Cardiovascular disease risk prediction in scleroderma

Abstract

OBJECTIVE: Cardiovascular disease risk prediction in scleroderma is important. In this study of scleroderma patients, the aim was to investigate the relationship between cardiac myosin-binding protein-C, sensitive troponin T, and trimethylamine N-oxide and cardiovascular disease risk with the Systematic COronary Risk Evaluation 2 model of the European Society of Cardiology. METHODS: Systematic COronary Risk Evaluation 2 risk groups of 38 healthy controls and 52 women with scleroderma were evaluated. Cardiac myosin-binding protein-C, sensitive troponin T, and trimethylamine N-oxide levels were analyzed with commercial ELISA kits. RESULTS: In scleroderma patients, cardiac myosin-binding protein-C and trimethylamine N-oxide levels were higher than healthy controls but sensitive troponin T was not (p0.001, p0.001, and p=0.274, respectively). Out of 52 patients, 36 (69.2%) were at low risk, and the other 16 (30.8%) patients were at high-moderate risk with the Systematic COronary Risk Evaluation 2 model. At the optimal cutoff values, trimethylamine N-oxide could discriminate high-moderate risk with sensitivity 76%, specificity 86% and cardiac myosin-binding protein-C with sensitivity 75%, specificity 83%. Patients with high trimethylamine N-oxide levels (10.28 ng/mL) could predict high-moderate-Systematic COronary Risk Evaluation 2 risk 15 times higher than those with low trimethylamine N-oxide (10.28 ng/mL) levels (odds ratio [OR]: 15.00, 95%CI 3.585 62.765, p0.001). Similarly, high cardiac myosin-binding protein-C (8.29 ng/mL) levels could predict significantly higher Systematic COronary Risk Evaluation 2 risk than low cardiac myosin-binding protein-C (8.29 ng/mL) levels (OR: 11.00, 95%CI 2.786 43.430). CONCLUSION: Noninvasive cardiovascular disease risk prediction indicators in scleroderma, cardiac myosin-binding protein-C, and trimethylamine N-oxide could be recommended to distinguish between high-moderate risk and low risk with the Systematic COronary Risk Evaluation 2 model.