Evidence map›Paper›PMID 41726045›Full record

ArticleJournal of the Society for Cardiovascular Angiography & Interventions2026

Diagnostic Performance of a Novel AI-Guided Coronary Computed Tomography Algorithm for Predicting Myocardial Ischemia (AI-QCT

Putri Annisa Kamila, Tara Hojjati, Nick S Nurmohamed, Ibrahim Danad, Yipu Ding, Ruurt A Jukema, Pieter G Raijmakers, Roel S Driessen, Michiel J Bom, Pepijn van Diemen and 9 more

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In one paragraph

Article in Journal of the Society for Cardiovascular Angiography & Interventions, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Putri Annisa KamilaDepartment of Cardiology, Leiden University Medical Center, Leiden, the Netherlands.
Tara HojjatiThe College of Liberal Arts and Sciences, Arizona State University, Tempe, Arizona.
Nick S NurmohamedDepartment of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Ibrahim DanadDepartment of Cardiology, Radboud University Medical Center, Nijmegen, the Netherlands.
Yipu DingDepartment of Cardiology, Leiden University Medical Center, Leiden, the Netherlands.
Ruurt A JukemaDepartment of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Pieter G RaijmakersDepartment of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Roel S DriessenDepartment of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Michiel J BomDepartment of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Pepijn van DiemenDepartment of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Gianluca PontoneDepartment of Cardiovascular Imaging, Centro Cardiologico Monzino, IRCCS, Milan, Italy.
Daniele AndreiniDepartment of University Cardiology and Cardiac Imaging, IRCCS Ospedale Galeazzi Sant'Ambrogio, Milan, Italy.
Hyuk-Jae ChangDivision of Cardiology, Severance Cardiovascular Hospital and Severance Biomedical Science Institute, Yonsei University College of Medicine, Yonsei University Health System, Seoul, South Korea.
Richard J KatzDivision of Cardiology, The George Washington University School of Medicine, Washington, District of Columbia.
Andrew D ChoiDivision of Cardiology, The George Washington University School of Medicine, Washington, District of Columbia.
Paul KnaapenDepartment of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Jeroen J BaxDepartment of Cardiology, Leiden University Medical Center, Leiden, the Netherlands.
Alexander van RosendaelDepartment of Cardiology, Leiden University Medical Center, Leiden, the Netherlands.
CREDENCE and PACIFIC-1 Investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: AI-QCT Methods: This post-hoc analysis included symptomatic patients with suspected coronary artery disease from the CREDENCE (Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia) (n = 305; 868 vessels) and PACIFIC-1 (Comparison of Coronary Computed Tomography Angiography, Single Photon Emission Computed Tomography [SPECT], Positron Emission Tomography [PET], and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve) (n = 208; 612 vessels) studies. All patients underwent coronary computed tomography angiography, myocardial perfusion imaging (SPECT and/or PET), and invasive coronary angiography with 3-vessel fractional flow reserve as the reference standard. Diagnostic performance was evaluated at the vessel level using receiver operating characteristic analysis and under the curve (AUC), stratified by sex and age groups. Results: In computed tomographic evaluation of atherosclerotic determinants of myocardial ischemia, AI-QCT Conclusions: AI-QCT

Indexed as

artificial intelligencecoronary artery diseasecoronary computed tomography angiography

Identifiers

PMID41726045
PMCPMC12923349

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.