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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: |
ChiCTR2500115382 |
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最近更新日期: Date of Last Refreshed on: |
2025-12-25 10:40:35 |
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注册时间: Date of Registration: |
2025-12-25 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: |
创伤性脑损伤患者ICU死亡与不良结局的预测:一项基于多中心大数据的机器学习研究 |
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Public title: |
Predicting ICU Mortality and Adverse Outcomes in Traumatic Brain Injury Patients: A Machine Learning Study Based on Multicenter Big Data |
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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: |
创伤性脑损伤患者ICU死亡与不良结局的预测:一项基于多中心大数据的机器学习研究 |
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Scientific title: |
Predicting ICU Mortality and Adverse Outcomes in Traumatic Brain Injury Patients: A Machine Learning Study Based on Multicenter Big Data |
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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: |
王盈 |
研究负责人: |
王伯栋 |
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Applicant: |
Wang Ying |
Study leader: |
Wang Bodong |
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申请注册联系人电话: Applicant telephone: |
+86 152 6566 8819 |
研究负责人电话:
Study leader's |
+86 198 6181 1291 |
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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: |
cywy0624@163.com |
研究负责人电子邮件: Study leader's E-mail: |
bdwang_neurosurg@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: |
中国山东省济南市天桥区师范路25号 |
研究负责人通讯地址: |
中国山东省济南市天桥区师范路25号 |
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Applicant address: |
25 Shifan road, Tianqiao district, Jinan, Shandong, China |
Study leader's address: |
25 Shifan road, Tianqiao district, Jinan, Shandong, 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: |
中国人民解放军联勤保障部队第九六〇医院 |
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Applicant's institution: |
The 960th Hospital of the PLA Joint Logistics Support Force |
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研究负责人所在单位: |
中国人民解放军联勤保障部队第九六〇医院 |
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Affiliation of the Leader: |
The 960th Hospital of the PLA Joint Logistics Support Force |
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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: |
(2025)科研伦理审第(215)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: |
解放军第九六〇医院科研伦理委员会 |
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Name of the ethic committee: |
The 960th Hospital of the PLA Joint Logistics Support Force Research Ethics Committee |
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伦理委员会批准日期: Date of approved by ethic committee: |
2025-10-28 00:00:00 | ||
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伦理委员会联系人: |
孙志东 |
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Contact Name of the ethic committee: |
Sun Zhidong |
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伦理委员会联系地址: |
中国山东省济南市天桥区师范路25号 |
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Contact Address of the ethic committee: |
25 Shifan road, Tianqiao district, Jinan, Shandong China |
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伦理委员会联系人电话: Contact phone of the ethic committee: |
+86 531 5166 6145 |
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: |
中国人民解放军联勤保障部队第九六〇医院 |
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Primary sponsor: |
The 960th Hospital of the PLA Joint Logistics Support Force |
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研究实施负责(组长)单位地址: |
中国山东省济南市天桥区师范路25号 |
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Primary sponsor's address: |
25 Shifan road, Tianqiao district, Jinan, Shandong, 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: |
山东省卫生健康科创团队建设项目 |
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Source(s) of funding: |
Shandong Provincial Health Science and Technology Innovation Team Development Project |
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研究疾病: |
创伤性脑损伤 |
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Target disease: |
Traumatic brain injury |
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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: |
其它 | ||||||||||||||||||||||
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Study phase: |
N/A |
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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: |
本研究的总体目的是充分利用多中心大数据资源,开发并验证一套能够综合预测TBI患者ICU 30天死亡率及VAP、AKI、DVT、GIB四种关键并发症的机器学习模型。该研究致力于通过整合国际公开数据库与国内真实临床数据,确保模型兼具高预测精度、良好的泛化能力以及临床可解释性。具体目标包括系统性地完成多源数据的整合与预处理以构建高质量数据集;应用多种先进算法分别构建五项结局的预测模型并进行严格的内部验证与优化;在独立的国内多中心数据上对优选模型进行外部验证以评估其稳健性;并利用可解释性人工智能技术揭示模型的决策依据,识别关键风险因素。最终,本研究旨在将理论模型转化为潜在的临床决策支持工具,为早期识别高危患者、实施个体化干预、合理分配医疗资源提供科学依据,从而有效改善患者预后,减轻社会医疗负担。 |
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Objectives of Study: |
The overarching objective of this study is to leverage multicenter big data resources to develop and validate a set of machine learning models capable of comprehensively predicting 30-day ICU mortality and four critical complications—VAP, AKI, DVT, and GIB—in patients with traumatic brain injury (TBI). By integrating international public databases with real-world domestic clinical data, this research aims to ensure that the models exhibit high predictive accuracy, robust generalization capability, and clinical interpretability. Specific objectives include systematically integrating and preprocessing multi-source data to construct a high-quality dataset; applying multiple advanced algorithms to develop predictive models for the five outcomes and conducting rigorous internal validation and optimization; performing external validation of the selected optimal models using an independent domestic multicenter dataset to assess their robustness; and utilizing explainable artificial intelligence techniques to untangle the decision-making rationale of the models and identify key risk factors. Ultimately, this study seeks to translate theoretical models into potential clinical decision support tools, providing a scientific basis for the early identification of high-risk patients, the implementation of individualized interventions, and the rational allocation of medical resources, thereby effectively improving patient outcomes and alleviating the societal healthcare burden. |
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药物成份或治疗方案详述: |
无 |
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Description for medicine or protocol of treatment in detail: |
None |
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纳入标准: |
1. 符合TBI诊断标准(ICD编码确认) 2. 年龄 >= 18岁 3. 入ICU治疗 >= 24小时 4. 具备完整的基本人口学信息、临床指标与结局数据 |
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Inclusion criteria |
1. Meeting the diagnostic criteria for TBI (confirmed by ICD codes) 2. Age >= 18 years 3. ICU stay >= 24 hours 4. Availability of complete basic demographic information, clinical indicators, and outcome data |
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排除标准: |
1.非首次ICU入院或数据缺失严重者 2.合并严重全身创伤或多发系统疾病干扰预后判断 3.妊娠妇女 |
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Exclusion criteria: |
1.Non-first ICU admission or severe data deficiency 2.Coexistence of severe systemic trauma or multiple system diseases that interfere with prognosis assessment 3.Pregnancy |
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研究实施时间: Study execute time: |
从 From 2026-02-15 00:00:00至 To 2026-12-31 00:00:00 |
征募观察对象时间: Recruiting time: |
从 From 2026-02-15 00:00:00 至 To 2026-12-31 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: |
尚未开始 Not yet 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): |
无 |
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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: |
无 |
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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 |
是Yes |
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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): |
数据在文章发表后可以共享,去标识化后的数据可以在合理请求下,从通讯作者处获取。 |
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The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url): |
The original raw data will be made publicly available after publica. However, de-identified data can be obtained from the corresponding author upon reasonable request |
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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: |
电子采集和管理系统 |
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Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture: |
Electronic Data Capture, EDC |
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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 |