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审核状态: Project audit state: |
通过审核 Successful |
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注册号: Registration number: |
ChiCTR2300079175 |
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最近更新日期: Date of Last Refreshed on: |
2023-12-26 17:45:01 |
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注册时间: Date of Registration: |
2023-12-26 00:00:00 |
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注册号状态: |
预注册 |
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Registration Status: |
Prospective registration |
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注册题目: |
基于可解释机器学习算法预测无痛胃镜检查患者镇静相关不良事件 |
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Public title: |
Predicting Sedation-Related Adverse Events in Patients Undergoing Painless Gastroscopy Based on Explainable Machine Learning Algorithms |
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注册题目简写: |
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English Acronym: |
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研究课题的正式科学名称: |
基于可解释机器学习算法预测无痛胃镜检查患者镇静相关不良事件 |
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Scientific title: |
Predicting Sedation-Related Adverse Events in Patients Undergoing Painless Gastroscopy Based on Explainable Machine Learning Algorithms |
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研究课题代号(代码): Study subject ID: |
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在二级注册机构或其它机构的注册号: The registration number of the Partner Registry or other register: |
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申请注册联系人: |
金晓伟 |
研究负责人: |
金晓伟 |
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Applicant: |
Xiaowei Jin |
Study leader: |
Xiaowei Jin |
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申请注册联系人电话: Applicant telephone: |
+86 139 5871 8529 |
研究负责人电话:
Study leader's |
+86 139 5871 8529 |
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申请注册联系人传真 : Applicant Fax: |
研究负责人传真: Study leader's fax: |
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申请注册联系人电子邮件: Applicant E-mail: |
xiaoweijinwz@163.com |
研究负责人电子邮件: Study leader's E-mail: |
xiaoweijinwz@163.com |
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申请单位网址(自愿提供): Applicant website(voluntary supply): |
研究负责人网址(自愿提供): Study leader's website(voluntary supply): |
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申请注册联系人通讯地址: |
中国浙江省温州市鹿城区温州市中西医结合医院锦绣路75号 |
研究负责人通讯地址: |
中国浙江省温州市鹿城区温州市中西医结合医院锦绣路75号 |
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Applicant address: |
No. 75 Jinxiu Road, Lucheng District, Wenzhou City, Wenzhou Integrated Traditional Chinese and Western Medicine Hospital, Zhejiang Province, China |
Study leader's address: |
No. 75 Jinxiu Road, Lucheng District, Wenzhou City, Wenzhou Integrated Traditional Chinese and Western Medicine Hospital, Zhejiang Province, China |
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申请注册联系人邮政编码: Applicant postcode: |
研究负责人邮政编码: Study leader's postcode: |
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申请人所在单位: |
温州市中西医结合医院 |
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Applicant's institution: |
Wenzhou Integrated Traditional Chinese and Western Medicine Hospital |
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研究负责人所在单位: |
温州市中西医结合医院 |
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Affiliation of the Leader: |
Wenzhou Integrated Traditional Chinese and Western Medicine Hospital |
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是否获伦理委员会批准: |
是 |
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Approved by ethic committee: |
Yes |
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伦理委员会批件文号: Approved No. of ethic committee: |
伦研批第(2023-L088)号 |
伦理委员会批件附件: Approved file of Ethical Committee: |
查看附件View |
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批准本研究的伦理委员会名称: |
温州市中西医结合医院医学伦理委员会 |
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Name of the ethic committee: |
Wenzhou Integrated Traditional Chinese and Western Medicine Hospital Medical Ethics Committee |
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伦理委员会批准日期: Date of approved by ethic committee: |
2023-11-27 00:00:00 | ||
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伦理委员会联系人: |
王萧枫 |
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Contact Name of the ethic committee: |
Xiaofeng Wang |
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伦理委员会联系地址: |
温州市中西医结合医院锦绣路75号 |
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Contact Address of the ethic committee: |
No. 75 Jinxiu Road, Lucheng District, Wenzhou City, Wenzhou Integrated Traditional Chinese and Western Medicine Hospital, Zhejiang Province, China |
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伦理委员会联系人电话: Contact phone of the ethic committee: |
+86 577 8891 8725 |
伦理委员会联系人邮箱: Contact email of the ethic committee: |
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研究实施负责(组长)单位: |
温州市中西医结合医院 |
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Primary sponsor: |
Wenzhou Integrated Traditional Chinese and Western Medicine Hospital |
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研究实施负责(组长)单位地址: |
中国浙江省温州市鹿城区温州市中西医结合医院锦绣路75号 |
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Primary sponsor's address: |
No. 75 Jinxiu Road, Lucheng District, Wenzhou City, Wenzhou Integrated Traditional Chinese and Western Medicine Hospital, Zhejiang Province, China |
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试验主办单位(项目批准或申办者): Secondary sponsor: |
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经费或物资来源: |
温州市科技局基础性科研项目(项目号:Y2023965) |
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Source(s) of funding: |
Wenzhou Science and Technology Bureau Basic Research Project(No:Y2023965) |
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研究疾病: |
无痛胃镜检查患者镇静相关不良事件 |
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Target disease: |
Sedation-Related Adverse Events in Patients Undergoing Painless Gastroscopy |
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研究疾病代码: |
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Target disease code: |
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研究类型: |
观察性研究 |
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Study type: |
Observational study |
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研究所处阶段: |
探索性研究/预试验 | ||||||||||||||||||||||
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Study phase: |
0 |
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研究设计: |
队列研究 |
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Study design: |
Cohort study |
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研究目的: |
本研究的目的是构建一个基于可解释性XGBoost机器学习算法的预测模型,该模型能够根据患者自身特征、操作过程和麻醉情况等数据,准确地识别出无痛胃镜检查中高风险患者,并给出相应的预防措施和干预建议。与传统的机器学习模型不同,本研究强调模型的可解释性,即能够清楚地说明模型是如何做出预测的,以及每个特征对预测结果的贡献程度。为此,本研究采用了SHAP作为可解释性工具,通过计算每个特征值的SHAP值,来反映特征值对预测结果的影响方向和大小。 |
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Objectives of Study: |
The purpose of this study is to construct a predictive model based on the explainable XGBoost machine learning algorithm. This model can accurately identify high-risk patients during painless gastroscopy examinations based on data such as the patient's own characteristics, the procedure process, and anesthesia conditions, and provide corresponding preventive measures and intervention suggestions. Unlike traditional machine learning models, this study emphasizes the explainability of the model, that is, it can clearly explain how the model makes predictions and the contribution of each feature to the predictive outcome. For this purpose, the study employs SHAP (SHapley Additive exPlanations) as the interpretability tool, reflecting the influence direction and magnitude of feature values on the prediction outcome by calculating the SHAP values for each feature. |
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药物成份或治疗方案详述: |
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Description for medicine or protocol of treatment in detail: |
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纳入标准: |
(1) 18周岁以上; (2) ASA麻醉风险Ⅰ ~ Ⅱ级; (3) 择期胃镜检查的适应症患者; (4) 能够接受丙泊酚镇静的患者。 |
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Inclusion criteria |
1) Aged 18 years or above; 2) ASA (American Society of Anesthesiologists) anesthesia risk levels I to II; 3) Patients scheduled for elective gastroscopy; 4) Patients able to undergo sedation with propofol. |
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排除标准: |
(1) 睡眠呼吸暂停综合征患者; (2) 气道管理困难患者; (3) 胃排空功能障碍明显者; (4) 消化道急性出血者; (5) 神经精神疾病患者; (6) 孕妇; (7) 对蛋黄或大豆油过敏者(可能对丙泊酚过敏); (8) 不同意签署知情同意书的患者。 |
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Exclusion criteria: |
1) Patients with sleep apnea syndrome; 2) Patients with difficult airway management; 3) Patients with significant gastric emptying dysfunction; 4) Patients with acute gastrointestinal bleeding; 5) Patients with neuropsychiatric disorders; 6) Pregnant women; 7) Patients allergic to egg yolk or soybean oil (may be allergic to propofol); 8) Patients who do not agree to sign the informed consent form. |
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研究实施时间: Study execute time: |
从 From 2024-01-01 00:00:00至 To 2024-07-31 00:00:00 |
征募观察对象时间: Recruiting time: |
从 From 2024-01-15 00:00:00 至 To 2024-07-31 00:00:00 |
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干预措施: Interventions: |
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研究实施地点: Countries of recruitment and research settings: |
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测量指标: Outcomes: |
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采集人体标本:
Collecting sample(s)
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征募研究对象情况: Recruiting status: |
正在进行 Recruiting |
年龄范围: Participant age: |
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性别: |
男女均可 |
Gender: |
Both |
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随机方法(请说明由何人用什么方法产生随机序列): |
None |
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Randomization Procedure (please state who generates the random number sequence and by what method): |
None |
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是否公开试验完成后的统计结果: Calculated Results after the Study Completed public access: |
公开/Public |
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盲法: |
None |
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Blinding: |
None |
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试验完成后的统计结果(上传文件): |
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Calculated Results after
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是否共享原始数据: IPD sharing |
否No |
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共享原始数据的方式(说明:请填入公开原始数据日期和方式,如采用网络平台,需填该网络平台名称和网址): |
None |
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The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url): |
None |
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数据采集和管理(说明:数据采集和管理由两部分组成,一为病例记录表(Case Record Form, CRF),二为电子采集和管理系统(Electronic Data Capture, EDC),如ResMan即为一种基于互联网的EDC: |
本研究采用全面的数据采集和管理方法,分为两个主要部分。第一部分是病例记录表(Case Record Form, CRF),用于系统地收集每位患者的数据。CRF旨在按照研究方案捕捉所有相关数据点,确保数据记录的准确性和一致性。第二部分是电子数据采集(Electronic Data Capture, EDC)系统,以基于互联网的平台ResMan为例。EDC系统便于电子化地收集、存储和管理研究数据。这种方法允许高效处理数据、实时监控数据质量,并安全处理患者信息,使其成为这项前瞻性研究中的重要工具。 |
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Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture: |
This study involves a comprehensive approach to data collection and management, which is divided into two main components. The first component is the Case Record Form (CRF), which is used for systematic collection of individual patient data. The CRF is designed to capture all relevant data points as per the study protocol, ensuring accuracy and consistency in data recording. The second component is the Electronic Data Capture (EDC) system, exemplified by ResMan, an internet-based platform. The EDC system facilitates the electronic collection, storage, and management of research data. This approach allows for efficient data processing, real-time monitoring of data quality, and secure handling of patient information, making it a vital tool in this prospective study. |
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数据与安全监察委员会: Data and Safety Monitoring Committee: |
暂未确定/Not yet |