title: Model-based optimal PEEP in mechanically ventilated ARDS patients in the intensive care unit.
abstract: BACKGROUND
  The optimal level of positive end-expiratory pressure (PEEP) is still widely debated in treating acute respiratory distress syndrome (ARDS) patients. Current methods of selecting PEEP only provide a range of values and do not provide unique patient-specific solutions. Model-based methods offer a novel way of using non-invasive pressure-volume (PV) measurements to estimate patient recruitability. This paper examines the clinical viability of such models in pilot clinical trials to assist therapy, optimise patient-specific PEEP, assess the disease state and response over time.
  
  
  METHODS
  Ten patients with acute lung injury or ARDS underwent incremental PEEP recruitment manoeuvres. PV data was measured at increments of 5 cmH2O and fitted to the recruitment model. Inspiratory and expiratory breath holds were performed to measure airway resistance and auto-PEEP. Three model-based metrics are used to optimise PEEP based on opening pressures, closing pressures and net recruitment. ARDS status was assessed by model parameters capturing recruitment and compliance.
  
  
  RESULTS
  Median model fitting error across all patients for inflation and deflation was 2.8% and 1.02% respectively with all patients experiencing auto-PEEP. In all three metrics' cases, model-based optimal PEEP was higher than clinically selected PEEP. Two patients underwent multiple recruitment manoeuvres over time and model metrics reflected and tracked the state or their ARDS.
  
  
  CONCLUSIONS
  For ARDS patients, the model-based method presented in this paper provides a unique, non-invasive method to select optimal patient-specific PEEP. In addition, the model has the capability to assess disease state over time using these same models and methods.
authors.affiliation: Department of Mechanical Engineering, College of Engineering, University of Canterbury, Private Bag 8140, Christchurch, New Zealand. asu33@uclive.ac.nz
authors.forename: Ashwath
authors.initials: A
authors.lastname: Sundaresan
authors.forename: J Geoffrey
authors.initials: JG
authors.lastname: Chase
authors.forename: Geoffrey M
authors.initials: GM
authors.lastname: Shaw
authors.forename: Yeong Shiong
authors.initials: YS
authors.lastname: Chiew
authors.forename: Thomas
authors.initials: T
authors.lastname: Desaive
mesh_terms: D055371:Acute Lung Injury; D000403:Airway Resistance; D006801:Humans; D007362:Intensive Care Units; D016014:Linear Models; D010865:Pilot Projects; D011175:Positive-Pressure Respiration / Q000379:methods*; D012119:Respiration; D012128:Respiratory Distress Syndrome / Q000628:therapy*; D012189:Retrospective Studies; D013990:Tidal Volume; D012122:Ventilators, Mechanical