Evidence map›Paper›PMID 38263819›Full record

ArticleThe British journal of radiology2024

Lesion-specific pericoronary adipose tissue CT attenuation improves risk prediction of major adverse cardiovascular events in coronary artery disease.

Meng Chen, Guangyu Hao, Su Hu, Can Chen, Qing Tao, Jialiang Xu, Yayuan Geng, Ximing Wang, Chunhong Hu

Abstract read
In one paragraph

Article in The British journal of radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 citing papers in PubMed.

  1. Article
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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

9 authors.

Meng ChenDepartment of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
Guangyu HaoDepartment of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
Su HuDepartment of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
Can ChenDepartment of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
Qing TaoDepartment of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
Jialiang XuDepartment of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
Yayuan GengDepartment of Research and Development, ShuKun Technology Co., Ltd, Beijing 100102, China.
Ximing WangDepartment of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
Chunhong HuDepartment of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.ORCID 0000-0002-6343-758X

Funding

Jiangsu Medical Association SYH-3201150-0016Suzhou Municipal Health Commission GSWS2020003
6 · The paper itself

Abstract

objectivesTo determine whether lesion-specific pericoronary adipose tissue CT attenuation (PCATa) is superior to PCATa around the proximal right coronary artery (PCATa-RCA) and left anterior descending artery (PCATa-LAD) for major adverse cardiovascular events (MACE) prediction in coronary artery disease (CAD).

methodsSix hundred and eight CAD patients who underwent coronary CTA from January 2014 to December 2018 were retrospectively included, with clinical risk factors, plaque features, lesion-specific PCATa, PCATa-RCA, and PCATa-LAD collected. MACE was defined as cardiovascular death, non-fatal myocardial infarction, unplanned revascularization, and hospitalization for unstable angina. Four models were established, encapsulating traditional factors (Model A), traditional factors and PCATa-RCA (Model B), traditional factors and PCATa-LAD (Model C), and traditional factors and lesion-specific PCATa (Model D). Prognostic performance was evaluated with C-statistic, area under receiver operator characteristic curve (AUC), and net reclassification index (NRI).

resultsLesion-specific PCATa was an independent predictor for MACE (adjusted hazard ratio = 1.108, P < .001). The C-statistic increased from 0.750 for model A to 0.762 for model B (P = .078), 0.773 for model C (P = .046), and 0.791 for model D (P = .005). The AUC increased from 0.770 for model A to 0.793 for model B (P = .027), 0.793 for model C (P = .387), and 0.820 for model D (P = .019). Compared with model A, the NRIs for models B, C, and D were 0.243 (-0.323 to 0.792, P = .392), 0.428 (-0.012 to 0.835, P = .048), and 0.708 (0.152-1.016, P = .001), respectively.

conclusionsLesion-specific PCATa improves risk prediction of MACE in CAD, which is better than PCATa-RCA and PCATa-LAD. ADVANCES IN KNOWLEDGE: Lesion-specific PCATa was superior to PCATa-RCA and PCATa-LAD for MACE prediction.

Indexed as

Coronary Artery DiseaseEpicardial Adipose TissueHumansRetrospective StudiesTomography, X-Ray Computedcoronary artery diseasemajor adverse cardiovascular eventspericoronary adipose tissue CT attenuationrisk prediction

Identifiers

PMID38263819
PMCPMC11651292

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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.