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Record W2793443734

Abstract 15668: Diffuse Interstitial Myocardial Fibrosis is Associated With Abnormal Left Atrial Mechanics in Hypertension

2016· article· en· W2793443734 on OpenAlexaboutno aff
Julio A. Chirinos, Amer Ahmed Syed, Zeba Hashmath, Timothy S. Phan, Maheswara R Koppula, Uzma Kawan, Zoubair Ahmed, Ravikantha Chandamuri, Swapna Varakantam, Ejaz Shah, Ryan Gorz, Scott Akers

Bibliographic record

VenueCirculation · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiologyInternal medicineMyocardial fibrosisDiastoleCompliance (psychology)FibrosisHeart failurePressure overloadPreloadBlood pressureHemodynamics
DOInot available

Abstract

fetched live from OpenAlex

Background: Varying degrees of myocardial fibrosis may accompany LV remodeling associated with pressure overload. However, the correlates of diffuse myocardial fibrosis are poorly understood. Given the role of ECV on left ventricular diastolic compliance, we hypothesized that ECV is associated with abnormal atrial mechanics in hypertension. Methods: We studied 151 subjects with hypertension. ECV was measured with myocardial T1 mapping before and after the administration of gadolinium, in a mid-ventricular short axis plane. Longitudinal atrial mechanics were measured with SSFP MRI, from the 4-chamber and 2-chamber views, using tissue tracking (CVI42; Circle CV Imaging; Calgary, Canada). Results: In models that adjusted for demographics, body size, blood pressure, the presence of heart failure, diabetes and medication use, ECV was independently predictive of a poorer reservoir, conduit and booster pump function (Table). Conclusions: ECV is independently associated atrial dysfunction in hypertension. Diffuse myocardial fibrosis play a role in the development of atrial arrhythmias and/or HFpEF in hypertensive subjects.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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)0.0030.000

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 head0.016
GPT teacher head0.235
Teacher spread0.219 · 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
Published2016
Admission routes1
Has abstractyes

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