MétaCan
Menu
Back to cohort
Record W3192870802 · doi:10.1093/eurheartj/ehab467

Does gut microbiota affect atrial rhythm? Causalities and speculations

2021· article· en· W3192870802 on OpenAlexafffund
Dominik Linz, Monika Gawałko, Prashanthan Sanders, John Penders, Na Li, Stanley Nattel, Dobromir Dobrev

Bibliographic record

VenueEuropean Heart Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsMcGill UniversityMontreal Heart Institute
FundersNational Heart, Lung, and Blood InstituteNational Institutes of HealthDeutsche ForschungsgemeinschaftCanadian Institutes of Health ResearchEuropean Commission
KeywordsMedicineAffect (linguistics)Gut floraRhythmInternal medicineImmunologyCommunication

Abstract

fetched live from OpenAlex

Dietary intake has been shown to change the composition of gut microbiota and some changes in microbiota (dysbiosis) have been linked to diabetes, hypertension, and obesity, which are established risk factors for atrial fibrillation (AF). In addition, intestinal dysbiosis generates microbiota-derived bioactive metabolites that might exert proarrhythmic actions. Although emerging preclinical investigations and clinical observational cohort studies suggest a possible role of gut dysbiosis in AF promotion, the exact mechanisms through which dysbiosis contributes to AF remain unclear. This Viewpoint article briefly reviews evidence suggesting that abnormalities in the intestinal microbiota play an important and little-recognized role in the pathophysiology of AF and that an improved understanding of this role may open up new possibilities in the management of AF.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.039
GPT teacher head0.349
Teacher spread0.310 · 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 designTheoretical or conceptual
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

Citations32
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueEuropean Heart JournalSame topicCardiac Health and Mental HealthFrench-language works237,207