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注册号: Registration number: |
ChiCTR2400090829 |
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最近更新日期: Date of Last Refreshed on: |
2024-10-14 11:15:36 |
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注册时间: Date of Registration: |
2024-10-14 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: |
基于机器学习的老年女性重度盆腔器官脱垂改良阴道封闭术后新发尿失禁风险预测模型研究 |
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Public title: |
Machine learning-based predictive modeling of the risk of de novo urinary incontinence after modified colpocleisis for severe pelvic organ prolapse in elderly women |
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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: |
基于机器学习的老年女性重度盆腔器官脱垂改良阴道封闭术后新发尿失禁风险预测模型研究 |
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Scientific title: |
Machine learning-based predictive modeling of the risk of de novo urinary incontinence after modified colpocleisis for severe pelvic organ prolapse in elderly women |
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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: |
王琪 |
研究负责人: |
王琪 |
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Applicant: |
Wang Qi |
Study leader: |
Wang Qi |
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申请注册联系人电话: Applicant telephone: |
+86 15606934752 |
研究负责人电话:
Study leader's |
+86 591 87620817 |
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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: |
wq19910908@126.com |
研究负责人电子邮件: Study leader's E-mail: |
wq19910908@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: |
福建省福州市鼓楼区道山路18号福建省妇幼保健院 |
研究负责人通讯地址: |
福建省福州市鼓楼区道山路18号 |
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Applicant address: |
Fujian Maternity and Child Health Hospital, No.18 Daoshan Road, Gulou District, Fuzhou, Fujian Provi |
Study leader's address: |
No.18 Daoshan Road, Fuzhou, Fujian P.R.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: |
福建省妇幼保健院 |
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Applicant's institution: |
Fujian Maternity and Child Health Hospital |
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研究负责人所在单位: |
福建省妇幼保健院 |
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Affiliation of the Leader: |
Fujian Maternity and Child Health 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: |
2024KY122 |
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: |
福建省妇幼保健院伦理委员会 |
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Name of the ethic committee: |
Medical Ethics Committee of Fujian Maternity and Child Health Hospital |
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伦理委员会批准日期: Date of approved by ethic committee: |
2024-05-29 00:00:00 | ||
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伦理委员会联系人: |
叶丽频 |
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Contact Name of the ethic committee: |
Ye Lipin |
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伦理委员会联系地址: |
福建省福州市鼓楼区道山路18号 |
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Contact Address of the ethic committee: |
No.18 Daoshan Road, Fuzhou, Fujian P.R.China |
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伦理委员会联系人电话: Contact phone of the ethic committee: |
+86 591 88312052 |
伦理委员会联系人邮箱: Contact email of the ethic committee: |
ylp121006@163.com |
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研究实施负责(组长)单位: |
福建省妇幼保健院 |
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Primary sponsor: |
Fujian Maternity and Child Health Hospital |
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研究实施负责(组长)单位地址: |
福建省福州市鼓楼区道山路18号 |
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Primary sponsor's address: |
No.18 Daoshan Road, Fuzhou, Fujian P.R.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: |
福建医科大学启航基金项目资助 |
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Source(s) of funding: |
Startup Fund for scientific research, Fujian Medical University |
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研究疾病: |
压力性尿失 |
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Target disease: |
Stress Urinary Incontinence (SUI) |
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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: |
干预性研究 |
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Study type: |
Interventional 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: |
随机平行对照 |
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Study design: |
Parallel |
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研究目的: |
阐明基于机器学习建立的老年女性重度盆腔器官脱垂改良阴道封闭术后新发尿失禁风险预测模型的预测效能,通过前瞻性队列进一步验证,并探讨评估其指导早期干预的效果。 |
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Objectives of Study: |
To demonstrate the predictive efficacy of a machine-learning based predictive model for the risk of de novo urinary incontinence after modified colpocleisis for severe pelvic organ prolapse in elderly women, to further validate it through a prospective cohort, and to explore the evaluation of its effectiveness in guiding early intervention. |
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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: |
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Inclusion criteria |
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排除标准: |
1.患者年龄 < 60 岁,有性生活要求; |
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Exclusion criteria: |
1.Patient age < 60 years, sexually active; 2.POP-Q < Stage III; 3.Combination of absolute contraindications to surgery; 4.History of anti-incontinence surgery or diseases that may affect urinary function, such as bladder cancer, urethral diverticula, etc. 5. Those who refuse to participate or withdraw midway. 5.Those who refuse to participate or drop out; |
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研究实施时间: Study execute time: |
从 From 2024-06-01 00:00:00至 To 2026-12-31 00:00:00 |
征募观察对象时间: Recruiting time: |
从 From 2025-01-01 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: |
尚未开始 Not yet 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): |
由江小香应用计算机生成随机数的方法产生随机数列 |
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Randomization Procedure (please state who generates the random number sequence and by what method): |
Generation of random number series by Jiang Xiaoxiang applying computer generated random number methods |
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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: |
开放标签,对评估者隐藏分组 |
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Blinding: |
Open-label study with blinded-evaluators |
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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): |
提供联系方式,感兴趣的人可以通过电子邮件(wq19910908@126.com)或其他方式联系你以获取数据。 |
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The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url): |
Contact information is provided and interested parties may contact me by e-mail (wq19910908@126.com) or other means to obtain the data. |
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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: |
1. 病例记录表(CRF) 病例记录表(CRF)用于系统地记录临床试验中每个受试者的所有观察和其他数据。 CRF将根据研究方案设计,包含受试者基本信息、病史、体检结果、实验室检查结果、研究干预数据和随访数据等。 CRF表格将包括强制填写项和检查提示,以减少遗漏数据。 2. 电子采集和管理系统 电子采集和管理系统用于提高数据采集的效率和准确性,并确保数据安全和隐私。系统将设置数据验证规则(例如范围检查、逻辑检查),以确保数据的准确性和一致性,提醒研究团队检查异常值和缺失数据。 数据将定期备份到本地安全存储设备,并测试恢复能力。 数据访问权限将基于角色分配,仅限授权的研究人员访问。 |
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Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture: |
1. Case Record Form (CRF) The Case Record Form (CRF) is used to systematically record all observations and other data for each subject in a clinical trial. The CRF will be designed according to the study protocol and will contain basic subject information, medical history, physical examination results, laboratory test results, study intervention data, and follow-up data. The CRF form will include mandatory fields and checking prompts to minimize missing data. 2. Electronic capture and management system Electronic capture and management systems are used to improve the efficiency and accuracy of data capture and to ensure data security and privacy. The system will set up data validation rules (e.g., range checks, logic checks) to ensure data accuracy and consistency, alerting the research team to check for outliers and missing data. Data will be regularly backed up to a local secure storage device and tested for resilience. Data access rights will be assigned based on roles, with access limited to authorized researchers. |
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数据与安全监察委员会: Data and Safety Monitoring Committee: |
有/Yes |