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A milestone in prediction of the coronary artery dimensions from the multiple linear regression equation. | LitMetric

A milestone in prediction of the coronary artery dimensions from the multiple linear regression equation.

Indian Heart J

Department of Cardiology, Care Hospital, Banjara Hills, Hyderabad, Hyderabad, 500034, India. Electronic address:

Published: May 2020

Bachground /aim: Coronary artery imaging is one of the most commonly used diagnostic methods. We aimed to investigate whether there is a correlation between left main coronary artery (LMCA), left anterior descending artery (LAD) and left circumflex artery (LCx) artery dimensions in normal cases and a possibility to express the coronary dimensions by multiple linear equations.

Materials And Methods: Images of coronary angiograms of 925 normal cases selected from 3855 cases made up the study population (515 men and 410 women; age range, 30-75 years). The mean age of the patients was 55.50 ± 6.49 years. The mean body mass index was 24.79 ± 1.45 kg/m (range, 31.30-21.26 kg/m). The mean dimensions of LMCA, LAD and LCx were 4.18 ± 0.65 mm, 3.22 ± 0.63 mm and 3.07 ± 0.65 mm, respectively. Correlation between LMCA, LAD and LCx diameters was investigated. Multiple linear regression analysis was used to develop a model to elucidate the relationship between LMCA, LAD and LCx diameters.

Results: There was a strong correlation between LMCA dimensions and LAD and LCx dimensions (r = 0.526**, p < 0.001* and r = 0.469**, p < 0.001*, respectively). The positive correlation indicated that a regression analysis can be carried out by incorporating the measurements. Coronary artery dimensions were gender specific.

Conclusion: The present study explored the possibility of explaining the relationship with the LMCA and its branches by multiple linear equations, which may then be used to estimate the reference diameter of a stenosed coronary artery when the other two arteries are normal.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6890961PMC
http://dx.doi.org/10.1016/j.ihj.2019.07.005DOI Listing

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