DocumentCode :
591174
Title :
Can functional cardiac age be predicted from the ECG in a normal healthy population?
Author :
Starc, Vito ; Leban, M.A. ; Sinigoj, P. ; Vrhovec, M. ; Potocnik, N. ; Fernlund, E. ; Liuba, P. ; Schlegel, Todd T.
Author_Institution :
Fac. of Med., Univ. of Ljubljana, Ljubljana, Slovenia
fYear :
2012
fDate :
9-12 Sept. 2012
Firstpage :
101
Lastpage :
104
Abstract :
We hypothesized that in a normal healthy population changes in several ECG parameters together might reliably characterize the functional age of the heart. Data from 377 healthy subjects (209 men, 168 women, aged 4 to 75 years) were included in the study. In all subjects, ECG recordings (resting 5-minute 12-lead high fidelity ECG) were evaluated via custom software programs to calculate up to 120 different conventional and advanced ECG parameters. Using factor analysis, those 5 parameters that exhibited the highest linear correlations with age and that were mutually the least correlated were evaluated by multiple linear regression analysis to predict the functional electrical age of the heart. Ignoring small differences between males and females, functional electrical age was best predicted (R2 of 0.76, P <; 0.001) by multiple linear regression analysis incorporating the RR-interval normalized high frequency variability of RRV; the RR-interval normalized value of a QT variability parameter called QTcor; the mean high frequency QRS (150-250 Hz) amplitude; the mean ST segment level at the J point; and the body mass index. In apparently healthy subjects, functional cardiac age can be estimated by multiple linear regression analysis of mostly advanced ECG parameters.
Keywords :
electrocardiography; medical signal processing; regression analysis; ECG recordings; QTcor; RR-interval normalized high frequency variability; advanced ECG parameters; body mass index; custom software programs; factor analysis; functional cardiac age; functional electrical age; heart functional age; linear correlations; mean ST segment level; multiple linear regression analysis; normal healthy population; Correlation; Electrocardiography; Heart; Indexes; Linear regression; Sociology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing in Cardiology (CinC), 2012
Conference_Location :
Krakow
ISSN :
2325-8861
Print_ISBN :
978-1-4673-2076-4
Type :
conf
Filename :
6420340
Link To Document :
بازگشت