药物流产结局预测模型的回顾性开发与前瞻性验证研究

注册号:

Registration number:

ChiCTR2500114798 

最近更新日期:

Date of Last Refreshed on:

2025-12-17 17:22:48 

注册时间:

Date of Registration:

2025-12-17 00:00:00 

注册号状态:

预注册

Registration Status:

Prospective registration

注册题目:

药物流产结局预测模型的回顾性开发与前瞻性验证研究

Public title:

Development and Validation of a Clinical Prediction Model for Medical Abortion Outcomes: A Study Involving Retrospective Model Development and Prospective Validation

注册题目简写:

English Acronym:

研究课题的正式科学名称:

药物流产结局预测模型的回顾性开发与前瞻性验证研究

Scientific title:

Development and Validation of a Clinical Prediction Model for Medical Abortion Outcomes: A Study Involving Retrospective Model Development and Prospective Validation

研究课题代号(代码):

Study subject ID:

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:

申请注册联系人:

胡昀昀 

研究负责人:

胡昀昀 

Applicant:

Hu Yunyun 

Study leader:

Hu Yunyun 

申请注册联系人电话:

Applicant telephone:

+86 138 5719 6940

研究负责人电话:

Study leader's
telephone:

+86 571 8600 8571

申请注册联系人传真 :

Applicant Fax:

研究负责人传真:

Study leader's fax:

申请注册联系人电子邮件:

Applicant E-mail:

fuddyhu@163.com

研究负责人电子邮件:

Study leader's E-mail:

fuddyhu@163.com

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):

申请注册联系人通讯地址:

浙江省杭州市上城区邮电路54号

研究负责人通讯地址:

浙江省杭州市上城区邮电路54号

Applicant address:

No. 54, Youdian Road, Shangcheng District, Hangzhou, Zhejiang Province, China

Study leader's address:

No. 54, Youdian Road, Shangcheng District, Hangzhou, Zhejiang Province, China

申请注册联系人邮政编码:

Applicant postcode:

310000

研究负责人邮政编码:

Study leader's postcode:

310000

申请人所在单位:

浙江中医药大学附属第一医院

Applicant's institution:

The First Affiliated Hospital of Zhejiang Chinese Medical University

研究负责人所在单位:

浙江中医药大学附属第一医院

Affiliation of the Leader:

The First Affiliated Hospital of Zhejiang Chinese Medical University

是否获伦理委员会批准:

Approved by ethic committee:

Yes

伦理委员会批件文号:

Approved No. of ethic committee:

2025-KLS-805-01

伦理委员会批件附件:

Approved file of Ethical Committee:

查看附件View

批准本研究的伦理委员会名称:

浙江中医药大学附属第一医院伦理委员会

Name of the ethic committee:

Ethics Committee of the First Affiliated Hospital of Zhejiang University of Traditional Chinese Medicine

伦理委员会批准日期:

Date of approved by ethic committee:

2025-10-22 00:00:00

伦理委员会联系人:

何强

Contact Name of the ethic committee:

He Qiang

伦理委员会联系地址:

浙江省杭州市上城区邮电路54号

Contact Address of the ethic committee:

No. 54, Youdian Road, Shangcheng District, Hangzhou, Zhejiang Province, China

伦理委员会联系人电话:

Contact phone of the ethic committee:

+86 571 8706 8001

伦理委员会联系人邮箱:

Contact email of the ethic committee:

研究实施负责(组长)单位:

浙江中医药大学附属第一医院

Primary sponsor:

The First Affiliated Hospital of Zhejiang Chinese Medical University

研究实施负责(组长)单位地址:

浙江省杭州市上城区邮电路54号

Primary sponsor's address:

No. 54, Youdian Road, Shangcheng District, Hangzhou, Zhejiang Province, China

试验主办单位(项目批准或申办者):

Secondary sponsor:

国家:

中国

省(直辖市):

浙江

市(区县):

杭州

Country:

China

Province:

Zhejiang

City:

Hangzhou

单位(医院):

浙江中医药大学附属第一医院

具体地址:

浙江省杭州市上城区邮电路54号

Institution
hospital:

The First Affiliated Hospital of Zhejiang Chinese Medical University

Address:

No. 54, Youdian Road, Shangcheng District, Hangzhou, Zhejiang Province, China

经费或物资来源:

Source(s) of funding:

NA

研究疾病:

早期人工流产;稽留流产  

Target disease:

medical abortion

研究疾病代码:

Target disease code:

研究类型:

观察性研究

Study type:

Observational study

研究所处阶段:

其它 

Study phase:

N/A

研究设计:

队列研究 

Study design:

Cohort study 

研究目的:

药物流产(药流)是终止早期妊娠的安全有效方法,但其成功率并非100%,存在15-20%的失败(包括不全流产和持续妊娠)风险。目前,临床医生主要依据孕周、孕囊大小等有限指标进行经验性判断,缺乏个体化的精准预测工具。这导致了两难困境:要么对所有患者进行过度随访和干预,造成医疗资源浪费和患者负担;要么对失败风险预估不足,导致患者面临不全流产、大出血等并发症风险。因此,开发一个基于常规临床和超声指标的预测模型,对药流结局进行个体化风险评估,对于优化临床决策、提高医疗资源利用效率和保障患者安全具有重大意义。  

Objectives of Study:

Medical abortion (medication abortion) is a safe and effective method for terminating early pregnancy. However, its success rate is not 100%, with a 15–20% risk of failure (including incomplete abortion and ongoing pregnancy). Currently, clinicians primarily rely on limited indicators such as gestational age and gestational sac size for empirical assessment, lacking individualized and precise prediction tools. This leads to a clinical dilemma: either implementing excessive follow-up and interventions for all patients, resulting in wasted medical resources and increased patient burden, or underestimating the risk of failure, thereby exposing patients to complications such as incomplete abortion and severe bleeding. Therefore, developing a prediction model based on routine clinical and ultrasound indicators to provide individualized risk assessment for medication abortion outcomes is of significant importance for optimizing clinical decision-making, improving the efficiency of medical resource utilization, and ensuring patient safety.

药物成份或治疗方案详述:

 

Description for medicine or protocol of treatment in detail:

 

纳入标准:

Inclusion criteria

排除标准:

1: 疑似或确诊为异位妊娠或葡萄胎 2: 存在药物流产禁忌症(如:肾上腺皮质功能不全、长期糖皮质激素治疗、青光眼、哮喘、出血性疾病、对所用药物过敏等) 3: 伴有严重的全身性疾病(如:心、肝、肾功能不全) 4: 无法按时随访或不能提供有效联系方式 5: 同时参与其他临床研究

Exclusion criteria:

1: Suspected or confirmed ectopic pregnancy or molar pregnancy; 2: Presence of any known contraindication to medical abortion (e.g., chronic adrenal failure, long-term corticosteroid therapy, glaucoma, severe asthma, bleeding disorders, or known allergy to the drugs used); 3: Coexisting severe systemic disease (e.g., cardiac, hepatic, or renal insufficiency); 4: Inability to adhere to the scheduled follow-up visits or lack of reliable contact information; 5: Concurrent participation in any other clinical trial.

研究实施时间:

Study execute time:

From 2026-01-01 00:00:00 To 2026-12-31 00:00:00  

征募观察对象时间:

Recruiting time:

From 2026-01-01 00:00:00 To 2026-12-31 00:00:00

干预措施:

Interventions:

组别:

药物流产失败组

样本量:

1200

Group:

Failed Medical Abortion Group

Sample size:

干预措施:

干预措施代码:

Intervention:

None

Intervention code:

组别:

药物流产成功组

样本量:

4800

Group:

Successful Medical Abortion Group

Sample size:

干预措施:

干预措施代码:

Intervention:

None

Intervention code:

研究实施地点:

Countries of recruitment and research settings:

国家:

中国

省(直辖市):

浙江 

市(区县):

 

Country:

China

Province:

Zhejiang

City:

单位(医院):

浙江中医药大学附属第一医院 

单位级别:

三甲 

Institution
hospital:

The First Affiliated Hospital of Zhejiang Chinese Medical University

Level of the institution:

Tertiary A

测量指标:

Outcomes:

指标中文名:

完全流产

指标类型:

主要指标

Outcome:

Complete abortion

Type:

Primary indicator

测量时间点:

治疗后2月

测量方法:

B超及血清检查

Measure time point of outcome:

at 2 months after treatment

Measure method:

Ultrasonography and Serum Tests

指标中文名:

不全流产

指标类型:

次要指标

Outcome:

Imcomplete abortion

Type:

Secondary indicator

测量时间点:

治疗后2月

测量方法:

B超及血清检查

Measure time point of outcome:

at 2 months after treatment

Measure method:

Ultrasonography and Serum Tests

指标中文名:

持续妊娠

指标类型:

次要指标

Outcome:

Persistent pregnancy

Type:

Secondary indicator

测量时间点:

测量方法:

Measure time point of outcome:

Measure method:

采集人体标本:

Collecting sample(s)
from participants:

标本中文名:

组织:

Sample Name:

NA

Tissue:

NA

人体标本去向

其它  

说明

NA

Fate of sample:

0thers  

Note:

NA

征募研究对象情况:

Recruiting status:

尚未开始

Not yet recruiting

年龄范围:

Participant age:

最小 Min age 18 years
最大 Max age 45 years

性别:

女性

Gender:

Female

随机方法(请说明由何人用什么方法产生随机序列):

NA

Randomization Procedure (please state who generates the random number sequence and by what method):

NA

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

盲法:

Blinding:

试验完成后的统计结果(上传文件):

Calculated Results after
the Study Completed(upload file):

是否共享原始数据:

IPD sharing

否No

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):

The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url):

None

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:

数据匿名化:为每位受试者生成一个唯一的研究识别码,取代所有个人身份信息。识别码与身份信息的对应关系(“钥匙文件”)将以加密形式单独存储,并由主要研究员严格保管。 电子数据采集系统:本研究将使用专业、安全的研究电子数据采集平台 数据验证:设置逻辑核查规则(如数值范围),在录入时即时提示错误。 审计追踪:自动记录所有数据的创建、修改和删除痕迹。 数据录入与质控: 所有关键变量(如主要结局、重要预测因子)将采用双人独立录入的方式进行,并进行一致性校验。 研究数据管理员将定期生成数据质量报告,识别缺失值、异常值和逻辑错误,并反馈给研究团队进行核查和修正。 数据存储与备份: 所有电子数据将存储在医院受密码保护的专用研究服务器上,并定期进行备份。 纸质文件(如签署的知情同意书)将存放在带锁的文件柜中。 数据保密与安全:仅授权的研究团队成员可访问与其职责相关的数据。

Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture:

Data Anonymization: A unique study identification code (Study ID) will be generated for each participant to replace all personally identifiable information (PII). The correspondence file (the "key file") linking these codes to personal identities will be stored separately in an encrypted format and kept strictly confidential by the principal investigator. Electronic Data Capture (EDC) System: This study will utilize a professional and secure Electronic Data Capture (EDC) platform. Data Validation: Logic checks (e.g., for value ranges) will be implemented within the EDC system to provide immediate prompts for errors during data entry. Audit Trail: An automated audit trail will be maintained to record all data activities, including creation, modification, and deletion of entries. Data Entry and Quality Control (QC): For all key variables (such as primary outcomes and important predictors), a double data entry procedure will be performed by two independent staff members, followed by consistency checks to identify discrepancies. The data manager will generate regular data quality reports to identify missing values, outliers, and logical errors. These reports will be provided to the research team for review and correction. Data Storage and Backup: All electronic data will be stored on a dedicated, password-protected research server at the hospital, with regular backups performed. Paper-based documents (e.g., signed informed consent forms) will be stored securely in locked filing cabinets. Data Confidentiality and Security: Access to study data will be restricted to authorized research team members and will be granted on a role-specific, need-to-know basis.

数据与安全监察委员会:

Data and Safety Monitoring Committee:

暂未确定/Not yet

注册人:

Name of Registration:

 2025-12-17 17:21:19