Abstract

Hemorrhage is a major cause of preventable death worldwide, and early identification can be lifesaving. Pulse wave contour analysis has previously been used to infer hemodynamic variables in a variety of settings. We hypothesized that pulse arrival time (PAT), a form of pulse wave contour analysis which is assessed via electrocardiography (ECG) and photoplethysmography (PPG), is associated with hemorrhage volume. Yorkshire-Cross swine were randomized to hemorrhage (30 mL/kg over 20 minutes) vs. control. Continuous ECG and PPG waveforms were recorded with a novel monitoring device, and algorithms were developed to calculate PAT and PAT variability throughout the respiratory cycle, termed "PAT index" or "PAT_I." Mixed effects models were used to determine associations between blood loss and PAT and between blood loss and PAT_I to account for clustering within subjects and investigate inter-subject variability in these relationships. PAT and PAT_I data were determined for ∼150 distinct intervals from five subjects. PAT and PAT_I were strongly associated with blood loss. Mixed effects modeling with PAT alone was substantially better than PAT_I alone (R2 0.93 vs. 0.57 and Akaike information criterion (AIC) 421.1 vs. 475.5, respectively). Modeling blood loss with PAT and PAT_I together resulted in slightly improved fit compared to PAT alone (R2 0.96, AIC 419.1). Mixed effects models demonstrated significant inter-subject variability in the relationships between blood loss and PAT. Findings from this pilot study suggest that PAT and PAT_I may be used to detect blood loss. Because of the simple design of a single-lead ECG and PPG, the technology could be packaged into a very small form factor device for use in austere or resource-constrained environments. Significant inter-subject variability in the relationship between blood loss and PAT highlights the importance of individualized hemodynamic monitoring.

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