The New Golden Standard: the Early Warning Score Algorithm

Early Warning Score Clinical Trial

— EAGLE  

Official title:

The New Golden Standard: the Early Warning Score Algorithm

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04292158
• Other study ID #: 2018/184
• Status: Completed
• Start date: April 1, 2019
• Est. completion date: April 30, 2020

Study information

• Verified date: May 2020
• Source: University of Liege
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The objective is this study is the development and implementation of a smart algorithm to compute an early warning indicator able to predict early patient deterioration.

Description:

Data will be collected at the three sites using the SomnoTouchTM and MOXTM devices, commercially available and CE approved. Every month, the data will be sent to the KUL and UM to develop the algorithm. Study centers will also send some pre-defined patient characteristics extracted from the patient's EMR to better contextualize the data.

The EWS formula has a free interpretation of the vital parameters weighting and the vital parameters to be taken into account in the scoring system. Therefore, many variants of the EWS arose the past decade (i.e. MEWS, NEWS). The algorithm developed in this study should define an objective approach for the EWS formula, diminishing the discordances regarding the weight per parameter. Using a patient-personalized approach, the definite algorithm should be based on the patient's vital parameter measured during his/her whole hospitalization, generating a patient-personalized weight per parameter and an overall reliable EWS scoring system.

The EWS score is often only measured twice per day per patient, creating a large window for disease worsening. The algorithm developed in this study could be deployed along the wearable device developed in the WearIT4Health project. The device would continuously feed the algorithm with data acquired from its sensors. Thus, the EWS would be computed every 10 seconds.

The EWS scoring system has already been proven to be an effective approach in reducing clinical deterioration, reducing the admission to intensive care units and thus overall reducing mortality. However, as mentioned above the EWS is measured in a rather low frequency. Therefore, estimation of the EWS score via continuous monitored parameters should further increase patient survival.

The primary objective of the EAGLE study is to collect continuously monitored vital and activity parameter data and use it to develop an algorithm that can early identify clinical deterioration to optimize the application of the EWS system.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 80
• Est. completion date: April 30, 2020
• Est. primary completion date: November 4, 2019
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

Exclusion Criteria:

• Suffering from infectious disease

• Participating to another study that could intervene with the study results (e.g. experimental medication that could affect the heart rate).

Related Conditions & MeSH terms

• Early Warning Score

Intervention

Device:
• SomnoTouch
The patient will be equipped with the SomnoTouch device. This device is able to record and estimate the following data: ECG data PPG data Heart rate Respiration rate Blood pressure (mmHg) Oxygen saturation (%). All patient will be stored for further analysis.
• MOX
The patient will be equipped with the MOX device. This device is able to record and estimate the following data: Accelerometers data Activity Body posture All patient will be stored for further analysis.

Locations

Country	Name	City	State
Belgium	Ziekenhuis Oost-Limburg	Genk	Limbourg
Belgium	Centre Hospitalier Universitaire de Liège	Liège
Netherlands	Maastricht University Medical Center+	Maastricht

Sponsors (6)

Lead Sponsor	Collaborator
University of Liege	Academisch Ziekenhuis Maastricht, Hasselt University, KU Leuven, Maastricht University, Ziekenhuis Oost-Limburg

Countries where clinical trial is conducted

Belgium,  Netherlands, 

References & Publications (5)

Ajami S, Teimouri F. Features and application of wearable biosensors in medical care. J Res Med Sci. 2015 Dec;20(12):1208-15. doi: 10.4103/1735-1995.172991. Review. — View Citation

Gerry S, Birks J, Bonnici T, Watkinson PJ, Kirtley S, Collins GS. Early warning scores for detecting deterioration in adult hospital patients: a systematic review protocol. BMJ Open. 2017 Dec 3;7(12):e019268. doi: 10.1136/bmjopen-2017-019268. — View Citation

Jarvis S, Kovacs C, Briggs J, Meredith P, Schmidt PE, Featherstone PI, Prytherch DR, Smith GB. Aggregate National Early Warning Score (NEWS) values are more important than high scores for a single vital signs parameter for discriminating the risk of adverse outcomes. Resuscitation. 2015 Feb;87:75-80. doi: 10.1016/j.resuscitation.2014.11.014. Epub 2014 Nov 26. — View Citation

Moon A, Cosgrove JF, Lea D, Fairs A, Cressey DM. An eight year audit before and after the introduction of modified early warning score (MEWS) charts, of patients admitted to a tertiary referral intensive care unit after CPR. Resuscitation. 2011 Feb;82(2):150-4. doi: 10.1016/j.resuscitation.2010.09.480. Epub 2010 Nov 5. — View Citation

Smith MEB, Chiovaro JC, O'Neil M, Kansagara D, Quinones A, Freeman M, Motu'apuaka M, Slatore CG. Early Warning System Scores: A Systematic Review [Internet]. Washington (DC): Department of Veterans Affairs; 2014 Jan. Available from http://www.ncbi.nlm.nih.gov/books/NBK259026/ — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Precision of predictive early warning score algorithm	Precision defined of truepositives divided by the sum of truepositives and truenegatives. This measure indicates how often the predictive EWS was right in identifying adverse events.	Up to 1 week