Model-based optimal PEEP in mechanically ventilated ARDS patients in the Intensive Care Unit

BioMedical Engineering OnLine

Ashwath Sundaresan²  J Geoffrey Chase⁴  Geoffrey M Shaw¹  Yeong Shiong Chiew²  Thomas Desaive³ 

[1] Department of Intensive Care, Christchurch Hospital, Private Bag 4710, Christchurch, New Zealand

[2] Department of Mechanical Engineering, College of Engineering, University of Canterbury, Private Bag 8140, Christchurch, New Zealand

[3] Cardiovascular Research Center, Institute of Physics, Allée du 6 Août, 17 (Bât B5), B4000 Liège (Belgium

[4] Department of Mechanical Engineering, University of Canterbury, Private Bag 8140, Christchurch, New Zealand

关键词: ARDS;    Model Based Methods;    PEEP;    Mechanical Ventilation;   

Others  :  798249
DOI  :  10.1186/1475-925X-10-64

 received in 2011-05-04, accepted in 2011-07-27,  发布年份 2011

【 摘 要 】

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.

【 授权许可】

   
2011 Sundaresan et al; licensee BioMed Central Ltd.

【 图 表 】

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