Reformulation of the pressure-dependent recruitment model (PRM) of respiratory mechanics

Paul D. Docherty, Christoph Schranz, Yeong Shiong Chiew, Knut Möller, J. Geoffrey Chase

Research output: Contribution to journalArticleResearchpeer-review

17 Citations (Scopus)

Abstract

Background: The pressure dependent recruitment model (PRM) is a comprehensive mathematical description of pulmonary mechanics in acute respiratory distress syndrome (ARDS). However, previous investigations of the PRM implied that the number of model parameters may cause inaccurate parameter estimation. Methods: PRM models were evaluated for 12 ARDS patients that underwent a low-flow recruitment manoeuvre. The identified parameter set formed the basis of a parameter reduction investigation of the PRM. The parameter reduction investigation measured the mean cohort residual error (ψ) yielded by each possible combination of identified parameter set with the non-identified parameter values set to a priori population constants. Results: Reducing the five variable PRM to a particular three variable model configuration produced a limited increase in model fit to data residuals (ψ5 = 22.68, ψ3 = 29.21 mbar). The reduced model evaluates airway-resistance, compliance and distension as model variables and uses population values for alveoli opening pressure and the ratio of open alveoli at end expiratory. Conclusions: The reduced PRM model captures all major pressure-volume response features in the ARDS patients. Reduced parameterisation allows more robust parameter identification and thus more reliable parameter estimates that may prove more useful in a clinical setting.

Original languageEnglish
Pages (from-to)47-53
Number of pages7
JournalBiomedical Signal Processing and Control
Volume12
Issue number1
DOIs
Publication statusPublished - Jul 2014
Externally publishedYes

Keywords

  • Acute respiratory distress syndrome (ARDS)
  • Parameter identification
  • Physiological modelling
  • Practical model identifiability
  • Pulmonary modelling

Cite this