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Background: We investigated clinical information underneath the beat-to-beatfluctuation of the arterial blood pressure (ABP) waveform morphology. Weproposed the Dynamical Diffusion Map algorithm (DDMap) to quantify thevariability of morphology. The underlying physiology could be the compensatorymechanisms involving complex interactions between various physiologicalmechanisms to regulate the cardiovascular system. As a liver transplant surgerycontains distinct periods, we investigated its clinical behavior in differentsurgical steps. Methods: Our study used DDmap algorithm, based on unsupervisedmanifold learning, to obtain a quantitative index for the beat-to-beatvariability of morphology. We examined the correlation between the variabilityof ABP morphology and disease acuity as indicated by Model for End-Stage LiverDisease (MELD) scores, the postoperative laboratory data, and 4 early allograftfailure (EAF) scores. Results: Among the 85 enrolled patients, the variabilityof morphology obtained during the presurgical phase was best correlated withMELD-Na scores. The neohepatic phase variability of morphology was associatedwith EAF scores as well as postoperative bilirubin levels, internationalnormalized ratio, aspartate aminotransferase levels, and platelet count.Furthermore, variability of morphology presents more associations with theabove clinical conditions than the common BP measures and their BP variabilityindices. Conclusions: The variability of morphology obtained during thepresurgical phase is indicative of patient acuity, whereas those during theneohepatic phase are indicative of short-term surgical outcomes.

Arterial blood pressure waveform in liver transplant surgery possesses  variability of morphology reflecting recipients' acuity and predicting short  term outcomes