Evidence map›Paper›PMID 34629991›Full record

ArticleContrast media & molecular imaging2021

Protection of Ivabradine Combined with Trimetazidine on Myocardial Injury after Percutaneous Coronary Intervention in Patients with Coronary Artery Disease Evaluated by Magnetic Resonance Image under Convolutional Neural Network.

Chunhua Chen

Open access · hybridAbstract read
In one paragraph

Article in Contrast media & molecular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

1 author.

Chunhua ChenDepartment of Cardiovascular Medicine, The First People's Hospital of Chun'an County, Hangzhou 311700, China.ORCID 0000-0003-4625-5327

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To evaluate the myocardial protection of Ivabradine (IBD) combined with Trimetazidine (TMZ) in patients with coronary artery disease (CAD) after percutaneous coronary intervention (PCI), magnetic resonance imaging (MRI) images under convolutional neural network (CNN) algorithm were used. Methods: A CNN artificial intelligence algorithm was proposed to process the image artifacts caused by undersampling magnetic resonance, so as to be used in the diagnosis and efficacy evaluation of myocardial injury. 120 patients with CAD after PCI were rolled into group Results: The accuracy, sensitivity, specificity, and area under the curve (AUC) of MRI images based on CNN algorithm for the diagnosis of myocardial injury were 91.04%, 97.60%, 87.04%, and 96.43%, respectively. After treatment, the left ventricular end diastolic diameter (LVEDD), LVE diastolic volume (LVEDV), LVE systolic diameter (LVESD), and LVE systolic volume (LVESV) were greatly reduced in all groups after treatment, whereas the left ventricular ejection fraction (LVEF) increased considerably ( Conclusion: MRI based on CNN had high application value in the diagnosis and efficacy evaluation of myocardial injury after PCI. For patients with CAD, IBD combined with TMZ after PCI can effectively play the role of anti-inflammatory and antioxidative damage and improve intradermal function.

Indexed as

Magnetic Resonance ImagingAgedAged, 80 and overArtificial IntelligenceCoronary Artery DiseaseFemaleHeartHeart InjuriesHumansIvabradineMaleMiddle AgedMyocardiumNeural Networks, ComputerPercutaneous Coronary InterventionTrimetazidineIvabradineTrimetazidine

Identifiers

PMID34629991
PMCPMC8476248
OpenAlexW3200483551

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.