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RecruitingNCT05349955GUARDUpdated May 14, 2025

Effects and Safety of Diabetic GUideline Algorithm Implementation Performed by Primary Care Physicians in the Community

An interventional study of Intensive guideline algorithm implementation and Conventional guideline algorithm implementation in Type 2 Diabetes, Cardiovascular Complication and Diabetic Kidney Disease, sponsored by Shanghai Zhongshan Hospital. Recruiting at 13 sites in China. Open to participants aged 65 Years and older. Per ClinicalTrials.gov, last updated 2025-05-14.

Sponsored by Shanghai Zhongshan Hospital · Not applicable, Interventional, and Treatment

From the registry’s dates

  • Started Nov 2022; still recruiting 3 years 10 months later.
Phase
Not applicable
Study type
Interventional
Enrollment
5,600
Allocation
Randomized
Ages
65 Years and older
Sex
All
01

Study summary

The Effects and Safety of Diabetic GUideline Algorithm Implementation in the Community (GUARD-Community) study is a 2-arm, cluster-randomized control trial to evaluate the effect and safety of guideline algorithm intervention performed by primary care physicians on cardiovascular and renal outcomes in elderly patients with high risk in community.

Read the detailed description

Diabetes is an important public health concern. Elderly diabetic patients are characterized by a long duration and complications, including chronic kidney disease and/or cardiovascular disease. In the past 30 years, the guidelines of CDS, EASD or ADA have been frequently updated. The latest guideline on pharmacological algorithm recommend that patients with cardiovascular, renal disease or very high/high CV risk patients should be treated with anti-diabetic drugs presenting target organ protection, including SGLT2i and GLP1RA. And the guideline recommend comprehensive control of the cardiovascular risk factors, such as hypertension and dyslipidemia.

This GUARD-Community study is a community based cluster-randomized controlled trial and will enroll 5600 or more participants in more than 120 clusters aged ≥ 65 years with T2DM and complicated with high/very high cardiovascular risk factors . The trial will evaluate the the effects and safety of intensive "Guideline" algorithm implementation on CVD and renal outcomes. The primary hypothesis is that guideline algorithm intervention implemented by primary care physicians will significantly reduce the risk of 4-point MACE (comprised of cardiovascular death, nonfatal myocardial infarction, nonfatal stroke or hospitalization of heart failure) rates. In Phase 1 study, the control of blood sugar, blood pressure and lipids will be evaluated at 18 months after intervention. In Phase 2 study, the CVD and renal outcomes will be evaluated at 3 years. The study will last for 4 years.

02

Conditions studied

  • Type 2 Diabetes
  • Cardiovascular Complication
  • Diabetic Kidney Disease

Keywords

  • Diabetes implementation study
  • Diabetes guideline algorithm
  • Cardiovascular disease
  • Chronic kidney disease
03

In context

Kidney Diseases

3,840 studies on the registry are indexed under Kidney Diseases; 500 are open to participants now.

This study's planned enrollment of 5,600 is above the median of 70 across 2,640 interventional studies indexed under Kidney Diseases.

Browse Kidney Diseases studies →

Lead sponsor

Shanghai Zhongshan Hospital is the lead sponsor of 636 studies on the registry; 283 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
65 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

  • ①Males or females aged 65 and above (≥65) receive treatment from the local community health service center;
  • ②Diagnosed type 2 diabetes (ADA criteria):
  • A. Typical symptoms of diabetes + random blood sugar ≥ 11.1mmol/L;
  • B. Fasting blood glucose (FPG) ≥ 7.0mmol/L (fasting blood glucose is defined as no caloric intake within 8 hours);
  • C. Oral glucose tolerance test 2h blood glucose (OGTT) ≥ 11.1mmol/L (2h after meal);
  • D. have been treated with antidiabetic drugs;
  • Each blood sugar test must be repeated to confirm the diagnosis;
  • ③Complicated with chronic kidney disease and/or very high/high risk of cardiovascular disease, meet any one of the following:
  • A. ASCVD, including coronary heart disease, cerebral infarction, peripheral vascular disease;
  • B. Or target organ damage (albuminuria, renal impairment with eGFR ≥ 30 ml/min/1.73m2, left ventricular hypertrophy or retinopathy);
  • C. ≥ 3 major risk factors (age ≥ 65 years old, hypertension, dyslipidemia, smoking, obesity );
  • D. Diabetes duration ≥ 10 years, with any one traditional cardiovascular risk factor such as advanced age, obesity, smoking, sedentary, family history of cardiovascular disease, hypertension, abnormal lipid metabolism.

Exclusion criteria

Exclusion Criteria:

  • ①Pregnant women or women planning to become pregnant;
  • ②eGFR\<30 mL/min/1.73m2 (CKD-EPI formula);
  • ③Patient cannot be followed up for 36 months (due to health condition or migration);
  • ④Unwilling or unable to sign the informed consent;
  • ⑤Type 1 diabetes;
05

Study design

Phase
Not applicable
Primary purpose
Treatment
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Single (Outcomes assessor)
Enrollment
5,600 participants (estimated)

Study arms

  • Experimental
    Intensive guideline algorithm implementation

    SGLT2i or GLP-1RA recommended in priority in subjects at very high/high CV risk. The targets of intervention will be achieved at HbA1C \<7%, blood pressure \<130/80mmHg, LDL-c\<1.8mmol/L at very high CV risk or \<2.6mmol/L at high CV risk patients, antiplatelet as secondary prevention of ASCVD.

    Other: Intensive guideline algorithm implementation

  • Active comparator
    Conventional guideline algorithm implementation

    Treatment based on the current approaches implemented by local physicians(primary care physicians). Guideline based education and consults will be conducted to primary care physicians.

    Other: Conventional guideline algorithm implementation

Interventions

  • OtherIntensive guideline algorithm implementation

    Diabetes guideline pharmacological algorithm will be implemented by primary care physicians in community. In brief, SGLT2i or GLP-1RA will be recommended to control blood glucose in priority when subjects at very high/high CV risk and meet the target HbA1C\<7%, control blood pressure \<130/80mmHg, LDL-c\<1.8mmol/L at very high CV risk patients or \<2.6mmol/L at high CV risk patients, and antiplatelet as secondary prevention of ASCVD.

  • OtherConventional guideline algorithm implementation

    The guideline intervention is based the guidance which the local physicians followed through self learning and education. The management of diabetes paitients will be decided by local physicians.

06

What researchers measure

Primary outcomes

  1. Primary Outcome of Phase 1: Comprehensive management effect of various cardiovascular risk factors in T2D,meeting control targets for a combination of A1c, BP, LDL-C.

    The proportion of participants with HbA1C\<7.0%, blood pressure\< 130/80 mm Hg,LDL-c\<1.8mmol/L at very high CV risk or \<2.6mmol/L at high CV risk.

    Time frame: 18 months since randomization

  2. Primary Outcome of Phase 2: Composite of 3P MACE and hospitalization for heart failure.

    Time to occurrence of cardiovascular and cerebrovascular death, non-fatal myocardial infarction, non-fatal Stroke, hospitalization for heart failure.

    Time frame: 3 years since randomization

Secondary outcomes

  1. Secondary Outcome of Phase 1: Glycemic control rate

    The proportion of participants with tight glucose control, targeting HbA1c \<7.0%

    Time frame: 18 months since randomization

  2. Secondary Outcome of Phase 1: Mean HbA1C changes

    Mean HbA1C changes of participants

    Time frame: 18 months since randomization

  3. Secondary Outcome of Phase 1: Mean systolic and diastolic pressure changes

    Mean systolic and diastolic pressure changes of participants

    Time frame: 18 months since randomization

  4. Secondary Outcome of Phase 1: Mean LDL-c changes

    Mean LDL-c changes of participants

    Time frame: 18 months since randomization

  5. Secondary Outcome of Phase 1: Adherence to guideline algorithm medication recommendation rate

    Use electronic medical recorded prescription and questionnaires to assess the proportion of participants who adhere to guideline recommended medication

    Time frame: 18 months since randomization

  6. Secondary Outcome of Phase 2: Incident or worsening nephropathy

    Time to composite of incident macroalbuminuria (UACR \>300 mg/g), a sustained decline in eGFR (decrease in the eGFR of 30% or more to a value of less than 60 when baseline ≥60ml per minute per 1.73 m2, decrease in the eGFR of 50% or more when baseline \<60ml per minute per 1.73 m2)from baseline, or chronic renal replacement therapy, or renal death.

    Time frame: 3 years since randomization

  7. Secondary Outcome of Phase 2: Cardiorenal composite endpoint

    Time to eGFR (CKD-EPI formula) decrease, renal replacement therapy, renal or cardiovascular death

    Time frame: 3 years since randomization

  8. Secondary Outcome of Phase 2: 3P MACE

    Time to events occurence: cardiovascular death, non-fatal myocardial infarction, non-fatal stroke

    Time frame: 3 years since randomization

  9. Secondary Outcome of Phase 2: New onset of macroalbuminuria.

    Time to UACR\>300mg/g

    Time frame: 3 years since randomization

  10. Secondary Outcome of Phase 2: Changes of myocardial ischemia in electrocardiogram (ECG)

    Participants number of ECG ischemia demonstration occurence: ST-T segment depression more than 0.1mv in two adjacent leads of ECG compared with baseline, poor R wave progression.

    Time frame: 3 years since randomization

  11. Secondary Outcome of Phase 2: New onset of albuminuria

    Time to UACR increase from \<30mg/g to ≥30mg/g

    Time frame: 3 years since randomization

  12. Secondary Outcome of Phase 2: Albuminuria progression

    Time to albuminuria progression: UACR increased by ≥30% and grade progression (ie, from normal to micro or macro, or from micro to macro)

    Time frame: 3 years since randomization

  13. Secondary Outcome of Phase 2: Albuminuria regression

    Time to albuminuria regression: UACR grade regression(ie, from macro to micro or normal, or from micro to normal), and the UACR value decreases by more than or equal to 30%

    Time frame: 3 years since randomization

  14. Secondary Outcome of Phase 2: Changes in the ratio of patients with normal or abnormal urine protein at the end of the study

    Rate change of normal or abnormal UACR. Normal means UACR\<30mg/g. Abnormal means UACR≥30mg/g

    Time frame: 3 years since randomization

  15. Secondary Outcome of Phase 2: Slope of eGFR decline

    Decrease of the eGFR over time

    Time frame: 3 years since randomization

  16. Secondary Outcome of Phase 2: Retinopathy changes

    Occurrence or regression of retinopathy(ETDRS-DRSS)

    Time frame: 3 years since randomization

  17. Secondary Outcome of Phase 2: Body weight change

    Absolute weight change and the percentage change of body weight

    Time frame: 3 years since randomization

  18. Secondary Outcome of Phase 2: Changes of fatty liver prevalence

    Rate change of fatty liver.

    Time frame: 3 years since randomization

  19. Secondary Outcome of Phase 2: Changes in beta-cell function

    Absolute change assessed by HOMA2-%β method

    Time frame: 3 years since randomization

  20. Secondary Outcome of Phase 2: Changes in cognitive function

    Improvement or progression of cognitive function: The Mini-CogTM scale

    Time frame: 3 years since randomization

  21. Secondary Outcome of Phase 2: The FRAIL scale

    Changes of the simple frailty questionnaire score

    Time frame: 3 years since randomization

  22. Secondary Outcome of Phase 2: All-cause death

    Time to the death due to any cause

    Time frame: 3 years since randomization

Other outcomes

  1. Health Economics Indicators

    Cost-effectiveness analysis: quantification of Incremental Cost Ratio Life Cycle (ICER) and Quality Adjusted Years (QALYs)

    Time frame: 3 years since randomization

  2. Changes in cardiovascular risk indicators

    Framingham score

    Time frame: 3 years since randomization

  3. Serology and urine testing

    Biomarkers associated with diagnosis or prognosis: using "omics" screening.

    Time frame: 3 years since randomization

  4. Genomics testing

    Gene polymorphism testing for drug response or prognosis: using genome-wide association study(GWAS) screening.

    Time frame: 3 years since randomization

  5. The time rate of glycemic target range

    Continous glucose monitor detection

    Time frame: 3 years since randomization

07

Study locations

13 of 13 sites recruiting
  • Xiangcheng Second People's Hospital
    Suzhou, Jaingsu 215501, China
    Recruiting
  • Caohu Community Healthcare Center
    Suzhou, Jiangsu 215006, China
    Recruiting
  • Huangqiao Community Healthcare Center
    Suzhou, Jiangsu 215006, China
    Recruiting
  • Xiangcheng People's Hospital.
    Suzhou, Jiangsu 215131, China
    Recruiting
  • Yuanhe Community Healthcare Center
    Suzhou, Jiangsu 215131, China
    Recruiting
  • Xiangcheng Third People's Hospital
    Suzhou, Jiangsu 215134, China
    Recruiting
  • Taiping Community Healthcare Center
    Suzhou, Jiangsu 215137, China
    Recruiting
  • Yangchenghu People's Hospital
    Suzhou, Jiangsu 215138, China
    Recruiting
  • Health Center of Xiangcheng Tourism Resort
    Suzhou, Jiangsu 215141, China
    Recruiting
  • Caohu People's Hospital
    Suzhou, Jiangsu 215144, China
    Recruiting
  • Dongqiao Community Healthcare Center
    Suzhou, Jiangsu 215152, China
    Recruiting
  • Xiangcheng Traditional Chinese Medicine Hospital
    Suzhou, Jiangsu 215155, China
    Recruiting
  • Chengyang Community Healthcare Center
    Suzhou, Jiangsu, China
    Recruiting
08

References and documents

Publications

  • Gu TW, Zhu DL. [Interpretation of treatment part of national guideline for the prevention and control of diabetes in primary care (2018)]. Zhonghua Nei Ke Za Zhi. 2019 Jul 1;58(7):538-540. doi: 10.3760/cma.j.issn.0578-1426.2019.07.011. Chinese. PubMed 31269573 ↗
  • Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group. Lancet. 1998 Sep 12;352(9131):837-53. PubMed 9742976 ↗
  • Gross JL, de Azevedo MJ, Silveiro SP, Canani LH, Caramori ML, Zelmanovitz T. Diabetic nephropathy: diagnosis, prevention, and treatment. Diabetes Care. 2005 Jan;28(1):164-76. doi: 10.2337/diacare.28.1.164. PubMed 15616252 ↗
  • Zinman B, Wanner C, Lachin JM, Fitchett D, Bluhmki E, Hantel S, Mattheus M, Devins T, Johansen OE, Woerle HJ, Broedl UC, Inzucchi SE; EMPA-REG OUTCOME Investigators. Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes. N Engl J Med. 2015 Nov 26;373(22):2117-28. doi: 10.1056/NEJMoa1504720. Epub 2015 Sep 17. PubMed 26378978 ↗
  • Wiviott SD, Raz I, Bonaca MP, Mosenzon O, Kato ET, Cahn A, Silverman MG, Zelniker TA, Kuder JF, Murphy SA, Bhatt DL, Leiter LA, McGuire DK, Wilding JPH, Ruff CT, Gause-Nilsson IAM, Fredriksson M, Johansson PA, Langkilde AM, Sabatine MS; DECLARE-TIMI 58 Investigators. Dapagliflozin and Cardiovascular Outcomes in Type 2 Diabetes. N Engl J Med. 2019 Jan 24;380(4):347-357. doi: 10.1056/NEJMoa1812389. Epub 2018 Nov 10. PubMed 30415602 ↗
  • Neal B, Perkovic V, Mahaffey KW, de Zeeuw D, Fulcher G, Erondu N, Shaw W, Law G, Desai M, Matthews DR; CANVAS Program Collaborative Group. Canagliflozin and Cardiovascular and Renal Events in Type 2 Diabetes. N Engl J Med. 2017 Aug 17;377(7):644-657. doi: 10.1056/NEJMoa1611925. Epub 2017 Jun 12. PubMed 28605608 ↗
  • Bhatt DL, Szarek M, Steg PG, Cannon CP, Leiter LA, McGuire DK, Lewis JB, Riddle MC, Voors AA, Metra M, Lund LH, Komajda M, Testani JM, Wilcox CS, Ponikowski P, Lopes RD, Verma S, Lapuerta P, Pitt B; SOLOIST-WHF Trial Investigators. Sotagliflozin in Patients with Diabetes and Recent Worsening Heart Failure. N Engl J Med. 2021 Jan 14;384(2):117-128. doi: 10.1056/NEJMoa2030183. Epub 2020 Nov 16. PubMed 33200892 ↗
  • Heerspink HJL, Stefansson BV, Correa-Rotter R, Chertow GM, Greene T, Hou FF, Mann JFE, McMurray JJV, Lindberg M, Rossing P, Sjostrom CD, Toto RD, Langkilde AM, Wheeler DC; DAPA-CKD Trial Committees and Investigators. Dapagliflozin in Patients with Chronic Kidney Disease. N Engl J Med. 2020 Oct 8;383(15):1436-1446. doi: 10.1056/NEJMoa2024816. Epub 2020 Sep 24. PubMed 32970396 ↗
  • Perkovic V, Jardine MJ, Neal B, Bompoint S, Heerspink HJL, Charytan DM, Edwards R, Agarwal R, Bakris G, Bull S, Cannon CP, Capuano G, Chu PL, de Zeeuw D, Greene T, Levin A, Pollock C, Wheeler DC, Yavin Y, Zhang H, Zinman B, Meininger G, Brenner BM, Mahaffey KW; CREDENCE Trial Investigators. Canagliflozin and Renal Outcomes in Type 2 Diabetes and Nephropathy. N Engl J Med. 2019 Jun 13;380(24):2295-2306. doi: 10.1056/NEJMoa1811744. Epub 2019 Apr 14. PubMed 30990260 ↗
  • Marso SP, Daniels GH, Brown-Frandsen K, Kristensen P, Mann JF, Nauck MA, Nissen SE, Pocock S, Poulter NR, Ravn LS, Steinberg WM, Stockner M, Zinman B, Bergenstal RM, Buse JB; LEADER Steering Committee; LEADER Trial Investigators. Liraglutide and Cardiovascular Outcomes in Type 2 Diabetes. N Engl J Med. 2016 Jul 28;375(4):311-22. doi: 10.1056/NEJMoa1603827. Epub 2016 Jun 13. PubMed 27295427 ↗
  • Gerstein HC, Colhoun HM, Dagenais GR, Diaz R, Lakshmanan M, Pais P, Probstfield J, Riesmeyer JS, Riddle MC, Ryden L, Xavier D, Atisso CM, Dyal L, Hall S, Rao-Melacini P, Wong G, Avezum A, Basile J, Chung N, Conget I, Cushman WC, Franek E, Hancu N, Hanefeld M, Holt S, Jansky P, Keltai M, Lanas F, Leiter LA, Lopez-Jaramillo P, Cardona Munoz EG, Pirags V, Pogosova N, Raubenheimer PJ, Shaw JE, Sheu WH, Temelkova-Kurktschiev T; REWIND Investigators. Dulaglutide and cardiovascular outcomes in type 2 diabetes (REWIND): a double-blind, randomised placebo-controlled trial. Lancet. 2019 Jul 13;394(10193):121-130. doi: 10.1016/S0140-6736(19)31149-3. Epub 2019 Jun 9. PubMed 31189511 ↗
  • Marso SP, Bain SC, Consoli A, Eliaschewitz FG, Jodar E, Leiter LA, Lingvay I, Rosenstock J, Seufert J, Warren ML, Woo V, Hansen O, Holst AG, Pettersson J, Vilsboll T; SUSTAIN-6 Investigators. Semaglutide and Cardiovascular Outcomes in Patients with Type 2 Diabetes. N Engl J Med. 2016 Nov 10;375(19):1834-1844. doi: 10.1056/NEJMoa1607141. Epub 2016 Sep 15. PubMed 27633186 ↗
  • Cosentino F, Grant PJ, Aboyans V, Bailey CJ, Ceriello A, Delgado V, Federici M, Filippatos G, Grobbee DE, Hansen TB, Huikuri HV, Johansson I, Juni P, Lettino M, Marx N, Mellbin LG, Ostgren CJ, Rocca B, Roffi M, Sattar N, Seferovic PM, Sousa-Uva M, Valensi P, Wheeler DC; ESC Scientific Document Group. 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD. Eur Heart J. 2020 Jan 7;41(2):255-323. doi: 10.1093/eurheartj/ehz486. No abstract available. PubMed 31497854 ↗
  • American Diabetes Association. 9. Pharmacologic Approaches to Glycemic Treatment: Standards of Medical Care in Diabetes-2021. Diabetes Care. 2021 Jan;44(Suppl 1):S111-S124. doi: 10.2337/dc21-S009. PubMed 33298420 ↗
  • Mosenzon O, Wiviott SD, Heerspink HJL, Dwyer JP, Cahn A, Goodrich EL, Rozenberg A, Schechter M, Yanuv I, Murphy SA, Zelniker TA, Gause-Nilsson IAM, Langkilde AM, Fredriksson M, Johansson PA, Bhatt DL, Leiter LA, McGuire DK, Wilding JPH, Sabatine MS, Raz I. The Effect of Dapagliflozin on Albuminuria in DECLARE-TIMI 58. Diabetes Care. 2021 Aug;44(8):1805-1815. doi: 10.2337/dc21-0076. Epub 2021 Jul 7. PubMed 34233928 ↗
  • Wanner C, Inzucchi SE, Lachin JM, Fitchett D, von Eynatten M, Mattheus M, Johansen OE, Woerle HJ, Broedl UC, Zinman B; EMPA-REG OUTCOME Investigators. Empagliflozin and Progression of Kidney Disease in Type 2 Diabetes. N Engl J Med. 2016 Jul 28;375(4):323-34. doi: 10.1056/NEJMoa1515920. Epub 2016 Jun 14. PubMed 27299675 ↗

Individual participant data

Plan to share: No — The data will be available from the principle investigator on reasonable request.

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on May 14, 2025, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT05349955
Lead sponsor
Shanghai Zhongshan Hospital
Responsible party
Xiaoying Li (Chief of Endocrinology Department, Shanghai Zhongshan Hospital) — Principal investigator
First posted
Apr 27, 2022
Start date
Nov 21, 2022
Primary completion
Nov 30, 2026 (estimated)
Completion
Nov 30, 2026 (estimated)
Last update
May 14, 2025

Study contacts

Xiaoying Li, MD
Contact
li.xiaoying@zs-hospital.sh.cn
13651913857
Xiaomu Li, MD
Contact
li.xiaomu@zs-hospital.sh.cn
13661676591
Xiaoying Li, MD
principal investigator · Fudan University

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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