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Nevin Manimala Statistics

Exploring vectorcardiography: An extensive vectocardiogram analysis across age, sex, BMI, and cardiac conditions

J Electrocardiol. 2023 Dec 13;82:100-112. doi: 10.1016/j.jelectrocard.2023.12.004. Online ahead of print.

ABSTRACT

BACKGROUND: The vectocardiogram (VCG) offers a three-dimensional view of the heart’s electrical activity, yet many VCG parameters remain unexplored in diverse clinical contexts.

OBJECTIVES: This study aims to explore the relationships between various VCG parameters and specific patient characteristics.

METHODS: ECG signals from adults were transformed into VCGs utilizing the Kors matrix, yielding 315 parameters per patient from the P, QRS and T loops. Univariable analysis, circular statistics, and stepwise logistic regression were employed to examine the relationships between VCG parameters and factors such as age, sex, BMI, hypertension, echocardiographic ischemic heart disease (Echo-IHD), and left ventricular hypertrophy (Echo-LVH).

RESULTS: We included 664 adults and considered an alpha value of 0.05 and a power of 90%. The study revealed significant associations, such as age with P loop roundness index (RI) (OR = 3.825, 95% confidence interval [95%CI] = 2.079-7.04), male sex with QRS loop RI (OR = 6.08, 95%CI = 1.835-20.153), abnormal BMI with the T loop’s RI (OR = 0.544, 95%CI = 0.325-0.909), hypertension with the T loop planarity index (PI) (OR = 8.01, 95%CI = 2.134-30.117), Echo-IHD with QRS loop curvature at the 4/10th segment (OR = 7.58, 95%CI = 1.954-29.458), and Echo-LVH with the T loop lag-1/10 dihedral angle (OR = 10.3, 95%CI = 1.822-58.101). In the study, several additional VCG parameters demonstrated statistically significant, albeit smaller, associations with patient demographics and cardiovascular conditions.

CONCLUSIONS: The findings enhance our understanding of the intricate relationships between VCG parameters and patient characteristics, emphasizing the potential role of VCG analysis in assessing cardiovascular diseases. These insights may guide future research and clinical applications in cardiology.

PMID:38113771 | DOI:10.1016/j.jelectrocard.2023.12.004

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