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Record W3021287123 · doi:10.1093/ehjci/jeaa041

Left atrial remodelling, mid-regional pro-atrial natriuretic peptide, and prognosis across a range of ejection fractions in heart failure

2020· article· en· W3021287123 on OpenAlexaff
Brendan Putko, Anamaria Savu, Padma Kaul, Justin A. Ezekowitz, Jason R.B. Dyck, Todd J. Anderson, James A. White, D. Ian Paterson, Richard B. Thompson, Gavin Y. Oudit

Bibliographic record

VenueEuropean Heart Journal - Cardiovascular Imaging · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsLibin Cardiovascular Institute of AlbertaCanadian VIGOUR CentreHealth Sciences CentreUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsMedicineCardiologyInternal medicineHeart failureEjection fractionStroke volumeNatriuretic peptideHazard ratioBrain natriuretic peptideConfidence interval

Abstract

fetched live from OpenAlex

AIMS: Measures of structural and functional remodelling of the left atrium (LA) are emerging as useful biomarkers in heart failure (HF). We hypothesized that LA volume and its contribution to stroke volume (SV) would predict a composite endpoint of HF hospitalization or death in patients with HF. METHODS AND RESULTS: We recruited 57 controls and 86 patients with HF, including preserved and reduced left ventricular ejection fraction (LVEF). Cardiac magnetic resonance imaging was used to evaluate LA volumes and contribution to LV SV. Plasma mid-region pro-atrial natriuretic peptide (MR-proANP) was evaluated. LA volume was negatively correlated with LVEF (P = 0.001) and positively correlated with LV mass in HFrEF (P < 0.001) but not in HFpEF. LA volume at end-diastole was associated with the composite endpoint in HFrEF (hazard ratio 1.26, 95% confidence interval 1.01-1.54; P = 0.044), but not HFpEF (1.06, 0.85-1.30; P = 0.612), per 10 mL/m increase. Active contribution to SV was negatively associated with the composite endpoint in HFpEF (0.32, 0.14-0.66; P = 0.001), but not HFrEF (0.91, 0.38-2.1; P = 0.828) per 10% increase. MR-proANP was associated with the composite endpoint in HFpEF (1.46, 1.03-1.94; P = 0.034), but not in HFrEF (1.14, 0.88-1.37; P = 0.278), per 100 pM increase. CONCLUSION: We found different relationships between LA remodelling and biomarkers in HFrEF and HFpEF. Our results support the hypothesis that the pathophysiologic underpinnings of HFpEF and HFrEF are different, and atrial remodelling encompasses distinct components for each HF subtype.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.283
Teacher spread0.245 · 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.

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

Citations14
Published2020
Admission routes1
Has abstractyes

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