- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04824066
The Role of Wearable Devices in Cardiothoracic Surgery: Predicting and Detecting Early Postoperative Complications
June 9, 2023 updated by: Chi-Fu Jeffrey Yang, Massachusetts General Hospital
The overarching goal of this research is to use machine learning analysis of high-resolution data-collected by wearable technology-of cardiothoracic surgical patients to assess recovery and detect complications at their earliest stage
Study Overview
Status
Recruiting
Conditions
Intervention / Treatment
Detailed Description
This is a single-center non-randomized prospective cohort study using wearable devices in cardiothoracic surgery patients to detect post-operative complications.
Patients undergoing cardiothoracic surgery who meet the inclusion and exclusion criteria will be enrolled consecutively with verbal informed consent from the time this protocol is approved by the IRB until 1,200 subjects are enrolled.
At ~30 days preoperatively the subjects will have a wearable device (such as a Fitbit) placed on their wrist and will wear the device until ~180 days post-operatively.
This device will wirelessly transmit data regarding activity and sleep quality to a smartphone application for the duration of wear and data will be analyzed by our collaborators at Case Western Reserve University.
Study Type
Observational
Enrollment (Estimated)
1200
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: Chi-Fu Jeffrey Yang, MD
- Phone Number: 617-726-5200
- Email: cjyang@mgh.harvard.edu
Study Contact Backup
- Name: Isha Mehta Warikoo, MD
- Phone Number: 857-250-1355
- Email: imehtawarikoo@mgh.harvard.edu
Study Locations
-
-
Massachusetts
-
Boston, Massachusetts, United States, 02114
- Recruiting
- Massachusetts General Hospital
-
Contact:
- Chi-Fu J Yang, M.D.
- Phone Number: 814-574-8695
- Email: cjyang@mgh.harvard.edu
-
-
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
18 years and older (Adult, Older Adult)
Accepts Healthy Volunteers
No
Sampling Method
Non-Probability Sample
Study Population
Patients undergoing cardiothoracic surgery that are amenable to wearing a device of interest and meet the inclusion and exclusion criteria above will be approached for informed consent.
Description
Inclusion Criteria:
- Age 18 years or older undergoing cardiothoracic surgery that is male or a non-pregnant female and are amenable to using one of the wearable devices of interest (Fitbit, iWatch, Biostrap).
- Individuals willing to provide informed consent and who have capacity for all study procedures
Exclusion Criteria:
- Individuals with mental incapacity and/or cognitive impairment that would preclude adequate understanding of, or cooperation with the study protocol.
- Any pregnant participant.
- Severe irreversible pulmonary hypertension.
- Congenital heart disease
- Chronic renal insufficiency or undergoing chronic renal replacement therapy
- Liver cirrhosis
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
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
Cardiothoracic Surgery Cohort
Adults patients who are scheduled to undergo cardiothoracic surgery and meet the inclusion and exclusion criteria.
|
A Wearable Device will be placed on the wrist of the patient ~30 days prior to the patient's scheduled surgery, removed during the operation, and replaced for ~180 days post-operatively.
The device will record activity in terms of steps, sleep quality, heart rate, etc.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Early detection of postoperative complications using machine learning analysis of patient biometric data.
Time Frame: Four Years
|
Proportion of complications detected by the machine learning algorithm.
|
Four Years
|
Prediction of the quality of postoperative recovery using pre- and intraoperative data.
Time Frame: Four Years
|
Proportion of patients whose quality of postoperative recovery is correctly predicted by the machine learning algorithm.
|
Four Years
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Collaborators
Investigators
- Principal Investigator: Chi-Fu Jeffrey Yang, Massachusetts General Hospital
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)
July 10, 2021
Primary Completion (Estimated)
January 1, 2026
Study Completion (Estimated)
June 30, 2027
Study Registration Dates
First Submitted
March 11, 2021
First Submitted That Met QC Criteria
March 26, 2021
First Posted (Actual)
April 1, 2021
Study Record Updates
Last Update Posted (Estimated)
June 13, 2023
Last Update Submitted That Met QC Criteria
June 9, 2023
Last Verified
June 1, 2023
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 2020P002984
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
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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