Evidence map›Paper›PMID 41988306›Full record

ArticleJournal of thoracic disease2026

Value of coronary computed tomography angiography-derived plaque multiparameter analysis for guiding the management of intermediate coronary stenosis.

Danling Guo, Jinke Zhu, Guanzuan Wu, Huaifeng Li, Le Guan, Jiahu Yang, Xiaoya Zhai, Sangying Lv

Abstract read
In one paragraph

Article in Journal of thoracic disease, 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

8 authors.

Danling Guo *Department of Radiology, Shaoxing People's Hospital, Shaoxing, China.ORCID https://orcid.org/0000-0002-6959-4930
Jinke Zhu *Department of Radiology, Shaoxing People's Hospital, Shaoxing, China.
Guanzuan WuDepartment of Radiology, Shaoxing People's Hospital, Shaoxing, China.
Huaifeng LiDepartment of Radiology, Shaoxing People's Hospital, Shaoxing, China.
Le GuanDepartment of Radiology, Shaoxing People's Hospital, Shaoxing, China.
Jiahu YangDepartment of Radiology, Zhejiang Hospital, Hangzhou, China.
Xiaoya ZhaiDepartment of Cardiovascular Medicine, Shaoxing People's Hospital, Shaoxing, China.
Sangying LvDepartment of Radiology, Shaoxing People's Hospital, Shaoxing, China.ORCID https://orcid.org/0000-0002-1488-528X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The treatment of intermediate coronary stenosis (ICS) is challenging. This study aimed to investigate the values of coronary computed tomography angiography (CCTA)-derived parameters for guiding the management of ICS. Methods: We retrospectively analyzed 106 patients with ICS between February 1, 2023 and December 30, 2024. All enrolled patients underwent CCTA. Patients were stratified into percutaneous coronary intervention (PCI) and non-PCI groups, and the values of the CCTA-derived plaque parameters of the two groups were compared. Results: In total, 106 patients with ICS were enrolled (180 plaques). The PCI group had smaller minimal lumen areas (MLAs), longer lesion length (LL), greater total plaque area and lipid area than the non-PCI group. All differences were statistically significant (P<0.05). Low-attenuation plaques were more prevalent in the PCI than in the non-PCI group (33 Conclusions: CCTA plaque characterization enables accurate quantification of plaque features and facilitates personalized treatment decision-making for ICS.

Indexed as

Coronary computed tomography angiography (CCTA)intermediate coronary stenosis (ICS)managementmultiparameterplaque analysis

Identifiers

PMID41988306
PMCPMC13077418

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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.