Clinical SYNTAX Score – a good predictor for renal artery stenosis in acute myocardial infarction patients: analysis from the REN-ACS trial
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Submission date: 2016-03-31
Final revision date: 2016-04-27
Acceptance date: 2016-04-29
Online publication date: 2016-06-06
Publication date: 2017-06-08
Arch Med Sci 2017;13(4):837–844
Introduction: In ST-elevation myocardial infarction (STEMI) patients, multisite artery disease represents a serious issue influencing evolution, outcomes and prognosis. We evaluated for the first time the power of the Myocardial Infarction SYNTAX Score (MI SS) and Clinical SYNTAX Score (MI CSS) as predictors for renal artery stenosis (RAS) in STEMI. We also stratified the study population according to the two scores, and identified the variables correlated with the higher score.
Material and methods: We used data from the REN-ACS study, which included 181 consecutive patients prospectively investigated for presence of RAS (through renal angiography), arterial stiffness (carotid-femoral pulse wave velocity, cf-PWV) and hydration status (bioimpedance). MI SS and CSS were computed.
Results: Multivariate regressions indicated that the independent variables correlated with MI SS were left ventricular ejection fraction < 40%, significant RAS (> 50%, defined as RAS+), history of heart failure, and multivascular coronary disease (CAD, p < 0.03 for each), while those correlated with MI CSS were RAS+, cf-PWV, history of CAD, multivascular CAD, cholesterol, and total body water (p < 0.02 for each). In order to evaluate the ability to predict RAS+ we generated receiver operating characteristics (ROC) and areas under curves (AUCs), and the Youden index for MI SS and CSS.
Conclusions: Both scores correlated with extensive atherosclerotic disease and presence of RAS+. A lower CSS proved to be a good predictor for exclusion of RAS+, with high specificity (85%) and negative predictive value (92%), and fair sensitivity (60%). We aim to further pursue this line of research and design a better predictor for RAS, with the inclusion of a novel biomarker in order to increase sensitivity.