GRAPPEL: A Graph-based Approach for Early Risk Assessment of Acute Hypertension in Critical Care

Abstract

An acute hypertensive episode (AHE) refers to a period of extremely high blood pressure (BP) that can arise suddenly in critical care, and, if not identified early, can subject patients to the risk of severe organ damage and even potential mortality. The early assessment of AHE risk saves lives by enabling proactive medical intervention.

We propose GRAPPEL, a novel graph-based approach that assesses a patient’s risk of experiencing an AHE before it occurs based on the analysis of their BP recorded over time in critical care. Our algorithm consists of two major components: (1) the construction of a time-evolving graph representation of a patient’s time-series BP data to encode the temporal BP variations into a graph and (2) the generation of real-time AHE risk scores based on quantifying the graph changes at each time step, triggered by the arrival of a new BP record. Notably, GRAPPEL provides real-time and early AHE risk assessment based solely on BP records that can be irregularly spaced in time, making it suitable for critical care environments. Via our extensive experiments on 3,476 critical-care visit records, we demonstrate the superiority of our approach over existing methods by achieving an AUC-ROC score of 91% in identifying patients at risk of experiencing an AHE up to 170 minutes in advance (and an AUC-ROC score of 94% up to 20 minutes in advance).