Evidence map›Paper›PMID 36776233›Full record

ArticleJournal of translational internal medicine2022

Functional Evaluation of Intermediate Coronary Lesions with Integrated Computed Tomography Angiography and Invasive Angiography in Patients with Stable Coronary Artery Disease.

Jingyi Xue, Jianqiang Li, Danghui Sun, Li Sheng, Yongtai Gong, Dingyu Wang, Song Zhang, Yilun Zou, Jing Shi, Wei Xu and 8 more

Abstract read
In one paragraph

Article in Journal of translational internal medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  11. Conquer coronary artery perforation with magic hands.Journal of geriatric cardiology : JGC · 2024
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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

18 authors.

Jingyi XueDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Jianqiang LiDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Danghui SunDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Li ShengDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Yongtai GongDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Dingyu WangDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Song ZhangDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Yilun ZouDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Jing ShiDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Wei XuDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Mengnan AnDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Chenguang DaiDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Weimin LiDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Linqun ZhengMolecular and Translational Cardiology, Hannover Medical University, Hannover 30625, Germany.
Asiia VinogradDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Guangzhong LiuDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Yihui KongDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Yue LiDepartment of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objectives: The hemodynamic evaluation of coronary stenoses undergoes a transition from wire-based invasive measurements to image-based computational assessments. However, fractional flow reserve (FFR) values derived from coronary CT angiography (CCTA) and angiography-based quantitative flow ratio have certain limitations in accuracy and efficiency, preventing their widespread use in routine practice. Hence, we aimed to investigate the diagnostic performance of FFR derived from the integration of CCTA and invasive angiography (FFR Methods: Forty stable CAD patients with 67 target vessels (50%-90% diameter stenosis) were included in this single-center retrospective study. All patients underwent CCTA followed by coronary angiography with FFR measurement within 30 days. Both CCTA and angiographic images were combined to generate a three-dimensional reconstruction of the coronary arteries using artificial intelligence. Subsequently, functional assessment was performed through a deep learning algorithm. FFR was used as the reference. Results: FFR Conclusions: FFR

Indexed as

artificial intelligenceCT angiography-derived fractional flow reservefractional flow reservequantitative flow ratiostable coronary artery disease

Identifiers

PMID36776233
PMCPMC9901557

What OpenQuestion holds

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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.