The Role of Wearable Devices in Predicting and Detecting Complications and Adverse Events
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 2,400
- 试验地点
- 1
- 主要终点
- Early detection of complications and adverse events using machine learning analysis of patient biometric data.
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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
排除标准
- •Individuals with mental incapacity and/or cognitive impairment that would preclude adequate understanding of, or cooperation with the study protocol.
- •Any pregnant participant.
研究组 & 干预措施
Treatment Group
Adults patients who are scheduled to undergo treatment for a benign or malignant condition and meet the inclusion and exclusion criteria.
干预措施: Device: Wearable Device (Device)
结局指标
主要结局
Early detection of complications and adverse events using machine learning analysis of patient biometric data.
时间窗: Five Years
Proportion of complications detected by the machine learning algorithm.
Prediction of the quality of recovery after treatment using patient biometric data.
时间窗: Four Years
Proportion of patients whose quality of recovery is correctly predicted by the machine learning algorithm.
次要结局
未报告次要终点
研究者
Chi-Fu Jeffrey Yang
MD
Massachusetts General Hospital