Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial

Abstract

Importance: Intraoperative hypotension is associated with increased morbidity and mortality. A machine learning-derived early warning system to predict hypotension shortly before it occurs has been developed and validated.

Objective: To test whether the clinical application of the early warning system in combination with a hemodynamic diagnostic guidance and treatment protocol reduces intraoperative hypotension.

Design, setting, and participants: Preliminary unblinded randomized clinical trial performed in a tertiary center in Amsterdam, the Netherlands, among adult patients scheduled for elective noncardiac surgery under general anesthesia and an indication for continuous invasive blood pressure monitoring, who were enrolled between May 2018 and March 2019. Hypotension was defined as a mean arterial pressure (MAP) below 65 mm Hg for at least 1 minute.

Interventions: Patients were randomly assigned to receive either the early warning system (n = 34) or standard care (n = 34), with a goal MAP of at least 65 mm Hg in both groups.

Main outcomes and measures: The primary outcome was time-weighted average of hypotension during surgery, with a unit of measure of millimeters of mercury. This was calculated as the depth of hypotension below a MAP of 65 mm Hg (in millimeters of mercury) × time spent below a MAP of 65 mm Hg (in minutes) divided by total duration of operation (in minutes).

Results: Among 68 randomized patients, 60 (88%) completed the trial (median age, 64 [interquartile range {IQR}, 57-70] years; 26 [43%] women). The median length of surgery was 256 minutes (IQR, 213-430 minutes). The median time-weighted average of hypotension was 0.10 mm Hg (IQR, 0.01-0.43 mm Hg) in the intervention group vs 0.44 mm Hg (IQR, 0.23-0.72 mm Hg) in the control group, for a median difference of 0.38 mm Hg (95% CI, 0.14-0.43 mm Hg; P = .001). The median time of hypotension per patient was 8.0 minutes (IQR, 1.33-26.00 minutes) in the intervention group vs 32.7 minutes (IQR, 11.5-59.7 minutes) in the control group, for a median difference of 16.7 minutes (95% CI, 7.7-31.0 minutes; P < .001). In the intervention group, 0 serious adverse events resulting in death occurred vs 2 (7%) in the control group.

Conclusions and relevance: In this single-center preliminary study of patients undergoing elective noncardiac surgery, the use of a machine learning-derived early warning system compared with standard care resulted in less intraoperative hypotension. Further research with larger study populations in diverse settings is needed to understand the effect on additional patient outcomes and to fully assess safety and generalizability.

Trial registration: ClinicalTrials.gov Identifier: NCT03376347.

Conflict of interest statement

Conflict of Interest Disclosures: Dr Wijnberge reported receipt of consultancy fees from Edwards Lifesciences outside the submitted work. Dr Geerts reported receipt of grants from Edwards Lifescience outside the submitted work and consultancy fees and research grants from Philips. Dr Hollmann reported serving as executive section editor of pharmacology for Anesthesia & Analgesia and as section editor of anesthesiology for the Journal of Clinical Medicine and receipt of speakers fees from CSL Behring and Eurocept BV and consultancy fees from Eurocept BV. Dr Vlaar reported receipt of personal fees from AKPA. Dr Veelo reported receipt of personal fees and other from Edwards Lifesciences outside the submitted work as well as consultancy fees and research grants from Philips and Hemologic. No other disclosures were reported.

Figures

Figure 1.. Participant Flow in the Hypotension Prediction (HYPE) Trial

Figure 2.. Hemodynamic Diagnostic Guidance and Treatment Protocol

aVasoplegia indicates decreased systemic vascular resistance. bImpaired left ventricular contractility.