Evidence map›Paper›PMID 39759439›Full record

ArticleJACC. Advances2025

The Relationship Between Quantitative Ischemia, Early Revascularization, and Major Adverse Cardiovascular Events: A Multicenter Study.

Robert Jh Miller, Bryan Bednarski, Yujie Cui, Vinicius Calsavara, Krishna Patel, Alan Rozanski, Joanna X Liang, Valerie Builoff, Wanda Acampa, Timothy M Bateman and 13 more

Abstract read
In one paragraph

Article in JACC. Advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Risk stratification with pre-operative myocardial perfusion imaging.European journal of nuclear medicine and molecular imaging · 2026
    Article
  2. Article
  3. Myocardial perfusion imaging in advanced coronary artery disease.European journal of clinical investigation · 2025
    Review
  4. Observational
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

23 authors.

Robert Jh MillerDepartment of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, United States.
Bryan BednarskiDepartment of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, United States.
Yujie CuiDepartment of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, United States.
Vinicius CalsavaraDepartment of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, United States.
Krishna PatelDivision of Cardiology and Department of Medicine, Mount Sinai Heart and the Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Alan RozanskiDepartment of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, United States.
Joanna X LiangDepartment of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, United States.
Valerie BuiloffDepartment of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, United States.
Wanda AcampaDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Timothy M BatemanCardiovascular Imaging Technologies, LLC, Kansas City, Missouri, United States.
Marcelo Di CarliDivision of Nuclear Medicine and Molecular Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, United States.
Sharmila DorbalaDivision of Nuclear Medicine and Molecular Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, United States.
Andrew J EinsteinDivision of Cardiology, Department of Medicine, and Radiology, Columbia University Irving Medical Center, New York, New York, United States.
Matthews B FishOregon Heart and Vascular Institute, Sacred Heart Medical Center, Springfield, Oregon, United States.
M Timothy HauserDepartment of Nuclear Cardiology, Oklahoma Heart Hospital, Oklahoma City, Oklahoma, United States.
Philipp A KaufmannDepartment of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Zurich, Switzerland.
Edward J MillerSection of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, Connecticut, United States.
Terrence D RuddyDivision of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada.
Tali SharirDepartment of Nuclear Cardiology, Assuta Medical Center, Tel Aviv, Israel.
Albert J SinusasSection of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, Connecticut, United States.
Damini DeyDepartment of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, United States.
Daniel S BermanDepartment of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, United States.
Piotr J SlomkaDepartment of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, United States.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Patient-specific Outcome Prediction from Cardiovascular Multimodality Imaging by Artificial IntelligenceR35HL161195 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI Piotr J Slomka · 2022 to 2026
$5.0M
NCATS NIH HHS UL1 TR001863NHLBI NIH HHS R35 HL161195
6 · The paper itself

Abstract

Background: Observational data have suggested that patients with moderate to severe ischemia benefit from revascularization. However, this was not confirmed in a large, randomized trial. Objectives: Using a contemporary, multicenter registry, the authors evaluated differences in the association between quantitative ischemia, revascularization, and outcomes across important subgroups. Methods: Patients who underwent myocardial perfusion imaging in 12 centers were included in this retrospective analysis. The population was divided into original (2009-2014) and recent (2014-2021) registry sites. Early revascularization was defined as any revascularization within 90 days of myocardial perfusion imaging. A propensity score was developed to adjust for nonrandomization. Propensity score-adjusted survival analyses were used to evaluate the associations between quantitative ischemia, early revascularization, and death or myocardial infarction (MI) to identify at what severity of ischemia the HR for early revascularization crosses 1 (threshold for potential benefit). Results: Overall, 40,449 patients were included with a median follow-up of 3.5 (IQR: 2.4-4.6) years, during which death or MI occurred in 2,797 (6.9%). Early revascularization was associated with reduced death or MI in patients with >9.0% myocardial ischemia (95% upper CI: 11.2%, interaction Conclusions: Early revascularization was associated with reduced risk in patients with a higher burden of quantitative ischemia in more recent populations. These findings suggest that methods integrating more factors than just ischemia are needed to improve patient selection for revascularization.

Indexed as

cardiovascular eventsischemiarevascularization

Identifiers

PMID39759439
PMCPMC11697767

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.