Recovery, Treatment Complication
Conditions
Brief summary
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.
Detailed description
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.
Interventions
DEVICEDevice: Wearable 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.
Sponsors
Massachusetts General Hospital
Case Western Reserve University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. Age 18 years or older 2. 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. 3. Amenable to using one of the wearable devices of interest (Fitbit, iWatch, Biostrap). 4. 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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Early detection of complications and adverse events using machine learning analysis of patient biometric data. | Five Years | Proportion of complications detected by the machine learning algorithm. |
| Prediction of the quality of recovery after treatment using patient biometric data. | Four Years | Proportion of patients whose quality of recovery is correctly predicted by the machine learning algorithm. |
Countries
United States
Contacts
CONTACTChi-Fu Jeffrey Yang, MD
CONTACTIsha Mehta Warikoo, MD
PRINCIPAL_INVESTIGATORChi-Fu Jeffrey Yang
Massachusetts General Hospital
Outcome results
None listed