RecruitingNot Applicable

The Role of Wearable Devices in Cardiothoracic Surgery: Predicting and Detecting Early Postoperative Complications

United States1,200 participantsStarted 2021-07-10

Plain-language summary

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

Who can participate

Age range18 Years

SexALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

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

What they're measuring

Early detection of postoperative complications using machine learning analysis of patient biometric data.

Timeframe: Four Years

Prediction of the quality of postoperative recovery using pre- and intraoperative data.

Timeframe: Four Years

Trial details

NCT IDNCT04824066

SponsorMassachusetts General Hospital

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2029-01-01

Contact for this trial

Chi-Fu Jeffrey Yang, MD

617-726-5200 cjyang@mgh.harvard.edu

View on ClinicalTrials.gov More Surgery--Complications trials