Reference : Model-based optimal PEEP in mechanically ventilated ARDS patients in the Intensive Ca...
Scientific journals : Article
Human health sciences : Anesthesia & intensive care
Model-based optimal PEEP in mechanically ventilated ARDS patients in the Intensive Care Unit
Sundaresan, Ashwath [> > > >]
Chase, J Geoffrey [> > > >]
Shaw, Geoffrey M [> > > >]
Chiew, Yeong Shiong [> > > >]
Desaive, Thomas mailto [Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > Thermodynamique des phénomènes irréversibles >]
Biomedical Engineering Online
Biomed Central Ltd
Yes (verified by ORBi)
[en] Mechanical Ventilation ; PEEP ; Model Based Methods ; ARDS
[en] 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 cmH(2)O 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.

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