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Published on: January 15, 2022
Time-domain heart rate dynamics in the prognosis of progressive atherosclerosis
Rahul Kumar1, Yogender Aggarwal1, Vinod Kumar Nigam1
1Department of Bioengineering and Biotechnology, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India.
Insights
High-fat diets worsen atherosclerosis, leading to autonomic dysfunction and reduced heart rate variability (HRV). This study found a negative correlation between HRV and atherosclerosis markers, with a support vector machine (SVM) model accurately predicting disease severity.
Area of Science:
- Cardiovascular Physiology
- Biomedical Engineering
- Autonomic Nervous System Research
Background:
- High-fat diets (HFD) and lifestyle changes contribute to atherosclerosis, a condition linked to cardiovascular diseases and autonomic dysfunction.
- Autonomic dysfunction, characterized by altered heart rate variability (HRV), is increasingly recognized as a consequence of atherosclerosis.
Purpose of the Study:
- To investigate the correlation between autonomic activity, assessed via HRV, and key lipid and atherosclerosis markers.
- To develop and evaluate a support vector machine (SVM) based model for predicting the severity of atherosclerosis.
Main Methods:
- Weekly measurements of Lead-II electrocardiograms and blood markers over nine weeks in control and experimental groups.
- Derivation of time-domain HRV parameters and correlation analysis with lipid and atherosclerosis markers.
- Utilizing statistically significant HRV parameters as features for an SVM model to predict atherosclerosis severity.
Main Results:
- Progressive atherosclerosis severity, induced by HFD, was associated with reduced time-domain HRV parameters.
- A significant negative correlation was observed between HRV parameters and lipid/atherosclerosis markers.
- The SVM model achieved prediction accuracies ranging from 86.58% to 98.71% for atherosclerosis severity.
Conclusions:
- Atherosclerosis progression is linked to autonomic dysfunction and diminished HRV.
- Autonomic parameters, particularly vagal activity, may play a crucial role in the prognosis of atherosclerosis.
- The developed SVM model demonstrates high accuracy in predicting atherosclerosis severity.
Background And Aim:
The regular uptake of a high-fat diet (HFD) with changing lifestyle causes atherosclerosis leading to cardiovascular diseases and autonomic dysfunction. Therefore, the current study aimed to investigate the correlation of autonomic activity to lipid and atherosclerosis markers. Further, the study proposes a support vector machine (SVM) based model in the prediction of atherosclerosis severity.
Methods And Results:
The Lead-II electrocardiogram and blood markers were measured from both the control and the experiment subjects each week for nine consecutive weeks. The time-domain heart rate variability (HRV) parameters were derived, and the significance level was tested using a one-way Analysis of Variance. The correlation analysis was performed to determine the relation between autonomic parameters and lipid and atherosclerosis markers. The statistically significant time-domain values were used as features of the SVM. The observed results demonstrated the reduced time domain HRV parameters with the increase in lipid and atherosclerosis index markers with the progressive atherosclerosis severity. The correlation analysis revealed a negative association between time-domain HRV parameters with lipid and atherosclerosis parameters. The percentage accuracy increases from 86.58% to 98.71% with the increase in atherosclerosis severity with regular consumption of HFD.
Conclusions:
Atherosclerosis causes autonomic dysfunction with reduced HRV. The negative correlation between autonomic parameters and lipid profile and atherosclerosis indexes marker revealed the potential role of vagal activity in the prognosis of atherosclerosis progression. The support vector machine presented a respectable accuracy in the prediction of atherosclerosis severity from the control group.
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