- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06644599
Wireless Monitoring for Clinical Deterioration (i-PROTECT)
February 25, 2026 updated by: Dr Yaseen Arabi, King Abdullah International Medical Research Center
Integrated Proactive Wireless Monitoring for Clinical Deterioration: A Stepped Wedge Randomized Trial
The study evaluates whether implementing a wireless monitoring system for patients admitted to hospital wards reduces mortality and cardiopulmonary failure.
Study Overview
Status
Recruiting
Conditions
Intervention / Treatment
Detailed Description
The trial is designed as a stepped-wedge cluster RCT.
Hospital wards (which constitute clusters in this design) will be randomized to have wireless monitoring, 7 wards at a time, with each 7 wards constituting a sequence.
The study consists of 5 periods of two-month sequences followed by a one-month transition time with a phased introduction of the intervention.
In the first period, all wards will have no wireless monitoring.
After a baseline period of 2 (+1 washout) months, the intervention (monitoring system) will be implemented in a randomly selected new sequence every 3-month period until the intervention is implemented in all sequences.
Study Type
Interventional
Enrollment (Estimated)
13160
Phase
- Not Applicable
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Yaseen M Arabi, MD
- Phone Number: 18899 018011111
- Email: arabi@mngha.med.sa
Study Locations
-
-
Riyadh Region
-
Riyadh, Riyadh Region, Saudi Arabia
- Recruiting
- King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
-
Contact:
- Yaseen M Arabi, MD, FCCP, FCCM, ATSF
- Phone Number: 18855 +966 (11) 801-1111
- Email: arabi@mngha.med.sa
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
No
Description
Inclusion Criteria:
Ward level Inpatient wards, defined as wards used to manage adult inpatients.
Patient level
- Aged 14 years or older
- Checked in as inpatient status to one of the study wards
Exclusion Criteria:
Ward level
- Cardiology, pediatric, obstetric wards
- ICUs and emergency departments
- Operating rooms
- Outpatient clinics
- Daycare wards, endoscopy, outpatient procedure areas, hemodialysis units
Patient level No commitment for full life support at the time of arrival to the study ward (designated as Do-Not-Resuscitate status)
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Primary Purpose: Supportive Care
- Allocation: Randomized
- Interventional Model: Sequential Assignment
- Masking: Triple
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Active Comparator: Wireless monitoring
Wireless monitoring will be applied on patients who are at high risk, identified as having a National Early Warning Score (NEWS)-2 score of 5 or higher, patients with lower NEWS-2 scores if the clinical team has a clinical concern, patients with Critical Care Response Team (CCRT) activation regardless of NEWS-2 score and post-ICU discharges regardless of NEWS-2 score.
The technology allows to have alarms for patients who meet preset thresholds for vital signs.
These alarms are transmitted through a mobile device to the charge nurse of the related ward.
The wireless system will be monitored 24/7 by a critical care nurse
|
The monitoring wireless system will continuously monitor the heart rate, oxygen saturation (SpO2), respiratory rate, and blood pressure and in selected patients electrocardiography (ECG).
|
|
No Intervention: Control
Usual care with no wireless monitoring.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Composite endpoint of 30-day in-hospital mortality, cardiac arrest, requirement of vasopressor or intubation
Time Frame: 30 days
|
After hospital admission within 30 days
|
30 days
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Cardiac arrest
Time Frame: 30 days
|
cardiac arrest within 30 days of hospital admission
|
30 days
|
|
Requirement of vasopressors
Time Frame: within 30 days of hospital admission
|
use of vasopressors/inotropic support
|
within 30 days of hospital admission
|
|
Requirement of intubation
Time Frame: 30 days
|
need for mechanical ventilation within 30 days of hospital admission
|
30 days
|
|
Hospital length of stay
Time Frame: 90 days
|
censored at 90 days
|
90 days
|
|
Transfer to ICU
Time Frame: 30 days
|
ICU admission within 30 days of hospital admission
|
30 days
|
|
ICU- free days
Time Frame: 30 days
|
in the first 30 days of hospital admission
|
30 days
|
|
CCRT activation
Time Frame: 30 days
|
Critical care response team activation within 30 days of hospital admission
|
30 days
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Jones D, Mitchell I, Hillman K, Story D. Defining clinical deterioration. Resuscitation. 2013 Aug;84(8):1029-34. doi: 10.1016/j.resuscitation.2013.01.013. Epub 2013 Jan 31.
- Buist M, Bernard S, Nguyen TV, Moore G, Anderson J. Association between clinically abnormal observations and subsequent in-hospital mortality: a prospective study. Resuscitation. 2004 Aug;62(2):137-41. doi: 10.1016/j.resuscitation.2004.03.005.
- Al-Qahtani S, Al-Dorzi HM, Tamim HM, Hussain S, Fong L, Taher S, Al-Knawy BA, Arabi Y. Impact of an intensivist-led multidisciplinary extended rapid response team on hospital-wide cardiopulmonary arrests and mortality. Crit Care Med. 2013 Feb;41(2):506-17. doi: 10.1097/CCM.0b013e318271440b.
- Arabi YM, Al-Dorzi HM, Alamry A, Hijazi R, Alsolamy S, Al Salamah M, Tamim HM, Al-Qahtani S, Al-Dawood A, Marini AM, Al Ehnidi FH, Mundekkadan S, Matroud A, Mohamed MS, Taher S. The impact of a multifaceted intervention including sepsis electronic alert system and sepsis response team on the outcomes of patients with sepsis and septic shock. Ann Intensive Care. 2017 Dec;7(1):57. doi: 10.1186/s13613-017-0280-7. Epub 2017 May 30.
- Armitage M, Eddleston J, Stokes T; Guideline Development Group at the NICE. Recognising and responding to acute illness in adults in hospital: summary of NICE guidance. BMJ. 2007 Aug 4;335(7613):258-9. doi: 10.1136/bmj.39272.679688.47. No abstract available.
- Smith GB. In-hospital cardiac arrest: is it time for an in-hospital 'chain of prevention'? Resuscitation. 2010 Sep;81(9):1209-11. doi: 10.1016/j.resuscitation.2010.04.017. Epub 2010 Jul 2.
- Breteler MJM MSc, Huizinga E, van Loon K, Leenen LPH, Dohmen DAJ, Kalkman CJ, Blokhuis TJ. Reliability of wireless monitoring using a wearable patch sensor in high-risk surgical patients at a step-down unit in the Netherlands: a clinical validation study. BMJ Open. 2018 Feb 27;8(2):e020162. doi: 10.1136/bmjopen-2017-020162.
- Breteler MJM, KleinJan EJ, Dohmen DAJ, Leenen LPH, van Hillegersberg R, Ruurda JP, van Loon K, Blokhuis TJ, Kalkman CJ. Vital Signs Monitoring with Wearable Sensors in High-risk Surgical Patients: A Clinical Validation Study. Anesthesiology. 2020 Mar;132(3):424-439. doi: 10.1097/ALN.0000000000003029.
- Bellomo R, Ackerman M, Bailey M, Beale R, Clancy G, Danesh V, Hvarfner A, Jimenez E, Konrad D, Lecardo M, Pattee KS, Ritchie J, Sherman K, Tangkau P; Vital Signs to Identify, Target, and Assess Level of Care Study (VITAL Care Study) Investigators. A controlled trial of electronic automated advisory vital signs monitoring in general hospital wards. Crit Care Med. 2012 Aug;40(8):2349-61. doi: 10.1097/CCM.0b013e318255d9a0.
- Subbe CP, Duller B, Bellomo R. Effect of an automated notification system for deteriorating ward patients on clinical outcomes. Crit Care. 2017 Mar 14;21(1):52. doi: 10.1186/s13054-017-1635-z.
- Mdege ND, Man MS, Taylor Nee Brown CA, Torgerson DJ. Systematic review of stepped wedge cluster randomized trials shows that design is particularly used to evaluate interventions during routine implementation. J Clin Epidemiol. 2011 Sep;64(9):936-48. doi: 10.1016/j.jclinepi.2010.12.003. Epub 2011 Mar 16.
- Porsdam Mann S, Savulescu J, Sahakian BJ. Facilitating the ethical use of health data for the benefit of society: electronic health records, consent and the duty of easy rescue. Philos Trans A Math Phys Eng Sci. 2016 Dec 28;374(2083):20160130. doi: 10.1098/rsta.2016.0130.
- Gonzales R, Anderer T, McCulloch CE, Maselli JH, Bloom FJ Jr, Graf TR, Stahl M, Yefko M, Molecavage J, Metlay JP. A cluster randomized trial of decision support strategies for reducing antibiotic use in acute bronchitis. JAMA Intern Med. 2013 Feb 25;173(4):267-73. doi: 10.1001/jamainternmed.2013.1589.
- van Wyk JT, van Wijk MA, Sturkenboom MC, Mosseveld M, Moorman PW, van der Lei J. Electronic alerts versus on-demand decision support to improve dyslipidemia treatment: a cluster randomized controlled trial. Circulation. 2008 Jan 22;117(3):371-8. doi: 10.1161/CIRCULATIONAHA.107.697201. Epub 2008 Jan 2.
- Hogan H, Healey F, Neale G, Thomson R, Vincent C, Black N. Preventable deaths due to problems in care in English acute hospitals: a retrospective case record review study. BMJ Qual Saf. 2012 Sep;21(9):737-45. doi: 10.1136/bmjqs-2011-001159.
- Weenk M, van Goor H, Frietman B, Engelen LJ, van Laarhoven CJ, Smit J, Bredie SJ, van de Belt TH. Continuous Monitoring of Vital Signs Using Wearable Devices on the General Ward: Pilot Study. JMIR Mhealth Uhealth. 2017 Jul 5;5(7):e91. doi: 10.2196/mhealth.7208.
- Taenzer AH, Pyke JB, McGrath SP, Blike GT. Impact of pulse oximetry surveillance on rescue events and intensive care unit transfers: a before-and-after concurrence study. Anesthesiology. 2010 Feb;112(2):282-7. doi: 10.1097/ALN.0b013e3181ca7a9b.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
February 1, 2026
Primary Completion (Estimated)
December 1, 2026
Study Completion (Estimated)
December 1, 2026
Study Registration Dates
First Submitted
October 15, 2024
First Submitted That Met QC Criteria
October 15, 2024
First Posted (Actual)
October 16, 2024
Study Record Updates
Last Update Posted (Actual)
February 27, 2026
Last Update Submitted That Met QC Criteria
February 25, 2026
Last Verified
February 1, 2026
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- ICT23R/006/08
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
YES
IPD Plan Description
Data will be shared at the discretion of the Principal investigator
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
Yes
product manufactured in and exported from the U.S.
Yes
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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