The SIC score is a combination of SI and renal function for the determining the prognosis of in-hospital mortality patients. This is the first study to utilize the SIC score for determination of in-hospital mortality in patients presenting with all spectrums of acute coronary syndrome. This study found that SIC had an acceptable predictive value for in-hospital mortality both as numeric or categorical variable (AUC = 0.789, 95% CI: 0.748–0.831, p < 0.001; AUC = 0.729, 95% CI: 0.684–0.774, p < 0.001 respectively). Chiang et al also demonstrated that SIC had an acceptable predictive value for in-hospital mortality in STEMI patients (AUC = 0.792, 95% CI: 0.748–0.836, p < 0.001).15 Ran et al, found that the predictive value and calibration of SIC for in-hospital mortality was excellent in derivation [area under the curve (AUC) = 0.877, p < 0.001; Hosmer-Lemeshow chi-square = 3.95, p = 0.861].13
In this study, an SIC cutoff of 25 had sensitivity of 71.5% and specificity of 74.4% for predicting in-hospital mortality in ACS patients. The high sensitivity and specificity was also found in the previous studies. Chiang et al, found that an SIC cut-off of 21.0 had sensitivity of 67.2% and specificity of 83.5% for in-hospital mortality of STEMI.15 Ran et al, found a sensitivity of 82.4% and specificity of 77.8% for SIC cutoff of 10 in predicting in-hospital mortality.13 Those findings indicate that SIC had good sensitivity and specificity for predicting in-hospital mortality in STEMI and all spectrums of ACS. Our results suggest that SIC is a rapid tool with good sensitivity and specificity for predicting in-hospital mortality in patients presenting with ACS.
ROC analysis in our study demonstrated that SIC had a good predictive value for in-hospital mortality. SIC had a better correlation to in-hospital mortality than SI and MSI score on spearman analysis. Our study also demonstrated that SIC had a significant association with in-hospital mortality both in univariate and multivariate analysis. Ran et al, also found that the discriminatory capacity of SIC for in-hospital mortality was non-inferior to the GRACE scale, but SIC was a better predictor than the TIMI risk score.13 Chiang et al, also found that SIC had better predictive power than that of SI and MSI.15
Decrement of parameters related to cardiac function such as cardiac index, stroke volume, and left ventricular (LV) stroke work developed during acute myocardial infarction, especially if cardiogenic shock. In other words, the heart's ability to meet systemic perfusion needs is decreased substantially. Baroreceptors in the blood vessel wall stimulate the vasomotor areas in the brainstem to increase heart rate and arterial vasoconstriction in hypotensive conditions. A series of neurohumoral reactions are triggered following myocardial infarction, including activation of the sympathetic nervous system. The release of catecholamines will trigger an increase in blood pressure (BP) and heart rate (HR) to compensate for decreased cardiac output due to myocardial infarction. This initial compensatory system can be represented by the components of the shock index: pulse rate and blood pressure.
The index of BP and HR after myocardial infarction may reflect the cardiovascular system and neuroendocrine system’s condition as well as the patient's hemodynamic status. It is a sensitive indicator of left ventricular dysfunction and the degree of hemodynamic stability rather than just relying on HR or SBP alone.16 Several previous studies have shown that the shock index can be a predictor of major adverse cardiac events (MACE) or death in patients with ACS.17,18 Wang et al. have attempted to determine whether the prognostic value of the shock index and its derivatives (MSI, age SI [age x SI], age MSI [age x MSI]) is better than the TIMI risk index for predicting adverse outcomes in STEMI patients undergoing primary PCI. Multivariate analysis shows that high SI (and its derivatives) values are associated with higher complication rates.19
Renal dysfunction is believed to be a risk factor for mortality in patients with myocardial infarction.4 Cywinski et al. showed that estimated renal function was a better prognostic indicator than Scr.20 CCr by Cockcroft- Gault has adequate discriminatory ability, with an AUC > 0.8 for prediction of poor outcomes, which was better than other equations for glomerular filtration rate estimation in patients with acute coronary syndrome.21 Therefore, it can be concluded that the addition of CCr to SI could result in better predictive accuracy in patients with STEMI. SIC included 3 factors that were easily collected and calculated, in contrast to the GRACE score which included more variables.13 The previous studies only evaluated the predictive value of SIC in the STEMI population, while in our study, patients with all ACS spectrums were included; adding unstable angina and NSTEMI patients into account.13,15 Our results showed that SIC is not only useful for predicting mortality in STEMI but also in all ACS spectrums.