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Correlation Between Targeted HbA1c Values and Prevention of Recurrent Cardiovascular Events in Type 2 Diabetes After PCI (CATHEDRAL)

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ClinicalTrials.gov Identifier: NCT05134129
Recruitment Status : Recruiting
First Posted : November 24, 2021
Last Update Posted : November 24, 2021
Sponsor:
Information provided by (Responsible Party):
Ya-Wei Xu, Shanghai 10th People's Hospital

Study Description
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Brief Summary:

Diabetes is a leading social and economic burden in the world. It is the main reason of macrovascular disease incidence and mortality. Prospective studies have demonstrated that high glycosylated hemoglobin (HbA1C) levels are associated with an increased risk of cardiovascular events in a population of diabetic patients without a history of coronary artery disease. Further, the predictive value of high preprocedural glycemia levels has been reported in diabetic patients undergoing percutaneous coronary intervention (PCI). The aim of the present study was to assess the predictive value of preprocedural HbA1C levels for cardiovascular complications in a large population of diabetic patients undergoing PCI with stent implantation. Glycosylated hemoglobin (HbA1c) reflects the average blood sugar level in the past 2-3 months. As glycosylated hemoglobin has been clinically tested and standardized internationally, increasing evidence is recommended for routine monitoring in diabetes care. The American Diabetes Association (ADA) suggested that in the treatment of diabetes, blood sugar control should control HbA1c level below 6.5%. Although，there is evidence that controlling blood glucose can reduce the incidence of microvascular complications, in the past three trials, intensive glycemic control did not significantly reduce adverse CV events in patients with onger duration of diabetes.Therefore, most primary and secondary prevention guidelines recommend HbA1c below 6.5% or 7% to prevent adverse cardiovascular outcomes in patients with diabetes mellitus. The optimal target level of glycosylated hemoglobin is still hotly debated. In addition, there is still lack of evidence for the level of HbA1c in patients with major vascular disease history in secondary prevention of recurrence cardiovascular events.

Therefore, to explore and determine the optimal level of blood glucose control is the focus of controversy in preventing recurrence cardiovascular events in diabetic patients. Investigator will combine epidemiology and metabolomics to study the effect of glycosylated hemoglobin on secondary cardiovascular events, and further determine whether to strengthen hypoglycemic treatment after PCI.


Condition or disease
Diabetes Mellitus Percutaneous Coronary Intervention

Detailed Description:
This is a longitudinal cohort study including retrospective study, prospective study and nested case-control study.The first cross-sectional survey was conducted in 2021.
Study Design
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Study Type : Observational
Estimated Enrollment : 1500 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Correlation Between Targeted Hemoglobin A1C Levels and Prevention of Recurrent Cardiovascular Events in Type 2 Diabetes After Coronary Intervention
Actual Study Start Date : April 25, 2021
Estimated Primary Completion Date : September 1, 2024
Estimated Study Completion Date : September 1, 2024

Resource links provided by the National Library of Medicine


Groups and Cohorts
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Outcome Measures
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Primary Outcome Measures :
  1. Coronary revascularization [ Time Frame: 3 years ]
    Coronary revascularization includes percutaneous coronary intervention, or/and percutaneous coronary artery dilatation, or/and percutaneous coronary artery bypass grafting.

  2. All cause mortality [ Time Frame: 3 years ]
    which refers to the total death caused by various causes in a certain period.

  3. Cardiac mortality [ Time Frame: 3 years ]
    Cardiac death refers to the death caused by serious cardiac dysfunction or failure caused by heart disease or injury in a certain period.

  4. Differential polar compound [ Time Frame: 3 years ]
    Metabonomic analysis uses non targeted detection methods to detect polar compounds in blood. The characteristic peaks of detectable substances were detected by chromatographic Series platform, and then these characteristic peaks were compared with the standard library containing more than 8000 metabolites, annotated the compounds, and screened out the different metabolites between groups.

  5. Differential lipid compounds [ Time Frame: 3 years ]
    Metabonomic analysis uses non targeted detection methods to detect lipid compounds in blood. The characteristic peaks of detectable substances were detected by chromatographic Series platform, and then these characteristic peaks were compared with the standard library containing more than 8000 metabolites, annotated the compounds, and screened out the different metabolites between groups.


Biospecimen Retention:   Samples Without DNA
Blood samples were taken for metabolomics study.

Eligibility Criteria
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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Sampling Method:   Probability Sample
Study Population
Demographic data, cardiovascular examinations and laboratory parameters were collected from 1500 hospitalized diabetic patients with PCI. Patients younger than 18 years old, pregnant, preoperative HbA1c deletion and chronic maintenance hemodialysis were excluded. According to ADA and AHA guidelines and predetermined glycosylated hemoglobin values, based on clinical relevance, especially glycosylated hemoglobin < 6.5%, 6.5% ≤ glycosylated hemoglobin ≤ 7.0%, glycosylated hemoglobin > 7.0%, and statistical end events including patients with more than or equal to two PCI enents, patients with all-cause motality and cardiac motality.Through prospective cohort study and nested case-control study,analysis related risk factors and metabolomics molecular differences between revascularization patients and non-revascularization patients.The instrument platforms of gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) are used to metabonomic analysis.
Criteria

Inclusion Criteria:

- 1. Age ≥ 18, male or female;

2. all patients with diabetes combined with PCI operation;

Exclusion Criteria:

  • 1. Less than 18 years old

    2. Pregnancy

    3. Patients with preoperative glycosylated hemoglobin index deficiency

    4. Chronic maintenance hemodialysis patients

Contacts and Locations
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Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT05134129


Contacts
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Contact: Yan Cang, MD 18917682207 cang_gu@aliyun.com
Contact: Zhicai Wang, MD 19154087651 19154087651@163.com

Locations
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China
Department of Cardiology,Shanghai Tenth People's Hospital Recruiting
Shanghai, China, 200072
Contact: Yan Cang, PhD    18917682207    cang_gu@aliyun.com   
Contact: Yawei Xu, PhD       xuyawei@tongji.edu.cn   
Sponsors and Collaborators
Shanghai 10th People's Hospital
Investigators
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Principal Investigator: Yan Cang, MD Department of Cardiology, Shanghai Tenth People's Hospital
Principal Investigator: Zheng Liu, pHD Department of Cardiology, Shanghai Tenth People's Hospital
Principal Investigator: Zhicai Wang, MD Department of Cardiology, Shanghai Tenth People's Hospital
More Information
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Responsible Party: Ya-Wei Xu, Chief Physician, Shanghai 10th People's Hospital
ClinicalTrials.gov Identifier: NCT05134129    
Other Study ID Numbers: CATHEDRAL
First Posted: November 24, 2021    Key Record Dates
Last Update Posted: November 24, 2021
Last Verified: November 2021

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Ya-Wei Xu, Shanghai 10th People's Hospital:
Glycated Hemoglobin
Percutaneous Coronary Intervention
Metabolomics
Diabetes Mellitus
Cardiovascular Risk
Additional relevant MeSH terms:
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Diabetes Mellitus
Glucose Metabolism Disorders
Metabolic Diseases
Endocrine System Diseases