Arterial blood pressure waveform in liver transplant surgery possesses variability of morphology reflecting recipients' acuity and predicting short term outcomes
Shen-Chih Wang, Chien-Kun Ting, Cheng-Yen Chen, Chin-Su Liu,, Niang-Cheng Lin, Che-Chuan Loon, Hau-Tieng Wu, Yu-Ting Lin

TL;DR
This study uses a novel algorithm to analyze arterial blood pressure waveform variability in liver transplant patients, revealing its potential to reflect patient acuity and predict short-term outcomes.
Contribution
The paper introduces the DDMap algorithm for quantifying ABP waveform variability and demonstrates its clinical relevance in liver transplant surgery.
Findings
Presurgical variability correlates with MELD-Na scores.
Neohepatic phase variability predicts early allograft failure.
Waveform variability provides more clinical insights than traditional BP measures.
Abstract
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…
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Taxonomy
TopicsLiver Disease and Transplantation · Liver Disease Diagnosis and Treatment · Organ Transplantation Techniques and Outcomes
