Lead Investigator: Wencai Jiang, Chengdu Second People’s Hospital
Title of Proposal Research: Predictive value of high‐sensitivity cardiac troponin‐T for Major Adverse Cardiovascular Events in patients with Chronic coronary heart disease
Vivli Data Request: 8603
Funding Source: None
Potential Conflicts of Interest: None
Summary of the Proposed Research:
Chronic coronary heart disease is a disease caused by the deposition of lipid components in the blood ( such as low-density lipoprotein, triglycerides, cholesterol, etc ) under the wall of the heart vessels, resulting in the narrowing of the lumen of the heart vessels, and thus the insufficient blood supply to myocardial cells (the muscle cells of the heart, which make up 75 percent of the heart’s weight ). Chronic coronary heart disease is the “top killer” threatening human health. At present, about 7.3 million people die from chronic coronary heart disease every year in the world, ranking the first among all diseases, accounting for 12.8% of all disease deaths. About 11.39 million people in China suffer from chronic coronary heart disease. In the face of such high mortality and morbidity, there is an urgent need for more refined management of patients with chronic coronary heart disease.
A special protein, hypersensitive troponin T ( HsTnT ), is found only in cardiomyocytes (cardiac muscle cells). HsTnT will be released into the blood when there is damage to the heart muscle or myocardial cells become ischemia-necrotic (cell death caused by lack of blood flow to the heart) due to a narrowing of the heart vessels. We can determine whether there is ischemic necrosis of myocardial cells due to chronic coronary heart disease by detecting the content of HsTnT in the blood. We will compare whether there are differences in mortality, incidence of acute myocardial infarction ( one of the complications of chronic coronary heart disease, myocardial cells die due to blood vessel occlusion in the heart, leading to acute complications such as shock or heart failure ) and hospitalization among patients with chronic coronary heart disease with different HsTnT levels.
The study aims to clarify the relationship between HsTnT and the prognosis of chronic coronary heart disease, help clinicians making decisions, guiding medication and controlling risk factors in patients with chronic coronary heart disease, and enable patients with chronic coronary heart disease to have more accurate management and treatment. To promote better risk stratification in patients with chronic coronary heart disease, improve the ability to identify the risk of cardiovascular death in patients with chronic coronary heart disease, reduce the family and social burden of cardiovascular disease, so as to benefit thousands of patients with chronic coronary heart disease.
Statistical Analysis Plan:
The research data we applied for included a large number of patients with chronic coronary heart disease, long-term follow-up data and troponin measurement data. Therefore, it is very valuable and worthy of use and secondary analysis. It provides important reference for the stratification and management of patients with chronic coronary heart disease and reduces the social burden of disease. Our proposed research doesn’t involve studies from other sources. Categorical variables will be represented by percentages (%), the comparison of which will be performed by the chi-square test. Continuous variables were compared with Kruskal‐Wallis nonparametric tests. Cox proportional-hazards model will be used to analyze and compare the incidence of cardiovascular events, mortality and survival rate of patients with chronic coronary heart disease with different troponin levels. The underlying proportional hazards assumptions of the Cox proportional hazard models were verified by visual inspection of Kaplan‐Meier graphs and Schoenfeld residual plots. The multivariate logistic regression model will be used to estimate the adjusted odds ratio (OR). All statistical analyses were performed using SPSS 26.0 (IBM, U.S.). If P < 0.05, the difference is statistically significant. And multivariate logistic regression model will be used to adjust the influence of risk factors such as age, gender, race, economic status, smoking, drinking, hypertension, diabetes, hyperlipidemia and hyperuricemia on the study results. We will perform subgroup analysis based on age, sex, race, and socioeconomic status. We will use multiple imputation to deal with missing data. We will use excel software for preliminary data sorting and SPSS software for drawing.
Requested Studies:
LPL100601, A Clinical Outcomes Study of Darapladib Versus Placebo in Subjects With Chronic Coronary Heart Disease to Compare the Incidence of Major Adverse Cardiovascular Events (MACE)
Data Contributor: GSK
Study ID: NCT00799903
Sponsor ID: LPL100601
Public Disclosure:
Jiang, W., Huang, G., Du, J., Yang, H., Zhou, S., Dai, D., Tang, K., Fang, Y., Wang, X. and Deng, X., 2024. White blood cell counts can predict 4-year cardiovascular disease risk in patients with stable coronary heart disease: a prospective cohort study. Frontiers in Cardiovascular Medicine, 11, p.1358378. Doi: 10.3389/fcvm.2024.1358378