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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: |
ChiCTR2500110818 |
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最近更新日期: Date of Last Refreshed on: |
2025-10-21 14:43:14 |
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注册时间: Date of Registration: |
2025-10-21 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: |
基于人工智能机器学习构建足月妊娠孕妇阴道试产发生宫内感染的预测模型 |
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Public title: |
Building a Predictive Model for Intrapartum Intrauterine Infection in Pregnant Women with Term Pregnancy Undergoing Vaginal Trial of Labor Based on Artificial Intelligence Machine Learning |
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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: |
基于人工智能机器学习构建足月妊娠孕妇阴道试产发生宫内感染的预测模型 |
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Scientific title: |
Building a Predictive Model for Intrapartum Intrauterine Infection in Pregnant Women with Term Pregnancy Undergoing Vaginal Trial of Labor Based on Artificial Intelligence Machine Learning |
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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: |
郑芳媛 |
研究负责人: |
郑芳媛 |
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Applicant: |
Fangyuan Zheng |
Study leader: |
Fangyuan Zheng |
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申请注册联系人电话: Applicant telephone: |
+86 571 5600 5277 |
研究负责人电话: Study leader's telephone: |
+86 571 5600 5277 |
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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: |
oywenru1234@163.com |
研究负责人电子邮件: Study leader's E-mail: |
oywenru1234@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: |
浙江省杭州市上城区鲲鹏路369号 |
研究负责人通讯地址: |
浙江省杭州市上城区鲲鹏路369号 |
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Applicant address: |
No. 369 Kunpeng Road, Shangcheng District, Hangzhou City, Zhejiang Province |
Study leader's address: |
No. 369 Kunpeng Road, Shangcheng District, Hangzhou City, Zhejiang Province |
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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: |
杭州市妇产科医院 |
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Applicant's institution: |
Hangzhou Women's Hospital |
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研究负责人所在单位: |
杭州市妇产科医院 |
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Affiliation of the Leader: |
Hangzhou Women's Hospital |
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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: |
【2025】医伦审A第(63)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: |
杭州市妇产科医院医学伦理委员会 |
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Name of the ethic committee: |
Ethics Committee of Hangzhou Obstetrics and Gynecology Hospital |
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伦理委员会批准日期: Date of approved by ethic committee: |
2025-04-09 00:00:00 |
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伦理委员会联系人: |
黄飞 |
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Contact Name of the ethic committee: |
Huang Fei |
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伦理委员会联系地址: |
浙江省杭州市上城区鲲鹏路369号 |
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Contact Address of the ethic committee: |
No. 369 Kunpeng Road, Shangcheng District, Hangzhou City, Zhejiang Province |
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伦理委员会联系人电话: Contact phone of the ethic committee: |
+86 571 56005077 |
伦理委员会联系人邮箱: Contact email of the ethic committee: |
601506529@qq.com |
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研究实施负责(组长)单位: |
杭州市妇产科医院 |
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Primary sponsor: |
Hangzhou Women's Hospital |
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研究实施负责(组长)单位地址: |
浙江省杭州市上城区鲲鹏路369号 |
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Primary sponsor's address: |
No. 369 Kunpeng Road, Shangcheng District, Hangzhou City, Zhejiang Province |
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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: |
杭州市医药卫生科技项目 |
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Source(s) of funding: |
Hangzhou Medical and Health Science and Technology Project |
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Target disease: |
Intrauterine infection (Acute chorioamnionitis) |
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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: |
连续入组 |
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Study design: |
Sequential |
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研究目的: |
基于机器学习等人工智能技术构建足月妊娠人群宫内感染的预测模型,早期且精准预测患者宫内感染的可能性,指导临床诊疗,改善妊娠结局和新生儿结局。 |
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Objectives of Study: |
Based on artificial intelligence technologies such as machine learning, a predictive model for intrauterine infection in the term pregnancy population is constructed to early and accurately predict the possibility of intrauterine infection in patients, guide clinical diagnosis and treatment, and improve pregnancy outcomes and neonatal outcomes. |
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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.有完整的病史资料,包括一般情况、孕妇病史、专科检查及检验、分娩相关资料及新生儿病史资料等; 2.头位、单活胎; 3.孕周满37周; 4.排除头盆不称、胎儿窘迫、胎盘早剥、前置胎盘等阴道分娩禁忌症; 5.无子宫手术史,如子宫肌瘤剔除术、剖宫产史; 6.选择阴道试产,且自愿参加本研究,由本人签署知情同意书. |
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Inclusion criteria |
1.Complete medical history data are available, including general conditions, maternal medical history, specialized examinations and tests, childbirth-related information, and neonatal medical history data, etc. 2.Cephalic presentation, single live fetus; 3.Gestational age >= 37 weeks; 4.Exclusion of contraindications for vaginal delivery, such as cephalopelvic disproportion, fetal distress, placental abruption, placenta previa, etc.; 5.No history of uterine surgery, such as myomectomy or cesarean section; 6.Selection of vaginal trial of labor and voluntary participation in this study, with informed consent signed by the participant herself. |
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排除标准: |
1.相关病史资料不完整; 2.基础体温37.5 ℃及以上; 3.存在呼吸道感染、消化系统、泌尿系统感染等其他系统感染. |
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Exclusion criteria: |
1.Incomplete relevant medical history data; |
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研究实施时间: Study execute time: |
从 From 2025-01-01 00:00:00至 To 2027-12-31 00:00:00 |
征募观察对象时间: Recruiting time: |
从From 2025-01-09 00:00:00 至 To 2025-12-31 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: |
正在进行 Recruiting |
年龄范围: Participant age: |
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性别: |
女性 |
Gender: |
Female |
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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 |
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): |
邮件联系研究者 |
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The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url): |
Contact the researcher by 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: |
数据通过电子病历系统采集,后续由项目组成员负责管理 |
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Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture: |
Data were collected via the electronic medical record (EMR) system and subsequently managed by the project team members. |
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数据与安全监察委员会: Data and Safety Monitoring Committee: |
无/No |