Evidence map›Paper›PMID 41143983›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2026

Risk stratification with pre-operative myocardial perfusion imaging.

Dayoung Kim, Valerie Builoff, Tali Sharir, M Timothy Hauser, Sharmila Dorbala, Marcelo F Di Carli, Mathews B Fish, Terrence D Ruddy, Timothy M Bateman, Andrew J Einstein and 9 more

Abstract readMulticenter Study
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Dayoung KimDepartment of Cardiac Sciences, University of Calgary and Libin Cardiovascular Institute, Calgary, AB, Canada.
Valerie BuiloffDepartments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Tali SharirDepartment of Nuclear Cardiology, Assuta Medical Centers, Tel Aviv, Israel and Ben Gurion University of the Negev, Beer Sheba, Israel.
M Timothy HauserDepartment of Nuclear Cardiology, Oklahoma Heart Hospital, Oklahoma City, OK, USA.
Sharmila DorbalaDepartment of Radiology, Division of Nuclear Medicine and Molecular Imaging, Brigham and Women's Hospital, Boston, MA, USA.
Marcelo F Di CarliDepartment of Radiology, Division of Nuclear Medicine and Molecular Imaging, Brigham and Women's Hospital, Boston, MA, USA.
Mathews B FishOregon Heart and Vascular Institute, Sacred Heart Medical Center, Springfield, OR, USA.
Terrence D RuddyDivision of Cardiology, University of Ottawa Heart Institute, Ottawa, ON, Canada.
Timothy M BatemanCardiovascular Imaging Technologies LLC, Kansas City, MO, USA.
Andrew J EinsteinDivision of Cardiology, Department of Medicine and Department of Radiology, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, NY, USA.
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 School of Medicine, New Haven, CT, USA.
Albert J SinusasSection of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA.
Wanda AcampaDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Julian HalcoxSwansea University Medical School, Swansea University, Swansea, UK.
Damini DeyDepartments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Daniel S BermanDepartments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Robert J H Miller *Department of Cardiac Sciences, University of Calgary and Libin Cardiovascular Institute, Calgary, AB, Canada. robert.miller@albertahealthservices.ca.ORCID 0000-0003-4676-2433
Piotr J Slomka *Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Funding

Quantitative Prediction of Disease and Outcomes from Next Generation SPECT and CTR01HL089765 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI SLOMKA, PIOTR J · 2007 to 2021
$6.1M
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
Foundation for the National Institutes of Health R01HL089765NHLBI NIH HHS R01 HL089765NHLBI NIH HHS R35 HL161195NHLBI NIH HHS R35HL161195
6 · The paper itself

Abstract

purposeMyocardial perfusion imaging (MPI) is frequently used to improve cardiac risk prediction in patients undergoing non-cardiac surgery. However, the data supporting this practice is derived from single center studies and predates current therapy for coronary artery disease (CAD). We evaluated the association between pre-operative testing indication and outcomes as well as predictors of death or myocardial infarction (MI) in these patients.

methodsWe include patients from the international, multicenter REFINE-SPECT registry (13 sites). Based on referral indication, patients were classified as pre-operative testing indications and non-pre-operative testing. We evaluated the associations between pre-operative testing and incidence of death or MI. We then evaluated associations with death or MI in patients referred for pre-operative testing compared to other patients.

resultsIn total, 32,711 patients were included with pre-operative testing as the indication in 2,173(6.6%) patients. Patients referred for pre-operative testing were more likely to experience death or MI (annualized rate 4.4% vs 1.6%, p < 0.001). In patients referred for pre-operative testing, stress, rest, and ischemic total perfusion deficit were associated with death or MI. Rest total perfusion deficit (adjusted hazard ratio [HR] 1.25, 95% confidence interval [CI] 1.07 - 1.45) was independently associated with death or MI, but pharmacologic stress testing was not (adjusted HR 0.88, 95% CI 0.70 - 1.12).

conclusionPatients undergoing pre-operative SPECT MPI are at increased cardiovascular risk which may reflect selection bias or unmeasured confounders. Resting perfusion abnormalities may identify patients at higher risk, potentially helping guide peri-operative care.

Indexed as

Coronary Artery DiseaseMyocardial Perfusion ImagingPreoperative CareAgedFemaleHumansMaleMiddle AgedMyocardial InfarctionPreoperative PeriodRegistriesRisk AssessmentTomography, Emission-Computed, Single-PhotonMyocardial perfusion imagingPeri-operativePre-operative testingPrognosisSingle photon emission computed tomography

Identifiers

PMID41143983
PMCPMC12810971

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Registered trials

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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.