Ensuring hemodynamic stability with adequate perfusion to vital organs is critical to the safe conduct of anesthesia. Recent advances in hemodynamic monitoring technologies allow pressure, flow, and resistance to be measured continuously; however, there is limited evidence to suggest that these technologies alter clinical management or improve patient outcomes significantly. This may be because the fundamental hemodynamic model, established by Starling and Guyton, fails to offer the granular level of insight needed to guide clinical management.
We collected hemodynamic data from 950 patients who underwent major surgery with advanced hemodynamic monitoring (AHM) that provided continuously derived cardiac output and vascular resistance measurements. These measurements were based on the hemodynamic model of Starling and Guyton. Additionally, investigational monitoring software was developed to visualize a different hemodynamic model, termed the “pressure field” model. This model expresses the pulsatile, beat-to-beat relationship between ventricular performance (measured by stroke volume) and vascular tone (indicated by systemic elastance).
Within this dataset were several patients who experienced major hemorrhage. Case studies of these patients demonstrate that abnormal pressure and flow regulation patterns are observed through the lens of the pressure field model, but these patterns are typically not visible through the lens of the traditional Starling and Guyton model (cardiac output and systemic vascular resistance, which involve averaging hemodynamic performance over successive cardiac cycles). Furthermore, “before and after” case studies using our investigational pressure field monitoring software suggest that the traditional Starling and Guyton hemodynamic model has limited utility in managing hemorrhage.
We propose that the pressure field model may allow hemorrhage to be managed more effectively via improved monitoring granularity [the beat-by-beat visualization of the stroke volume-systemic elastance relationship, rather than the use of the composite metrics of cardiac output (heart rate × stroke volume) and systemic vascular resistance]. Further research into the utility of the pressure field model is warranted.