Model based prediction of plateau pressure in mechanically ventilated patients

Abstract

The risk of ventilator induced lung injury in mechanically ventilated (MV) critically ill patients can be mitigated by patient-specific optimisation of ventilator settings. Recent studies have shown that driving pressure, i.e. the difference between plateau pressure (Pplat) and PEEP, is a strong indicator for survival in MV patients suffering from ARDS. However, to measure Pplat, an extended end-inspiratory pause (EIP) has to be applied, possibly interrupting ventilation therapy. This study presents a method for predicting Pplat from normal breaths in MV patients.

A total of 859 MV breaths with a 5 second EIP were recorded in 27 MV patients with ARDS. Two methods for determining Pplat were tested, one using an exponential fit of the pressure data and the other using a four-parameter viscoelastic model (VEM). Each method was identified using various lengths of data after the peak inspiratory pressure (PIP). Using the identified parameters, both methods were then used to predict the Pplat recorded at 5 seconds.

The exponential method showed a median coefficient of variation (CV) from the real Pplat of 42.9% using data from PIP to 0.5 seconds after PIP, 24.9% using 1 second of data and 15.2% using 1.5 seconds of data. The respective VEM prediction median CVs were of 17.2%, 9.7% and 8.4%. Therefore, the VEM showed a better prediction than the non-physiological exponential model, allowing it to be used to reduce the clinical burden of determining Pplat by reducing the required length of the EIP to 1.5 seconds.

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Current Directions in Biomedical Engineering is an open access journal and closely related to the journal Biomedical Engineering - Biomedizinische Technik. CDBME is a forum for the exchange of knowledge in the fields of biomedical engineering, medical information technology and biotechnology/bioengineering for medicine and addresses engineers, natural scientists, and clinicians working in research, industry, or clinical practice.

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