An observational study in Surgery and Inpatients, sponsored by University of Edinburgh. Recruiting at 17 sites in 8 countries. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-02-10.
Sponsored by University of Edinburgh · Observational
Patients can become critically unwell following surgical operations. Delay in recognition of this deterioration can result in patient harm and even death. Wearable wireless sensors that record patients vital signs such as heart rate could help improve recognition of patient deterioration. The goal of this observational study: Enhanced Monitoring Using Sensors After Surgery (EMUs) is to determine if data from wearable physiological monitors can be used for the early detection of postoperative deterioration, while being acceptable to patients and healthcare staff. The study participants and surgical inpatients undergoing open surgery. There are 3 objectives which each represent a stage of the study:
This registration focuses on the shadow-mode cohort study.
Participants will wear wireless sensors on their chest and fingers, pre-, intra-, and post-operatively for up to 10 days. The sensors will record their vital signs such as heart rate, and oxygen levels. This will then be analysed, and used to aid the design of early detection algorithms that may be able to predict clinical illness or complications in this patient group. This is an observational study gathering real time data only. No changes in patient care will result, and in Stages 2 and 3 no sensor data will be available to clinical teams. This study will be performed in departments of general surgery in Benin, Ghana, Guatemala, India, Mexico, Nigeria, Rwanda, and the United Kingdom.
Patients who die after surgery frequently have treatable complications which are not identified in a timely manner. This is due to a failure to "recognize", "relay" or "react" to the deterioration of a patient in the postoperative period. This study aims to determine whether data from wearable physiological monitors can be used for the early detection of patient deterioration, while being acceptable to patients and healthcare staff. If found useful, future studies would be conducted to determine the performance and safety of such a device.
This study has three objectives which will be addressed in three stages.
STAGE 1. Usability testing of device with clinicians, nurses, and healthcare workers in non-clinical environment.
STAGE 2. Baseline postoperative monitoring practice assessment and device usability testing in clinical environment.
STAGE 3. Shadow-mode cohort study with collection of time-stamped sensor and clinical event data to determine relationships between physiological waveforms and patient deterioration.
This registration focuses on the shadow-mode cohort study.
This study will be performed in departments of general surgery in Benin, Ghana, Guatemala, India, Mexico, Nigeria, Rwanda, and the UK. In Stages 2 and 3, patients will have undergone major surgery and will be recovering in postoperative wards.
This study can be performed using any suitable wearable device (it is device agnostic), as it seeks to gather generalisable information. In the first instance, the Sibel ANNE® One device will be used. ANNE® One is a wireless ICU-grade dual sensor system that provides real-time physiological monitoring. The system features two skin-mounted, bio-integrated sensors that provide continuous storage of vital sign measurements and physiological waveforms.
This is an observational study gathering real time data only. No changes in patient care will result, and in Stages 2 and 3 no sensor data will be available to clinical teams. True equipoise exists: it is not clear whether these data are useful or how they should be used. Patients will be managed with standard care throughout.
Wearable sensors have potential application in improving postoperative monitoring and consequently, the reduction of avoidable morbidity and mortality. Sensor data may be used to generate prediction algorithms providing a continuous readout of individual patient risk. Such algorithms could enhance healthcare workers' capacity to identify and intervene upon patients with early complications. However, few high-quality studies have yet been performed in this area.
This study has approvals form the following ethical review boards:
Edinburgh Medical School Research Ethics Committee West of Scotland Research Ethics Service (on behalf of NHS Health Research Authority) Health and Care Research Wales (on behalf of NHS Health Research Authority) Ghana Health Service Ethics Review Committee Comite de Investigacion, Hospital General San Juan de Dios, Guatemala, Guatemala Christian Medical College and Hospital, Institutional Ethics Committee, Ludhiana, India El Comite de Etica en Investigacion del Hospital General de Boca del Rio, Veracruz, Mexico Lagos University Teaching Hospital Health Research Ethics Committee, Lagos Nigeria Lagos State University Teaching Hospital Health Research Ethics Committee, Ikeja, Nigeria Obafemi Awolowo University Hospitals Teaching Complex, Ethics and Research Committee, Ife, Nigeria Ethics Committee of University Teaching Hospital of Kigali, Kigali, Rwanda
University of Edinburgh is the lead sponsor of 403 studies on the registry; 64 are open to participants now.
Counted across the registry records on this site, refreshed daily.
The study population are all patients undergoing a surgical procedure at the NIHR Global Health Research Unit on Global Surgery hubs/spoke hospitals in India, Nigeria, Ghana, Guatemala, Mexico, Rwanda, Benin and the United Kingdom that fit the eligibility criteria.
Participant Inclusion Criteria:
Participant Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
All surgical patients that fit the study eligibility criteria.
Device: Wearable Wireless Sensor
Stage III is a shadow mode evaluation of the device with participants wearing sensors pre-, intra-, and post-operatively. Sensor and clinical data will be collected contemporaneously in the clinical environment. No sensor data is made available to clinical teams for decision making, with no change in patient care.
Cardiovascular data from wearable device
Data includes core vital sign measures to assess the patient's cardiovascular function (e.g. heart rate in beats per minute), advanced indices (e.g., pulse arrival time, Heart Rate (HR) /Respiratory Rate (RR) quotient) and raw waveform data.
Time frame: 0-10 days from device application.
Respiratory data from wearable device
Data includes core vital sign measures to assess the patient's respiratory function (e.g. oxygen saturation as a percentage), advanced indices (e.g, Heart Rate (HR) /Respiratory Rate (RR) quotient) and raw waveform data.
Time frame: 0-10 days from device application.
Body temperature data from wearable device
Data includes core vital sign measures (e.g. temperature measurement in degrees centigrade), advanced indices, and raw waveform data.
Time frame: 0-10 days from device application.
Standard-of-care cardiovascular vital sign observation data
Standard-of-care vital sign observation data to assess cardiovascular function e.g. heart rate in beats per minute, blood pressure in mmHg at a frequency normally collected. These will be assessed as part of the National Early Warning Score 2 system (NEWS2) which a validated early warning score for detecting patient deterioration or equivalent in participating centers.
Time frame: 0-10 days from day of device application.
Standard-of-care respiratory vital sign observation data
Standard-of-care vital sign observation data to assess respiratory function e.g. respiratory rate in breaths per minute, oxygen saturations in percentage, at a frequency normally collected. These will be assessed as part of the National Early Warning Score 2 system (NEWS2) which a validated early warning score for detecting patient deterioration, or equivalent in participating centers.
Time frame: 0-10 days from day of device application.
Standard-of-care temperature vital sign observation data
Standard-of-care vital sign observation data to assess temperature e.g. in degrees centigrade or Fahrenheit, at a frequency normally collected. These will be assessed as part of the National Early Warning Score 2 system (NEWS2) which a validated early warning score for detecting patient deterioration or equivalent in participating centers.
Time frame: 0-10 days from day of device application.
Standard-of-care neurological observation data
Standard-of-care vital sign observation data to assess neurological function e.g. Alert Verbal Pain Unresponsive (AVPU) at a frequency normally collected. These will be assessed as part of the National Early Warning Score 2 system (NEWS2) which a validated early warning score for detecting patient deterioration or equivalent in participating centres.
Time frame: 0-10 days from day of device application.
Incidence of clinical complications during the study period
Incidence of clinical diagnosis data such as bleeding, major adverse cardiac event, sepsis will be derived from patient records and recorded and any uncertainty reviewed post hoc by an expert adjudication panel. Clinical complication data will also be gathered at 30 days.
Time frame: 0-10 days from the day of device application and then 30 day follow up will be performed.
Incidence of clinical investigations during the study period
The incidence of clinical investigations and descriptive details about the investigations will be derived from the patient records such as chest xray, CT abdomen, and wound swab.
Time frame: 0-10 days from the day of device application.
Incidence of clinical interventions during the study period
The incidence of clinical interventions performed and descriptive details, during the period of the device being worn will be recorded, e.g. commencement of antibiotics, unplanned admission to critical care, unplanned reoperation.
Time frame: 0-10 days from the day of device application.
Incidence and results of blood tests to assess patient physiological status during the study period
The incidence of blood tests will be recorded and the associated results from during the 10 day study period. Bloods tests recorded will include full blood count, urea and electrolytes, inflammatory markers, liver function tests and coagulation profile as well as blood gas results. They will be recorded using whichever the standard units are at participating centres.
Time frame: 0-10 days from the day of device application.
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