Isansys Lifecare, developer of the Patient Status Engine patient monitoring platform, and the Lifetouch wireless ‘smart patch’ cardiac sensor, today announced the results of a study pointing to a new pathway for managing patients with advanced liver disease based on new methods employing data-driven biomarkers.
One hundred and 11 patients were included in the collaborative study between the University College London, Royal Free Hospital, and the University of Bonn, Germany, which showed that a significant reduction in heart rate variability is a feature of acute decompensation of cirrhosis and, remarkably, predicts 90-day mortality in these patients.
We are pleased to have been able to contribute to this important and groundbreaking work that has shown how patients, clinicians and providers will benefit from a new class of data-driven biomarkers
In a preliminary study, the London team validated the Patient Status Engine and Lifetouch sensor as an ideal remote monitoring system and used it to create a baseline heart rate variability (HRV) data set from a group of healthy volunteers.
They then used the Lifetouch to assess heart rate variability (HRV) remotely and non-invasively on patients admitted to the Royal Free Hospital with an acute a significant deterioration of advanced cirrhosis.
The results concluded that continuous, wireless monitoring of HRV is feasible in patients with advanced liver disease.
The study also supported the hypothesis of both hospital teams that reduced HRV correlates with severity of liver decompensation, facilitating the identification of high-risk patients and allowing for timely interventions.
In light of these findings, the study suggests the future potential for such continuous monitoring and the prospective health economic benefit of measuring HRV remotely.
The report states: “Traditional ECG measurement of HRV encompasses short-term five-minute ECG segments being interpreted separately as reflecting HRV in that specific time window, under stable physiological conditions.
“The Lifetouch system, by contrast, not only facilitates continuous monitoring irrespective of the individuals’ daily activity or physical ill health, but also helps negate the shortcoming of limited ECG time capture which make further interpretation difficult.
“Using the remote monitoring device, we were able to interpret HRV in all monitored in-patients with acute decompensation.”
Keith Errey, chief executive of Isansys, adds: “We are pleased to have been able to contribute to this important and groundbreaking work that has shown how patients, clinicians and providers will benefit from a new class of data-driven biomarkers.
These data sets are the basic requirements for transformative new ways of diagnosing and managing patients as AI and deep learning methods become more widely used in healthcare
“We look forward to continuing the work with the two teams on the next full-scale demonstrator phase of this vital project.
"The Patient Status Engine is more than a remote patient monitoring platform. It is able to directly produce the most-complete and accurate physiological data sets outside an intensive care unit, for all patients, including those at home.
“These data sets are the basic requirements for transformative new ways of diagnosing and managing patients as AI and deep learning methods become more widely used in healthcare.”
- Companies:
- University College London
- Royal Free London NHS Foundation Trust
- Isansys Lifecare
