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Prevalence of asymptomatic atrial fibrillation among multimorbid elderly patients: diagnostic implications

2022· article· en· W4214498130 on OpenAlexaff

Bibliographic record

VenueMinerva Cardiology and Angiology · 2022
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsAsymptomaticAtrial fibrillationPopulationComorbiditySubclinical infectionCardiac arrhythmia

Abstract

fetched live from OpenAlex

Advancing age of the global population is one of the main reasons for the uprising trend in atrial fibrillation (AF) prevalence worldwide leading to a proper "AF epidemic". Strictly related to the increasing prevalence of AF in the elderly is the relevant burden of cardiac end extra-cardiac comorbidities that these patients show. Patients with AF are frequently asymptomatic (i.e., asymptomatic or silent AF) and thus the arrhythmia is generally underdiagnosed. Detainment of proper treatment in elderly and comorbid patients may potentially result in significant morbidity and mortality. Therefore, in recent years, several screening strategies (systematic vs opportunistic screening) for asymptomatic AF have been developed and early diagnosis of AF is an important treatment goal that can improve prognosis. This review will focus on the prevalence of asymptomatic AF in the elderly, frequently associated comorbidities, screening strategies, and implications for a correct AF diagnosis.

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)0.001
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 score0.005
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.026
GPT teacher head0.289
Teacher spread0.263 · 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
Published2022
Admission routes1
Has abstractyes

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