The Role of Wearable Devices in Predicting and Detecting Complications and Adverse Events
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Device: Wearable Device.
- Who it may be relevant to
- Registry conditions: Recovery, Treatment Complication. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United States
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
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
- Device Device: 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.
Primary outcome measures
- Early detection of complications and adverse events using machine learning analysis of patient biometric data. [Time frame: Five Years]
- Prediction of the quality of recovery after treatment using patient biometric data. [Time frame: Four Years]
Eligibility criteria
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.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
United States · 1 center
- Massachusetts General Hospital — Boston
Publications
- Wang D, Fang Z, Zhu A, Rettner B, Potter AL, McCarthy M, Zhang L, Kim J, Zhang Y, Powell J, Pope A, Beqari J, Cranor J, Smock G, Warikoo IM, Aaron A, Guo Q, Hanna G, Mitri J, Zarif M, Melki A, Wilkins I, Lin MW, Lee H, Costantino C, Furlow PW, Sachdeva UM, Auchincloss HG, Wright C, Lanuti M, Li X, Jeffrey Yang CF. Changes in patient-reported quality of life after lobectomy versus sublobar resectio PMID 41213469
Identifiers
NCT: NCT04824066 · 2020P002984