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Clinical Trial Summary

This study looks to develop a multi-scale computational model of Pulmonary Hypertension, this clinical model will be calibrated using longitudinal, retrospectively and prospectively acquired human clinical data.


Clinical Trial Description

Pulmonary hypertension (PH) is a complex disorder associated with elevated pulmonary arterial pressure. Unlike systemic hypertension, PH is difficult to detect in routine physical examinations and the current gold standard for diagnosing PH is through invasive right heart catheterization. Prolonged PH results in functional, structural and anatomical changes in the right ventricle (RV), large pulmonary arteries, and the pulmonary micro-circulation that ultimately lead to decompensated RV failure and death. Unlike in systemic hypertension, for which patients have effective pharmacological management of blood pressure for decades, PH prognosis remains poor with 15% mortality within 1 year on modern therapy. Our current understanding of PH has largely been obtained through animal models and clinical studies. However, surgical banding or chronic hypoxia animal models do not fully reproduce the etiology of human PH, whereas invasive clinical measurements of pulmonary vascular resistance (PVR), stiffness and ventricular elastance provide limited insight into disease progression. Therefore, there is a pressing need to develop a multi-scale (MS) computational model that can couple the short term (e.g. hemodynamics) and long-term G&R interactions between the RV and the pulmonary circulation. The overall goals of this project are to use the framework to (1) describe the time course of the biomechanical alterations and (2) identify the key mechanical culprits associated with PH-induced heart failure so that clinical interventions can be targeted against them. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT03564522
Study type Observational
Source University of Michigan
Contact
Status Completed
Phase
Start date April 1, 2017
Completion date July 28, 2023

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