• Brian Shin, Steven A Maler, Keerthi Reddy, and Neal W Fleming.
• University of California, Davis, Department of Anesthesiology and Pain Medicine, Sacramento, CA.
• J. Cardiothorac. Vasc. Anesth. 2021 Jun 1; 35 (6): 1769-1775.

ObjectiveThe hypotension prediction index (HPI) is a novel parameter developed by Edwards Lifesciences (Irvine, CA) that is obtained through an algorithm based on arterial pressure waveform characteristics. Past studies have demonstrated its accuracy in predicting hypotensive events in noncardiac surgeries. The authors aimed to evaluate the use of the HPI in cardiac surgeries requiring cardiopulmonary bypass (CPB).DesignProspective cohort feasibility study.SettingSingle university medical center.ParticipantsSequential adult patients undergoing elective cardiac surgeries requiring CPB between October 1, 2018, and December 31, 2018.InterventionsHPI monitor was connected to the patient's arterial pressure transducer. Anesthesiologists and surgeons were blinded to the monitor output.Measurements And Main ResultsHPI values and hypotensive events were recorded before and after CPB. The primary outcomes were the area under the curve (AUC) of the receiver operating characteristic curve, sensitivity, and specificity of HPI predicting hypotension. The AUC, sensitivity, and specificity for HPI lead time to hypotension five minutes before the event were 0.90 (95% confidence interval [CI]: 0.853-0.949), 84% (95% CI: 77.7-90.5), and 84% (95% CI: 70.9-96.8), respectively. Ten minutes before the event AUC, sensitivity, and specificity for HPI lead time to hypotension were 0.83 (95% CI: 0.750-0.905), 79% (95% CI: 69.8-88.1), and 74% (95% CI: 58.8-89.6), respectively. Fifteen minutes before the hypotensive event AUC, sensitivity, and specificity for HPI lead time to hypotension were 0.83 (95% CI: 0.746-0.911), 79% (95% CI: 68.4-89.0), and 74% (95% CI: 58.8-89.6), respectively.ConclusionHPI predicted hypotensive episodes during cardiac surgeries with a high degree of sensitivity and specificity.Copyright © 2020 Elsevier Inc. All rights reserved.

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