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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: |
ChiCTR2600125680 |
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最近更新日期: Date of Last Refreshed on: |
2026-05-29 11:17:26 |
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注册时间: Date of Registration: |
2026-05-29 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: |
社区真实世界环境下不同人机协同体重管理模式对肥胖成年人结局影响的前瞻性队列研究 |
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Public title: |
A Prospective Cohort Study on the Impact of Different Human-Machine Collaborative Weight Management Models on Outcomes in Obese Adults in a Real-World Community Setting |
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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: |
真实世界慢病?群研究:模型构建与数智化管理 |
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Scientific title: |
Real-world Research on Chronic Disease Population: Model Construction and Digital Intelligent Management |
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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: |
孙中华 |
研究负责人: |
张文红 |
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Applicant: |
Zhonghua Sun |
Study leader: |
Wenhong Zhang |
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申请注册联系人电话: Applicant telephone: |
+86 153 8088 7220 |
研究负责人电话: Study leader's telephone: |
+86 25 8359 1175 |
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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: |
sunzhonghua20@163.com |
研究负责人电子邮件: Study leader's E-mail: |
whzhang@nju.edu.cn |
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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: |
江苏省南京市鼓楼区汉口路22号 |
研究负责人通讯地址: |
江苏省南京市鼓楼区汉口路22号 |
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Applicant address: |
No.22 Hankou Road, Gulou District, Nanjing City, Jiangsu Province |
Study leader's address: |
No.22 Hankou Road, Gulou District, Nanjing City, Jiangsu Province |
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申请注册联系人邮政编码: Applicant postcode: |
210093 |
研究负责人邮政编码: Study leader's postcode: |
210093 |
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申请人所在单位: |
南京大学医学院 |
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Applicant's institution: |
Nanjing University Medical School |
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研究负责人所在单位: |
南京大学医学院 |
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Affiliation of the Leader: |
Nanjing University Medical School |
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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: |
NIUIRB20250918004 |
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: |
南京?学科学与技术伦理委员会医学伦理分委会 |
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Name of the ethic committee: |
Medical Ethics Subcommittee of the Science and Technology Ethics Committee of Nanjing University |
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伦理委员会批准日期: Date of approved by ethic committee: |
2025-09-18 00:00:00 |
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伦理委员会联系人: |
范文静 |
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Contact Name of the ethic committee: |
Wenjing Fan |
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伦理委员会联系地址: |
江苏南京市鼓楼区东南楼212室 |
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Contact Address of the ethic committee: |
Room 212, Southeast Building, Gulou District, Nanjing City, Jiangsu Province, China |
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伦理委员会联系人电话: Contact phone of the ethic committee: |
+86 25 8368 6043 |
伦理委员会联系人邮箱: Contact email of the ethic committee: |
irb@nju.edu.cn |
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研究实施负责(组长)单位: |
南京大学医学院 |
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Primary sponsor: |
Nanjing University Medical School |
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研究实施负责(组长)单位地址: |
江苏省南京市鼓楼区汉口路22号 |
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Primary sponsor's address: |
No.22 Hankou Road, Gulou District, Nanjing City, Jiangsu 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: |
国家科技重大专项 —— 慢性非传染性疾病(项目编号:2023ZD0503604) |
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Source(s) of funding: |
Noncommunicable Chronic Diseases-National Science and Technology Major Project (Grant No.2023ZD0503604) |
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Target disease: |
Obesity |
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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: |
探索性研究/预试验 | ||||||||||||||||||||||
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Study phase: |
0 |
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研究设计: |
队列研究 |
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Study design: |
Cohort study |
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研究目的: |
肥胖是社区慢性病管理中的重要问题,与高血压、糖代谢异常、血脂异常及多种心血管代谢风险密切相关。随着数字健康工具和大语言模型技术的发展,社区体重管理已逐渐从单纯的患者自我管理和医生主导管理,扩展到患者端AI支持、医生端AI辅助以及多主体协同管理等多种模式。然而,不同管理模式在真实世界环境中的短期效果、可接受性及成本-效果差异,仍缺乏直接比较证据。 |
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Objectives of Study: |
Obesity has become a critical component of community-based management for non-communicable diseases (NCDs) in China, strongly associated with hypertension, hyperglycemia, dyslipidemia, and various cardiometabolic risks. With the advancement of digital health tools and artificial intelligence (AI) technologies, community weight management has evolved from traditional patient self-management models to human-AI collaborative approaches. However, there is a lack of systematic evaluations comparing the real-world effectiveness, adherence, patient experience, and health economic outcomes of different human-AI collaborative models. This study aims to systematically assess the weight loss effects, health-related quality of life (HRQoL), functional status improvement, satisfaction, and cost-effectiveness of different human-AI collaborative management models through a prospective cohort study, providing evidence-based support for optimizing high-quality weight management in the community. |
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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.年龄≥18 周岁。 2.确诊肥胖,满足以下任一条件: 体重指数(BMI)≥28 kg/m2; 或符合高体脂 / 中心性肥胖标准之一:男性腰围>90 cm、女性腰围>85 cm;男性腰臀比≥0.90、女性腰臀比≥0.85;腰高比≥0.50;男性体脂率>25%、女性体脂率>30%。 3.研究期间在社区真实诊疗环境中接受以下四种体重管理模式之一:患者自我管理、减重门诊医生管理、AI 赋能患者管理、AI 赋能医生管理。 4.能够完成基线及 3 个月随访的体格测量、实验室检查及问卷调查。 5.理解研究内容并自愿签署知情同意书。 6.具备使用智能手机完成平台记录的能力,或可在研究人员协助下完成电子问卷与随访。 |
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Inclusion criteria |
1. Aged >=18 years. 2. Confirmed obesity, meeting any one of the following criteria: Body mass index (BMI) >=28 kg/m2; Or meeting one of the criteria for high body fat/central obesity: waist circumference >90 cm in males, >85 cm in females; waist-to-hip ratio >=0.90 in males, >=0.85 in females; waist-to-height ratio >=0.50; body fat percentage >25% in males, >30% in females. 3. Receiving one of the four weight management models in the real community clinical setting during the study period: patient self-management, physician-led management in weight loss clinics, AI-enabled patient management, AI-enabled physician management. 4. Able to complete physical measurements, laboratory tests and questionnaires at baseline and the 3-month follow-up. 5. Understand the study content and voluntarily sign the informed consent form. 6. Able to use a smartphone to complete platform records, or complete electronic questionnaires and follow-up with the assistance of researchers. |
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排除标准: |
1.妊娠期、哺乳期,或 3 个月内有妊娠计划。 2.已知继发性肥胖且病因尚未稳定控制。 3.既往 6 个月内接受减重手术。 4.合并严重心、肝、肾等器官功能不全,或存在明显不适合参加生活方式管理者。 5.严重精神障碍、认知障碍或其他无法完成知情同意与随访者。 6.基线时已参加其他可能显著影响体重的干预性研究。 7.研究者判断不适合纳入者。 |
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Exclusion criteria: |
1. Pregnant or lactating women, or those planning pregnancy within 3 months. 2. Secondary obesity with unstable underlying causes. 3. Undergoing bariatric surgery within the past 6 months. 4. Severe impairment of cardiac, hepatic, renal or other vital organ function, or unsuitable for lifestyle intervention. 5. Severe mental disorder or cognitive impairment, unable to provide informed consent or complete follow-up. 6. Participation in other weight-affecting intervention studies at baseline. 7. Judged ineligible by the investigator. |
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研究实施时间: Study execute time: |
从 From 2026-06-01 00:00:00至 To 2026-12-31 00:00:00 |
征募观察对象时间: Recruiting time: |
从From 2026-06-01 00:00:00 至 To 2026-07-31 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: |
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): |
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: |
公开/Public |
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盲法: |
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Blinding: |
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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 |
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): |
本研究不计划公开共享个体参与者原始数据。研究结束后,汇总分析结果将以论文形式发表。 |
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The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url): |
No individual participant data (IPD) sharing is planned for this study. Aggregated results will be published in a scientific paper after the study is completed. |
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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: |
本研究采用标准化病例记录表(CRF)收集数据,使用基于互联网的电子数据采集系统(EDC)进行数据录入与管理。所有数据将进行双人录入、逻辑核查与定期质量控制,确保数据真实、完整、可溯源。 |
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Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture: |
Standardized Case Report Forms (CRF) will be used for data collection. An internet-based Electronic Data Capture (EDC) system will be used for data entry and management. All data will undergo double entry, logical checks, and regular quality control to ensure accuracy, completeness, and traceability |
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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 |