Evidence map›Paper›PMID 32802300›Full record

ArticleJournal of healthcare engineering2020

A Comparison of Three-Dimensional Speckle Tracking Echocardiography Parameters in Predicting Left Ventricular Remodeling.

Junda Zhong, Peng Liu, Shuang Li, Xiaomin Huang, Qunhui Zhang, Jianyu Huang, Yan Guo, Meixiang Chen, Zheng Ruan, Changyu Qin and 1 more

Open access · hybridAbstract readComparative Study
In one paragraph

Article in Journal of healthcare engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. [Area strain as prognostic factor of functional recovering in myocardial infarction].Revista medica del Instituto Mexicano del Seguro Social · 2025
    Observational
  2. Article
  3. Article
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  5. Review
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

11 authors at 2 institutions in 1 country.

Junda ZhongDepartment of Geriatric Cardiology, General Hospital of the Southern Theatre Command, PLA, Guangzhou 510016, China.
Peng LiuDepartment of Cardiology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Shuang LiDepartment of Geriatric Cardiology, General Hospital of the Southern Theatre Command, PLA, Guangzhou 510016, China.
Xiaomin HuangDepartment of Geriatric Cardiology, General Hospital of the Southern Theatre Command, PLA, Guangzhou 510016, China.
Qunhui ZhangDepartment of Geriatric Cardiology, General Hospital of the Southern Theatre Command, PLA, Guangzhou 510016, China.
Jianyu HuangDepartment of Geriatric Cardiology, General Hospital of the Southern Theatre Command, PLA, Guangzhou 510016, China.
Yan GuoDepartment of Geriatric Cardiology, General Hospital of the Southern Theatre Command, PLA, Guangzhou 510016, China.
Meixiang ChenDepartment of Geriatric Cardiology, General Hospital of the Southern Theatre Command, PLA, Guangzhou 510016, China.
Zheng RuanDepartment of Geriatric Cardiology, General Hospital of the Southern Theatre Command, PLA, Guangzhou 510016, China.
Changyu QinDepartment of Geriatric Cardiology, General Hospital of the Southern Theatre Command, PLA, Guangzhou 510016, China.
Lin XuDepartment of Geriatric Cardiology, General Hospital of the Southern Theatre Command, PLA, Guangzhou 510016, China.ORCID 0000-0001-7750-8011
Third Affiliated Hospital of Southern Medical University · CNZhujiang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Three-dimensional speckle tracking echocardiography (3D STE) is an emerging noninvasive method for predicting left ventricular remodeling (LVR) after acute myocardial infarction (AMI). Previous studies analyzed the predictive value of 3D STE with traditional models. However, no models that contain comprehensive risk factors were assessed, and there are limited data on the comparison of different 3D STE parameters. In this study, we sought to build a machine learning model for predicting LVR in AMI patients after effective percutaneous coronary intervention (PCI) that contains the majority of the clinical risk factors and compare 3D STE parameters values for LVR prediction. We enrolled 135 first-onset AMI patients (120 males, mean age 54 ± 9 years). All patients went through a 3D STE and a traditional transthoracic echocardiography 24 hours after reperfusion. A second echocardiography was repeated at the three-month follow-up to detect LVR (defined as a 20 percent increase in left ventricular end-diastolic volume). Six models were constructed using 15 risk factors. A receiver operator characteristic curve and four performance measurements were used as evaluation methods. Feature importance was used to compare 3D STE parameters. 26 patients (19.3%) had LVR. Our evaluation showed that RF can best predict LVR with the best AUC of 0.96. 3D GLS was the most valuable 3D STE parameters, followed by GCS, global area strain, and global radial strain (feature importance 0.146, 0.089, 0.087, and 0.069, respectively). To sum up, RF models can accurately predict the LVR after AMI, and 3D GLS was the best 3D STE parameters in predicting the LVR.

Indexed as

Machine LearningAdultAgedArea Under CurveCoronary AngiographyEchocardiographyFemaleHeart VentriclesHumansImaging, Three-DimensionalMaleMiddle AgedModels, StatisticalMyocardial InfarctionPercutaneous Coronary InterventionPredictive Value of Tests

Identifiers

PMID32802300
PMCPMC7416266
OpenAlexW3046571957

What OpenQuestion holds

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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.