Evidence map›Paper›PMID 31133862›Full record

ArticleFrontiers in physiology2019

Prediction of Plaque Progression in Coronary Arteries Based on a Novel Hemodynamic Index Calculated From Virtual Stenosis Method.

Kyung Eun Lee, Sung Woong Shin, Gook Tae Kim, Jin Ho Choi, Eun Bo Shim

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 29% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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 at 4 institutions in 1 country.

Kyung Eun LeeDepartment of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, South Korea.
Sung Woong ShinDepartment of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, South Korea.
Gook Tae KimSiliconSapiens Inc., Seoul, South Korea.
Jin Ho ChoiDepartment of Cardiology, Samsung Medical Center, Sungkyunkwan University, Seoul, South Korea.
Eun Bo ShimDepartment of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, South Korea.
Kangwon National University · KRKorea Institute of Industrial Technology · KRSamsung Medical Center · KRSiliconSapiens (South Korea) · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

rationalePredicting the sites in coronary arteries that are susceptible to plaque deposition is essential for the development of clinical treatment strategies and prevention. However, to date, no physiological biomarkers for this purpose have been developed. We hypothesized that the possibility of plaque deposition at a specific site in the coronary artery is associated with wall shear stress (WSS) and fractional flow reserve (FFR). BACKGROUND AND

objectiveWe proposed a new biomarker called the stenosis susceptibility index (SSI) using the FFR and WSS derived using virtual stenosis method. To validate the clinical efficacy of this index, we applied the method to actual pilot clinical cases. This index non-invasively quantifies the vasodilation effects of vascular endothelial cells relative to FFR variation at a specific coronary artery site. METHODS AND

resultsUsing virtual stenosis method, we computed maximum WSS and FFR according to the variation in stenotic severity at each potential stenotic site and then plotted the variations of maximum WSS (

conclusionThe SSI index can be used as a predictive biomarker to identify plaque deposition sites. Patients with relatively smaller SSI values also had a higher tendency for myocardial infarction. In conclusion, sites susceptible to plaque deposition can be identified using the SSI index.

Indexed as

coronary plaque depositionfractional flow reservestenosis susceptibility indexvirtual stenosis methodwall shear stress

Identifiers

PMID31133862
PMCPMC6526757
OpenAlexW2944526449

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.