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.
Patients admitted to the cardiothoracic ward after cardiac surgery
Age ≥ 18
Willing and able to sign informed consent form
Pregnancy
Inability to provide written informed consent
Mental disability
Language barrier
The intended population for this study will be cardiac surgery patients admitted to the cardiothoracic ward of the Catharina hospital in Eindhoven. The research team will approach eligible patients who are scheduled to undergo cardiac surgery, in collaboration with the cardiothoracic surgeons. Due to the limited number of rooms equipped with the video-monitoring technology, patient placement on these rooms will be supported by the EuroSCORE II. When a room with the video-monitoring equipment is available, the EuroSCORE II ranking can be used as guidance by the day coordinator of the CTC to assign the room to an incoming patient with the highest estimated operative risk. Final room allocation will remain the responsibility of the CTC day coordinator.
Case-only
Prospective
Camera-based monitoring technology
DeviceParticipants will be continuously monitored with multiple video cameras placed in their room on cardiothoracic surgery ward. The cameras record RGB, NIR and thermal video to allow extraction of vital signs and other non-regulated parameters. No physical contact or additional procedures are required and all usual clinical care continues as normal.
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.
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.
Sensitivity, specificity and time interval between algorithm-based detection and clinical confirmation.
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.
Accuracy and data coverage of video-derived heart rate and respiratory rate measurements under varying conditions.
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.
Accuracy and feasibility of extracting physiological and behavioral parameters such as oxygen saturation, eye movement, paleness and patient movement using the camera monitoring system.
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.
Performance of the data management solution
Performance is evaluated by calculating the RMSE of vital sign measurements using various data-management techniques.
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Catharina Ziekenhuis Eindhoven
Lead sponsor
ZonMw: The Netherlands Organisation for Health Research and Development
Collaborator
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