Med Biol Eng Comput - Discrimination power of long-term heart rate variability measures for chronic heart failure detection.

Tópicos

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Resumo

The aim of this study was to investigate the discrimination power of standard long-term heart rate variability (HRV) measures for the diagnosis of chronic heart failure (CHF). The authors performed a retrospective analysis on four public Holter databases, analyzing the data of 72 normal subjects and 44 patients suffering from CHF. To assess the discrimination power of HRV measures, an exhaustive search of all possible combinations of HRV measures was adopted and classifiers based on Classification and Regression Tree (CART) method was developed, which is a non-parametric statistical technique. It was found that the best combination of features is: Total spectral power of all NN intervals up to 0.4 Hz (TOTPWR), square root of the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD) and standard deviation of the averages of NN intervals in all 5-min segments of a 24-h recording (SDANN). The classifiers based on this combination achieved a specificity rate and a sensitivity rate of 100.00 and 89.74%, respectively. The results are comparable with other similar studies, but the method used is particularly valuable because it provides an easy to understand description of classification procedures, in terms of intelligible "if ? then ?" rules. Finally, the rules obtained by CART are consistent with previous clinical studies.

Resumo Limpo

aim studi investig discrimin power standard longterm heart rate variabl hrv measur diagnosi chronic heart failur chf author perform retrospect analysi four public holter databas analyz data normal subject patient suffer chf assess discrimin power hrv measur exhaust search possibl combin hrv measur adopt classifi base classif regress tree cart method develop nonparametr statist techniqu found best combin featur total spectral power nn interv hz totpwr squar root mean sum squar differ adjac nn interv rmssd standard deviat averag nn interv min segment h record sdann classifi base combin achiev specif rate sensit rate respect result compar similar studi method use particular valuabl provid easi understand descript classif procedur term intellig rule final rule obtain cart consist previous clinic studi

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