PURPOSE: There is growing interest in the use of both variable and pressure-controlled ventilation (PCV). The combination of these approaches as "noisy PCV" requires adaptation of the mechanical ventilator to the respiratory system mechanics. Thus, we developed and evaluated a new control system based on the least-mean-squares adaptive approach, which automatically and continuously adjusts the driving pressure during PCV to achieve the desired variability pattern of tidal volume (V (T)). METHODS: The controller was tested during numerical simulations and with a physical model reproducing the mechanical properties of the respiratory system. We applied step changes in respiratory system mechanics and mechanical ventilation settings. The time needed to converge to the desired V (T) variability pattern after each change (t (c)) and the difference in minute ventilation between the measured and target pattern of V (T) (DeltaMV) were determined. RESULTS: During numerical simulations, the control system for noisy PCV achieved the desired variable V (T) pattern in less than 30 respiratory cycles, with limited influence of the dynamic elastance (E*) on t (c), except when E* was underestimated by >25%. We also found that, during tests in the physical model, the control system converged in <60 respiratory cycles and was not influenced by airways resistance. In all measurements, the absolute value of DeltaMV was <25%. CONCLUSION: The new control system for noisy PCV can prove useful for controlled mechanical ventilation in the intensive care unit.
PURPOSE: There is growing interest in the use of both variable and pressure-controlled ventilation (PCV). The combination of these approaches as "noisy PCV" requires adaptation of the mechanical ventilator to the respiratory system mechanics. Thus, we developed and evaluated a new control system based on the least-mean-squares adaptive approach, which automatically and continuously adjusts the driving pressure during PCV to achieve the desired variability pattern of tidal volume (V (T)). METHODS: The controller was tested during numerical simulations and with a physical model reproducing the mechanical properties of the respiratory system. We applied step changes in respiratory system mechanics and mechanical ventilation settings. The time needed to converge to the desired V (T) variability pattern after each change (t (c)) and the difference in minute ventilation between the measured and target pattern of V (T) (DeltaMV) were determined. RESULTS: During numerical simulations, the control system for noisy PCV achieved the desired variable V (T) pattern in less than 30 respiratory cycles, with limited influence of the dynamic elastance (E*) on t (c), except when E* was underestimated by >25%. We also found that, during tests in the physical model, the control system converged in <60 respiratory cycles and was not influenced by airways resistance. In all measurements, the absolute value of DeltaMV was <25%. CONCLUSION: The new control system for noisy PCV can prove useful for controlled mechanical ventilation in the intensive care unit.
Authors: C Putensen; S Zech; H Wrigge; J Zinserling; F Stüber; T Von Spiegel; N Mutz Journal: Am J Respir Crit Care Med Date: 2001-07-01 Impact factor: 21.405
Authors: Peter M Spieth; Alysson R Carvalho; Andreas Güldner; Paolo Pelosi; Oleg Kirichuk; Thea Koch; Marcelo Gama de Abreu Journal: Anesthesiology Date: 2009-02 Impact factor: 7.892
Authors: Peter M Spieth; Alysson R Carvalho; Paolo Pelosi; Catharina Hoehn; Christoph Meissner; Michael Kasper; Matthias Hübler; Matthias von Neindorff; Constanze Dassow; Martina Barrenschee; Stefan Uhlig; Thea Koch; Marcelo Gama de Abreu Journal: Am J Respir Crit Care Med Date: 2009-01-16 Impact factor: 21.405
Authors: Marcelo Gama de Abreu; Peter M Spieth; Paolo Pelosi; Alysson R Carvalho; Christiane Walter; Anna Schreiber-Ferstl; Peter Aikele; Boriana Neykova; Matthias Hübler; Thea Koch Journal: Crit Care Med Date: 2008-03 Impact factor: 7.598
Authors: Abdulaziz Boker; M Ruth Graham; Keith R Walley; Bruce M McManus; Linda G Girling; Elizabeth Walker; Gerald R Lefevre; W Alan C Mutch Journal: Am J Respir Crit Care Med Date: 2002-02-15 Impact factor: 21.405
Authors: Massimo Antonelli; Elie Azoulay; Marc Bonten; Jean Chastre; Giuseppe Citerio; Giorgio Conti; Daniel De Backer; Herwig Gerlach; Goran Hedenstierna; Michael Joannidis; Duncan Macrae; Jordi Mancebo; Salvatore M Maggiore; Alexandre Mebazaa; Jean-Charles Preiser; Jerôme Pugin; Jan Wernerman; Haibo Zhang Journal: Intensive Care Med Date: 2011-02-03 Impact factor: 17.440
Authors: Anurak Thungtong; Matthew F Knoch; Frank J Jacono; Thomas E Dick; Kenneth A Loparo Journal: Front Physiol Date: 2018-06-19 Impact factor: 4.566
Authors: Tito Bassani; Vlasta Bari; Andrea Marchi; Maddalena Alessandra Wu; Giuseppe Baselli; Giuseppe Citerio; Alessandro Beda; Marcelo Gama de Abreu; Andreas Güldner; Stefano Guzzetti; Alberto Porta Journal: Auton Neurosci Date: 2013-04-08 Impact factor: 3.145