Thomas P Olson1, Bruce D Johnson. 1. Department of Internal Medicine, Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN 55905, United States.
Abstract
BACKGROUND: This study examined the validity of a novel software application to quantify measures of periodic breathing rest (PB) and oscillatory ventilation during exercise (EOV) in heart failure patients (HF). METHODS: Eleven male HF patients (age=53±8yrs, ejection fraction=17±4, New York Heart Association Class=III(7)/IV(4)) were recruited. Ventilation and gas exchange were collected breath-by-breath. Amplitude and period of oscillations in ventilation (V˙E), tidal volume (VT), end-tidal carbon dioxide [Formula: see text] , and oxygen consumption [Formula: see text] were measured manually (MAN) and using novel software which included a peak detection algorithm (PK), sine wave fitting algorithm (SINE), and Fourier analysis (FOUR). RESULTS: During PB, there were no differences between MAN and PK for amplitude of V˙E, VT, [Formula: see text] , or [Formula: see text] . Similarly, there were no differences between MAN and SINE for amplitude of V˙E or VT although [Formula: see text] and [Formula: see text] were lower with SINE (p<0.05). In contrast, the PK demonstrated significantly shorter periods for V˙E, VT, [Formula: see text] , and [Formula: see text] compared to MAN (p<0.05) whereas there were no differences in periods of oscillations between MAN and SINE or FOUR for all variables. During EOV, there were no differences between MAN and PK for amplitude of V˙E, VT, [Formula: see text] , and [Formula: see text] . SINE demonstrated significantly lower amplitudes for VT, [Formula: see text] , and [Formula: see text] (p<0.05) although V˙E was not different. PK demonstrated shorter periods for all variables (p<0.05) whereas there were no differences between MAN and SINE or FOUR for all variables. CONCLUSION: These data suggest PK consistently captures amplitudes while underestimating period. In contrast, SINE and FOUR consistently capture period although SINE underestimates amplitude. Thus, an optimal algorithm for the quantification of PB and/or EOV in patients with HF might combine multiple analysis methods.
BACKGROUND: This study examined the validity of a novel software application to quantify measures of periodic breathing rest (PB) and oscillatory ventilation during exercise (EOV) in heart failurepatients (HF). METHODS: Eleven male HF patients (age=53±8yrs, ejection fraction=17±4, New York Heart Association Class=III(7)/IV(4)) were recruited. Ventilation and gas exchange were collected breath-by-breath. Amplitude and period of oscillations in ventilation (V˙E), tidal volume (VT), end-tidal carbon dioxide [Formula: see text] , and oxygen consumption [Formula: see text] were measured manually (MAN) and using novel software which included a peak detection algorithm (PK), sine wave fitting algorithm (SINE), and Fourier analysis (FOUR). RESULTS: During PB, there were no differences between MAN and PK for amplitude of V˙E, VT, [Formula: see text] , or [Formula: see text] . Similarly, there were no differences between MAN and SINE for amplitude of V˙E or VT although [Formula: see text] and [Formula: see text] were lower with SINE (p<0.05). In contrast, the PK demonstrated significantly shorter periods for V˙E, VT, [Formula: see text] , and [Formula: see text] compared to MAN (p<0.05) whereas there were no differences in periods of oscillations between MAN and SINE or FOUR for all variables. During EOV, there were no differences between MAN and PK for amplitude of V˙E, VT, [Formula: see text] , and [Formula: see text] . SINE demonstrated significantly lower amplitudes for VT, [Formula: see text] , and [Formula: see text] (p<0.05) although V˙E was not different. PK demonstrated shorter periods for all variables (p<0.05) whereas there were no differences between MAN and SINE or FOUR for all variables. CONCLUSION: These data suggest PK consistently captures amplitudes while underestimating period. In contrast, SINE and FOUR consistently capture period although SINE underestimates amplitude. Thus, an optimal algorithm for the quantification of PB and/or EOV in patients with HF might combine multiple analysis methods.
Authors: Clinton A Brawner; Jonathan K Ehrman; Jonathan Myers; Paul Chase; Baruch Vainshelboim; Shadi Farha; Matthew A Saval; Rita McGuire; Bunny Pozehl; Steven J Keteyian Journal: Med Sci Sports Exerc Date: 2018-02 Impact factor: 5.411
Authors: Renata Rodrigues Teixeira de Castro; Sabrina Pedrosa Lima; Allan Robson Kluser Sales; Antonio Claudio Lucas da Nóbrega Journal: Arq Bras Cardiol Date: 2017-09 Impact factor: 2.000