Patient Deterioration Predictor could Surpass Limits of Traditional Vital Signs

An artificial intelligence-driven device that works to detect and predict hemodynamic instability may provide a more accurate picture of patient deterioration than traditional vital sign measurements, a Michigan Medicine study suggests.

Researchers captured data from over 5,000 adult patients at University of Michigan Health with the Analytic for Hemodynamic Instability. Developed at the U-M Weil Institute for Critical Care Research and Innovation, AHI is a software as a medical device designed to detect and predict changes in hemodynamic status in real-time using data from a single electrocardiogram lead. The researchers compared the results against gold standard vital sign measurements of continuous heart rate and blood pressure measured by invasive arterial monitoring in several intensive care units to determine if the AHI could indicate hemodynamic instability in real-time.

They found that the AHI detected standard indications of hemodynamic instability, a combination of elevated heart rate and low blood pressure, with nearly 97% sensitivity and 79% specificity. The results are published in Critical Care Explorations (a Society of Critical Care Medicine journal).

The findings suggest that the AHI may be able to provide continuous dynamic monitoring capabilities in patients who traditionally have intermittent static vital sign measurements, says senior author Ben Bassin, M.D., director of the Joyce and Don Massey Family Foundation Emergency Critical Care Center, also known as EC3, and an associate professor of emergency medicine at U-M Medical School.

"AHI performs extremely well, and it functions in a way that we think may have transformative clinical utility," Bassin said. "Most vital signs measurements are static, subject to human error, and require validation and interpretation. AHI is the opposite of that. It's dynamic, produces a binary output of 'stable' or 'unstable,' and it may enable early martialing of resources to patients who may not have been on a clinician's radar."

Traditional vital signs have limitations, including limited accuracy in non-invasive monitoring and the fact that patients who are not at obvious risk for immediate deterioration may only be monitored periodically every 4-6 hours or longer. The AHI, which was approved by the United States Food and Drug Administration in 2021 and is licensed to Fifth Eye, Inc. (a U-M spinoff), was designed to address those limitations.

"The vision of AHI was born out of our continued inability to identify unstable patients and to predict when patients would become unstable, especially in settings where they cannot be intensively monitored, said co-author Kevin Ward, M.D., executive director of the Weil Institute and professor of emergency medicine and biomedical engineering at Michigan Medicine.

"AHI is ideally suited to be utilized with wearable monitors such as ECG patches, that could make any hospital bed, waiting room or other setting into a sophisticated monitoring environment. The implication of such a technology is that it has the potential to save lives not only in the hospital, but also at home, in the ambulance and on the battlefield."

Researchers say future studies are needed to determine if AHI provides clinical and resource allocation benefits in patients undergoing infrequent blood pressure monitoring. The next phase of research will focus on how AHI is used at Michigan Medicine.

Schmitzberger FF, Hall AE, Hughes ME, Belle A, Benson B, Ward KR, Bassin BS.
Detection of Hemodynamic Status Using an Analytic Based on an Electrocardiogram Lead Waveform.
Crit Care Explor. 2022 May 17;4(5):e0693. doi: 10.1097/CCE.0000000000000693

Most Popular Now

AI-Powered CRISPR could Lead to Faster G…

Stanford Medicine researchers have developed an artificial intelligence (AI) tool to help scientists better plan gene-editing experiments. The technology, CRISPR-GPT, acts as a gene-editing “copilot” supported by AI to help...

Groundbreaking AI Aims to Speed Lifesavi…

To solve a problem, we have to see it clearly. Whether it’s an infection by a novel virus or memory-stealing plaques forming in the brains of Alzheimer’s patients, visualizing disease processes...

AI Spots Hidden Signs of Depression in S…

Depression is one of the most common mental health challenges, but its early signs are often overlooked. It is often linked to reduced facial expressivity. However, whether mild depression or...

AI Tools Help Predict Severe Asthma Risk…

Mayo Clinic researchers have developed artificial intelligence (AI) tools that help identify which children with asthma face the highest risk of serious asthma exacerbation and acute respiratory infections. The study...

ChatGPT 4o Therapeutic Chatbot 'Ama…

One of the first randomized controlled trials assessing the effectiveness of a large language model (LLM) chatbot 'Amanda' for relationship support shows that a single session of chatbot therapy...

AI Model Forecasts Disease Risk Decades …

Imagine a future where your medical history could help predict what health conditions you might face in the next two decades. Researchers have developed a generative AI model that uses...

AI Model Indicates Four out of Ten Breas…

A project at Lund University in Sweden has trained an AI model to identify breast cancer patients who could be spared from axillary surgery. The model analyses previously unutilised information...

AI Distinguishes Glioblastoma from Look-…

A Harvard Medical School–led research team has developed an AI tool that can reliably tell apart two look-alike cancers found in the brain but with different origins, behaviors, and treatments. The...

Overcoming the AI Applicability Crisis a…

Opinion Article by Harry Lykostratis, Chief Executive, Open Medical. The government’s 10 Year Health Plan makes a lot of the potential of AI-software to support clinical decision making, improve productivity, and...

Smart Device Uses AI and Bioelectronics …

As a wound heals, it goes through several stages: clotting to stop bleeding, immune system response, scabbing, and scarring. A wearable device called "a-Heal," designed by engineers at the University...

Dartford and Gravesham Implements Clinis…

Dartford and Gravesham NHS Trust has taken a significant step towards a more digital future by rolling out electronic test ordering using Clinisys ICE. The trust deployed the order communications...