Continuous Wireless Monitoring of Vital Signs and Automated Alerts in Participants at Home and During Hospitalization

Last updated: April 8, 2025
Sponsor: University Hospital Bispebjerg and Frederiksberg
Overall Status: Active - Recruiting

Phase

N/A

Condition

Hematological Disorders

Cardiac Disease

Cancer

Treatment

Vital signs measurements with new app

Clinical Study ID

NCT05378139
2203648
  • Ages > 18
  • All Genders

Study Summary

The primary aim of this study is to test and assess the implementation and effectiveness of continuous wireless vital signs monitoring with real-time alerts on:

The frequency of patients monitored with adequate data quality as adequate clinical user satisfaction in the initial versus the last part of the trial (primary outcome).

Eligibility Criteria

Inclusion

Inclusion Criteria:

  • Adult participants (≥18 years)

  • Patients assessed by the clinical staff as having an acute condition with risk forclinical deterioration and being either at home (with no apparent need forhospitalization), and/or in hospital OR

  • Patients at either at home before, in-hospital and/or after hospitalization forelective major surgery, defined as surgery lasting more than one hour under general-or regional anaesthesia

Exclusion

Exclusion Criteria:

  • The participant expected not to cooperate with study procedures.

  • Allergy to plaster or silicone.

  • Having pacemaker or Implantable Cardioverter Defibrillator (ICD) device.

  • Inability to give informed consent.

Study Design

Total Participants: 3095
Treatment Group(s): 1
Primary Treatment: Vital signs measurements with new app
Phase:
Study Start date:
February 01, 2021
Estimated Completion Date:
December 22, 2025

Study Description

Over the last years, the applicants and research team partners have developed the WARD (Wireless Assessment of Respiratory and circulatory Distress) project, using continuous wireless monitoring of vital signs and artificial intelligence algorithms for data interpretation in high-risk patient admitted to medical and surgical wards. The WARD project combines continuous measurements of 10 different physiological modalities with machine learning to develop the WARD-Clinical Support System (WARD-CSS), based on multiple intelligent algorithms, that automatically monitors, interprets, predicts and alert clinical staff. Through a mobile device with a purpose-built Graphic User Interface (GUI), the WARD-CSS stimulates human-machine interaction to improve the monitoring of high-risk hospitalized patients.

The WARD project has hitherto proven an unmet need for continuous monitoring and the potential for automatic detection and prediction of physiological deterioration events. Specifically, observational pilot studies of both patients with acute exacerbations of Chronic Obstructive Pulmonary Disease (AECOPD) and postoperative abdominal cancer surgery patients have shown that episodes of desaturation, tachycardia, tachypnea, and bradypnea are much more frequently detected using continuous vital signs monitoring than with existing Early Warning Score (EWS) systems.

Ongoing investigations will determine the efficacy in two very selected populations of high-risk surgical patients and acutely ill medical patients with severe disease. This study will investigate the WARD-systems' implementation, and effectiveness of use and impact in a cohort of patientparticipants admitted

Connect with a study center

  • Rigshospitalet

    Copenhagen, 2100
    Denmark

    Active - Recruiting

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