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Wearable Device-Based Early Warning of Postoperative Complications in Thoracic Surgery (wearable)

2026年6月12日 更新者：Zhang Ni、Tongji Hospital

Development and Validation of a Wearable Device-Based Early Warning Model for Postoperative Complications in Thoracic Surgery: A Retrospective and Prospective Cohort Study

After thoracic surgery, some patients may develop complications such as lung infection, abnormal heart rhythm, fluid around the lung, prolonged air leak, wound infection, emergency department visits, or hospital readmission. These problems may not be found early if monitoring is only done during routine vital sign checks or follow-up visits.

This study will evaluate whether data collected by a wearable device can help identify early warning signs of postoperative complications in patients undergoing thoracic surgery. The wearable device will collect information such as heart rate, oxygen level, skin temperature, physical activity, sleep, and wearing status.

The study includes two parts. First, the researchers will review previously collected wearable device and medical record data to develop an early warning model. Second, new patients undergoing thoracic surgery will wear the device from hospital admission until about 30 days after discharge. The model will then be tested to see how well it predicts complications that require medical intervention within 30 days after surgery.

The main goal is to evaluate how accurately the wearable device-based model can identify patients who develop postoperative complications and how early the model can provide a warning before the complication is clinically confirmed.

研究概览

地位

招聘中

条件

干预/治疗

详细说明

Postoperative complications are an important concern after thoracic surgery. Conventional perioperative monitoring mainly relies on intermittent vital sign measurements, nursing assessments, physician rounds, and routine post-discharge follow-up. This approach may miss short-lasting, nighttime, or activity-related physiological changes that occur before a complication becomes clinically apparent.

Wearable devices can continuously collect physiological and behavioral information, including heart rate, oxygen saturation, skin temperature, activity, sleep, and wearing status. Combining these data with electronic medical record information may help identify early changes associated with postoperative complications.

This study uses a retrospective and prospective cohort design. In the retrospective stage, previously collected wearable device data and electronic medical record data from thoracic surgery patients will be analyzed. The researchers will evaluate the agreement between wearable device measurements and routine clinical vital signs, describe physiological signal patterns before postoperative complications, and develop a preliminary early warning model.

In the prospective validation stage, newly enrolled patients scheduled for thoracic surgery will wear the study wearable device from hospital admission to approximately 30 days after discharge. The early warning model developed from the retrospective data will be applied prospectively using predefined parameters. Model-generated warnings will be recorded. The occurrence of postoperative complications will be verified through inpatient medical records and follow-up after discharge.

The primary reference outcome is postoperative complications requiring medical intervention within 30 days after surgery. These complications may include pulmonary infection, pleural effusion requiring treatment, prolonged air leak, wound infection, postoperative arrhythmia, emergency department visit, or readmission. Model performance will be evaluated using sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and warning lead time. Wearable device adherence, data completeness, and the added predictive value of wearable device-derived features beyond routine clinical variables will also be assessed.

研究类型

观察性的

注册 (估计的)

650

联系人和位置

本节提供了进行研究的人员的详细联系信息，以及有关进行该研究的地点的信息。

学习联系方式

学习地点

  • 中国
    • Hubei
      • Wuhan、Hubei、中国、430030
        • 招聘中
        • Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
        • 接触：

参与标准

研究人员寻找符合特定描述的人，称为资格标准。这些标准的一些例子是一个人的一般健康状况或先前的治疗。

资格标准

适合学习的年龄

  • 成人
  • 年长者

接受健康志愿者

不

取样方法

非概率样本

研究人群

The study population includes adult patients aged 18 years or older who are hospitalized in the Department of Thoracic Surgery of Tongji Hospital and are scheduled to undergo thoracic surgery. Eligible patients should be able to wear the study-designated wearable device after hospital admission and are expected to continue wearing the device and/or uploading data within 30 days after discharge.

描述

Inclusion Criteria:

  1. Age 18 years or older.
  2. Hospitalized in the Department of Thoracic Surgery of Tongji Hospital and scheduled to undergo thoracic surgery.
  3. Able to wear the study-designated wearable device after hospital admission and expected to continue wearing the device and/or uploading data within 30 days after discharge.

Exclusion Criteria:

  1. Patients or family members are unwilling to wear the wearable device or unable to meet the required wearing time.
  2. Severe or unstable psychiatric disease, such as severe depression or schizophrenia.
  3. Pregnancy or lactation.
  4. Allergy to the watch strap material or local skin conditions that prevent wearing the device.
  5. Unable to complete follow-up within 30 days after discharge.

学习计划

本节提供研究计划的详细信息，包括研究的设计方式和研究的衡量标准。

研究是如何设计的？

设计细节

队列和干预

团体/队列
干预/治疗
Retrospective Cohort
Patients who previously underwent thoracic surgery and had available wearable device data and electronic medical record data during the perioperative period. This cohort will be used to evaluate agreement between wearable device measurements and routine clinical vital signs, analyze physiological signal trajectories before postoperative complications, and develop a preliminary early warning model.
设备：Wearable device-based perioperative monitoring
Participants will wear a study wearable device that continuously collects physiological and behavioral data, including heart rate, oxygen saturation, skin temperature, activity, sleep, and wearing status, from hospital admission to approximately 30 days after discharge. The device is used for monitoring and data collection and does not change routine clinical care.
Prospective Validation Cohort
Newly enrolled patients scheduled for thoracic surgery who will wear the study wearable device from hospital admission to approximately 30 days after discharge. This cohort will be used to prospectively validate the wearable device-based early warning model for postoperative complications within 30 days after surgery.
设备：Wearable device-based perioperative monitoring
Participants will wear a study wearable device that continuously collects physiological and behavioral data, including heart rate, oxygen saturation, skin temperature, activity, sleep, and wearing status, from hospital admission to approximately 30 days after discharge. The device is used for monitoring and data collection and does not change routine clinical care.

研究衡量的是什么？

主要结果指标

结果测量
措施说明
大体时间
Area under the receiver operating characteristic curve of the wearable device-based early warning model for 30-day postoperative complications
大体时间：From the day of surgery to 30 days after surgery
The area under the receiver operating characteristic curve will be used to evaluate the ability of the wearable device-based early warning model to distinguish participants who develop postoperative complications requiring medical intervention within 30 days after surgery from those who do not. Postoperative complications may include pulmonary infection, pleural effusion requiring treatment, prolonged air leak, wound infection, postoperative arrhythmia, emergency department visit, or hospital readmission.
From the day of surgery to 30 days after surgery

次要结果测量

结果测量
措施说明
大体时间
Warning lead time before clinically confirmed postoperative complications
大体时间：From the day of surgery to 30 days after surgery
Warning lead time will be defined as the time interval between the first model-generated warning signal and the clinical confirmation of a postoperative complication requiring medical intervention.
From the day of surgery to 30 days after surgery
Sensitivity of the wearable device-based early warning model for 30-day postoperative complications
大体时间：From the day of surgery to 30 days after surgery
Sensitivity will be defined as the proportion of participants with postoperative complications requiring medical intervention within 30 days after surgery who are correctly identified by the wearable device-based early warning model.
From the day of surgery to 30 days after surgery
Specificity of the wearable device-based early warning model for 30-day postoperative complications
大体时间：From the day of surgery to 30 days after surgery
Specificity will be defined as the proportion of participants without postoperative complications requiring medical intervention within 30 days after surgery who are correctly classified as not having a warning signal by the wearable device-based early warning model.
From the day of surgery to 30 days after surgery

合作者和调查者

在这里您可以找到参与这项研究的人员和组织。

赞助

Tongji Hospital

研究记录日期

这些日期跟踪向 ClinicalTrials.gov 提交研究记录和摘要结果的进度。研究记录和报告的结果由国家医学图书馆 (NLM) 审查，以确保它们在发布到公共网站之前符合特定的质量控制标准。

研究主要日期

学习开始 (实际的)

2025年12月16日

初级完成 (估计的)

2026年11月30日

研究完成 (估计的)

2026年12月15日

研究注册日期

首次提交

2026年6月9日

首先提交符合 QC 标准的

2026年6月12日

首次发布 (实际的)

2026年6月15日

研究记录更新

最后更新发布 (实际的)

2026年6月15日

上次提交的符合 QC 标准的更新

2026年6月12日

最后验证

2026年6月1日

更多信息

与本研究相关的术语

关键字

其他相关的 MeSH 术语

其他研究编号

  • TJ-IRB202512090 (其他标识符：Medical Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology)

计划个人参与者数据 (IPD)

计划共享个人参与者数据 (IPD)？

不

IPD 计划说明

No individual participant data will be shared because the study data include wearable device monitoring data and clinical information from electronic medical records, which may contain sensitive health information. Only aggregate results will be reported.

药物和器械信息、研究文件

研究美国 FDA 监管的药品

不

研究美国 FDA 监管的设备产品

不

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