ChiCTR2400093578 版本V1.0 版本创建时间2024/12/09 10:13:02 中国临床试验注册中心

审核状态:

Project audit state:

通过审核

Successful

注册号:

Registration number:

ChiCTR2400093578 

最近更新日期:

Date of Last Refreshed on:

2024-12-09 10:12:27 

注册时间:

Date of Registration:

2024-12-09 00:00:00 

注册号状态:

预注册

Registration Status:

Prospective registration

注册题目:

人工智能筛查模型在冠心病识别任务中的性能评估

Public title:

Performance evaluation of artificial intelligence screening model in coronary heart disease recognition task

注册题目简写:

English Acronym:

研究课题的正式科学名称:

人工智能筛查模型在冠心病识别任务中的性能评估

Scientific title:

Performance evaluation of artificial intelligence screening model in coronary heart disease recognition task

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:

纪宏伟 

研究负责人:

陈婷丽 

Applicant:

Ji Hongwei 

Study leader:

Chen Tingli 

申请注册联系人电话:

Applicant telephone:

+86 131 2051 8791

研究负责人电话:

Study leader's
telephone:

+86 185 6165 3019

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:

hongweijicn@gmail.com

研究负责人电子邮件:

Study leader's E-mail:

chentingli1028@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:

北京市海淀区清华园

研究负责人通讯地址:

江苏省无锡市大箕山华东疗养院(上海市保健医疗中心)

Applicant address:

Qinghua Yuan, Haidian, Beijing, China

Study leader's address:

East China Sanatorium in Dajishan, Wuxi City, Jiangsu Province (Shanghai Health and Medical Center)

申请注册联系人邮政编码:

Applicant postcode:

100084

研究负责人邮政编码:

Study leader's postcode:

申请人所在单位:

清华大学

Applicant's institution:

Tsinghua University

研究负责人所在单位:

上海市保健医疗中心

Affiliation of the Leader:

Shanghai Health and Medical Center

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:

(2024)伦研批会第 12号

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:

上海市保健医疗中心医学伦理委员会

Name of the ethic committee:

Medical Ethics Committee of Shanghai Health and Medical Center

伦理委员会批准日期:

Date of approved by ethic committee:

2024-06-15 00:00:00

伦理委员会联系人:

王静

Contact Name of the ethic committee:

Wang Jing

伦理委员会联系地址:

江苏省无锡市大箕山华东疗养院(上海市保健医疗中心)

Contact Address of the ethic committee:

East China Sanatorium in Dajishan, Wuxi City, Jiangsu Province (Shanghai Health and Medical Center)

伦理委员会联系人电话:

Contact phone of the ethic committee:

+86 186 2609 2096

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:

上海市保健医疗中心

Primary sponsor:

Shanghai Health and Medical Center

研究实施负责(组长)单位地址:

江苏省无锡市大箕山华东疗养院(上海市保健医疗中心)

Primary sponsor's address:

East China Sanatorium in Dajishan, Wuxi City, Jiangsu Province (Shanghai Health and Medical Center)

试验主办单位(项目批准或申办者):

Secondary sponsor:

国家:

中国

省(直辖市):

江苏

市(区县):

无锡

Country:

China

Province:

Jiangsu

City:

Wuxi

单位(医院):

上海市保健医疗中心

具体地址:

江苏省无锡市大箕山华东疗养院(上海市保健医疗中心)

Institution
hospital:

Shanghai Health and Medical Center

Address:

East China Sanatorium in Dajishan, Wuxi City, Jiangsu Province (Shanghai Health and Medical Center)

经费或物资来源:

国家自然科学基金

Source(s) of funding:

National Natural Science Foundation

研究疾病:

冠状动脉粥样硬化性心脏病  

Target disease:

coronary heart disease

研究疾病代码:

Target disease code:

研究类型:

干预性研究

Study type:

Interventional study

研究所处阶段:

探索性研究/预试验 

Study phase:

0

研究设计:

横断面 

Study design:

Cross-sectional 

研究目的:

本研究旨在通过开展一项对照实验,进一步验证和优化基于眼底图像和临床数据的深度学习系统(DeepCHD)在冠心病筛查中的有效性和实用性。具体目标如下: 1. 验证DeepCHD系统在门诊疑似冠心病人群中筛查冠心病的准确性和可行性。 2. 与传统的冠心病评估模型进行对照分析,评估DeepCHD系统在临床诊疗流程中的应用价值。 3. 提出优化DeepCHD系统的方法,提高其在实际应用中的泛化能力和稳定性。  

Objectives of Study:

This study aims to further validate and optimize the effectiveness and practicality of a deep learning system (DeepCHD) based on fundus images and clinical data in coronary heart disease screening through a prospective experiment. The specific objectives are as follows: 1. Verify the accuracy and feasibility of the DeepCHD system in screening suspected coronary heart disease in outpatient populations. 2. Compare and analyze with traditional coronary heart disease assessment models to evaluate the application value of DeepCHD system in clinical diagnosis and treatment processes. 3. Propose methods to optimize the DeepCHD system and improve its generalization ability and stability in practical applications.

药物成份或治疗方案详述:

 

Description for medicine or protocol of treatment in detail:

 

纳入标准:

1. 有冠心病症状者 2. 年龄18-75周岁 3. 能接受、配合入选临床试验后的检查以及随访工作 4. 冠心病诊断标准:CHD is defined as a history of myocardial infarction (MI), revascularization (coronary artery bypass grafting [CABG] or percutaneous coronary intervention [PCI]), or known ≥50% stenosis in a major epicardial coronary artery.

Inclusion criteria

1. Individuals with symptoms of coronary heart disease 2. Age range: 18-75 years old 3. Can accept and cooperate with the examination and follow-up work after being selected for clinical trials 4. Diagnostic criteria for coronary heart disease: CHD is defined as a history of myocardial infarction (MI), revascularization (coronary artery bypass grafting [CABG] or percutaneous coronary intervention [PCI]), or known ≥50% stenosis in a major epicardial coronary artery.

排除标准:

1. 严重高血压(>180/110mmHg) 2. 复杂心律失常(房颤、房扑、频发性早搏) 3. 严重肺疾病和胸部畸形或手术者 4. 急性心肌梗死发病不足3个月 5. 心动图显示束支传导阻滞 6. 超声心动图证实为左室肥厚,或扩张性心肌病 7. 严重肝肾功能障碍及电解质紊乱者 8. 失随访者

Exclusion criteria:

1. Severe hypertension (>180/110mmHg) 2. Complex arrhythmia (atrial fibrillation, atrial flutter, frequent premature beats) 3. Severe lung disease and chest malformation or surgery patients 4. Acute myocardial infarction occurring less than 3 months ago 5. Echocardiography shows bundle branch block 6. Echocardiography confirms left ventricular hypertrophy or dilated cardiomyopathy 7. Individuals with severe liver and kidney dysfunction and electrolyte imbalance 8. Follow up loss

研究实施时间:

Study execute time:

From 2024-12-15 00:00:00 To 2025-01-15 00:00:00  

征募观察对象时间:

Recruiting time:

From 2024-12-15 00:00:00 To 2025-01-15 00:00:00

干预措施:

Interventions:

组别:

DeepCHD深度学习系统辅助医师决策组

样本量:

450

Group:

DeepCHD deep learning system assists physician decision-making group

Sample size:

干预措施:

干预措施代码:

Intervention:

None

Intervention code:

组别:

PTP(RFCL)模型辅助医师决策组

样本量:

450

Group:

PTP (RFCL) model assists physician decision-making 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):

江苏 

市(区县):

无锡 

Country:

China

Province:

jiangsu

City:

wuxi

单位(医院):

华东疗养院(上海市保健医疗中心) 

单位级别:

三级 

Institution
hospital:

East China Sanatorium in Dajishan (Shanghai Health and Medical Center)

Level of the institution:

Tertiary

国家:

中国

省(直辖市):

上海 

市(区县):

上海 

Country:

China

Province:

Shanghai

City:

Shanghai

单位(医院):

上海市第六人民医院 

单位级别:

三级 

Institution
hospital:

Shanghai Sixth People's Hospital

Level of the institution:

Tertiary

测量指标:

Outcomes:

指标中文名:

准确性

指标类型:

主要指标

Outcome:

accuracy

Type:

Primary indicator

测量时间点:

测量方法:

医师判断是否有冠心病的准确性

Measure time point of outcome:

Measure method:

The accuracy of physicians in determining whether there is coronary heart disease

指标中文名:

时间

指标类型:

次要指标

Outcome:

time consumed

Type:

Secondary indicator

测量时间点:

测量方法:

医师判断是否有冠心病所花费的时间

Measure time point of outcome:

Measure method:

The time it takes for a physician to determine whether there is coronary heart disease

采集人体标本:

Collecting sample(s)
from participants:

标本中文名:

组织:

Sample Name:

none

Tissue:

人体标本去向

其它  

说明

Fate of sample:

0thers  

Note:

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 75 years

性别:

男女均可

Gender:

Both

随机方法(请说明由何人用什么方法产生随机序列):

由计算机科学家使用随机数码对参与者进行1:1随机化分组(对已收集病例进行随机分组再评估)

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

Computer scientists use random numbers to randomize participants into 1:1 groups

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):

患者个人原始数据不会被共享

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

Individual level data will not be shared

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:

数据管理:研究人员通过手动录入患者信息、临床数据、预测结果等。

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

Data management: Researchers manually input patient information, clinical data, prediction results, etc.

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:

 2024-12-09 10:12:27