ABC | Volume 115, Nº2, August 2020

Original Article Viana et al. ACS prognosis based on models and outcomes Arq Bras Cardiol. 2020; 115(2):219-225 Table 3 - Comparison of clinical characteristics between patients who presented non-fatal outcome Versus those free of outcomes Outcome No Outcome p Value Sample Size 39 346 Age 68 ± 13 64 ± 13 0.05 Systolic Arterial 159 ± 30 152 ± 28 0.15 Hypertension Heart Rate 74 ± 19 80 ± 18 0.06 Creatine 0.9 ± 0.3 1.0 ± 0.7 0.058 Killip > 1 5 (13%) 46 (14%) 0.82 Positive Troponin 30 (77%) 237 (73%) 0.58 Ischemic ECG 16 (41%) 110 (34%) 0.36 based precisely on the severity of existing coronary lesions and manages to fill the gap left by the previous score. In addition, new coronary events (ACS recurrence) potentially influence the prediction of mortality, since infarction causes death. On the other hand, cardiovascular death as an initial event could not influence the occurrence of a subsequent recurrent event. This obvious observation reinforces the logic of our results that when recurrent events are predicted, death is also (SYNTAX score), but the prediction of death due to a cardiac insult does not guarantee prediction of recurrent ischemic events (GRACE score). It is a hypothesis-generating study, which evidenced an eventual need to discriminate the outcomes resulting from an ACS, defining a practical utility for the clinical and anatomical predictive models. The use of combined outcomes has emerged in large registries and clinical trials to address potential limitations of statistical power, however this method establishes the same weight for different outcomes, not distinguishing the relative significance of eachone. 22 The practical implications of this study lie in the need to assess, within the clinical-anatomical context, the isolated probability of different outcomes, in addition to recognizing the limited knowledge of clinical data in predicting recurrent coronary events. This could influence the decision-making process for the treatment of patients with ACS, where the initial clinical risk usually dictates the magnitude of the treatment. This study refutes this practice, because in the face of an individual with lowGRACE, therewould still be the possibility of a high angiographic risk. Thus, a global event prediction, taking into account complementary predictor models and a predilection for different outcomes, is the best way for an adequate risk stratification. Table 2 - Comparing Clinical Characteristics between patients who died versus those who survived the event Variables Death Survival p value Sample Size 19 346 Age 78 ± 10 63 ± 13 < 0,001 Systolic Arterial Hypertension 139 ± 32 153 ± 28 0,06 Heart rate 89 ± 20 79 ± 18 0,03 Creatine 3,24 ± 2,6 1,15 ± 0,6 <0,001 Killip > 1 9 (48%) 42 (12%) <0,001 Positive Troponin 19 (100%) 248 (72%) 0,007 Ischemic ECG 10 (53%) 116 (34%) 0,08 The main limitation of this study is its sample size, which may be subject to type II error. In addition, although we use two scores frequently used in clinical practice, it would still be interesting to have a comparative assessment of the other clinical and anatomical scores for the prediction of different outcomes, from the perspective of the anatomical and clinical paradigms. Conclusion In conclusion, the present study indicates that anatomical data contribute to the prediction of recurrent non-fatal events and cardiovascular death in ACS. On the other hand, clinical data are able to predict death, but do not influence the likelihood of non-fatal outcomes. Author contributions Conception and design of the research: Viana MS, Correia VCA, Correia LCL; Acquisition of data: Viana MS, Correia VCA, Ferreira FM, Lacerda YF, Bagano GO, Fonseca LL, Kertzman LQ, Melo MV, Noya-Rabelo MM; Analysis and interpretation of the data: Viana MS, Correia VCA, Ferreira FM, Lacerda YF, Bagano GO; Statistical analysis: Viana MS, Correia VCA, Ferreira FM, Lacerda YF, Fonseca LL, Kertzman LQ, Melo MV, Noya-Rabelo MM, Correia LCL; Critical revision of the manuscript for intellectual content: Viana MS, Correia VCA, Ferreira FM, Lacerda YF, Bagano GO, Fonseca LL, Kertzman LQ, Melo MV, Noya-Rabelo MM, Correia LCL. 223