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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: |
ChiCTR2600126748 |
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最近更新日期: Date of Last Refreshed on: |
2026-06-15 14:41:22 |
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注册时间: Date of Registration: |
2026-06-15 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AI的糖尿病肾病辅助决策预测模型的前瞻性临床验证与应用研究 |
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Public title: |
Prospective clinical validation and application research of an AI-based auxiliary decision-making prediction model for diabetic nephropathy |
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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AI的糖尿病肾病辅助决策预测模型的前瞻性临床验证与应用研究 |
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Scientific title: |
Prospective clinical validation and application research of an AI-based auxiliary decision-making prediction model for diabetic nephropathy |
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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: |
赵洪雯 |
研究负责人: |
赵洪雯 |
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Applicant: |
Zhao Hongwen |
Study leader: |
Zhao Hongwen |
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申请注册联系人电话: Applicant telephone: |
+86 139 8336 0655 |
研究负责人电话:
Study leader's |
+86 139 8336 0655 |
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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: |
zhaohongwen@tmmu.edu.cn |
研究负责人电子邮件: Study leader's E-mail: |
zhaohw212@126.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: |
陆军军医大学第一附属医院肾内科 |
研究负责人通讯地址: |
重庆市沙坪坝区高滩岩正街29号 |
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Applicant address: |
Department of Nephrology, The First Affiliated Hospital of Army Medical University |
Study leader's address: |
No 29 Gaotanyan Main Street, Shapingba District, Chongqing |
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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: |
陆军军医大学第一附属医院(西南医院) |
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Applicant's institution: |
Department of Nephrology, The First Affiliated Hospital of Army Medical University |
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研究负责人所在单位: |
中国人民解放军陆军军医大学第一附属医院 |
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Affiliation of the Leader: |
The First Affiliated Hospital of Army Medical University |
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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: |
(A)KY2026041 |
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: |
中国人民解放军陆军军医大学第一附属医院伦理委员会 |
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Name of the ethic committee: |
Ethics Committee of the First Affiliated Hospital of Army Medical University PLA |
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伦理委员会批准日期: Date of approved by ethic committee: |
2026-02-03 00:00:00 | ||
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伦理委员会联系人: |
贺莉 |
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Contact Name of the ethic committee: |
He Li |
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伦理委员会联系地址: |
重庆市沙坪坝区高滩岩正街29号 |
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Contact Address of the ethic committee: |
No 29 Gaotanyan Main Street, Shapingba District, Chongqing |
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伦理委员会联系人电话: Contact phone of the ethic committee: |
+86 23 68754035 |
伦理委员会联系人邮箱: Contact email of the ethic committee: |
cqhl13@qq.com |
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研究实施负责(组长)单位: |
中国人民解放军陆军军医大学第一附属医院 |
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Primary sponsor: |
The First Affiliated Hospital of Army Medical University |
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研究实施负责(组长)单位地址: |
重庆市沙坪坝区高滩岩正街29号 |
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Primary sponsor's address: |
No 29 Gaotanyan Main Street, Shapingba District, Chongqing |
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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: |
重庆市技术创新与应用发展专项重点项目 |
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Source(s) of funding: |
Chongqing Key Project for Technological Innovation and Application Development |
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研究疾病: |
糖尿病肾病 |
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Target disease: |
Diabetic Kidney Disease |
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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: |
诊断试验 |
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Study type: |
Diagnostic test |
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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: |
诊断试验诊断准确性 |
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Study design: |
Diagnostic test for accuracy |
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研究目的: |
本研究拟开展一项前瞻性、观察性临床验证研究,对既往构建的糖尿病肾病精准诊断机器学习模型进行系统评估。通过在前瞻性入组人群中并行运行模型预测结果,验证其在真实临床场景下对糖尿病肾病的诊断一致性、判别能力及校准性能。 |
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Objectives of Study: |
This study intends to conduct a prospective, observational clinical validation to systematically evaluate the previously established machine learning model for accurate diagnosis of Diabetic Kidney Disease . By running the model prospectively in enrolled participants and comparing its predictive outcomes, this study aims to validate its diagnostic consistency, discriminative ability and calibration performance for Diabetic Kidney Disease in real clinical settings. |
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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.年龄≥18岁且≤80岁; |
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Inclusion criteria |
1. Age >= 18 years and <= 80 years; 2. Confirmed diagnosis of type 2 diabetes mellitus according to WHO or ADA criteria; 3. Evidence of renal impairment, defined as persistent albuminuria (urinary albumin-to-creatinine ratio [UACR] >= 30 mg/g) and/or estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73m2; 4. Scheduled for percutaneous renal biopsy as determined by the treating clinician for diagnostic purposes; 5. Voluntarily provided written informed consent to participate in this study and authorized the use of their clinical and follow-up data. |
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排除标准: |
1.合并其他明确导致肾损害的系统性疾病(如系统性红斑狼疮、ANCA相关性血管炎、多发性骨髓瘤等); |
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Exclusion criteria: |
1.Comorbidity with other systemic diseases known to cause renal damage (e.g., systemic lupus erythematosus, ANCA-associated vasculitis, multiple myeloma, etc.); |
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研究实施时间: Study execute time: |
从 From 2025-10-01 00:00:00至 To 2027-05-31 00:00:00 |
征募观察对象时间: Recruiting time: |
从 From 2026-06-25 00:00:00 至 To 2027-05-31 00:00:00 |
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诊断试验: Diagnostic Tests: |
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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: |
不公开/Private |
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盲法: |
无 |
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Blinding: |
None |
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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): |
本研究所涉及的原始数据可在合理请求的情况下,通过电子邮件向通讯作者获取。 |
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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 data involved in this study are available from the corresponding author upon reasonable request via email. |
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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: |
所有数据均来源于医院电子病历系统及实验室信息系统,由专人提取并录入至加密的电子数据库。为保证数据质量,采用双人独立录入与逻辑核查相结合的方式进行数据校验;对缺失值及异常值进行核实与追踪。 |
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Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture: |
All data were obtained from the hospital electronic medical record system and laboratory information system. The data were extracted by designated personnel and entered into a secure, password-protected electronic database. To ensure data quality, double independent data entry combined with logical consistency checks was performed for validation. Missing values and outliers were verified and traced accordingly. |
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数据与安全监察委员会: Data and Safety Monitoring Committee: |
有/Yes |