Assessment of arterial baroreflex sensitivity by different computational analyses of pressure wave signals alone. (April 2019)

• Record Type: Journal Article
• Authors: Papaioannou, Theodore G.; Fasoulis, Romanos; Toumpaniaris, Petros; Tsioufis, Constantinos; Dilaveris, Polychronis; Soulis, Dimitrios; Koutsouris, Dimitrios; Tousoulis, Dimitrios
• Is Part Of: Computer methods and programs in biomedicine. Volume 172(2019)
• Page Start: 25
• Page End: 34
• Publication Date: 2019-04
• Subjects: Baroreceptors -- Arteries -- Pulse wave analysis -- Hemodynamics -- Blood pressure; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2019.02.002
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: BRS estimation by proper analysis of pressure wave signals alone is feasible and accurate, compared to BRS estimation using ECG derived RR interval time series. Frequency based methods (i.e. spectral analysis) provides the most accurate estimations of BRS compared to time-domain pulse wave analysis. For spectral methods, any algorithm for pulse interval calculation is sufficient, as all show excellent agreement with the respective RR-intervals determined by ECG time series. The spectral method yields a robust and accurate BRS estimation (by analysis of the arterial pressure waveform alone), provided that the Lomb-Scargle method is used. Abstract: Background and objective: Baroreflex sensitivity (BRS) is an important indicator of the functionality of the arterial baroreceptors, and its assessment may have major research and clinical implications. An important requirement for its quantification is the continuous recording of electrocardiography (ECG) signal, so as to extract the RR interval, in parallel with continuous beat-to-beat blood pressure recording. We aimed to accurately calculate the RR Interval from pressure wave recordings per se, namely, the Pulse Interval (PI) using various arterial pulse wave analysis algorithms and to evaluate the precision and accuracy of BRS values calculated with the PI compared to BRS values calculated with the RR Interval. Methods: We analyzed the open access data of the Eurobavar study, which contains a set of ECG and arterial blood pressure (BP) wave signals recorded at 11 European centers. Pressure waveforms were continuously recorded by the Finapres apparatus which uses a finger cuff. The cuff pressure around the finger is dynamically adjusted by a servo-system to equal intra-arterial pressure, thus allowing the continuous recording of beat-to-beat BP waves. RR Interval was calculated from the ECG, whereas, PI was extracted from the arterial pulse waveforms, using 4 different methods (minimum, maximum, maximum 1st derivative and intersecting tangents method). BRS values were estimated by time domain and frequency domain methods. In order to compare agreement, accuracy, precision, variability, and the association between the reference BRS using the RR Interval and the BRS values using PI, standard statistical methods (i.e. intraclass correlation coefficients, RMSE, regression analysis) and Bland-Altman methods were performed. Results: We found that analysis of pressure waves alone by frequency-based (i.e. spectral) methods, provides the most accurate results of BRS estimation compared to time-domain methods (ICC > 0.9, R > 0.9, RMSE > 0.8 ms/mmHg). Concerning the spectral method, any algorithm for PI calculation is sufficient, as all show excellent agreement with the respective RR-intervals determined by ECG time series. Only the intersecting tangents and the maximum 1st derivative methods for PI calculation produce the most accurate results in time domain BRS estimation. Conclusion: BRS estimation by proper analysis of pressure wave signals alone is feasible and accurate. Further studies are needed to investigate the clinical validity and relevance of the different BRS estimations in diagnostic, prognostic and therapeutic levels.