Aim Calcific aortic stenosis (AS) is a common valvular disease especially in elderly population. Inflammation plays significant role in the pathophysiological mechanism. Systemic immune‐inflammation index (SII) is a novel marker of immune system and inflammation that includes neutrophil, lymphocyte, and platelet cell counts. The aim of this study was to investigate the predictive value of SII in calcific severe AS. Materials and Methods Severe calcific AS patients were categorized into two groups: High flow‐high gradient (HFHG) AS (n = 289) and low flow‐low gradient AS (n = 79). Control group included 273 patients with similar clinical and demographic characteristics but without AS. SII was calculated as absolute platelet count × absolute neutrophil count/absolute lymphocyte count. Results SII levels were 525 ± 188, 835 ± 402, and 784 ± 348 in control, HFHG AS, and LFLG AS groups, respectively (P < .001). Correlation analyses revealed significant and positive correlation between SII and mean aortic transvalvular pressure gradient (r = .342, P < .001), and negative and significant correlation between SII and AVA (r = −.461, P < .001). Multivariate analysis performed in separate models demonstrated sex, CAD, LDL, and SII levels (Odds ratio [OR]: 1.004, 95 CI%:1.003–1.004) as independent predictors of severe AS in Model 1. According to Model 2, sex, CAD, LDL, and high SII (>661) (OR:5.78, 95 CI%:3.93–4.89) remained as independent predictors of severe AS. Conclusion SII levels can be useful to predict severe calcific AS patients and significantly correlate with AVA and mean aortic transvalvular pressure gradient.
Contrast-induced nephropathy (CIN) is a common cause of hospital-acquired acute renal failure and related with prolonged hospitalization, increased morbidity, mortality, and economic costs. 1 Given that inflammation plays a significant role in the pathophysiology of CIN and acute coronary syndrome (ACS), inflammation-related biomarkers have been investigated for the prediction of CIN. 2 Among these biomarkers, hematological parameters have been the focus of research due to fact that they are cheap, simple to calculate, and easily accessible. Zorlu and Koseoglu 3 compared several admission hematological inflammatory markers for the prediction of CIN in ACS patients who underwent percutaneous coronary intervention (PCI). Among several inflammatory parameters including mean platelet volume (MPV), lymphocyte count, platelet to lymphocyte ratio (PLR), neutrophil to lymphocyte ratio, and mean platelet volume to lymphocyte ratio (MPVLR), only the MPVLR remained as an independent predictor of CIN. Although this study has several limitations (eg, retrospective and observational design as well as the number of patients) as described by the authors, it has several "take home messages." In this context, we would like to comments on the study design and statistical analysis. The authors 3 performed multiple linear regression analysis to investigate predictors of CIN. In addition to various hematological and inflammatory markers, they also included clinical variables into regression model such as age, left ventricular ejection fraction (LVEF), and diabetes mellitus, which are associated with CIN development. 4,5 Multivariate analysis demonstrated that age and LVEF are also independent predictors of CIN in addition to hematological parameters including hemoglobin and lymphocyte counts and MPVLR. Moreover, there were significant differences between the 2 study groups in terms of these clinical variables. Making a firm conclusion about the superiority and predictive power of these inflammatory markers for CIN may not be possible in the light of these results. From a biomarker perspective, it would be preferable if the authors had performed a propensity score matching analysis
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