A new method to analyze lung compliance when pressure-volume relationship is nonlinear.
Changes in dynamic lung compliance during inspiration and expiration cannot be modeled accurately with conventional algorithms. We developed a simple method to analyze pressure-volume (P/V) relationships under condition of nonlinearity (APVNL) and tested it in a lung model with known resistance and nonlinear P/V relationship. In addition, pulmonary mechanics in 22 infants, 11 of them with nonlinear P/V relationships, were analyzed with the new method. The findings were compared with those obtained by a recently introduced algorithm, multiple linear regression analysis (MLR) of the equation of motion. The APVNL method described the changing compliance (C) of the lung model accurately, whereas the MLR method underestimated C especially in the first half of the breath. In infants the MLR method gave highly variable, often nonphysiological C values in the beginning of a breath. In contrast, the coefficient of variability of measurements obtained by the APVNL method was significantly smaller (p < 0.02), and the indices of model-fit showed better agreement between calculated and observed pressure than for the MLR method (p < 0.02). We conclude that the APVNL method accurately describes nonlinear P/V relationships present during spontaneous breathing or mechanical ventilation. The method may be helpful in identifying and preventing pulmonary overdistention.
Nikischin
W
W
Division of Neonatology, Department of Pediatrics, University of Miami School of Medicine, Miami, Florida, USA.
Gerhardt
T
T
Everett
R
R
Bancalari
E
E
D000403:Airway Resistance / Q000502:physiology; D000465:Algorithms; D001997:Bronchopulmonary Dysplasia / Q000503:physiopathology; D006801:Humans; D006819:Hyaline Membrane Disease / Q000503:physiopathology; D007231:Infant, Newborn; D007234:Infant, Premature; D007235:Infant, Premature, Diseases / Q000503:physiopathology; D001239:Inhalation / Q000502:physiology; D016014:Linear Models; D008170:Lung Compliance / Q000502:physiology*; D008171:Lung Diseases / Q000517:prevention & control; D008954:Models, Biological; D017711:Nonlinear Dynamics; D011312:Pressure; D012119:Respiration; D012121:Respiration, Artificial; D015656:Respiratory Mechanics / Q000502:physiology*; D012680:Sensitivity and Specificity