Evidence map›Paper›PMID 39781616›Full record

ArticleScience progress

Noninvasive prediction of coronary artery disease severity: Comparative analysis of electrocardiographic findings and risk factors with SYNTAX and Gensini score.

Farzaneh-Sadat Mirjalili, Tahere Baghiani, Faezeh Badkoubeh, Abbas Andishmand, Mohammadtaghi Sarebanhassanabadi, Hamidreza Mohammadi, Amin Salehi-Abargouei, Maryam Motallaei, Seyed Mostafa Seyedhosseini

Abstract readComparative Study
PubMed Full text at PMC Publisher
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Article in Science progress. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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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

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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

1 citing paper in PubMed.

  1. 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

9 authors.

Farzaneh-Sadat MirjaliliYazd Cardiovascular Research Center, Non-communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Tahere BaghianiYazd Cardiovascular Research Center, Non-communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Faezeh BadkoubehSchool of Medicine, Arak University of Medical Sciences, Arak, Iran.
Abbas AndishmandYazd Cardiovascular Research Center, Non-communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Mohammadtaghi SarebanhassanabadiYazd Cardiovascular Research Center, Non-communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Hamidreza MohammadiYazd Cardiovascular Research Center, Non-communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.ORCID 0000-0002-7104-5295
Amin Salehi-AbargoueiYazd Cardiovascular Research Center, Non-communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Maryam MotallaeiYazd Cardiovascular Research Center, Non-communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Seyed Mostafa SeyedhosseiniYazd Cardiovascular Research Center, Non-communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveCoronary artery disease (CAD) remains a significant global health burden, characterized by the narrowing or blockage of coronary arteries. Treatment decisions are often guided by angiography-based scoring systems, such as the Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) and Gensini scores, although these require invasive procedures. This study explores the potential of electrocardiography (ECG) as a noninvasive diagnostic tool for predicting CAD severity, alongside traditional risk factors.

methodsThis retrospective cross-sectional study was conducted on 348 CAD patients who underwent coronary angiography. Demographic data, ECG findings, SYNTAX, and Gensini scores were collected. The association between ECG findings and demographic information with the severity of coronary artery stenosis, as assessed by SYNTAX and Gensini scores, was investigated using SPSS software, version 23.

resultsSignificant associations were observed between CAD severity and risk factors such as male gender, diabetes mellitus (DM), and smoking. Additionally, certain ECG indicators, including Q waves and ST depression (STD), showed significant correlations with CAD severity, particularly according to the Gensini score.

conclusionThis study underscores the utility of ECG and clinical factors in identifying severe CAD, offering cost-effective diagnostic alternatives to angiography. Integrating various parameters into a single score is crucial in clinical practice, providing a stronger diagnostic and prognostic tool without increasing costs. Further comprehensive studies are warranted to refine risk prediction models and improve CAD management strategies.

Indexed as

Coronary AngiographyCoronary Artery DiseaseElectrocardiographySeverity of Illness IndexAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsCoronary artery diseaseelectrocardiographyGensinirisk factorsSYNTAX

Identifiers

PMID39781616
PMCPMC11713963

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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.