OBJECTIVE: Adaptation of ventilator settings to the individual's respiratory system mechanics requires information about the pressure-volume relationship and the change of compliance which is dependent on inflated volume. Unfortunately, established methods of obtaining this information are invasive and time-consuming, and, therefore, not well suited for clinical routine. We propose a new standardized diagnostic concept based on the recently developed slice method. This multiple linear regression method (MLR) determines volume-dependent respiratory system compliance (C(SLICE)) within the tidal volume (V(T)) during ongoing mechanical ventilation. The impact of a ventilator strategy, recommended by a consensus conference, on the course of compliance within V(T) was investigated in patients with the acute respiratory distress syndrome (ARDS) or acute lung injury (ALI). DESIGN: Prospective observational study. SETTING: Intensive care unit of a university hospital. PATIENTS: 14 ARDS patients, 2 patients with ALI. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: After measurement of flow and airway pressure and calculation of tracheal pressure, C(SLICE) was determined. The resulting course of C(SLICE) within V(T) was estimated using a mathematical algorithm. C(SLICE) data were compared to those obtained by standard MLR. We found decreasing C(SLICE) mainly in the upper part of V(T) in all patients. In 7 patients, we found an additional increasing C(SLICE) mainly in the lower part of V(T). CONCLUSIONS: C(SLICE) was not constant in patients with ARDS/ALI whose lungs were ventilated according to consensus conference recommendations. The proposed diagnostic concept may serve as a new tool to obtain a standardized estimation of respiratory system compliance within V(T) non-invasively without interfering with ongoing mechanical ventilation.
OBJECTIVE: Adaptation of ventilator settings to the individual's respiratory system mechanics requires information about the pressure-volume relationship and the change of compliance which is dependent on inflated volume. Unfortunately, established methods of obtaining this information are invasive and time-consuming, and, therefore, not well suited for clinical routine. We propose a new standardized diagnostic concept based on the recently developed slice method. This multiple linear regression method (MLR) determines volume-dependent respiratory system compliance (C(SLICE)) within the tidal volume (V(T)) during ongoing mechanical ventilation. The impact of a ventilator strategy, recommended by a consensus conference, on the course of compliance within V(T) was investigated in patients with the acute respiratory distress syndrome (ARDS) or acute lung injury (ALI). DESIGN: Prospective observational study. SETTING: Intensive care unit of a university hospital. PATIENTS: 14 ARDSpatients, 2 patients with ALI. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: After measurement of flow and airway pressure and calculation of tracheal pressure, C(SLICE) was determined. The resulting course of C(SLICE) within V(T) was estimated using a mathematical algorithm. C(SLICE) data were compared to those obtained by standard MLR. We found decreasing C(SLICE) mainly in the upper part of V(T) in all patients. In 7 patients, we found an additional increasing C(SLICE) mainly in the lower part of V(T). CONCLUSIONS: C(SLICE) was not constant in patients with ARDS/ALI whose lungs were ventilated according to consensus conference recommendations. The proposed diagnostic concept may serve as a new tool to obtain a standardized estimation of respiratory system compliance within V(T) non-invasively without interfering with ongoing mechanical ventilation.
Authors: You Hao; Jayaram K Udupa; Yubing Tong; Caiyun Wu; Hua Li; Joseph M McDonough; Carina Lott; Catherine Qiu; Nirupa Galagedera; Jason B Anari; Drew A Torigian; Patrick J Cahill Journal: Med Image Anal Date: 2021-04-25 Impact factor: 13.828
Authors: Akos Szlavecz; Yeong Shiong Chiew; Daniel Redmond; Alex Beatson; Daniel Glassenbury; Simon Corbett; Vincent Major; Christopher Pretty; Geoffrey M Shaw; Balazs Benyo; Thomas Desaive; J Geoffrey Chase Journal: Biomed Eng Online Date: 2014-09-30 Impact factor: 2.819