Evidence mapPaperPMID 41233700Full record

Observational studyThe international journal of cardiovascular imaging2025

Predictive value of plaque features quantified by coronary CT angiography for periprocedural myocardial infarction in Non-ST-Segment elevation acute coronary syndrome.

Zhong-Fei Lu, Yijun Cao, Sameer Abrol, Wei-Hua Yin, Bin Zhang, Ziang Li, Aluo Wang, Jinxing Liu, Zhicheng Xiao, Debiao Li and 1 more

Abstract readMulticenter StudyObservational Study
PubMed Publisher
In one paragraph

Observational study in The international journal of cardiovascular imaging, 2025. 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

11 authors.

Zhong-Fei Lu *Department of Radiology, State Key Laboratory of Cardiovascular Disease, National Clinical Research Center for Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #167 Bei-Li-Shi Street, Beijing, People's Republic of China.
Yijun Cao *Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, #110 Yan'an Road (South), Changzhi City, Shanxi Province, People's Republic of China.
Sameer AbrolDepartment of Radiology and Radiological Science, Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA.
Wei-Hua YinDepartment of Radiology, State Key Laboratory of Cardiovascular Disease, National Clinical Research Center for Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #167 Bei-Li-Shi Street, Beijing, People's Republic of China.
Bin ZhangDepartment of Cardiology, State Key Laboratory of Cardiovascular Disease, National Clinical Research Center for Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #167 Bei-Li-Shi Street, Beijing, People's Republic of China.
Ziang LiDepartment of Cardiology, State Key Laboratory of Cardiovascular Disease, National Clinical Research Center for Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #167 Bei-Li-Shi Street, Beijing, People's Republic of China.
Aluo WangDepartment of Radiology, State Key Laboratory of Cardiovascular Disease, National Clinical Research Center for Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #167 Bei-Li-Shi Street, Beijing, People's Republic of China.
Jinxing LiuDepartment of Cardiology, State Key Laboratory of Cardiovascular Disease, National Clinical Research Center for Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #167 Bei-Li-Shi Street, Beijing, People's Republic of China.
Zhicheng XiaoDepartment of Cardiology, Yantai Yuhuangding Hospital, Qingdao University, #20 Yuhuangdingdong Street, Yantai, People's Republic of China.
Debiao Li *Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. debiao.li@cshs.org.
Bin Lu *Department of Radiology, State Key Laboratory of Cardiovascular Disease, National Clinical Research Center for Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #167 Bei-Li-Shi Street, Beijing, People's Republic of China. blu@vip.sina.com.

Funding

CAMS Innovation Fund for Medical Sciences(CIFMS) 2023-I2M-C&T-B-065Ministry of Science and Technology of China, National key research and development project 2016YFC1300403National Natural Science Foundation of China 82102036Postdoctoral Fellowship Program (Grade C) of China Postdoctoral Science Foundation GZC20251418
6 · The paper itself

Abstract

Periprocedural myocardial infarction (PMI) is associated with adverse outcomes, but determinants of its occurrence in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) remain unclear. This study aimed to investigate the predictive value of plaque characteristics quantified by coronary CT angiography (CCTA) for PMI in this population. In this secondary analysis of a prospective multicenter NSTE-ACS cohort, participants who underwent CCTA before percutaneous coronary intervention were analyzed. Plaque components were defined by CT thresholds: lipid core (< 30 HU), fibrous (30-350 HU), and calcified (≥ 350 HU). Plaque characteristics were comprehensively quantified on CCTA. PMI was adjudicated according to the Fourth Universal Definition of Myocardial Infarction. A total of 201 participants (mean age 56.8 years ± 11.3 [SD]; 170 male) were included for the analysis. PMI occurred in 30 (14.9%) participants. Lipid core burden (adjusted OR: 1.05; 95% CI: 1.01-1.09; P = 0.03) and plaque length (adjusted OR: 1.04; 95% CI: 1.01-1.07; P = 0.02) were independent predictors of PMI, with optimal cutoffs of 30.6% and 45.0 mm. The addition of dichotomized lipid core burden and plaque length to a baseline model significantly improved predictive performance, as indicated by an integrated discrimination improvement (IDI) of 0.11 (P < 0.001) and a net reclassification improvement (NRI) of 0.60 (P = 0.002). In patients with NSTE-ACS, CCTA-quantified lipid core burden and plaque length were independently associated with the risk of PMI. Pre-procedural CCTA plaque assessment improves risk stratification for PMI and may aid in planning individualized PCI strategies.

Indexed as

Acute Coronary SyndromeComputed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseCoronary VesselsMultidetector Computed TomographyNon-ST Elevated Myocardial InfarctionPlaque, AtheroscleroticVascular CalcificationAgedArea Under CurveChi-Square DistributionFemaleFibrosisHumansLipidsLipidsAcute coronary syndromeAtherosclerotic plaquesCT angiographyMyocardial infarctionRisk assessment

Identifiers

What Socratic holds

Textmetadata
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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 Socratic graph.