Cardiovascular risk analysis by means of pulse morphology and clustering methodologies

Computer Methods and Programs in Biomedicine

Volumn 117, Issue 2, 2014, Pages 257-266

  Almeida, Vânia G ^a   Borba, J ^a   Pereira, H Catarina ^a,b   Pereira, Tânia ^a   Correia, Carlos ^a   Pêgo, Mariano ^c   Cardoso, João ^a  

^a UNIVERSITY OF COIMBRA   (Portugal)

^b Intelligent Sensing Anywhere ^*  (Portugal)

^c CENTRO HOSPITALAR E UNIVERSITÁRIO DE COIMBRA   (Portugal)

Author keywords

Arterial stiffness; Clustering analysis; Pulse wave analysis; Risk scores

Indexed keywords

ALGORITHMS; CLUSTER ANALYSIS; MAXIMUM PRINCIPLE; RISK ASSESSMENT;

ARTERIAL STIFFNESS; BIOCHEMICAL PARAMETERS; CARDIOVASCULAR RISK; CLINICAL PRACTICES; CLUSTERING ANALYSIS; EXPECTATION MAXIMIZATION; PULSE WAVE ANALYSIS; RISK SCORE;

RISK ANALYSIS;

ANTIHYPERTENSIVE AGENT; CHOLESTEROL; HIGH DENSITY LIPOPROTEIN CHOLESTEROL; INSULIN; ORAL ANTIDIABETIC AGENT; TRIACYLGLYCEROL;

ADULT; AGED; ARTERIAL PRESSURE WAVEFORM; ARTICLE; ASSESSING CARDIOVASCULAR RISK USING SCOTTISH INTERCOLLEGIATE GUIDELINES NETWORK SCORE; AUGMENTATION INDEX; BLOOD VESSEL PARAMETERS; CARDIOVASCULAR DISEASE; CARDIOVASCULAR RISK; CHEMICAL ANALYSIS; CHOLESTEROL BLOOD LEVEL; CLINICAL ARTICLE; CLINICAL PRACTICE; CLUSTER ANALYSIS; CONTROLLED STUDY; DIABETES MELLITUS; DIASTOLIC BLOOD PRESSURE; EXPECTATION MAXIMIZATION; FEMALE; FRAMINGHAM RISK SCORE; HEART LEFT VENTRICLE EJECTION TIME; HUMAN; HYPERTENSION; MALE; MIDDLE AGED; PROCAM SCORE; PULSE WAVE; REFLECTED WAVE TRANSIT TIME; REFLECTION WAVE AMPLITUDE; RISK ASSESSMENT; SCORING SYSTEM; STATISTICAL PARAMETERS; SYSTEMATIC CORONARY RISK EVALUATION SCORE; SYSTOLIC BLOOD PRESSURE; SYSTOLIC WAVE TRANSIT TIME; TRIACYLGLYCEROL BLOOD LEVEL; ATHEROSCLEROSIS; BLOOD PRESSURE MEASUREMENT; COMPUTER ASSISTED DIAGNOSIS; DEVICES; INCIDENCE; PORTUGAL; PROCEDURES; PROGNOSIS; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICS AND NUMERICAL DATA;

ATHEROSCLEROSIS; BLOOD PRESSURE DETERMINATION; CLUSTER ANALYSIS; DIAGNOSIS, COMPUTER-ASSISTED; FEMALE; HUMANS; INCIDENCE; MALE; MIDDLE AGED; PORTUGAL; PROGNOSIS; PULSE WAVE ANALYSIS; REPRODUCIBILITY OF RESULTS; RISK ASSESSMENT; SENSITIVITY AND SPECIFICITY;

EID: 84908031677     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2014.06.010     Document Type: Article

References (33)

1. W.H.Organization The Global Burden of Disease: 2004 Update 2004, World Health Organization.
2. Kavey R.E.W., Daniels S.R., Lauer R.M., Atkins D.L.A., Hayman L.L., Taubert K. American heart association guidelines for primary prevention of atherosclerotic cardiovascular disease beginning in childhood. Circulation 2003, 107(11):1562-1566.
3. Perk J., De Backer G., Gohlke H., Graham I., Reiner Z., Verschuren M., Albus C., Benlian P., Boysen G., Cifkova R., Deaton C., Ebrahim S., Fisher M., Germano G., Hobbs R., Hoes A., Karadeniz S., Mezzani A., Prescott E., Ryden L., Scherer M., Syvanne M., Scholte op Reimer W.J., Vrints C., Wood D., Zamorano J.L., Zannad F. European guidelines on cardiovascular disease prevention in clinical practice (version 2012). The fifth joint task force of the European society of cardiology and other societies on cardiovascular disease prevention in clinical practice (constituted by representatives of nine societies and by invited experts). Developed with the special contribution of the European association for cardiovascular prevention & rehabilitation (EACPR). Eur. Heart J. 2012, 33(13):1635-1701.
4. Beswick A., Brindle P. Risk scoring in the assessment of cardiovascular risk. Curr. Opin. Lipidol. 2006, 17:375-386.
5. Whitfield M.D., Gillett M., Holmes M., Ogden E. Predicting the impact of population level risk reduction in cardio-vascular disease and stroke on acute hospital admission rates over a 5 year period - a pilot study. Public Health 2006, 120(12):1140-1148.
6. Cooney M.T., Dudina A.L., Graham I.M. Value and limitations of existing scores for the assessment of cardiovascular risk: a review for clinicians. J. Am. Coll. Cardiol. 2009, 54(14):1209-1227.
7. Siontis G.C.M., Tzoulaki I., Siontis K.C., Ioannidis J.P.A. Comparisons of established risk prediction models for cardiovascular disease: systematic review. BMJ 2012, 344. 10.1136/bmj.e3318.
8. Haq I.U., Ramsay L.E., Yeo W., Jackson P.R., Wallis E.J. Is the Framingham risk function valid for northern European populations? A comparison of methods for estimating absolute coronary risk in high risk men. Heart Vessels 1999, 81:40-46.
9. London G.M., Guerin A.P. Influence of arterial pulse and reflected waves on blood pressure and cardiac function. Am. Heart J. 1999, 138(3):220-223.
10. Cameron J.D., McGrath B.P., Dart A.M. Use of radial artery applanation tonometry and a generalized transfer function to determine aortic pressure augmentation in subjects with treated hypertension. J. Am. Coll. Cardiol. 1998, 32(5):1214-1220.
11. Laurent S., Cockcroft J., Bortel L.V., Boutouyrie P., Giannattasio C., Hayoz D., Pannier B., Vlachopoulos C., Wilkinson I., Struijker-Boudier H. Expert consensus document on arterial stiffness methodological issues and clinical applications. Eur. Heart J. 2006, 27(21):2588-2605.
12. Ikonomidis I., Tzortzis S., Papaioannou T., Protogerou A., Stamatelopoulos K., Papamichael C., Zakopoulos N., Lekakis J. Incremental value of arterial wave reflections in the determination of left ventricular diastolic dysfunction in untreated patients with essential hypertension. J. Hum. Hypertens. 2008, 22(10):687-698.
13. Avolio A.P., Butlin M., Walsh A. Arterial blood pressure measurement and pulse wave analysis - their role in enhancing cardiovascular assessment. Physiol. Meas. 2010, 31(1):R1-R47.
14. Hametner B., Wassertheurer S., Kropf J., Mayer C., Holzinger A., Eber B., Weber T. Wave reflection quantification based on pressure waveforms alone - methods, comparison, and clinical covariates. Comput. Methods Programs Biomed. 2013, 109(3):250-259.
15. Almeida V., Vieira J., Santos P., Pereira T., Pereira H., Correia C., Pego M., Cardoso J. Machine learning techniques for arterial pressure waveform analysis. J. Personal. Med. 2013, 3(2):82-101.
16. Yoo I., Alafaireet P., Marinov M., Pena Hernandez K., Gopidi R., Chang J., Hua L. Data mining in healthcare and biomedicine: a survey of the literature. J. Med. Syst. 2012, 36(4):2431-2448.
17. Wagholikar K.B., Sundararajan V., Deshpande A.W. Modeling paradigms for medical diagnostic decision support: a survey and future directions. J. Med. Syst. 2012, 36(5):3029-3049.
18. Tsipouras M.G., Exarchos T.P., Fotiadis D.I., Kotsia A., Vakalis K., Naka K.K., Michalis L.K. Automated diagnosis of coronary artery disease based on data mining and fuzzy modeling. IEEE Trans. Inform. Technol. Biomed. 2008, 12(4):447-458.
19. Paredes S., Rocha T., de Carvalho P., Henriques J., Harris M., Morais J. Long term cardiovascular risk models' combination. Comput. Methods Program Biomed. 2011, 101(3):231-242.
20. Jovic A., Bogunovic N. Electrocardiogram analysis using a combination of statistical, geometric, and nonlinear heart rate variability features. Artif. Intell. Med. 2011, 51:175-186.
21. Kuncheva L.I., Bezdek J.C., Duin R.P. Decision templates for multiple classifier fusion: an experimental comparison. Pattern Recogn. Lett. 2001, 34(2):299-314.
22. Ruta D., Gabrys B. An overview of classifier fusion methods. Comput. Inform. Syst. 2000, 7:1-10.
23. Han J., Kamber M. Data Mining. Concepts and Techniques 2006, Elsevier, San Francisco, CA.
24. Melnykov V., Shen G. Clustering through empirical likelihood ratio. Comput. Stat. Data Anal. 2013, 62:1-10.
25. Shah A.S., Dolan L.M., Gao Z., Kimball T.R., Urbina E.M. Clustering of risk factors: a simple method of detecting cardiovascular disease in youth. Pediatrics 2011, 127(2):e312-e318.
26. Haseena H.H., Mathew A.T., Paul J.K. Fuzzy clustered probabilistic and multi layered feed forward neural networks for electrocardiogram arrhythmia classification. J. Med. Syst. 2011, 35(2):179-188.
27. Namayanja J., Janeja V.P. An assessment of patient behavior over time-periods: a case study of managing type 2 diabetes through blood glucose readings and insulin doses. J. Med. Syst. 2012, 36(S1):65-80.
28. Almeida V.G., Pereira H.C., Pereira T., Figueiras E., Borges E., Cardoso J.M.R., Correia C. Piezoelectric probe for pressure waveform estimation in flexible tubes and its applications to the cardiovascular system. Sens. Actuators A 2011, 169:217-226.
29. Almeida V., Pereira H., Pereira T., Ferreira L., Correia C., Cardoso J. Assessment of the pulse wave variability for a new non-invasive device. The International Conference on Health Informatics, IFMBE Proceedings, vol. 42 2014, 240-243. Springer International Publishing, Vilamoura, Portugal. Y.-T. Zhang (Ed.).
30. Frimodt-Moller M., Nielsen A.H., Kamper A.L., Strandgaard S. Reproducibility of pulse-wave analysis and pulse-wave velocity determination in chronic kidney disease. Nephrol. Dial. Transpl. 2008, 23(2):594-600.
31. Murgo J., Westerhof N., Giolma J.P., Altobelli S. Aortic input impedance in normal man: relationship to pressure wave forms, circulation. Circulation 1980, 62:105-116.
32. Versteylen M., Joosen I., Shaw L., Narula J., Hofstra L. Comparison of Framingham, PROCAM, SCORE, and diamond forester to predict coronary atherosclerosis and cardiovascular events. J. Nucl. Cardiol. 2011, 18(5):904-911.
33. Assign score website, 2014, http://assign-score.com/.