  Background: We investigated clinical information underneath the beat-to-beat
fluctuation of the arterial blood pressure (ABP) waveform morphology. We
proposed the Dynamical Diffusion Map algorithm (DDMap) to quantify the
variability of morphology. The underlying physiology could be the compensatory
mechanisms involving complex interactions between various physiological
mechanisms to regulate the cardiovascular system. As a liver transplant surgery
contains distinct periods, we investigated its clinical behavior in different
surgical steps. Methods: Our study used DDmap algorithm, based on unsupervised
manifold learning, to obtain a quantitative index for the beat-to-beat
variability of morphology. We examined the correlation between the variability
of ABP morphology and disease acuity as indicated by Model for End-Stage Liver
Disease (MELD) scores, the postoperative laboratory data, and 4 early allograft
failure (EAF) scores. Results: Among the 85 enrolled patients, the variability
of morphology obtained during the presurgical phase was best correlated with
MELD-Na scores. The neohepatic phase variability of morphology was associated
with EAF scores as well as postoperative bilirubin levels, international
normalized ratio, aspartate aminotransferase levels, and platelet count.
Furthermore, variability of morphology presents more associations with the
above clinical conditions than the common BP measures and their BP variability
indices. Conclusions: The variability of morphology obtained during the
presurgical phase is indicative of patient acuity, whereas those during the
neohepatic phase are indicative of short-term surgical outcomes.
