title: Pressure-time curve predicts minimally injurious ventilatory strategy in an isolated rat lung model.
abstract: BACKGROUND
  We tested the hypothesis that the pressure-time (P-t) curve during constant flow ventilation can be used to set a noninjurious ventilatory strategy.
  
  
  METHODS
  In an isolated, nonperfused, lavaged model of acute lung injury, tidal volume and positive end-expiratory pressure were set to obtain: (1) a straight P-t curve (constant compliance, minimal stress); (2) a downward concavity in the P-t curve (increasing compliance, low volume stress); and (3) an upward concavity in the P-t curve (decreasing compliance, high volume stress). The P-t curve was fitted to: P = a. tb +c, where b describes the shape of the curve, b = 1 describes a straight P-t curve, b < 1 describes a downward concavity, and b > 1 describes an upward concavity. After 3 h, lungs were analyzed for histologic evidence of pulmonary damage and lavage concentration of inflammatory mediators. Ventilator-induced lung injury occurred when injury score and cytokine concentrations in the ventilated lungs were higher than those in 10 isolated lavaged rats kept statically inflated for 3 h with an airway pressure of 4 cm H2O.
  
  
  RESULTS
  The threshold value for coefficient b that discriminated best between lungs with and without histologic and inflammatory evidence of ventilator-induced lung injury (receiver-operating characteristic curve) ranged between 0.90-1.10. For such threshold values, the sensitivity of coefficient b to identify noninjurious ventilatory strategy was 1.00. A significant relation (P < 0.001) between values of coefficient b and injury score, interleukin-6, and macrophage inflammatory protein-2 was found.
  
  
  CONCLUSIONS
  The predictive power of coefficient b to predict noninjurious ventilatory strategy in a model of acute lung injury is high.
authors.affiliation: Division of Respiratory Medicine, Samuel Lunenfeld Research Institute, and Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada. mranieri@teseo.it
authors.forename: V M
authors.initials: VM
authors.lastname: Ranieri
authors.forename: H
authors.initials: H
authors.lastname: Zhang
authors.forename: L
authors.initials: L
authors.lastname: Mascia
authors.forename: M
authors.initials: M
authors.lastname: Aubin
authors.forename: C Y
authors.initials: CY
authors.lastname: Lin
authors.forename: J B
authors.initials: JB
authors.lastname: Mullen
authors.forename: S
authors.initials: S
authors.lastname: Grasso
authors.forename: M
authors.initials: M
authors.lastname: Binnie
authors.forename: G A
authors.initials: GA
authors.lastname: Volgyesi
authors.forename: P
authors.initials: P
authors.lastname: Eng
authors.forename: A S
authors.initials: AS
authors.lastname: Slutsky
mesh_terms: D000818:Animals; D016207:Cytokines / Q000378:metabolism; D004195:Disease Models, Animal; D008168:Lung / Q000378:metabolism; D008297:Male; D011175:Positive-Pressure Respiration / Q000009:adverse effects / Q000379:methods*; D011237:Predictive Value of Tests; D012372:ROC Curve; D051381:Rats; D017207:Rats, Sprague-Dawley; D012128:Respiratory Distress Syndrome / Q000209:etiology* / Q000378:metabolism / Q000517:prevention & control*; D013990:Tidal Volume; D012122:Ventilators, Mechanical / Q000009:adverse effects
chemical_list: D016207:Cytokines