[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100647472":3},{"organization":4,"armGroups":7,"interventions":20,"overallOfficials":26,"centralContacts":31,"locations":37,"responsibleParty":54,"collaborators":26,"id":58,"slug":59,"hasResults":60,"nctId":61,"briefTitle":62,"officialTitle":62,"acronym":63,"eligibilityCriteria":64,"healthyVolunteers":60,"sex":65,"minAge":66,"maxAge":67,"enrollmentInfo":68,"targetDuration":26,"studyType":71,"phases":72,"briefSummary":74,"conditions":75,"keywords":78,"overallStatus":84,"whyStopped":26,"lastUpdateSubmitDate":85,"lastUpdatePostDateStruct":86,"startDateStruct":89,"completionDateStruct":91,"leadSponsor":93,"locationsCount":94},{"fullName":5,"class":6},"First Affiliated Hospital of Chongqing Medical University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"DKD Clinical Decision Support System Intervention Group","EXPERIMENTAL","The participating primary medical institutions in this group adopt the DKD standardized screening and intelligent graded management software embedded as a plug-in into the HIS system. The digital tool can automatically calculate eGFR, complete DKD risk stratification, send intelligent reminders for UACR screening, and provide individualized treatment targets, follow-up plans and referral prompts in line with relevant guidelines. All enrolled subjects receive unified physical examinations and laboratory tests at each scheduled visit according to the research protocol.",[13],"Behavioral: Intervention Name Clinical decision support system for diabetic kidney disease (DKD-CDSS)",{"label":15,"type":16,"description":17,"interventionNames":18},"Routine Conventional Diabetes Management Group","ACTIVE_COMPARATOR","The participating primary medical institutions in this group carry out routine diabetes management in accordance with the National Primary Diabetes Prevention and Control Guidelines and national basic public health service requirements, without using the DKD intelligent screening and graded management tool developed in this study. There are no digital auxiliary functions such as automatic eGFR calculation, risk grading, intelligent follow-up and referral reminders during the whole management process. All enrolled subjects receive the same physical examination items and laboratory testing frequency as the intervention group.",[19],"Behavioral: Routine guideline-based diabetes management",[21,27],{"type":22,"name":23,"description":24,"armGroupLabels":25,"otherNames":26},"BEHAVIORAL","Intervention Name Clinical decision support system for diabetic kidney disease (DKD-CDSS)","This study's intervention is a hospital information system-embedded diabetic kidney disease clinical decision support system (DKD-CDSS). It automatically computes eGFR, completes DKD risk stratification, triggers UACR screening reminders, and outputs individualized guideline-aligned glycemic, blood pressure, lipid control targets, medication adjustment suggestions, follow-up schedules and specialist referral advice for type 2 diabetes patients. Unlike general diabetes management software, this CDSS focuses specifically on early renal injury screening and hierarchical standardized treatment of DKD, and is tailored for primary care community and township medical institutions. The control arm only adopts traditional manual routine diabetes management without this dedicated DKD auxiliary decision-making module.",[9],null,{"type":22,"name":28,"description":29,"armGroupLabels":30,"otherNames":26},"Routine guideline-based diabetes management","Participants in this arm receive routine diabetes management in accordance with national primary diabetes prevention and control guidelines without access to the dedicated DKD clinical decision support system. Clinicians rely on their own clinical experience to judge DKD risk, arrange UACR screening, adjust hypoglycemic and hypotensive drugs, and formulate follow-up plans, without automatic system reminders or standardized hierarchical treatment recommendations targeting diabetic kidney disease. The inspection schedule and physical examination items are completely consistent with the intervention group, while all medical decision-making links do not get auxiliary prompts from the DKD-specific CDSS.",[15],[32],{"name":33,"role":34,"phone":35,"phoneExt":26,"email":36},"Zhihong Wang, Doctor of Philosophy","CONTACT","+86 13883021919","towzh713@126.com",[38],{"facility":39,"status":26,"city":39,"state":40,"zip":26,"country":41,"countryCode":42,"cosmosGeoPoint":43,"geoPoint":48,"contacts":49},"Chongqing","Chongqing Municipality","China","CN",{"type":44,"coordinates":45},"Point",[46,47],106.55771,29.56026,{"lat":47,"lon":46},[50],{"name":51,"role":34,"phone":52,"phoneExt":26,"email":53},"Qing Yan, Bachelor","+86 023-89011876","cyfyykyc@cqmu.edu.cn",{"type":55,"investigatorFullName":56,"investigatorTitle":57,"investigatorAffiliation":5,"oldNameTitle":26,"oldOrganization":26},"PRINCIPAL_INVESTIGATOR","Zhihong Wang","Professor","100647472","evaluating-the-effectiveness-of-a-smart-screening-and-tiered-management-tool-for-diabetic-kidney-disease-in-primary-care-a-cluster-randomized-trial-100647472",false,"NCT07707518","Evaluating the Effectiveness of a Smart Screening and Tiered Management Tool for Diabetic Kidney Disease in Primary Care: A Cluster Randomized Trial","SMART-DKD","Inclusion Criteria:\n\n* Aged 18-75 years old.\n* Diagnosed with type 2 diabetes mellitus.\n* Able to complete follow-up visits and relevant examinations as required.\n* Voluntary participation with signed informed consent.\n\nExclusion Criteria\n\n* Complicated with severe hepatic, renal, cardiac or malignant tumor diseases.\n* With acute complications of diabetes or severe infectious diseases within 3 months.\n* Pregnant or lactating women.\n* Participating in other similar clinical intervention studies.\n* Unable to cooperate with study management due to cognitive or mental disorders.","ALL","18 Years","75 Years",{"count":69,"type":70},3000,"ESTIMATED","INTERVENTIONAL",[73],"NA","This is a cluster-randomized controlled trial aiming to evaluate the effectiveness of an intelligent standardized screening and risk-stratified management tool for diabetic kidney disease (DKD) among adults with type 2 diabetes in primary care settings.\n\nBackground China has a high prevalence of type 2 diabetes, and 30%-40% of diabetic patients develop DKD, the leading cause of end-stage kidney disease. Primary care facilities lack convenient, standardized digital tools to screen, grade and manage DKD systematically, leading to delayed detection and suboptimal kidney protection for diabetic patients. This study develops a localized intelligent DKD management system integrated into primary care electronic medical records (HIS) to solve this gap.\n\nStudy Design \\& Participants\n\nWe will recruit 30 primary healthcare institutions (15 urban community health centers, 15 rural township health centers) across Longyou County, with at least 200 registered type 2 diabetes patients at each site. A total of 3,000 eligible adults aged 18-75 years diagnosed with type 2 diabetes will be enrolled, randomly assigned in a 1:1 cluster ratio to two groups:\n\nIntervention group (15 sites, 1,500 patients): Receive the intelligent DKD screening and graded management plug-in embedded in local HIS. The tool automatically calculates estimated glomerular filtration rate (eGFR), generates DKD risk stratification, sends reminders for regular urine albumin creatinine ratio (UACR) testing, and provides individualized treatment, follow-up and referral guidance.\n\nControl group (15 sites, 1,500 patients): Receive routine standard diabetes management following national primary care diabetes guidelines, without access to the intelligent DKD digital support system.\n\nStudy Procedures All participants complete a baseline screening visit (V1) to sign informed consent, review medical history, complete physical examinations, and undergo lab tests including UACR, serum creatinine, fasting blood glucose, glycated hemoglobin, lipid profile and urinalysis. Follow-up visits are scheduled at 3 months (V2), 6 months (V3), and 12 months (V4) after baseline, repeating physical checks and core laboratory testing. An optional extended observational follow-up continues until 24 months, with biospecimens collected and shipped to the central research laboratory for unified testing. Participants may withdraw voluntarily at any time without impact on routine clinical care, and unscheduled visits will be arranged if adverse events or abnormal lab results occur.\n\nKey Study Outcomes Primary Outcome: Change in log-transformed urine albumin creatinine ratio (UACR) from baseline to the 12-month follow-up, comparing the two management models.\n\nSecondary Outcomes: 12-month DKD screening rate, DKD diagnosis rate, standardized DKD treatment rate, and change in eGFR over 12 months. The study also assesses the operability of the intelligent management tool and patient treatment adherence in primary care.\n\nRisks \\& Benefits Potential Risks: Participants will undergo routine fasting blood draws and urine collection at each visit, which may cause minor temporary pain, bruising, or rare vasovagal reactions during venipuncture.\n\nBenefits: All participants receive free regular DKD-related laboratory testing covered by the research team. Intervention group patients receive personalized, automated kidney risk management recommendations to slow DKD progression. Any study-related injury will receive free medical treatment and corresponding compensation from the research project.\n\nData Protection \\& Ethics All participant personal information and biological samples are fully anonymized with unique study codes and stored in encrypted databases with restricted access. The study strictly complies with the Declaration of Helsinki, Chinese GCP, and domestic clinical research regulations. All participants provide written informed consent before enrollment, with full rights to withdraw at any stage without penalty. Study results will be published in peer-reviewed journals and presented at academic conferences to improve nationwide primary care DKD prevention and control.\n\nStatistical Analysis All analyses will use intention-to-treat, modified intention-to-treat, per-protocol, and safety analysis datasets. Mixed models for repeated measures, t-tests, rank-sum tests, and Fisher's exact tests will be applied to compare between-group differences, with multiple imputation used to handle missing primary endpoint data. All adverse events will be coded using MedDRA and summarized to evaluate the safety profile of the intervention strategy.",[76,77],"Type 2 Diabetes Mellitus","Diabetic Kidney Disease",[79,80,81,82,83],"Type 2 diabetes","Diabetic kidney disease","Primary care","CDSS","Cluster randomized trial","NOT_YET_RECRUITING","2026-07-13",{"date":87,"type":88},"2026-07-16","ACTUAL",{"date":90,"type":70},"2026-07-30",{"date":92,"type":70},"2028-09-30",{"name":5,"class":6},1]