Title
Cardiovascular risk analysis by means of pulse morphology and clustering methodologies.
Abstract
The purpose of this study was the development of a clustering methodology to deal with arterial pressure waveform (APW) parameters to be used in the cardiovascular risk assessment. One hundred sixteen subjects were monitored and divided into two groups. The first one (23 hypertensive subjects) was analyzed using APW and biochemical parameters, while the remaining 93 healthy subjects were only evaluated through APW parameters. The expectation maximization (EM) and k-means algorithms were used in the cluster analysis, and the risk scores (the Framingham Risk Score (FRS), the Systematic COronary Risk Evaluation (SCORE) project, the Assessing cardiovascular risk using Scottish Intercollegiate Guidelines Network (ASSIGN) and the PROspective Cardiovascular munster (PROCAM)), commonly used in clinical practice were selected to the cluster risk validation. The result from the clustering risk analysis showed a very significant correlation with ASSIGN (r = 0.582, p < 0.01) and a significant correlation with FRS (r = 0.458, p < 0.05). The results from the comparison of both groups also allowed to identify the cluster with higher cardiovascular risk in the healthy group. These results give new insights to explore this methodology in future scoring trials. (C) 2014 Elsevier Ireland Ltd. All rights reserved.
Year
DOI
Venue
2014
10.1016/j.cmpb.2014.06.010
Computer Methods and Programs in Biomedicine
Keywords
Field
DocType
Arterial stiffness,Pulse wave analysis,Risk scores,Clustering analysis
Data mining,Risk evaluation,Computer science,Risk assessment,Blood pressure,Cluster analysis,Framingham Risk Score,Internal medicine,Risk analysis (business),Cardiology,Arterial stiffness,Correlation,Statistics
Journal
Volume
Issue
ISSN
117
2
0169-2607
Citations 
PageRank 
References 
1
0.35
11
Authors
7
Name
Order
Citations
PageRank
Vânia G. Almeida131.22
J. Borba221.05
Helena Catarina Pereira396.17
Tânia Pereira4248.61
A. Correia5198.62
Mariano Pêgo610.35
João Cardoso7107.92