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483 CORONARY ATHEROSCLEROSIS PHENOTYPES IN FOCAL AND DIFFUSE DISEASE

2022· article· en· W4311750312 on OpenAlexaff
Marta Belmonte, Koshiro Sakai, Takuya Mizukami, Jonathon Leipsic, Jeroen Sonck, Bjarne Linde Nørgaard, Brian Ko, Michael Mæng, Jesper Moller Jansen, Daniele Andreini, Hirofumi Ohashi, Toshiro Shinke, Charles A. Taylor, Bernard De Bruyne, Carlos Collet

Bibliographic record

VenueEuropean Heart Journal Supplements · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineFractional flow reserveCoronary artery diseaseCardiologyInternal medicineProspective cohort studyRadiologyCoronary angiographyMyocardial infarction

Abstract

fetched live from OpenAlex

Abstract Introduction The pathophysiological interplay between coronary physiology and plaque characteristics remains poorly understood. Pullback pressure gradient (PPG) is a novel physiological index that discriminates focal from diffuse coronary artery disease (CAD) based on coronary physiology. We aimed to compare plaque characteristics using between atherosclerotic patterns defined by coronary physiology. Methods Multicenter, prospective, controlled, single-arm study conducted in five countries (NCT03782688). Patients with functionally significant lesions based on invasive fractional flow reserve (FFR<0.80) were included. Subjects underwent coronary computed tomography angiography (CCTA) with quantitative plaque analysis followed by an invasive procedure with optical coherence tomography (OCT) and motorized intracoronary pressure recordings. Fractional flow reserve (FFR) pullback curves were processed to calculate the PPG. The PPG ranges from 0, indicating diffuse disease, to 1, pointing to focal CAD. Focal and diffuse CAD were defined according to the median PPG value. Results Overall, 117 patients (120 vessels) were included. The mean age was 64±9, 80% were male, and 22% had diabetes (no difference between focal vs. diffuse). Median PPG was 0.66 [0.54, 0.75]. In CCTA analysis, the plaque burden at minimum lumen area was higher in patients with focal CAD (87±8% focal vs. 82±10% diffuse, p=0.003). Calcifications were significantly more prevalent in patients with diffuse CAD (Agatston score per vessel 50 [9, 166] focal vs. 151 [46, 360] diffuse, p=0.019). In OCT plaque analysis, patients with focal CAD had a significantly higher prevalence of circumferential lipid-rich plaque (37% focal vs. 4% diffuse, p=0.001) and thin-cap fibroatheroma (TCFA 47% focal vs. 10% diffuse, p=0.002). High PPG predicted the presence of TCFA with an AUC of 0.73 (95% CI 0.58 to 0.87). PPG and fibrous cap thickness were negatively correlated (r=-0.55, 95% CI -0.74 to -0.28) independently of FFR. Conclusions Atherosclerotic plaque phenotypes associate with intracoronary hemodynamics. Vessels with focal disease (high PPG) had a higher plaque burden and predominantly lipid-rich plaque with a high prevalence of TCFA, whereas calcifications were the hallmark of vessels with diffuse pressure loss.

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 score0.065
Threshold uncertainty score0.892

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)0.0010.000

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 head0.032
GPT teacher head0.291
Teacher spread0.260 · 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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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