Linear analysis is surprisingly useful for understanding hypertension in the Guyton model

Given populations of normotensive and hypertensive “virtual individuals” (over 200,000 simulations with randomized parameter values) based on the Guyton model (Guyton et al. 1972; van Vliet & Montani 2005), we used linear analysis techniques to identify the key factors that determine which simulations result in hypertension. A Generalized Linear Model (GLM) was fitted to each population to predict the long‐term arterial pressure from the model parameters. The GLMs were then reduced to a minimal set of the model parameters, and we compared the effect of each parameter on the two GLMs, demonstrating a difference in parameter sensitivity. We also used this approach to examine the parameter sensitivity of other properties, such as cardiac output and total peripheral resistance, again demonstrating some differences between the normotensive and hypertensive populations. Identifying these differences is the first step in using the Guyton model to reveal possible new therapies for hypertension in human patients. The Guyton model of whole‐body cardiovascular physiology was the first integrated mathematical model of human physiology and remains a landmark achievement. First published in 1972, this model was particularly instrumental in exploring the relationship between blood pressure and sodium balance, and in demonstrating the key role of the kidney in long‐term regulation of blood pressure, due to its importance in salt and water balance. The present study is a further part of our extensive ongoing global sensitivity analysis of the Guyton model.