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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: |
ChiCTR2500105735 |
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最近更新日期: Date of Last Refreshed on: |
2025-07-09 16:52:30 |
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注册时间: Date of Registration: |
2025-07-09 00:00:00 |
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注册号状态: |
补注册 |
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Registration Status: |
Retrospective registration |
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注册题目: |
基于深度卷积神经网络的股骨颈骨折内固定策略选择评估体系的研发及临床评价 |
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Public title: |
Development and Clinical Evaluation of a System for Choosing Femoral Neck Fracture Internal Fixation Strategies Based on Deep Convolutional Neural Networks |
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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: |
基于深度卷积神经网络的股骨颈骨折内固定策略选择评估体系的研发及临床评价 |
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Scientific title: |
Development and Clinical Evaluation of a System for Choosing Femoral Neck Fracture Internal Fixation Strategies Based on Deep Convolutional Neural Networks |
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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: |
卞玉泉 |
研究负责人: |
贾伟涛 |
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Applicant: |
Yuquan Bian |
Study leader: |
Weitao Jia |
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申请注册联系人电话: Applicant telephone: |
+86 186 5290 9974 |
研究负责人电话: Study leader's telephone: |
+86 186 5190 5573 |
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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: |
2442608453@qq.com |
研究负责人电子邮件: Study leader's E-mail: |
2442608253@qq.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: |
上海市徐汇区宜山路600号 |
研究负责人通讯地址: |
上海市徐汇区宜山路600号 |
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Applicant address: |
No. 600, Yishan Road, Xuhui District, Shanghai, China |
Study leader's address: |
No. 600, Yishan Road, Xuhui District, Shanghai, 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: |
上海交通大学附属第六人民医院 |
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Applicant's institution: |
Shanghai Sixth People's Hospital Affiliated to Shanghai JiaoTong University |
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研究负责人所在单位: |
上海交通大学附属第六人民医院 |
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Affiliation of the Leader: |
Shanghai Sixth People's Hospital Affiliated to Shanghai JiaoTong University |
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是否获伦理委员会批准: |
是/Yes |
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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: |
2024-141-(1) |
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: |
上海市第六人民医院伦理委员会审查批件 |
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Name of the ethic committee: |
Approval Letter of Ethics Commitee of Shanghai Sixth People's Hospital |
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伦理委员会批准日期: Date of approved by ethic committee: |
2025-04-15 00:00:00 |
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伦理委员会联系人: |
庞路阳 |
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Contact Name of the ethic committee: |
Luyang Pang |
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伦理委员会联系地址: |
上海市徐汇区宜山路600号 |
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Contact Address of the ethic committee: |
No. 600, Yishan Road, Xuhui District, Shanghai, China |
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伦理委员会联系人电话: Contact phone of the ethic committee: |
+86 21 3829 7000 |
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: |
上海交通大学附属第六人民医院 |
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Primary sponsor: |
Shanghai Sixth People's Hospital Affiliated to Shanghai JiaoTong University |
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研究实施负责(组长)单位地址: |
上海市徐汇区宜山路600号 |
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Primary sponsor's address: |
No. 600, Yishan Road, Xuhui District, Shanghai, 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: |
自筹 |
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Source(s) of funding: |
Self-raised |
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Target disease: |
Hip fracture |
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Target disease code: |
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研究类型: |
干预性研究 |
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Study type: |
Interventional study |
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研究所处阶段: |
I期临床试验 | ||||||||||||||||||||||
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Study phase: |
1 |
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研究设计: |
随机平行对照 |
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Study design: |
Parallel |
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研究目的: |
2.1.1主要目的 针对中青年股骨颈骨折,探讨采用深度卷积神经网络(DCNN)辅助内固定方案制定是否会降低临床失败率。 2.1.2关键次要目的 探讨采用深度卷积神经网络(DCNN)辅助内固定方案制定是否会降低骨不连、股骨颈短缩、股骨头坏死率,以及降低再手术率,提高患者髋关节功能。 |
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Objectives of Study: |
2.1.1 Primary Objective To investigate whether the use of a deep convolutional neural network (DCNN) in assisting with internal fixation planning reduces the clinical failure rate in young and middle-aged patients with femoral neck fractures. 2.1.2 Key Secondary Objectives To evaluate whether DCNN-assisted internal fixation planning decreases the rates of nonunion, femoral neck shortening, and femoral head necrosis, while also reducing the need for revision surgery and improving hip joint function in patients. |
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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: |
纳入标准: (1)因股骨颈骨折入院治疗的患者; (2)年龄大于20岁,小于60岁; |
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Inclusion criteria |
Inclusion Criteria: (1) Patients hospitalized for femoral neck fracture; (2) Age >20 years and <60 years; |
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排除标准: |
排除标准: (1)存在病理性骨折或多发性骨折; (2)开放性骨折或合并严重软组织损伤; (3)骨折前存在严重合并症(如肾病、神经系统疾患等); |
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Exclusion criteria: |
Exclusion criteria: (1) Presence of pathological fractures or multiple fractures; (2) Open fractures or combined with severe soft tissue injuries; (3) Pre-existing severe comorbidities (e.g., kidney disease, neurological disorders, etc.) before the fracture; |
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研究实施时间: Study execute time: |
从 From 2025-04-01 00:00:00至 To 2027-06-01 00:00:00 |
征募观察对象时间: Recruiting time: |
从From 2025-04-21 00:00:00 至 To 2026-12-01 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): |
由于考虑到患者年龄、骨折移位程度与临床预后密切相关,为避免可能存在的选择偏移,本研究的分组方法采用分层随机化(图1)。我们先按患者年龄分为两个亚组(20-45岁,45-60岁),再按骨折移位程度将两个亚组再分别细分为两亚组(移位型骨折、非移位型骨折)。在这四个亚组中,分别采用随机数方法将实验对象随机分为实验组和对照组,最后将所有实验组、对照组合并,形成新的实验组和对照组。 |
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Randomization Procedure (please state who generates the random number sequence and by what method): |
Stratified randomization was used to avoid selection bias . Patients were first divided by age (20-45 years, 45-60 years), then by fracture displacement (displaced/non-displaced). Within each subgroup, random allocation assigned patients to experimental or control groups. Finally, all experimental and control subgroups were merged accordingly. |
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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: |
开放 |
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Blinding: |
Open label |
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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 |
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): |
国家生物信息中心 https://ngdc.cncb.ac.cn/gsub/ |
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The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url): |
China National center for Bioinformation (https://ngdc.cncb.ac.cn/gsub/) |
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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 |