Use of a continuous single lead electrocardiogram analytic to predict patient deterioration requiring rapid response team activation

Identifying the onset of patient deterioration is challenging despite the potential to respond to patients earlier with better vital sign monitoring and rapid response team (RRT) activation. In this study an ECG based software as a medical device, the Analytic for Hemodynamic Instability Predictive Index (AHI-PI), was compared to the vital signs of heart rate, blood pressure, and respiratory rate, evaluating how early it indicated risk before an RRT activation. A higher proportion of the events had risk indication by AHI-PI (92.71%) than by vital signs (41.67%). AHI-PI indicated risk early, with an average of over a day before RRT events. In events whose risks were indicated by both AHI-PI and vital signs, AHI-PI demonstrated earlier recognition of deterioration compared to vital signs. A case-control study showed that situations requiring RRTs were more likely to have AHI-PI risk indication than those that did not. The study derived several insights in support of AHI-PI's efficacy as a clinical decision support system. The findings demonstrated AHI-PI's potential to serve as a reliable predictor of future RRT events. It could potentially help clinicians recognize early clinical deterioration and respond to those unnoticed by vital signs, thereby helping clinicians improve clinical outcomes.

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Publication Details

Journal
PLOS Digital Health
Published
2024-10-24
DOI
https://doi.org/10.1371/journal.pdig.0000465
Citations
1
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
Field-Weighted Citation Impact
0.40
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article

Use of a continuous single lead electrocardiogram analytic to predict patient deterioration requiring rapid response team activation

Bryce Benson, Richard P. Medlin, Kevin R. Ward, Ashwin Belle et al.
1 citations
PLOS Digital Health
Heart Rate Variability and Autonomic Control
0.40
article

Use of a continuous single lead electrocardiogram analytic to predict patient deterioration requiring rapid response team activation

Bryce Benson, Richard P. Medlin, Kevin R. Ward, Ashwin Belle, Sooin Lee, David Jerkins, Ashish K. Khanna, Michael A. DeVita, Foster Goss
article en
1 citations

Abstract

Identifying the onset of patient deterioration is challenging despite the potential to respond to patients earlier with better vital sign monitoring and rapid response team (RRT) activation. In this study an ECG based software as a medical device, the Analytic for Hemodynamic Instability Predictive Index (AHI-PI), was compared to the vital signs of heart rate, blood pressure, and respiratory rate, evaluating how early it indicated risk before an RRT activation. A higher proportion of the events had risk indication by AHI-PI (92.71%) than by vital signs (41.67%). AHI-PI indicated risk early, with an average of over a day before RRT events. In events whose risks were indicated by both AHI-PI and vital signs, AHI-PI demonstrated earlier recognition of deterioration compared to vital signs. A case-control study showed that situations requiring RRTs were more likely to have AHI-PI risk indication than those that did not. The study derived several insights in support of AHI-PI's efficacy as a clinical decision support system. The findings demonstrated AHI-PI's potential to serve as a reliable predictor of future RRT events. It could potentially help clinicians recognize early clinical deterioration and respond to those unnoticed by vital signs, thereby helping clinicians improve clinical outcomes.

PLOS Digital HealthVol. 3(10)
Atrium Health Wake Forest Baptist (US), University of Michigan (US), Michigan United (US), Michigan Medicine (US), University of Colorado Anschutz Medical Campus (US), Columbia University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 32%
Heart Rate Variability and Autonomic Control
0.40
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