ABC | Volume 112, Nº6, June 2019

Original Article Carvalhal et al. Does GRACE Score modulate invasiveness? Arq Bras Cardiol. 2019; 112(6):721-726 Methods Sample selection Patients consecutively admitted to the coronary care unit (CCU) of a tertiary-care hospital due to non-ST elevation acute coronary syndromes between August 2007 and October 2014 were included in the study. Inclusion criteria was typical chest discomfort plus at least 1 of the 3 objective criteria: electrocardiographic changes consisting of transient ST‑segment depression (0.05 mV), or T wave inversion (0.1 mV); troponin change to a level beyond the 99 th percentile threshold of a healthy reference population, with 10% coefficient of variability; 11 or previous documentation of coronary artery disease, defined as a definitive history of myocardial infarction, or coronary obstruction ≥ 50% at angiography. Patient’s option not to participate in the Registry was the sole exclusion criteria. All participants provided written informed consent. Study protocol Patients included were classified as for invasive or selective strategies according to medical decision. Management strategy was decided by the cardiology team in the CCU and was not influenced by the study protocol. Invasive strategy was prospectively defined by a decision to perform invasive coronary angiography, followed by a revascularization procedure if anatomically indicated. Selective strategy was defined as an indication of angiography conditioned to a positive non-invasive test, or clinical instability. GRACE Score was used for evaluation of baseline risk, defined by tertiles of the original study (low risk: 1-108; intermediate risk: 109-140; high risk: 141-372). Death during hospitalization was the outcome of interest. Statistical analysis In order to evaluate whether baseline risk influenced the physician’s decision regarding management strategy, GRACE Score was compared between the groups undergoing invasive versus selective strategy by the Mann-Whitney statistic. Secondly , in order to understand the determinants of medical decision, logistic regression was utilized to assess independent predictors of the invasive strategy. The selection of variables for this analysis was based on their univariate association with the invasive strategy (p < 0.10). A propensity score for the invasive strategy was derived from the logistic regression. Thirdly, in order to evaluate whether medical decision was correctly driven by prognosis, the value of the propensity score for predicting death during hospitalization was tested by the C-statistics (area under the ROC curve). C-statistics of the propensity score was compared with the c-statistics of GRACE Score by Hanley-Mcneil's test. The analysis of normality was done through the combination of histogramandQ-Qplots visualization, description of skewness and kurtosis with confidence intervals and normality tests (Shapiro-Wilk and Kolmogorov-Smirnov). Numeric variables were expressed by means (standard deviation) or medians (interquartile range), and compared by unpaired student’s t test or Mann-Whitney test. Categorical variables were described by frequencies and compared by Pearson’s chi-square test, or Fisher’s exact test. SPSS Statistical Software (Version 21, SPSS Inc., Chicago, Illinois, USA) was utilized for data analysis. Results A sample of 570 consecutive patients admitted with non‑ST‑segment elevation ACS was studied, aged 69 ± 14 years, 50% males. GRACE Score had a normal distribution, with mean of 118 ± 38. According to GRACE definition, 46% of patients were defined as low risk, 30% as intermediate risk, and 24% as high risk. Management through an invasive strategy took place in 69% of the patients. GRACE Score of patients who underwent an invasive strategy was 118 ± 38, similar to patients managed conservatively (116 ± 38; p = 0.64). Seemingly, the area under the ROC curve for GRACE Score predicting an invasive strategy was not significant (0.51; 95% CI = 0.47 - 0.57; p = 0.51) - Figure 1A. There was no difference in the frequency of invasive strategy among patients with low, intermediate and high risk according to GRACE (68%, 77%, 73%, respectively; p = 0.48). Table 1 depicts univariate association between patients’ characteristics and management strategies. Among GRACE variables, Killip class, systolic blood pressure, heart rate, and creatinine did not have any association with the strategy chosen. On the contrary, positive troponin (OR = 2.7; 95% CI = 1.8 - 3.8; p < 0.001), ST-deviation (OR = 2.0; 95% CI = 1.2 - 3.2; p = 0.006), and the numeric value of hemoglobin at admission (OR = 1.2; 95% CI = 1.1 - 1.4; p < 0.001) predicted an invasive strategy. Conversely, age as a numeric variable had an inverse relationship with invasive strategy (OR = 0.98; 95% CI = 0.97 - 0.99; p < 0.013). Finally, the risk of bleeding according to CRUSADE Score was protective against invasive strategy (OR = 0.98; 95% CI = 0.97 - 0.99; p < 0.018). A logistic regression model was used to build a propensity score for invasive strategy. The 5 variables associated with the invasive strategy in a univariate analysis were included. Positive troponin (OR = 2.5; 95% CI = 1.7 - 3.7; p < 0.001), ST-deviation (OR = 1.8; 95% CI = 1.1 - 3.1; p = 0.026), and hemoglobin on admission remained positively associated (OR = 1.2; 95% CI = 1.1 - 1.4; p < 0.001). Age and CRUSADE Score lost statistical significance (p = 0.09 and 0.29, respectively) - Table 2. This propensity model was statistically significant (chi-square = 48; p < 0.001; R 2 = 0.2), calibrated (H-L χ 2 = 12; p = 0.17), and had an area under the ROC curve (AUC) of 0.68 (95% CI = 0.63 - 0.73; p < 0.001) for predicting an invasive strategy. This AUC was significantly better than GRACE Score area for the strategy prediction (p < 0.001) - Figure 1A. A secondary model was built only with variables commonly utilized as part of a risk profile in ACS patients. In this model, hemoglobin and CRUSADE were not included, making age an inversely associated independent predictor of invasive strategy, and positive troponin and ST-deviation positively associated with invasive strategy - Table 2. 722