The Role of Wearable Devices in Predicting and Detecting Complications and Adverse Events
Ориентир для пациента и семьи
Простыми словами
Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.
- Что изучают
- В протоколе указаны: Device: Wearable Device.
- Кому может быть актуально
- Состояния в реестре: Recovery, Treatment Complication. Базовые параметры: от 18 лет · Все.
- Что важно проверить
- Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
- Где проводится
- США
- Следующий шаг
- Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →
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Обзор
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.
Подробное описание
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.
Вмешательства
- Устройство 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.
Первичные конечные точки
- Early detection of complications and adverse events using machine learning analysis of patient biometric data. [Срок оценки: Five Years]
- Prediction of the quality of recovery after treatment using patient biometric data. [Срок оценки: Four Years]
Критерии участия
Критерии включения
- 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
Критерии исключения
- Individuals with mental incapacity and/or cognitive impairment that would preclude adequate understanding of, or cooperation with the study protocol.
- Any pregnant participant.
Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.
Здоровые добровольцы: Нет
Дизайн исследования
- Модель наблюдения
- Когортное
Центры проведения
США · 1 центр
- Massachusetts General Hospital — Boston
Публикации
- 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
Идентификаторы
NCT: NCT04824066 · 2020P002984