Non-invasive venous waveform analysis (NIVA) for volume assessment in patients undergoing hemodialysis: an observational study.

BACKGROUND: Accurate assessment of volume status to direct dialysis remains a clinical challenge. Despite current attempts at volume-directed dialysis, inadequate dialysis and intradialytic hypotension (IDH) are common occurrences. Peripheral venous waveform analysis has recently been developed as a method to accurately determine intravascular volume status through algorithmic quantification of changes in the waveform that occur at different volume states. A noninvasive method to capture peripheral venous signals is described (Non-Invasive Venous waveform Analysis, NIVA). The objective of this proof-of-concept study was to characterize changes in NIVA signal with dialysis. We hypothesized that there would be a change in signal after dialysis and that the rate of intradialytic change in signal would be predictive of IDH. METHODS: Fifty subjects undergoing inpatient hemodialysis were enrolled. A 10-mm piezoelectric sensor was secured to the middle volar aspect of the wrist on the extremity opposite to the access site. Signals were obtained fifteen minutes before, throughout, and up to fifteen minutes after hemodialysis. Waveforms were analyzed after a fast Fourier transformation and identification of the frequencies corresponding to the cardiac rate, with a NIVA value generated based on the weighted powers of these frequencies. RESULTS: Adequate quality (signal to noise ratio > 20) signals pre- and post- dialysis were obtained in 38 patients (76%). NIVA values were significantly lower at the end of dialysis compared to pre-dialysis levels (1.203 vs 0.868, p < 0.05, n = 38). Only 16 patients had adequate signals for analysis throughout dialysis, but in this small cohort the rate of change in NIVA value was predictive of IDH with a sensitivity of 80% and specificity of 100%. CONCLUSIONS: This observational, proof-of-concept study using a NIVA prototype device suggests that NIVA represents a novel and non-invasive technique that with further development and improvements in signal quality may provide static and continuous measures of volume status to assist with volume directed dialysis and prevent intradialytic hypotension.

Observational Study of Noninvasive Venous Waveform Analysis to Assess Intracardiac Filling Pressures During Right Heart Catheterization.

BACKGROUND: Outpatient monitoring and management of patients with heart failure (HF) reduces hospitalizations and health care costs. However, the availability of noninvasive approaches to assess congestion is limited. Noninvasive venous waveform analysis (NIVA) uses a unique physiologic signal, the morphology of the venous waveform, to assess intracardiac filling pressures. This study is a proof of concept analysis of the correlation between NIVA value and pulmonary capillary wedge pressure (PCWP) and the ability of the NIVA value to predict PCWP > 18 mmHg in subjects undergoing elective right heart catheterization (RHC). PCWP was also compared across common clinical correlates of congestion. METHODS AND RESULTS: A prototype NIVA device, which consists of a piezoelectric sensor placed over the skin on the volar aspect of the wrist, connected to a data-capture control box, was used to collect venous waveforms in 96 patients during RHC. PCWP was collected at end-expiration by an experienced cardiologist. The venous waveform signal was transformed to the frequency domain (Fourier transform), where a ratiometric algorithm of the frequencies of the pulse rate and its harmonics was used to derive a NIVA value. NIVA values were successfully captured in 83 of 96 enrolled patients. PCWP ranged from 4-40 mmHg with a median of 13 mmHg. NIVA values demonstrated a linear correlation with PCWP (r = 0.69, P < 0.05). CONCLUSIONS: This observational proof-of-concept study using a prototype NIVA device demonstrates a moderate correlation between NIVA value and PCWP in patients undergoing RHC. NIVA, thus, represents a promising developing technology for noninvasive assessment of congestion in spontaneously breathing patients.