title: Model-based PEEP optimisation in mechanical ventilation.
abstract: BACKGROUND
  Acute Respiratory Distress Syndrome (ARDS) patients require mechanical ventilation (MV) for breathing support. Patient-specific PEEP is encouraged for treating different patients but there is no well established method in optimal PEEP selection.
  
  
  METHODS
  A study of 10 patients diagnosed with ALI/ARDS whom underwent recruitment manoeuvre is carried out. Airway pressure and flow data are used to identify patient-specific constant lung elastance (E lung) and time-variant dynamic lung elastance (E drs) at each PEEP level (increments of 5 cm H2O), for a single compartment linear lung model using integral-based methods. Optimal PEEP is estimated using E lung versus PEEP, Edrs-Pressure curve and E drs Area at minimum elastance (maximum compliance) and the inflection of the curves (diminishing return). Results are compared to clinically selected PEEP values. The trials and use of the data were approved by the New Zealand South Island Regional Ethics Committee.
  
  
  RESULTS
  Median absolute percentage fitting error to the data when estimating time-variant E drs is 0.9% (IQR = 0.5-2.4) and 5.6% [IQR: 1.8-11.3] when estimating constant E lung. Both E lung and E drs decrease with PEEP to a minimum, before rising, and indicating potential over-inflation. Median E drs over all patients across all PEEP values was 32.2 cmH2O/l [IQR: 26.1-46.6], reflecting the heterogeneity of ALI/ARDS patients, and their response to PEEP, that complicates standard approaches to PEEP selection. All E drs-Pressure curves have a clear inflection point before minimum E drs, making PEEP selection straightforward. Model-based selected PEEP using the proposed metrics were higher than clinically selected values in 7/10 cases.
  
  
  CONCLUSIONS
  Continuous monitoring of the patient-specific E lung and E drs and minimally invasive PEEP titration provide a unique, patient-specific and physiologically relevant metric to optimize PEEP selection with minimal disruption of MV therapy.
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, New Zealand.
authors.forename: Yeong Shiong
authors.initials: YS
authors.lastname: Chiew
authors.forename: J Geoffrey
authors.initials: JG
authors.lastname: Chase
authors.forename: Geoffrey M
authors.initials: GM
authors.lastname: Shaw
authors.forename: Ashwath
authors.initials: A
authors.lastname: Sundaresan
authors.forename: Thomas
authors.initials: T
authors.lastname: Desaive
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D004548:Elasticity; D005260:Female; D006801:Humans; D008168:Lung / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011175:Positive-Pressure Respiration / Q000379:methods*; D057285:Precision Medicine; D012119:Respiration; D012121:Respiration, Artificial; D012128:Respiratory Distress Syndrome / Q000503:physiopathology / Q000628:therapy; D013997:Time Factors; D016896:Treatment Outcome; D055815:Young Adult