Circulation. Heart failure · 2025
Plasma SVEP1 Levels Predict Cardiovascular Events in Hypertrophic Cardiomyopathy Beyond Conventional Clinical Risk Models Including NT-proBNP.
Сравнительное исследованиеСтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Osawa Itsuki, Akita Keitaro, Hasegawa Kohei, Fifer Michael A, Tower-Rader Albree, Reilly Muredach P, Maurer Mathew S, Stitziel Nathan O, Javaheri Ali, Shimada Yuichi J
Аннотация
BACKGROUND: Hypertrophic cardiomyopathy is the most common genetic cardiomyopathy and causes major adverse cardiovascular events (MACE). SVEP1 (Sushi, von Willebrand factor type A, epidermal growth factor, and pentraxin domain containing 1) is a large extracellular matrix protein that is detectable in the plasma. However, it is unknown whether adding plasma SVEP1 levels to clinical predictors including NT-proBNP (N-terminal pro-B-type natriuretic peptide) improves the prognostication in patients with hypertrophic cardiomyopathy.
METHODS: We performed a multicenter prospective cohort study of 610 patients with hypertrophic cardiomyopathy. The outcome was MACE defined as heart failure hospitalization or cardiac death. In 4 groups stratified by the median levels of SVEP1 and NT-proBNP, we compared the risk of MACE using the Cox proportional hazards model adjusting for 15 clinical predictors. We also developed a Lasso-regularized Cox proportional hazards model to predict time to first MACE by adding SVEP1 to the 15 clinical predictors with or without NT-proBNP and compared the predictive performance based on C statistics using 10-fold cross-validation.
RESULTS: Even in the low NT-proBNP groups, the high SVEP1 group had higher risks of MACE compared with the low SVEP1 group (adjusted hazard ratio, 4.52 [95% CI, 1.05-19.4]; P=0.042). In predicting time to first MACE, the addition of SVEP1 improved the C statistics of the clinical plus NT-proBNP model (0.87 [0.83-0.91] versus 0.82 [0.78-0.86]; P=0.01). The clinical plus SVEP1 model also outperformed the clinical plus NT-proBNP model (0.86 [0.82-0.91] versus 0.82 [0.78-0.86]; P=0.04).
CONCLUSIONS: SVEP1 improved the predictive performance of conventional models, including known clinical parameters with or without NT-proBNP, to predict future MACE in patients with hypertrophic cardiomyopathy.
METHODS: We performed a multicenter prospective cohort study of 610 patients with hypertrophic cardiomyopathy. The outcome was MACE defined as heart failure hospitalization or cardiac death. In 4 groups stratified by the median levels of SVEP1 and NT-proBNP, we compared the risk of MACE using the Cox proportional hazards model adjusting for 15 clinical predictors. We also developed a Lasso-regularized Cox proportional hazards model to predict time to first MACE by adding SVEP1 to the 15 clinical predictors with or without NT-proBNP and compared the predictive performance based on C statistics using 10-fold cross-validation.
RESULTS: Even in the low NT-proBNP groups, the high SVEP1 group had higher risks of MACE compared with the low SVEP1 group (adjusted hazard ratio, 4.52 [95% CI, 1.05-19.4]; P=0.042). In predicting time to first MACE, the addition of SVEP1 improved the C statistics of the clinical plus NT-proBNP model (0.87 [0.83-0.91] versus 0.82 [0.78-0.86]; P=0.01). The clinical plus SVEP1 model also outperformed the clinical plus NT-proBNP model (0.86 [0.82-0.91] versus 0.82 [0.78-0.86]; P=0.04).
CONCLUSIONS: SVEP1 improved the predictive performance of conventional models, including known clinical parameters with or without NT-proBNP, to predict future MACE in patients with hypertrophic cardiomyopathy.