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

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

Study Contact Backup

Study Locations

    • Massachusetts
      • Boston, Massachusetts, United States, 02114
        • Recruiting
        • Massachusetts General Hospital
        • Contact:

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:

  1. 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).
  2. Individuals willing to provide informed consent and who have capacity for all study procedures

Exclusion Criteria:

  1. Individuals with mental incapacity and/or cognitive impairment that would preclude adequate understanding of, or cooperation with the study protocol.
  2. Any pregnant participant.
  3. Severe irreversible pulmonary hypertension.
  4. Congenital heart disease
  5. Chronic renal insufficiency or undergoing chronic renal replacement therapy
  6. 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.

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.

Clinical Trials on Surgery--Complications

Clinical Trials on Device: Wearable Device

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