Abstract 6: Validation of a Computational Platform for the Analysis of the Physiologic Mechanisms of a Human Experimental Model of Hemorrhage
Objective: Computational models of integrative physiology may serve as a framework for understanding the complex adaptive responses essential for homeostasis in critical illness and resuscitation and may provide insights for design of diagnostics and therapeutics. In this study a computer model of human physiology was compared to results obtained from experiments using a Lower Body Negative Pressure (LBNP) analog model of human hemorrhage. LBNP has been demonstrated to produce physiologic changes consistent with hemorrhage.
Methods: The computer model contains over 4000 parameters that describe the detailed integration of physiology based upon basic physical principles and established biologic interactions. The LBNP protocol consists of a 5 min rest period (0 mm Hg) followed by 5 min of chamber decompression of the lower body to −15, −30, −45, and −60 mm Hg and additional increments of −10 mm Hg every 5 min until the onset of cardiovascular collapse (n = 20). Physiologic parameters recorded include MAP, cardiac output (CO), and SvO2 (from peripheral venous blood), during the last 30 seconds at each LBNP level. The computer model analytic procedure recreates the investigational protocol for a virtual individual in an In Silico environment. After baseline normalization, the model predicted measurements for MAP, CO, and SVO2 were compared to those observed through the entire range of LBNP. Differences were evaluated using standard statistical performance error measurements (median performance error (PE) < 5%).
Results: The simulation results closely tracked the average changes seen during LBNP. The predicted MAP fell outside the standard error measurement for the experimental data at only LBNP −30 mmHg while CO was more variable. The predicted SVO2 fell outside the standard error measurement for the experimental data only during the post LBNP recovery point. However, the statistical median PE measurement was found to be within the 5% objective error measure (1.3 % for MAP, −3.5% for CO, and 3.95% for SVO2).
Conclusions: The computer model was found to accurately predict the experimental results observed using LBNP. The model should be explored as a platform for studying concepts and physiologic mechanisms of hemorrhage including its diagnosis and treatment.