4.5 Article

Model-based setting of inspiratory pressure and respiratory rate in pressure-controlled ventilation

Journal

PHYSIOLOGICAL MEASUREMENT
Volume 35, Issue 3, Pages 383-397

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/0967-3334/35/3/383

Keywords

respiratory mechanics; model-based therapy; pressure-controlled ventilation; lung-protective ventilation; modeling and system identification

Funding

  1. German Federal Ministry of Education and Research (WiM-Vent) [01IB10002D, 01IB10002F]

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Mechanical ventilation carries the risk of ventilator-induced-lung-injury (VILI). To minimize the risk of VILI, ventilator settings should be adapted to the individual patient properties. Mathematical models of respiratory mechanics are able to capture the individual physiological condition and can be used to derive personalized ventilator settings. This paper presents model-based calculations of inspiration pressure (p(I)), inspiration and expiration time (t(I), t(E)) in pressure-controlled ventilation (PCV) and a retrospective evaluation of its results in a group of mechanically ventilated patients. Incorporating the identified first order model of respiratory mechanics in the basic equation of alveolar ventilation yielded a nonlinear relation between ventilation parameters during PCV. Given this patient-specific relation, optimized settings in terms of minimal p(I) and adequate t(E) can be obtained. We then retrospectively analyzed data from 16 ICU patients with mixed pathologies, whose ventilation had been previously optimized by ICU physicians with the goal of minimization of inspiration pressure, and compared the algorithm's 'optimized' settings to the settings that had been chosen by the physicians. The presented algorithm visualizes the patient-specific relations between inspiration pressure and inspiration time. The algorithm's calculated results highly correlate to the physician's ventilation settings with r = 0.975 for the inspiration pressure, and r = 0.902 for the inspiration time. The nonlinear patient-specific relations of ventilation parameters become transparent and support the determination of individualized ventilator settings according to therapeutic goals. Thus, the algorithm is feasible for a variety of ventilated ICU patients and has the potential of improving lung-protective ventilation by minimizing inspiratory pressures and by helping to avoid the build-up of clinically significant intrinsic positive end-expiratory pressure.

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