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Record W2617203767 · doi:10.1136/heartjnl-2016-310357

Chocolate intake and risk of clinically apparent atrial fibrillation: the Danish Diet, Cancer, and Health Study

2017· article· en· W2617203767 on OpenAlexaff
Elizabeth Mostofsky, Martin Berg Johansen, Anne Tjønneland, Harpreet S. Chahal, Murray A. Mittleman, Kim Overvad

Bibliographic record

VenueHeart · 2017
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsWestern University
FundersNational Center for Research ResourcesNational Heart, Lung, and Blood InstituteHarvard UniversityKræftens BekæmpelseNational Center for Advancing Translational SciencesStrategiske ForskningsrådHarvard CatalystNational Institutes of Health
KeywordsMedicineAtrial fibrillationDanishCancerInternal medicineEpidemiologyCardiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the association between chocolate intake and incident clinically apparent atrial fibrillation or flutter (AF). METHODS: The Danish Diet, Cancer, and Health Study is a large population-based prospective cohort study. The present study is based on 55 502 participants (26 400 men and 29 102 women) aged 50-64 years who had provided information on chocolate intake at baseline. Incident cases of AF were ascertained by linkage with nationwide registries. RESULTS: During a median of 13.5 years there were 3346 cases of AF. Compared with chocolate intake less than once per month, the rate of AF was lower for people consuming 1-3 servings/month (hazard ratio (HR) 0.90, 95% confidence interval (CI) 0.82 to 0.98), 1 serving/week (HR 0.83, 95% CI 0.74 to 0.92), 2-6 servings/week (HR 0.80, 95% CI 0.71 to 0.91) and ≥1 servings/day (HR 0.84, 95% CI 0.65 to 1.09; p-linear trend <0.0001), with similar results for men and women. CONCLUSIONS: Accumulating evidence indicates that moderate chocolate intake may be inversely associated with AF risk, although residual confounding cannot be ruled out.

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)0.001
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 score0.050
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.083
GPT teacher head0.410
Teacher spread0.327 · 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

Citations39
Published2017
Admission routes1
Has abstractyes

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