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Abstract 17226: Increased Risk of Heart Failure Associated With Left Atrial Remodeling Without Known Atrial Fibrillation

2018· article· en· W4212883990 on OpenAlexaffabout
Jodi D. Edwards, Jiming Fang, Jeff S. Healey, Kathy Yip, Lisa Mielniczuk, David J. Gladstone

Bibliographic record

VenueCirculation · 2018
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsPopulation Health Research InstituteSunnybrook Health Science CentreInstitute for Clinical Evaluative SciencesOttawa Heart Institute
Fundersnot available
KeywordsMedicineAtrial fibrillationInternal medicineCardiologyLeft atrial enlargementHeart failureHazard ratioProportional hazards modelSinus rhythmConfidence interval

Abstract

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Background: Atrial fibrillation (AF) significantly increases risk for heart failure (HF) and independently increases mortality and adverse in-hospital outcomes in HF patients. Validated clinical risk scores (ARC2H) can predict HF in patients with AF, but are limited in application as AF is frequently clinically silent or undetected. However, AF may be preceded by significant preclinical remodeling (left atrial enlargement (LAE) or excessive atrial ectopy (EAE)). Whether LAE and EAE are associated with HF prior to AF is unclear. Method(s): We analyzed consecutive adults >65 years with outpatient echocardiography or Holter at 11 Ontario community cardiology clinics (2010-2017). Exclusions were history of AF, anticoagulation, pacemaker/ICD/ILR, and prosthetic valve. Using linked administrative databases, we assessed 5-year rates of HF (primary) and incident AF and death (secondary) associated with LAE and EAE and among subgroups (M vs. F; <75 vs. >75; CHADS-VASC 0-2 vs. 3-6). Competing risks cox proportional hazards estimated adjusted hazard of HF for severe LAE: >47mm (M);>52mm (F)) or increased APBs/hour (EAE: >30) or both LAE and EAE, adjusting for age, vascular comorbidities and left ventricular (LV) dysfunction. Results: In 28,261 adults (mean 73+/-6 years), direct age-adjusted survival was reduced for those with severe LAE and EAE. 5-year rates of HF were increased for severe (8.8%) vs. moderate (3.5%) and mild (1.4%) LAE and for those with excessive (3.8%) vs. normal (2.5%) ectopy. For both LAE and EAE, those >75 and with a CHADS score 3-6 showed marked increases in HF at 5 years compared to <75 (LAE: 10.6% vs. 7.9%; EAE: 4.3% vs. 1.9%) and CHADS score 0-2 (LAE:21.4% vs. 6.6%; EAE: 8.9% vs. 2.4%). Severe LAE increased hazard of HF 2-fold (HR=2.07; p<.0001), and incident AF over 3-fold (HR= 3.43; p<.0001) and EAE increased hazard of HF (HR=1.31; p<.0001) and incident AF (HR=1.13; p<.0001). Those with both LAE and EAE showed an over 3-fold increased hazard of HF (HR=3.28; p<.0014). Conclusions: Severe LAE and EAE without known AF are associated with increased risk of HF and AF after adjusting for LV dysfunction, particularly for those >75 and with high vascular burden. These data have implications for risk stratification, AF screening, and trials for HF prevention in individuals with left atrial remodeling.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.035
GPT teacher head0.301
Teacher spread0.266 · 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 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

Citations0
Published2018
Admission routes2
Has abstractyes

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