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NCT Number: NCT04824066

The Role of Wearable Devices in Predicting and Detecting Complications and Adverse Events

The overarching goal of this research is to use machine learning analysis of high-resolution data-collected by wearable technology-to predict complications and poor recovery in patients undergoing treatment for benign or malignant conditions.

Recruiting

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Massachusetts General Hospital

Boston, Massachusetts, 02114, United States

Location status: Recruiting

Location contact

Chi-Fu J Yang, M.D.

CONTACT

[email protected]

814-574-8695

About this study

This is a multi-center non-randomized prospective cohort study using wearable devices and machine learning to predict complications and poor recovery in patients undergoing treatment for benign or malignant conditions.

Patients 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 2,400 subjects are enrolled. At ~30 days before treatment the subjects will have a wearable device (such as a Fitbit) placed on their wrist and will wear the device for up to 5 years following treatment. 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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age 18 years or older
  • Individuals scheduled to undergo one of the following surgical or non-surgical treatments: cardiothoracic surgery, orthopedic surgery, vascular surgery, colorectal surgery, pancreatic surgery, other major abdominal surgeries, treatment for chronic disease, or systemic therapy (i.e., chemotherapy, immunotherapy, or targeted therapy), radiotherapy, or ablation.
  • 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.

Treatment and study plan

Device: Wearable Device

Device

A Wearable Device will be placed on the wrist of the patient ~30 days prior to the patient's scheduled treatment and for up to 5 years following treatment. The device will record activity in terms of steps, sleep quality, heart rate, etc.

Primary outcomes

  1. Early detection of complications and adverse events using machine learning analysis of patient biometric data.

    Time frame: Five Years

    Proportion of complications detected by the machine learning algorithm.

  2. Prediction of the quality of recovery after treatment using patient biometric data.

    Time frame: Four Years

    Proportion of patients whose quality of recovery is correctly predicted by the machine learning algorithm.

Study contacts

Contact information is provided by the study sponsor or research team.

Chi-Fu Jeffrey Yang, MD

CONTACT

[email protected]

617-726-5200

Isha Mehta Warikoo, MD

CONTACT

[email protected]

857-250-1355

Sponsors and collaborators

Lead sponsor

Massachusetts General Hospital

Other

Collaborators

  • Case Western Reserve University

Registry information

Important dates

Study start
2021
Primary completion
2029
Study completion
2029
First posted
Apr 1, 2021
Registry last updated
May 28, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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