Time-frequency analysis of cardiac and respiratory parameters for the prediction of ventilator weaning.
Mechanical ventilators are used to provide life support in patients with respiratory failure. Assessing autonomic control during the ventilator weaning provides information about physiopathological imbalances. Autonomic parameters can be derived and used to predict success in discontinuing from the mechanical support. Time-frequency analysis is used to derive cardiac and respiratory parameters, as well as their evolution in time, during ventilator weaning in 130 patients. Statistically significant differences have been observed in autonomic parameters between patients who are considered ready for spontaneous breathing and patients who are not. A classification based on respiratory frequency, heart rate and heart rate variability spectral components has been proposed and has been able to correctly classify more than 80% of the cases.
Orini
Michele
M
CIBER de Bioingenierá, Biomateriales y Nanomedicina from ISCIII, Spain. michele@unizar.es
Giraldo
Beatriz F
BF
Bailón
Raquel
R
Vallverdu
Montserrat
M
Mainardi
Luca
L
Benito
Salvador
S
Díaz
Ivan
I
Caminal
Pere
P
D016208:Databases, Factual; D004562:Electrocardiography / Q000379:methods; D001330:Electronic Data Processing; D006801:Humans; D015233:Models, Statistical; D012119:Respiration; D012121:Respiration, Artificial; D012131:Respiratory Insufficiency / Q000628:therapy*; D015656:Respiratory Mechanics; D012132:Respiratory Muscles / Q000503:physiopathology*; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors; D015300:Ventilator Weaning; D012122:Ventilators, Mechanical; D014939:Work of Breathing