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Background: The purpose of this study was to develop a coronary artery disease (CAD) prediction model that optimally estimates the pre-test probability of CAD for patients suspected of CAD., Methods and Results: This retrospective, multi-centre study included 7360 consecutive patients (4678 men, 57.87±11.42 years old; 2682 women, 61.60±9.58 years old) who underwent coronary angiography for evaluation of CAD. A prediction model was fitted for diagnosis of CAD with the help of eight significant risk factors including sex, age, smoking status, diabetes, hypertension, dyslipidaemia, serum creatinine and angina. All potential predictors were significantly associated with the presence of CAD. The prevalence of CAD was significantly higher in men than in women. The clinical model gives a relatively accurate prediction of CAD with an area under the curve (AUC) of 0.74 (95% CI, 0.88-0.96; P<0.001). Addition of angina to the prediction model improves the predictive precision of the model. The optimal cut-off for predicting CAD in this model was 0.79 with a sensitivity of 0.658 and a specificity of 0.709., Conclusion: A prediction model including age, sex, and cardiovascular risk factors allow for an accurate estimation of the pre-test probability of coronary artery disease in Chinese populations. This algorithm may be useful in making decisions relating to the diagnosis of CAD., (Copyright © 2017. Published by Elsevier B.V.)

Recent studies have found that cardiac stem cells (CSCs) are present in the adult heart. CSCs play an important role in maintaining the balance of the number of myocardial cells. The purpose of this study was to examine characteristics of human CSCs and their correlation with clinical characteristics of patients. We collected heart auricles of 105 patients (age range, 1-78 years; mean, 55.6 ± 17.0 years) undergoing cardiac surgery to obtain CSCs. We assayed the percentage of c-kit positive (c-kit(+)) CSCs with flow cytometry. Plasma N(ɛ)-(carboxymethyl)lysine (CML) concentrations were measured by enzyme-linked immunosorbent assay. The percentage of c-kit(+) CSCs was 4.96 ± 3.12% (0.98-17.17%), and this was significantly negatively correlated with age, the presence of diabetes mellitus (DM) and coronary heart disease (CHD) (r values were -0.797 [P < 0.01], -0.500 [P < 0.01] and -0.250 [P = 0.011], respectively). The percentage of c-kit(+) CSCs was significantly negatively correlated with CML concentrations (r = -0.859, P < 0.01). The percentage of c-kit(+) CSCs decreases with ageing and is further decreased in patients with DM and/or CHD. Furthermore, plasma CML concentrations may have potential as an indicator of the number of c-kit(+) CSCs., (© The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.)

Heart disease is one of the most important causes of death in developed countries. N(ε)-carboxymethyllysine (CML) is a major advanced glycation end product formed by combined reactions of non-enzymatic glycation and oxidation (glycoxidation), and it represents a general marker of oxidative stress. CML has been suggested to be involved in the pathogenesis of heart disease. Plasma CML is elevated in aging, atherosclerosis and/or diabetes. In this study, we measured cardiac CML levels to elucidate its role in the pathogenesis of heart disease. Cardiac tissues were collected from 105 patients (55.6 ± 17.0 years old: age range, 1-78 years) undergoing cardiac surgery. The diseases comprised coronary heart disease (CHD), CHD associated with diabetes mellitus (DM), valvular heart disease and congenital heart disease. The concentration of CML in cardiac tissues of each group was 4.31 ± 0.66, 5.29 ± 0.59, 2.74 ± 1.05 and 1.75 ± 1.16 μg/g, respectively. ELISA was used for measuring cardiac and plasma CML concentrations. Multiple linear regression analysis showed a significant positive correlation of CML concentrations with age (r = 0.803, p < 0.001), DM (r = 0.567, p < 0.001) and CHD (r = 0.523 p < 0.001). R(2) was 0.872 (p < 0.001); the three independent variables could explain 87.2% variation of CML concentrations. Cardiac CML concentrations exhibited a significant positive correlation with plasma CML (r = 0.983, p < 0.001). Our data indicate that cardiac CML concentrations increase with age, DM and/or CHD, and exhibit a positive correlation with plasma CML concentrations.