| dc.description.abstract | Heart failure is the leading cause of hospitalization in the elderly and there remains an unmet need for accurate non-invasive assessment of congestion in patients with heart failure. Non-Invasive Venous waveform Analysis (NIVA) is a novel, non-invasive technology that acquires and analyzes the peripheral venous waveform from the wrist. The main objective of this thesis was to develop an algorithm for calculation of a NIVA value and assess the correlation between NIVA value and pulmonary capillary wedge pressure (PCWP). The secondary objectives were to assess the ability of NIVA to detect PCWP>18mmHg, and to investigate the correlation between non-invasive thoracic impedance technology (ZOE®) and PCWP. NIVA signals were acquired from 78 subjects undergoing right heart catheterization (RHC). The NIVA algorithm to estimate PCWP was developed using Lasso linear regression. ZOE® measurements were also obtained in 20 subjects. Pearson correlation was used to determine correlations between NIVA value or ZOE® value and PCWP. A Receiver Operating Characteristic (ROC) curve was used to determine whether a NIVA value could predict PCWP>18 mmHg (a value consistent with congestion or volume overload). 50 subjects had adequate signal for analysis. The NIVA value demonstrated a positive correlation with PCWP (r=0.76, p<0.05). ZOE® did not correlate with PCWP (r=-0.03, p=0.89). NIVA was able to predict PCWP>18mmHg with a sensitivity of 73% and specificity of 80% (AUC=0.83, p<0.05). NIVA is a non-invasive monitoring technology that provides an estimate of PCWP and has potential for guidance of decongestive therapy in heart failure patients. | |
