We're building a better ClinicalTrials.gov. Check it out and tell us what you think!
Working…
ClinicalTrials.gov
ClinicalTrials.gov Menu

Covid-19 Triage Using Camera-based AI

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04383457
Recruitment Status : Completed
First Posted : May 12, 2020
Last Update Posted : December 1, 2020
Sponsor:
Collaborator:
Detectivio AB
Information provided by (Responsible Party):
Vastra Gotaland Region

Brief Summary:

The vital signs are critical in assessing the severity and prognosis of infections, such as Covid-19. The devices used today for measuring the vital signs have to be in physical contact with the patients. There is an apparent risk of transferring infections from one patient to the next (or to healthcare professionals).

This project aims to evaluate a new camera-based system for contactless measurement of vital signs as well as an artificial intelligence (AI) predicting hospitalization or death within 30 days. This particular study will evaluate the new system's ability without interfering with standard care of the patient.


Condition or disease Intervention/treatment
Coronavirus Infections Device: RIA-device (Remote Investigation and Assessment)

Detailed Description:

Background and aim:

The vital signs are critical in assessing the severity and prognosis of infections, i.e., Covid-19, influenza, sepsis and pneumonia. Quick and accurate triage is critical when facing a pandemic with an overwhelming number of cases (confirmed and suspected). This study aims a) to evaluate a new method for rapid camera-based non-contact measurement of five vital signs; body temperature, heart rate, blood oxygen saturation, respiratory rate, and blood pressure, and b) if an AI can predict hospitalization or death within 30 days.

Methods:

A method-comparison study design is used comparing each vital sign measured with the new method to the corresponding standard reference method. Furthermore, a cohort design is used to follow up any hospitalization or death within 30 days. The investigated new system consists of a high-speed digital video camera, a digital radiometric infrared camera, LED lights and a computer for data recording. This system faces the subject at a distance of approximately one meter, capturing a 30 second recording of the subject's face. First, all vital signs will be measured using one set of reference devices. Secondly the investigated device will record a 30 second video of the patient's face. Thirdly, and last, all vital signs will be measured using the same set of reference devices. A copy of the vital sign readings (using the standard reference methods) will be handed over by an investigator to the clinical professionals responsible for the subsequent medical care for each subject. Afterwards, the collected 30-second recordings will be run through specific software algorithms to extract the vital signs. The results from the new camera-based contactless measurement of vital signs and the outcome of the AIs prediction of risk for hospitalization or death will not be presented in the care situation of the patient.

Expected Findings:

It is expected that the proposed study will show that the new method can estimate body temperature, heart rate, respiratory rate, blood oxygen level, and blood pressure with an acceptable agreement compared with the reference method and also estimate hospitalization or death within 30 days.

Implications of the expected findings:

Being able to measure vital signs quicker than before by using a new contactless method would greatly facilitate triage of large number of patients. Also being able to predict hospitalization or increased risk for death would further improve the triage of patients.

Layout table for study information
Study Type : Observational [Patient Registry]
Actual Enrollment : 214 participants
Observational Model: Cohort
Time Perspective: Prospective
Target Follow-Up Duration: 30 Days
Official Title: Covid-19 Triage Using Camera-based AI
Actual Study Start Date : June 15, 2020
Actual Primary Completion Date : October 8, 2020
Actual Study Completion Date : October 8, 2020

Resource links provided by the National Library of Medicine



Intervention Details:
  • Device: RIA-device (Remote Investigation and Assessment)
    The investigated new system consists of a high-speed digital video camera, a digital radiometric infrared camera, LED lights and a computer for data recording. This system faces the subject at a distance of approximately one meter, capturing a 30 second recording of the subject's face.


Primary Outcome Measures :
  1. Agreement between the new camera based method and reference standard to estimate body temperature [ Time Frame: Two minutes between measurements ]
    Body temperature will be measured with the new camera based method as well as with a conventional ear thermometer. Both measurements will estimate the body temperature in degrees Celsius. The agreement between body temperature estimated with the new method and the reference method will be made using the statistical methods Bland-Altman plots and limits of agreement as the outcome.

  2. Agreement between the new camera based method and reference standard to estimate heart rate [ Time Frame: Two minutes between measurements ]
    Heart rate will be measured with the new camera based method as well as with a conventional apparatus for measuring pulse rate. Both measurements will estimate the heart rate in beats per minute. The agreement between body temperature estimated with the new method and the reference method will be made using the statistical methods Bland-Altman plots and limits of agreement as the outcome.

  3. Agreement between the new camera based method and reference standard to estimate blood oxygen saturation [ Time Frame: Two minutes between measurements ]
    Blood oxygen saturation will be measured with the new camera based method as well as with a conventional apparatus for measuring blood oxygen saturation. Both measurements will estimate the blood oxygen saturation in percent (ranging from 0-100%). The agreement between blood oxygen saturation estimated with the new method and the reference method will be made using the statistical methods Bland-Altman plots and limits of agreement as the outcome.

  4. Agreement between the new camera based method and reference standard to estimate systolic blood pressure [ Time Frame: Two minutes between measurements ]
    Systolic blood pressure will be measured with the new camera based method as well as with a conventional apparatus for measuring systolic blood pressure. Both measurements will estimate the systolic blood pressure in mm Hg. The agreement between systolic blood pressure estimated with the new method and the reference method will be made using the statistical methods Bland-Altman plots and limits of agreement as the outcome.

  5. Agreement between the new camera based method and reference standard to estimate diastolic blood pressure [ Time Frame: Two minutes between measurements ]
    Diastolic blood pressure will be measured with the new camera based method as well as with a conventional apparatus for measuring diastolic blood pressure. Both measurements will estimate the diastolic blood pressure in mm Hg. The agreement between diastolic blood pressure estimated with the new method and the reference method will be made using the statistical methods Bland-Altman plots and limits of agreement as the outcome.

  6. Agreement between the new camera based method and reference standard to estimate respiratory rate [ Time Frame: Two minutes between measurements ]
    Respiratory rate will be measured with the new camera based method as well as manually using a stethoscope. Both measurements will estimate the respiratory rate in breath per minute. The agreement between respiratory rate estimated with the new method and the reference method will be made using the statistical methods Bland-Altman plots and limits of agreement as the outcome.


Secondary Outcome Measures :
  1. Prediction of hospital admission using vital signs estimated using reference standard methods [ Time Frame: Hospital admission for any cause up until 30 days after inclusion ]
    An artificial intelligence (AI) algorithm will use 75% of patient observations of vital signs for training and the remaining 25% will be used to test the AIs predictive capabilities to predict hospital admission within 30 days. For each patient the AI will produce a probability (0-100%) for hospital admission within 30 days. These probabilities will undergo a receiver operating (ROC) analysis where area under curve (AUC) with 95% confidence interval will be the reported outcome measure.

  2. Prediction of death using vital signs estimated using reference standard methods [ Time Frame: Death for any cause up until 30 days after inclusion ]
    An artificial intelligence (AI) algorithm will use 75% of patient observations of vital signs for training and the remaining 25% will be used to test the AIs predictive capabilities to predict death within 30 days. For each patient the AI will produce a probability (0-100%) for death within 30 days. These probabilities will undergo a receiver operating (ROC) analysis where area under curve (AUC) with 95% confidence interval will be the reported outcome measure.

  3. Prediction of hospital admission using vital signs estimated using the new camera based method [ Time Frame: Hospital admission for any cause up until 30 days after inclusion ]
    An artificial intelligence (AI) algorithm will use 75% of patient observations of vital signs for training and the remaining 25% will be used to test the AIs predictive capabilities to predict hospital admission within 30 days. For each patient the AI will produce a probability (0-100%) for hospital admission within 30 days. These probabilities will undergo a receiver operating (ROC) analysis where area under curve (AUC) with 95% confidence interval will be the reported outcome measure.

  4. Prediction of death using vital signs estimated using the new camera based method [ Time Frame: Death for any cause up until 30 days after inclusion ]
    An artificial intelligence (AI) algorithm will use 75% of patient observations of vital signs for training and the remaining 25% will be used to test the AIs predictive capabilities to predict death within 30 days. For each patient the AI will produce a probability (0-100%) for hospitalization within 30 days. These probabilities will undergo a receiver operating (ROC) analysis where area under curve (AUC) with 95% confidence interval will be the reported outcome measure.

  5. Prediction of hospital admission using raw camera data [ Time Frame: Hospital admission for any cause up until 30 days after inclusion ]
    An artificial intelligence (AI) algorithm will use 75% of patient observations of raw camera data for training and raw data from the remaining 25% of patients will be used to test the AIs predictive capabilities to predict hospital admission within 30 days. For each patient the AI will produce a probability (0-100%) for hospital admission within 30 days. These probabilities will undergo a receiver operating (ROC) analysis where area under curve (AUC) with 95% confidence interval will be the reported outcome measure.

  6. Prediction of death using raw camera data [ Time Frame: Death for any cause up until 30 days after inclusion ]
    An artificial intelligence (AI) algorithm will use 75% of patient observations of raw camera data for training and raw data from the remaining 25% of patients will be used to test the AIs predictive capabilities to predict death within 30 days. For each patient the AI will produce a probability (0-100%) for death within 30 days. These probabilities will undergo a receiver operating (ROC) analysis where area under curve (AUC) with 95% confidence interval will be the reported outcome measure.



Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.


Layout table for eligibility information
Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Adult patients attending the emergency department at Östra sjukhuset Gothenburg for a suspected infection.
Criteria

Inclusion Criteria:

  1. The patient is attending for triage presenting with symptoms of an infection.
  2. Subject has provided informed consent
  3. Age ≥18 years
  4. Fluent in Swedish (reading, writing, conversational)
  5. Mental state is such that he or she is able to understand and give informed consent to participation in the study by signing the Information and Consent Form
  6. The investigator determines that the new method, and the reference methods, can be used as intended with adequate reliability and safety
  7. The time for investigations in this study is estimated to approximately 15-20 minutes. Vital signs will be handed over to the care provider responsible for the further management of the patient saving approximately 5-10 minutes of their time. Hence, the delay in the management of each patient introduced by this study is approximately 10 minutes. Patients deemed being in such a severe medical condition on arrival, that 10 minutes of delay is deemed detrimental will not be included.

Exclusion Criteria:

  1. Depressed level of consciousness from inclusion up until all investigations are completed (during approximately 15-20 minutes).
  2. Patient request to be withdrawn from the study.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04383457


Locations
Layout table for location information
Sweden
Östra Sjukhuset
Gothenburg, Sweden
Sponsors and Collaborators
Vastra Gotaland Region
Detectivio AB
Investigators
Layout table for investigator information
Principal Investigator: Ronny K Gunnarsson, MD PhD Primary Health care, Regionhalsan, Region Vastra Gotaland, Sweden
Publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):
Layout table for additonal information
Responsible Party: Vastra Gotaland Region
ClinicalTrials.gov Identifier: NCT04383457    
Other Study ID Numbers: U1111-1251-4114
First Posted: May 12, 2020    Key Record Dates
Last Update Posted: December 1, 2020
Last Verified: November 2020
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: Yes
Plan Description: De-identified data from patients observations
Supporting Materials: Study Protocol
Statistical Analysis Plan (SAP)
Time Frame: It will be made available upon final publication
Access Criteria: A complete de-identified data set will be made made publicly available in a data repository. The exact data-repository is not yet decided.

Layout table for additional information
Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Vastra Gotaland Region:
Vital signs
Pulse
Blood pressure
Respiratory rate
Oxygen saturation
Temperature
Additional relevant MeSH terms:
Layout table for MeSH terms
Coronavirus Infections
Coronaviridae Infections
Nidovirales Infections
RNA Virus Infections
Virus Diseases
Infections