Prediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort study

Bryce Benson; Ashwin Belle; Sooin Lee; Benjamin S Bassin; Richard P Medlin; Michael W Sjoding; Kevin R Ward

doi:10.1186/s12871-023-02283-x

Prediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort study

BMC Anesthesiol. 2023 Sep 22;23(1):324. doi: 10.1186/s12871-023-02283-x.

Authors

Bryce Benson¹, Ashwin Belle¹, Sooin Lee¹, Benjamin S Bassin^{2

3}, Richard P Medlin^{2

3}, Michael W Sjoding^{3

4}, Kevin R Ward^{5

6}

Affiliations

¹ Fifth Eye Inc, 110 Miller Avenue, Suite 300, Ann Arbor, MI, 48104, USA.
² Department of Emergency Medicine, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI, 48109-5301, USA.
³ Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, NCRC 10-A103 2800 Plymouth Road, Ann Arbor, MI, 48109, USA.
⁴ Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI, 48109-5642, USA.
⁵ Department of Emergency Medicine, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI, 48109-5301, USA. keward@umich.edu.
⁶ Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, NCRC 10-A103 2800 Plymouth Road, Ann Arbor, MI, 48109, USA. keward@umich.edu.

Abstract

Background: Predicting the onset of hemodynamic instability before it occurs remains a sought-after goal in acute and critical care medicine. Technologies that allow for this may assist clinicians in preventing episodes of hemodynamic instability (EHI). We tested a novel noninvasive technology, the Analytic for Hemodynamic Instability-Predictive Indicator (AHI-PI), which analyzes a single lead of electrocardiogram (ECG) and extracts heart rate variability and morphologic waveform features to predict an EHI prior to its occurrence.

Methods: Retrospective cohort study at a quaternary care academic health system using data from hospitalized adult patients between August 2019 and April 2020 undergoing continuous ECG monitoring with intermittent noninvasive blood pressure (NIBP) or with continuous intraarterial pressure (IAP) monitoring.

Results: AHI-PI's low and high-risk indications were compared with the presence of EHI in the future as indicated by vital signs (heart rate > 100 beats/min with a systolic blood pressure < 90 mmHg or a mean arterial blood pressure of < 70 mmHg). 4,633 patients were analyzed (3,961 undergoing NIBP monitoring, 672 with continuous IAP monitoring). 692 patients had an EHI (380 undergoing NIBP, 312 undergoing IAP). For IAP patients, the sensitivity and specificity of AHI-PI to predict EHI was 89.7% and 78.3% with a positive and negative predictive value of 33.7% and 98.4% respectively. For NIBP patients, AHI-PI had a sensitivity and specificity of 86.3% and 80.5% with a positive and negative predictive value of 11.7% and 99.5% respectively. Both groups performed with an AUC of 0.87. AHI-PI predicted EHI in both groups with a median lead time of 1.1 h (average lead time of 3.7 h for IAP group, 2.9 h for NIBP group).

Conclusions: AHI-PI predicted EHIs with high sensitivity and specificity and within clinically significant time windows that may allow for intervention. Performance was similar in patients undergoing NIBP and IAP monitoring.

Keywords: Blood pressure; Critical care; Heart rate variability; Hemodynamic instability; Hemodynamic monitoring; Hypotension; Predictive analytic.

MeSH terms

Adult
Electrocardiography*
Heart Rate
Humans
Retrospective Studies