurocognitive functional testing and included global cognition measurement with a cognitive construct score. Cerebral MRI and cognition were evaluated at baseline. Cross-sectional associations between chocolate consumption and MRI findings were analysed by multivariate logistic regression models and associations with neurocognitive function by multivariate linear regression models. Clinical outcome events during follow-up were recorded and assessed by a clinical event committee. The associations between chocolate consumption and clinical outcomes were evaluated by Cox regression models. The median follow-up time was 6 years. RESULTS: Chocolate consumption was not associated with prevalence or volume of vascular brain lesions on MRI, nor major adverse cardiac events (ischaemic stroke, myocardial infarction, cardiovascular death). However, No/Low-Ch was independently associated with a lower cognitive construct score compared to Mod-Ch (No/Low-Ch vs. Mod-Ch: coeff. -0.05, 95% CI -0.10-0), whereas other neurocognitive function tests were not independently associated with chocolate consumption categories. In addition, there was a higher risk of heart failure hospitalisation (No/Low-Ch vs. Mod-Ch: HR 1.24, 95% CI 1.01-1.52) and of all-cause mortality (No/Low-Ch vs. Mod-Ch: HR 1.29, 95% CI 1.06-1.58) in No/Low-Ch compared to Mod-Ch. No significant associations with the evaluated outcomes were observed when High-Ch was compared to Mod-Ch. CONCLUSION: While chocolate consumption was not associated with MRI findings and major adverse cardiac events in an atrial fibrillation population, No/Low-Ch was associated with a lower cognitive construct score, higher risk of heart failure hospitalisation and increased all-cause mortality compared to Mod-Ch. CLINICALTRIALS: gov Identifier: NCT02105844.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.016
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.060
GPT teacher head0.339
Teacher spread0.280 · 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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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