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Record W4410010677 · doi:10.1016/j.jscai.2025.103664

Coronary Computed Tomography Angiography to Guide Percutaneous Coronary Intervention: Expert Opinion from a SCAI/SCCT Roundtable

2025· article· en· W4410010677 on OpenAlexaff
Yader Sandoval, Jonathon Leipsic, Carlos Collet, Ziad A. Ali, Lorenzo Azzalini, Emanuele Barbato, João L. Cavalcante, Ricardo A. Costa, Héctor M. García‐García, Daniel A. Jones, John King Khoo, Anbukarasi Maran, Koen Nieman, Natalia Pinilla‐Echeverri, Arnold H. Seto, Evan Shlofmitz, Emmanouil S. Brilakis

Bibliographic record

VenueJournal of the Society for Cardiovascular Angiography & Interventions · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsMcMaster UniversityHamilton Health SciencesUniversity of British Columbia
Fundersnot available
KeywordsMedicineConventional PCIPercutaneous coronary interventionPsychological interventionRadiologyTriageComputed tomography angiographyExpert opinionCoronary angiographyMedical physicsPercutaneousAngiographyCardiologyIntensive care medicineMyocardial infarctionMedical emergencyNursing

Abstract

fetched live from OpenAlex

Coronary computed tomography angiography (CCTA) has emerged as an important tool for planning percutaneous coronary intervention (PCI). While it has traditionally been employed for diagnostic purposes, increasing evidence and real-world experience suggest that CCTA can be used for the preprocedural planning of PCI and can inform patient triage, shared decision making, case complexity, and resource use. This approach mirrors how computed tomography angiography is routinely used to plan structural interventions. To address these emerging opportunities, the Society for Cardiovascular Angiography & Interventions (SCAI) and the Society of Cardiovascular Computed Tomography (SCCT) organized a multidisciplinary, expert scientific roundtable on the use of CCTA for guiding PCI. The goal of this document is to provide a state-of-the-art overview of CCTA-guided PCI focused on practical applications and key coronary lesion subsets, define unmet needs and barriers, and outline future directions.

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 categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.358
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.305
Teacher spread0.286 · 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 designNot applicable
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

Citations8
Published2025
Admission routes1
Has abstractyes

Explore more

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