Three Dimensions global radial strain and coronary artery disease severity

Background: The most prevalent cardiovascular disease is coronary artery disease (CAD). According to the European Society of Cardiology&#039;s (ESC) current classification, stable angina pectoris, also known as chronic coronary syndrome, is a common condition that can be disabling. Early-stage coronary artery disease detection may benefit from the use of certain novel noninvasive techniques. In our study, we assessed the relationship between coronary artery disease (CAD) severity and the 3-dimensional global radial strain (GRS) at rest among individuals with stable angina pectoris. Methods: This Prospective cohort work had been performed on 90 participants aging from 18 to 80 years old, with Stable angina pectoris. Participants had been subdivided into three groups: Group I (n=30): control group with normal coronary angiography and group II (n=60): patients group which subdivided according to Gensini score into two equal subgroups: IIa: simple lesion, low gensini score (Gensini score < 20) and group IIb: complex lesion, high gensini (Gensini score of ≥20). Results: LV end-diastolic volume , Left ventricular (LV) end-systolic volume, , global radial strain (GRS and LV ejection fraction (LVEF) had been significantly various across the three groups (P <0.0.05). GRS can significantly predict severity of CAD in CCS at cut-off ≤ 32 and 90.0% sensitivity, 73.33% specificity, 62.79% PPV and 93.62% NPV with accuracy of 78.89%. Conclusions: GRS significantly predict severity of CAD in CCS.

Authors

Institutions

Publication Details

Journal
Minia Journal of Medical Research
Published
2024-10-13
DOI
https://doi.org/10.21608/mjmr.2024.325142.1808
Primary Topic
Elasticity and Material Modeling
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Three Dimensions global radial strain and coronary artery disease severity

Khaled Sayed Mahmoud, Hossam Eldin M. Mahmoud, Mohamed A. Elsayed, Amr Mostafa Setohi Abdelhafez
Minia Journal of Medical Research
Elasticity and Material Modeling
article

Three Dimensions global radial strain and coronary artery disease severity

Khaled Sayed Mahmoud, Hossam Eldin M. Mahmoud, Mohamed A. Elsayed, Amr Mostafa Setohi Abdelhafez
article en

Abstract

Background: The most prevalent cardiovascular disease is coronary artery disease (CAD). According to the European Society of Cardiology&#039;s (ESC) current classification, stable angina pectoris, also known as chronic coronary syndrome, is a common condition that can be disabling. Early-stage coronary artery disease detection may benefit from the use of certain novel noninvasive techniques. In our study, we assessed the relationship between coronary artery disease (CAD) severity and the 3-dimensional global radial strain (GRS) at rest among individuals with stable angina pectoris. Methods: This Prospective cohort work had been performed on 90 participants aging from 18 to 80 years old, with Stable angina pectoris. Participants had been subdivided into three groups: Group I (n=30): control group with normal coronary angiography and group II (n=60): patients group which subdivided according to Gensini score into two equal subgroups: IIa: simple lesion, low gensini score (Gensini score < 20) and group IIb: complex lesion, high gensini (Gensini score of ≥20). Results: LV end-diastolic volume , Left ventricular (LV) end-systolic volume, , global radial strain (GRS and LV ejection fraction (LVEF) had been significantly various across the three groups (P <0.0.05). GRS can significantly predict severity of CAD in CCS at cut-off ≤ 32 and 90.0% sensitivity, 73.33% specificity, 62.79% PPV and 93.62% NPV with accuracy of 78.89%. Conclusions: GRS significantly predict severity of CAD in CCS.

Minia Journal of Medical ResearchVol. 0(0)
South Valley University (EG), Minia University (EG)
Good health and well-being
Openalex Percentile: Top 83%
Elasticity and Material Modeling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.