A Multicenter Randomized Double-Blind Trial of Chrocare CDSS for Integrated Management of Type 2 Diabetes
Chrocare-DM
A Randomized, Double-Blind, Parallel-Group, Multicenter Clinical Trial to Evaluate the Effectiveness and Safety of a Chrocare Large Model-Based Clinical Decision Support System for Integrated Management of Patients With Type 2 Diabetes
1 other identifier
interventional
1,200
1 country
1
Brief Summary
This is a multicenter, randomized, double-blind, parallel-group clinical study for adults with type 2 diabetes and early diabetic kidney or retinal complications. A total of 1,200 eligible participants will be randomly divided into two groups at a 1:1 ratio. Participants in the intervention group will receive clinical management suggestions generated by the Chrocare large language model clinical decision support system, while those in the control group will receive standard diabetes care formulated by experienced endocrinologists. All participants will complete 3 study visits over 6 months to test blood glucose, glycated hemoglobin, blood lipids, kidney and eye indicators, and record hypoglycemia or other adverse events. The main goal of this research is to compare whether the AI-assisted management can help more patients reach target blood glucose levels, as well as evaluate the safety of this AI system for long-term diabetes integrated treatment.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Oct 2026
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
September 6, 2026
CompletedFirst Posted
Study publicly available on registry
September 22, 2026
CompletedStudy Start
First participant enrolled
October 8, 2026
ExpectedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2027
Study Completion
Last participant's last visit for all outcomes
December 30, 2027
September 22, 2026
September 1, 2026
1.1 years
September 6, 2026
September 20, 2026
Conditions
Outcome Measures
Primary Outcomes (1)
Proportion of participants achieving HbA1c less than 7.0% at Month 6
The percentage of subjects whose HbA1c level is below 7.0% after 6 months of intervention, compared between the Chrocare AI clinical decision support system group and the routine physician care control group. This indicator reflects the overall blood glucose control effect of integrated diabetes management.
6 months after participant enrollment
Secondary Outcomes (6)
Change in HbA1c from baseline to Month 3 and Month 6
3 months and 6 months after participant enrollment
Change in urine albumin-creatinine ratio (UACR) from baseline to Month 6
6 months after participant enrollment
Change in diabetic retinopathy from baseline to Month 6
6 months after participant enrollment
Proportion of treatment plans complying with domestic and international diabetes guidelines
Throughout the 6-month intervention period
Incidence of hypoglycemia and all adverse events during follow-up
From baseline visit to Month 6 follow-up visit
- +1 more secondary outcomes
Study Arms (2)
Chrocare-Intervention Group
EXPERIMENTALParticipants receive integrated type 2 diabetes management recommendations generated by the Chrocare large language model clinical decision support system. The model automatically extracts multi-source clinical data, generates individualized hypoglycemic, hypotensive and lipid-lowering regimens consistent with diabetes guidelines, and assesses microvascular complication risks. All participants complete standardized follow-up visits at baseline, Month 3 and Month 6 with unified laboratory and imaging tests.
Routine-Control Group
ACTIVE COMPARATORParticipants receive standard integrated type 2 diabetes care formulated by experienced attending endocrinologists through double independent review. Physicians develop individualized treatment plans based on identical clinical data sources used in the intervention group. All participants complete the same 3 standardized follow-up visits and unified laboratory/imaging examinations within 6 months.
Interventions
This artificial intelligence large language model system automatically extracts electronic medical, laboratory and imaging data of type 2 diabetes patients, generates individualized hypoglycemic, hypotensive and lipid-lowering treatment plans complying with domestic and international diabetes guidelines, and provides risk assessment of diabetic microvascular complications for integrated chronic disease management during 6-month standardized follow-up.
Individualized 2-type diabetes comprehensive management schemes formulated by attending endocrinologists through double independent review, with identical 6-month unified follow-up and test indicators as the AI intervention group.
Eligibility Criteria
You may qualify if:
- Aged ≥ 18 years old;
- Clinically diagnosed with Type 2 Diabetes Mellitus;
- Baseline glycated hemoglobin (HbA1c) ranges from 7.0% to 9.0%;
- Complicated with mild-to-moderate diabetic nephropathy (UACR 3.39-33.9 mg/mmol) or mild non-proliferative diabetic retinopathy;
- Voluntarily sign written informed consent form;
- Able to complete all scheduled 6-month follow-up visits.
You may not qualify if:
- Type 1 diabetes, monogenic diabetes or secondary diabetes;
- Severe cardiac, hepatic or renal dysfunction; proliferative diabetic retinopathy;
- History of diabetic acute complications within 3 months before screening; active infectious diseases;
- Pregnant, breastfeeding or planning pregnancy during the trial period;
- Participated in other interventional clinical trials within the past 3 months;
- Investigators judge the subject unsuitable for enrollment for any other reason.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Ruijin Hospital, Shanghai Jiaotong University School of Medicine
Shanghai, China
Related Publications (18)
Ning G. Medical Education in Diabetes Management on the New Horizon: Insights From Metabolic Management Center. J Diabetes. 2025 Mar;17(3):e70075. doi: 10.1111/1753-0407.70075. No abstract available.
PMID: 40107961BACKGROUNDZhang Y, Shi J, Peng Y, Zhao Z, Zheng Q, Wang Z, Liu K, Jiao S, Qiu K, Zhou Z, Yan L, Zhao D, Jiang H, Dai Y, Su B, Gu P, Su H, Wan Q, Peng Y, Liu J, Hu L, Ke T, Chen L, Xu F, Dong Q, Terzopoulos D, Ning G, Xu X, Ding X, Wang W. Artificial intelligence-enabled screening for diabetic retinopathy: a real-world, multicenter and prospective study. BMJ Open Diabetes Res Care. 2020 Oct;8(1):e001596. doi: 10.1136/bmjdrc-2020-001596.
PMID: 33087340BACKGROUNDZhang Y, Wang W, Ning G. Metabolic Management Center: An innovation project for the management of metabolic diseases and complications in China. J Diabetes. 2019 Jan;11(1):11-13. doi: 10.1111/1753-0407.12847. Epub 2018 Oct 3. No abstract available.
PMID: 30284373BACKGROUNDHu C, Zhang Y, Zhang J, Huo Y, Wan Q, Li M, Qi H, Du R, Zhu Y, Qin Y, Hu R, Shi L, Su Q, Yu X, Yan L, Qin G, Tang X, Chen G, Xu M, Wang T, Zhao Z, Chen Y, Gao Z, Wang G, Shen F, Luo Z, Chen L, Li Q, Ye Z, Zhang Y, Liu C, Wang Y, Wu S, Yang T, Deng H, Chen L, Zhao J, Mu Y, Wang W, Xu Y, Bi Y, Lu J, Ning G; REACTION Study Group. Age at menarche, ideal cardiovascular health metrics, and risk of diabetes in adulthood: Findings from the REACTION study. J Diabetes. 2021 Jun;13(6):458-468. doi: 10.1111/1753-0407.13128. Epub 2020 Dec 29.
PMID: 33135296BACKGROUNDWang T, Lu J, Su Q, Chen Y, Bi Y, Mu Y, Chen L, Hu R, Tang X, Yu X, Li M, Xu M, Xu Y, Zhao Z, Yan L, Qin G, Wan Q, Chen G, Dai M, Zhang D, Gao Z, Wang G, Shen F, Luo Z, Qin Y, Chen L, Huo Y, Li Q, Ye Z, Zhang Y, Liu C, Wang Y, Wu S, Yang T, Deng H, Li D, Lai S, Bloomgarden ZT, Shi L, Ning G, Zhao J, Wang W; 4C Study Group. Ideal Cardiovascular Health Metrics and Major Cardiovascular Events in Patients With Prediabetes and Diabetes. JAMA Cardiol. 2019 Sep 1;4(9):874-883. doi: 10.1001/jamacardio.2019.2499.
PMID: 31365039BACKGROUNDLook AHEAD Research Group; Wing RR, Bolin P, Brancati FL, Bray GA, Clark JM, Coday M, Crow RS, Curtis JM, Egan CM, Espeland MA, Evans M, Foreyt JP, Ghazarian S, Gregg EW, Harrison B, Hazuda HP, Hill JO, Horton ES, Hubbard VS, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Kitabchi AE, Knowler WC, Lewis CE, Maschak-Carey BJ, Montez MG, Murillo A, Nathan DM, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Reboussin D, Regensteiner JG, Rickman AD, Ryan DH, Safford M, Wadden TA, Wagenknecht LE, West DS, Williamson DF, Yanovski SZ. Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. N Engl J Med. 2013 Jul 11;369(2):145-54. doi: 10.1056/NEJMoa1212914. Epub 2013 Jun 24.
PMID: 23796131BACKGROUNDTaheri S, Zaghloul H, Chagoury O, Elhadad S, Ahmed SH, El Khatib N, Amona RA, El Nahas K, Suleiman N, Alnaama A, Al-Hamaq A, Charlson M, Wells MT, Al-Abdulla S, Abou-Samra AB. Effect of intensive lifestyle intervention on bodyweight and glycaemia in early type 2 diabetes (DIADEM-I): an open-label, parallel-group, randomised controlled trial. Lancet Diabetes Endocrinol. 2020 Jun;8(6):477-489. doi: 10.1016/S2213-8587(20)30117-0.
PMID: 32445735BACKGROUNDLean ME, Leslie WS, Barnes AC, Brosnahan N, Thom G, McCombie L, Peters C, Zhyzhneuskaya S, Al-Mrabeh A, Hollingsworth KG, Rodrigues AM, Rehackova L, Adamson AJ, Sniehotta FF, Mathers JC, Ross HM, McIlvenna Y, Stefanetti R, Trenell M, Welsh P, Kean S, Ford I, McConnachie A, Sattar N, Taylor R. Primary care-led weight management for remission of type 2 diabetes (DiRECT): an open-label, cluster-randomised trial. Lancet. 2018 Feb 10;391(10120):541-551. doi: 10.1016/S0140-6736(17)33102-1. Epub 2017 Dec 5.
PMID: 29221645BACKGROUNDLeslie WS, Ford I, Sattar N, Hollingsworth KG, Adamson A, Sniehotta FF, McCombie L, Brosnahan N, Ross H, Mathers JC, Peters C, Thom G, Barnes A, Kean S, McIlvenna Y, Rodrigues A, Rehackova L, Zhyzhneuskaya S, Taylor R, Lean ME. The Diabetes Remission Clinical Trial (DiRECT): protocol for a cluster randomised trial. BMC Fam Pract. 2016 Feb 16;17:20. doi: 10.1186/s12875-016-0406-2.
PMID: 26879684BACKGROUNDDavies MJ, Aroda VR, Collins BS, Gabbay RA, Green J, Maruthur NM, Rosas SE, Del Prato S, Mathieu C, Mingrone G, Rossing P, Tankova T, Tsapas A, Buse JB. Management of hyperglycaemia in type 2 diabetes, 2022. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia. 2022 Dec;65(12):1925-1966. doi: 10.1007/s00125-022-05787-2. Epub 2022 Sep 24.
PMID: 36151309BACKGROUNDMartindale APL, Llewellyn CD, de Visser RO, Ng B, Ngai V, Kale AU, di Ruffano LF, Golub RM, Collins GS, Moher D, McCradden MD, Oakden-Rayner L, Rivera SC, Calvert M, Kelly CJ, Lee CS, Yau C, Chan AW, Keane PA, Beam AL, Denniston AK, Liu X. Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines. Nat Commun. 2024 Feb 22;15(1):1619. doi: 10.1038/s41467-024-45355-3.
PMID: 38388497BACKGROUNDCruz Rivera S, Liu X, Chan AW, Denniston AK, Calvert MJ; SPIRIT-AI and CONSORT-AI Working Group; SPIRIT-AI and CONSORT-AI Steering Group; SPIRIT-AI and CONSORT-AI Consensus Group. Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension. Nat Med. 2020 Sep;26(9):1351-1363. doi: 10.1038/s41591-020-1037-7. Epub 2020 Sep 9.
PMID: 32908284BACKGROUNDShow us the evidence for the value of medical AI. Nat Med. 2026 Apr;32(4):1163. doi: 10.1038/s41591-026-04389-4. No abstract available.
PMID: 42014883BACKGROUNDNie J, Haft C, Xia A, Wang X. AI-Powered Diabetes Precision Health: From Data to Action. NEJM AI. 2025 Sep;2(9):10.1056/AIp2500475. doi: 10.1056/AIp2500475. Epub 2025 Aug 28.
PMID: 40918692BACKGROUNDAhmad E, Lim S, Lamptey R, Webb DR, Davies MJ. Type 2 diabetes. Lancet. 2022 Nov 19;400(10365):1803-1820. doi: 10.1016/S0140-6736(22)01655-5. Epub 2022 Nov 1.
PMID: 36332637BACKGROUNDGBD 2021 Diabetes Collaborators. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021. Lancet. 2023 Jul 15;402(10397):203-234. doi: 10.1016/S0140-6736(23)01301-6. Epub 2023 Jun 22.
PMID: 37356446BACKGROUNDWang L, Gao P, Zhang M, Huang Z, Zhang D, Deng Q, Li Y, Zhao Z, Qin X, Jin D, Zhou M, Tang X, Hu Y, Wang L. Prevalence and Ethnic Pattern of Diabetes and Prediabetes in China in 2013. JAMA. 2017 Jun 27;317(24):2515-2523. doi: 10.1001/jama.2017.7596.
PMID: 28655017BACKGROUNDXu Y, Wang L, He J, Bi Y, Li M, Wang T, Wang L, Jiang Y, Dai M, Lu J, Xu M, Li Y, Hu N, Li J, Mi S, Chen CS, Li G, Mu Y, Zhao J, Kong L, Chen J, Lai S, Wang W, Zhao W, Ning G; 2010 China Noncommunicable Disease Surveillance Group. Prevalence and control of diabetes in Chinese adults. JAMA. 2013 Sep 4;310(9):948-59. doi: 10.1001/jama.2013.168118.
PMID: 24002281BACKGROUND
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Weiqing Wang
Ruijin Hospital: Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- DOUBLE
- Who Masked
- PARTICIPANT, CARE PROVIDER
- Purpose
- TREATMENT
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Professor, Chief Physician, Department of Endocrinology and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine
Study Record Dates
First Submitted
September 6, 2026
First Posted
September 22, 2026
Study Start (Estimated)
October 8, 2026
Primary Completion (Estimated)
December 1, 2027
Study Completion (Estimated)
December 30, 2027
Last Updated
September 22, 2026
Record last verified: 2026-09
Data Sharing
- IPD Sharing
- Will not share