Patient-Ventilator Asynchrony Detection
- 35% experience asynchrony
- Asynchrony is associated with
- 5x increase in ICU mortality
- 3x increase in mechanical ventilation time
- 2x increase in hospital length of stay
- Detection is tedious, imprecise, time-consuming
Syncron-E™ is a machine learning-based technology, which performs real-time analysis of flow and pressure waveforms currently available from mechanical ventilators to detect various types of patient-ventilator asynchrony.
Closed-Loop Fluid Management
- 40% of patients experience fluid overload
- Fluid overload is associated with
- 70% (2.6 days) increase in ICU length of stay
- 43% (3.5 days) increase in hospital length of stay
Fluid-Autopilot™ is an automated fluid management system. The system can operate in two modes: i) fully-automated (closed-loop) mode; and ii) clinical decision support mode.