Evidence map›Paper›PMID 35187886›Full record

ArticleJournal of Zhejiang University. Science. B2022

Index of microcirculatory resistance: state-of-the-art and potential applications in computational simulation of coronary artery disease.

Yingyi Geng, Xintong Wu, Haipeng Liu, Dingchang Zheng, Ling Xia

Abstract read
In one paragraph

Article in Journal of Zhejiang University. Science. B, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

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

  1. Angiography-based coronary microvascular assessment with and without intracoronary pressure measurements: a systematic review.Clinical research in cardiology : official journal of the German Cardiac Society · 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

5 authors.

Yingyi GengKey Laboratory for Biomedical Engineering of Ministry of Education, Institute of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
Xintong WuKey Laboratory for Biomedical Engineering of Ministry of Education, Institute of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
Haipeng LiuResearch Centre of Intelligent Healthcare, Faculty of Health and Life Science, Coventry University, Coventry CV1 5FB, UK.
Dingchang ZhengResearch Centre of Intelligent Healthcare, Faculty of Health and Life Science, Coventry University, Coventry CV1 5FB, UK. dingchang.zheng@coventry.ac.uk.
Ling XiaKey Laboratory for Biomedical Engineering of Ministry of Education, Institute of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China. xialing@zju.edu.cn.

Funding

the Key Research and Development Program of Zhejiang Province 2020C03016the Medical Health Science and Technology Project of Zhejiang Provincial Health Commission 2020RC094the Natural Science Foundation of China 61527811 and 61701435the Zhejiang Provincial Natural Science Foundation of China LY17H180003
6 · The paper itself

Abstract

The dysfunction of coronary microcirculation is an important cause of coronary artery disease (CAD). The index of microcirculatory resistance (IMR) is a quantitative evaluation of coronary microcirculatory function, which provides a significant reference for the prediction, diagnosis, treatment, and prognosis of CAD. IMR also plays a key role in investigating the interaction between epicardial and microcirculatory dysfunctions, and is closely associated with coronary hemodynamic parameters such as flow rate, distal coronary pressure, and aortic pressure, which have been widely applied in computational studies of CAD. However, there is currently a lack of consensus across studies on the normal and pathological ranges of IMR. The relationships between IMR and coronary hemodynamic parameters have not been accurately quantified, which limits the application of IMR in computational CAD studies. In this paper, we discuss the research gaps between IMR and its potential applications in the computational simulation of CAD. Computational simulation based on the combination of IMR and other hemodynamic parameters is a promising technology to improve the diagnosis and guide clinical trials of CAD.

Indexed as

Coronary Artery DiseaseCoronary AngiographyCoronary CirculationHumansMicrocirculationPredictive Value of TestsVascular ResistanceComputational simulationCoronary artery disease (CAD)Index of microcirculatory resistance (IMR)

Identifiers

PMID35187886
PMCPMC8861561

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.