- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT07486258
ADVANCE-FORSEE. ADVANCEd Video Monitoring FOR Early Signaling of Adverse Events and Optimal dischargE Planning.
In this study cameras placed at the bedside will be evaluated for their ability to safely and accurately measure vital signs, such as heart rate and breathing, continuously after heart surgery. Camera-based measurements will be compared with the usual checks that nurses perform several times a day using sensors on the skin or finger clip.
The goal is to see whether camera monitoring can help notice changes in a patient's condition earlier. Another aim of the study is to find out whether the camera monitoring can predict if a patient's health is improving or worsening.
Patients and healthcare staff will be asked by the investigators about their experience to learn whether this type of monitoring is acceptable in daily care.
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Rationale: Over the past decades cardiothoracic surgery has advanced substantially resulting in reduced complication rates. However, when postoperative complications do occur they potentially can have a life-changing impact and sometimes even have death as a result. Therefore, timely detection of clinical deterioration is essential as early treatment may limit the severity of the complication and sometimes prevent their occurrence. The current method of vital signs monitoring, by nurses, usually 3 times a day, often leads to delayed detection of deterioration since early warning signs are missed and to standardized discharge protocols.
Objective: The primary objective of the ADVANCE FORSEE project is to evaluate the feasibility and acceptability of continuous video-based monitoring for early detection of postoperative deterioration as well as confirmation of uneventful recovery in cardiothoracic surgery patients. Secondary objectives are (1) to timely detect specific complications such as: atrial fibrillation, tamponade and acute coronary syndrome, (2) to assess the robustness of the video-based monitoring system, (3) to explore if additional physiological and other parameters can reliably be extracted and (4) to develop and evaluate a data management solution capable of efficiently handling large-scale video data.
Study design: Observational study, prospective for the data generation and retrospective for the data analysis. User-Centered Design with action research, allowing design and practice-oriented research to iteratively-reinforce each other.
Study population: 200-300 cardiac surgery patients.
Main study parameters/endpoints: The primary study endpoints are the performance of the deterioration detection and uneventful recovery algorithm assessed using a ROC-analysis. The secondary endpoints are (1) sensitivity, specificity and the time interval between algorithm-based deterioration detection and clinical confirmation by medical staff, (2) the accuracy of heart rate and respiratory rate for varying conditions, (3) the accuracy and feasibility of extracting additional parameters, (4) assessing the data management solution using RMSE as a function of bitrate across compression and storage models, (5) assessment of data loss, incorrect ROI detection and occlusion reported as percentages with 95% CI and compared to reference standards and (6) acceptability of the video-based monitoring system assessed by questionnaires, focus group and interviews.
Nature and extent of the burden and risks associated with participation, benefit and group relatedness: Participation to the study is not accompanied by clinical risk to the patient as the proposed technology is completely unobtrusive. Given the objective and hypothesis, the use of video-based monitoring in cardiac surgery patients has potential benefits to patients that outweigh the ethical constraints.
Furthermore, the technique has the potential to support Value-Based Health Care (VBHC) principles since it is expected to reduce the number of unexpected adverse events, better risk prediction, reduce hospital stay, reduce the workload of the nursing staff and hereby increase patient wellbeing by freeing up staff time for the patient.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Locations
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North Brabant
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Eindhoven, North Brabant, Netherlands, 5623 EJ
- Catharina Ziekenhuis Eindhoven
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Patients admitted to the cardiothoracic ward after cardiac surgery
- Age ≥ 18
- Willing and able to sign informed consent form
Exclusion Criteria:
- Pregnancy
- Inability to provide written informed consent
- Mental disability
- Language barrier
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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The primary study endpoints are the performance of the deterioration detection and uneventful recovery algorithms and the acceptability of the video-based monitoring system among healthcare staff and patients.
Time Frame: From arrival on the cardiothoracic surgery ward until discharge (typically 2-7 days after surgery).
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Algorithm performance will be assessed using receiver operating characteristics (ROC) analysis expressed as the area under the curve (AUC) with corresponding 95% confidence intervals.
As a comparison a ROC curve will be made based on the conventional EWS data.
Sensitivity, specificity, positive and negative predictive value will be calculated accordingly.
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From arrival on the cardiothoracic surgery ward until discharge (typically 2-7 days after surgery).
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Sensitivity, specificity and time interval between algorithm-based detection and clinical confirmation.
Time Frame: From arrival on the cardiothoracic surgery ward until discharge (typically 2-7 days after surgery).
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Agreement between algorithm-based detection and clinical confirmation of postoperative complications.
Sensitivity, specificity, and the time interval between the algorithm detection and confirmation by medical staff for events such as atrial fibrillation, acute coronary syndrome, tamponade, and other complications will be assessed.
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From arrival on the cardiothoracic surgery ward until discharge (typically 2-7 days after surgery).
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Accuracy and data coverage of video-derived heart rate and respiratory rate measurements under varying conditions.
Time Frame: From arrival on the cardiothoracic surgery ward until discharge (typically 2-7 days after surgery).
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Accuracy of video-derived heart rate and respiratory rate are compared with telemetry measurements under varying conditions.
Data coverage is defined as the proportion of the monitoring period with usable video-based data.
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From arrival on the cardiothoracic surgery ward until discharge (typically 2-7 days after surgery).
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Accuracy and feasibility of extracting physiological and behavioral parameters such as oxygen saturation, eye movement, paleness and patient movement using the camera monitoring system.
Time Frame: From arrival on the cardiothoracic surgery ward until discharge (typically 2-7 days after surgery).
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Accuracy and feasibility of video-derived metrics including oxygen saturation, eye movement, paleness and patient movement using the camera monitoring system will be evaluated by comparing camera-based measurements with reference clinical measurements (telemetry-based monitoring) and clinical staff assessments.
Measurement validity will be expressed using metrics such as sensitivity, specificity, correlation coefficients and agreement rates.
Feasibility will be assessed based on the proportion of usable recordings and successful parameters extractions during postoperative monitoring.
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From arrival on the cardiothoracic surgery ward until discharge (typically 2-7 days after surgery).
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Performance of the data management solution
Time Frame: From arrival on the cardiothoracic surgery ward until discharge (typically 2-7 days after surgery).
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Performance is evaluated by calculating the RMSE of vital sign measurements using various data-management techniques.
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From arrival on the cardiothoracic surgery ward until discharge (typically 2-7 days after surgery).
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Quantitative assessment of acceptability of the video-based monitoring
Time Frame: At postoperative day 5 or at hospital discharge whichever occurs first.
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Quantitative assessment of the acceptability of the video-based monitoring in terms of privacy, comfort, feeling of safety, ease of use and trust in the system will be assessed using structured questionnaires (Likert scale).
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At postoperative day 5 or at hospital discharge whichever occurs first.
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Qualitative assessment of acceptability of the video-based monitoring
Time Frame: At postoperative day 5 or at hospital discharge whichever occurs first.
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Qualitative assessment of the acceptability of the video-based monitoring in terms of privacy, comfort, feeling of safety, ease of use and trust in the system using semi-structured interviews and focus groups.
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At postoperative day 5 or at hospital discharge whichever occurs first.
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Collaborators and Investigators
Study record dates
Study Major Dates
Study Start (Estimated)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Other Study ID Numbers
- ADVANCE_FORSEE_1
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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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