Secondary prevention of acute coronary syndrome (ACS), a common disease with high mortality and morbidity around the world, has been a critical task for decades. Although patients with ACS share a relatively common pathophysiological process, response to treatment as well as long-term prognosis varies from person to person in multiple ways due to high heterogeneity. For better prevention of adverse events, guidelines recommend that risk stratification and clinical prediction algorithms combining clinical history, physical examination, electrocardiography (ECG), and cardiac troponins should be applied soon after admission.1–3 Numerous risk scores derived from large studies predict both in-hospital and postdischarge ischemic risks, such as the thrombolysis in myocardial infarction (TIMI) and Global Registry of Acute Coronary Events (GRACEs) risk scores.4,5
The GRACE score represents the most notable and extensively acknowledged measure that has been applied in various studies. However, its predictive value differs across populations and clinical conditions. On the one hand, some studies seek to perfect the scoring model by adding new biomarkers.6,7 On the other hand, researchers established new models encompassing other critical clinical, laboratorial, and angiographic variables.8,9 Recently, the EPICOR (long-term follow-up of antithrombotic management patterns in acute coronary syndrome patients) and EPICOR Asia studies established a risk-scoring model for 2-year postdischarge survival with data collected at admission, during hospitalization, and at discharge in ACS patients, and demonstrated good discrimination (c-statistic = 0.80, 95% CI = 0.79-0.82).10
Currently, there is no published research about the capability of the EPICOR score in predicting 2-year mortality in Chinese patients after percutaneous coronary intervention (PCI). Therefore, in this study, we aimed to investigate the predictive value of the EPICOR for 2-year mortality in a large cohort of Chinese patients.
2.1. Study population
This was a prospective observational study in a large cardiovascular center in China. From January to December 2013, a total of 6431 consecutive patients presenting with ACS (ie, unstable angina, non-ST-elevated myocardial infarction [MI], and ST-elevated myocardial infarction [STEMI]), who were scheduled for PCI, were enrolled. Results of ECG, echocardiography, X-ray examination, and blood tests within 24 hours of admission, and clinical baseline data were recorded. Patients were followed up for 2 years. The Institutional Review Board approved the study protocol, and all patients provided written informed consent before the intervention. We excluded patients whose relevant data were missed and those who died during hospitalization or failed 2-year follow-up.
Before the procedure, patients received aspirin 300 mg and clopidogrel (loading dose of 300 or 600 mg) as soon as possible. During the procedure, unfractionated heparin (100 U/kg) was administered to all patients, and glycoprotein IIb/IIIa inhibitors were used, according to the operator’s judgment. If PCI proceeded for longer than an hour, an additional 1000 U of heparin sodium was administered. Results of coronary angiography were interpreted by experienced cardiologists. More than 70% stenosis of vessels was an indication for stent implantation. After the procedure, aspirin was prescribed at a dose of 100 mg daily indefinitely, and clopidogrel 75 mg daily or ticagrelor 90 mg twice daily for at least 1 year after PCI was advised.
2.3. Definitions of the EPICOR score and GRACE score 2.0
The EPICOR score was established by the EPICOR and EPICOR Asia registries, taken from prospective international cohort studies of unselected populations comprising consecutive ACS patients. The online calculator (www.acsrisk.org) provides the percentage probability of death in 2-year follow-up. We used its simplified score algorithm to evaluate 2-year mortality risk, which includes 11 independent variables: age, gender, ACS subtype, ejection fraction, serum creatinine, hemoglobin and fasting blood glucose at admission, interventions during admission, EuroQol-5D (EQ-5D) score at discharge (to characterize current health status), previous cardiac disease, and chronic obstructive pulmonary disease (COPD). Of note, the EPICOR calculator offers the option “Unknown” for several items. As EQ-5D was not available for the present study, “Unknown” was included as an alternative for all of the subjects we evaluated.
The GRACE score 2.0 employs nonlinear functions and is more accurate than the original version for predicting the risk of death (or death/MI) in the long term.11 It contains eight variables: ST segment deviation, age, heart rate, systolic blood pressure, creatinine/renal failure, Killip class/diuretic usage, cardiac arrest at admission, and elevated biomarkers of necrosis.
2.4. Endpoints and definitions
All patients were evaluated by telephone, messages, or clinic visit at 30 days, 6 months, 12 months, and 24 months through the follow-up center of the participating hospital. The primary end point was 2-year all-cause death. The secondary outcome was major adverse cardiovascular and cerebrovascular events (MACCEs), a composite of all-cause death, MI, revascularization, stent thrombosis, and stroke. MI was defined by the Third Universal Definition of myocardial infarction.12 Revascularization refers to coronary artery bypass grafting and PCI. Definite, probable, or possible stent thrombosis was recorded based on the Academic Research Consortium criteria.13 All adverse events were identified and assessed centrally by two independent cardiologists and disagreements were resolved by consensus.
2.5. Statistical analysis
Continuous variables were expressed as mean ± SD or median (P25, P75) and were compared using the Student’s t test or analysis of variance (ANOVA). Categorical variables were expressed as percentages and compared using χ2 statistics or Fisher’s exact test as indicated. The abilities of both the EPICOR and GRACE scores for distinguishing patients with or without events were assessed using area under the receiver operating characteristics curves (AUROCs), and these AUROCs were compared using the Z-test. According to the EPICOR calculator, patients can be stratified into six risk groups, from “low” risk (group 1) to “very high” risk (group 6). In the present study, patients were divided accordingly into three strata: low-risk (groups 1 and 2), medium-risk (groups 3 and 4), and high-risk (groups 5 and 6). A Kaplan–Meier survival curve was used to evaluate differences among these groups. In addition, Cox regression analysis was performed to find independent predictors for long-term outcomes. A two-tailed p value <0.05 was considered to be statistically significant. All of the analyses were performed with SPSS Statistics version 20.0 (SPSS, Chicago, IL, USA).
A total of 6087 consecutive patients with ACS were evaluated after exclusion of those whose baseline data were incomplete (n = 298, 4.6%), those who died in hospital (n = 13, 0.2%), and those who did not achieve 2-year follow-up (n = 33, 0.5%). Their average age was 58 ± 10 years; 4684 (77%) were male and 1383 (22.7%) presented with STEMI. During the 2-year follow-up, 68 (1.1%) patients died after discharge and 744 (12.2%) patients had MACCEs.
Baseline characteristics of the subjects studied, grouped as death or survival, are shown in Table 1. In the death group, patients were older and had a significantly higher proportion of a history of cerebrovascular disease (p < 0.001) and previous PCI (p = 0.016), while other comorbidities as well as ACS type at admission were comparable between them. With regard to laboratory parameters at admission, those reflecting inflammation (ie, white blood cell and C-reactive protein) and renal function (ie, blood urea nitrogen and creatinine) differed somewhat between the two groups. Dual antiplatelet therapy (DAPT) was applied to 5887 (98.3%) patients, 97.1% of whom received at least 1 year of DAPT and 29.4% of whom were still on DAPT at 2-year follow-up. The proportions of patients with DAPT, calcium-channel blockers, and diuretics were inequivalent between these two groups.
According to the EPICOR system, the estimated risk ranged from 0.4% to 26.6%. The distribution of risk groups indicated that most patients were classified in the low- and intermediate-risk categories (Fig. 1).
The result of the ROC analysis is shown in Fig. 2. The predictive value of the EPICOR score for 2-year all-cause mortality was moderate (AUROC 0.712, 95% CI, 0.65-0.772; p < 0.001). When patients with STEMI or non-ST-segment elevation ACS (NSTE-ACS) were evaluated separately, the discriminatory power improved for the STEMI proportion. A cut-off value of 4.45% had 68.4% sensitivity and 81.3% specificity for prediction, as the AUROC was 0.790 (95% CI, 0.676-0.903; p < 0.001). However, the discrimination performance was not adequate (AUROC 0.683, 95% CI, 0.615-0.751; p < 0.001) for patients with NSTE-ACS. Compared with the revised GRACE score, EPICOR displayed noninferior results in ACS and its subgroups alike.
We divided patients into three groups as described in the Methods section: low-risk (n = 3382, 55.6%), medium-risk (n = 2547, 41.8%), and high-risk (n = 158, 2.6%). The Kaplan–Meier curve demonstrated that mortality rates differed significantly among them (0.6% vs 1.3% vs 9.5%, p < 0.001). Moreover, ongoing divergence was also observed in MACCE rates (11.8% vs 12.3% vs 19.6%, p = 0.014). Cox proportional regression analysis revealed that the estimated percentage risk (whether as a continuous variable or a categorical one) was an independent predictor of all-cause death but not of MACCEs (Fig. 3 and Table 2).
In the present study, we investigated the predictive value of the simplified EPICOR score for long-term mortality of ACS patients undergoing PCI treatment in a large Chinese cardiovascular center. The major findings of this study are as follows: (1) Patients who died after discharge during 2-year follow-up were more often harboring risk factors and comorbidities; (2) The EPICOR score showed fair discriminatory power of 2-year mortality in patients with ACS and an improved performance in the STEMI subgroup. There were no differences between the EPICOR and GRACE scores; (3) The multivariate Cox regression model suggested that it could aid in risk stratification of ACS patients as an independent predictor.
The GRACE risk score (version 1.0) was established from a large international population of real-world patients admitted with ACS. It consists of variables concerning clinical history, signs, ECG change, and cardiac markers to estimate the risk of in-hospital death and of death at 6 months after discharge.5,14 Previous studies have extensively validated its performance across races, nationalities, gender, subtypes of ACS, and periods of follow-up (from hospitalization to 2 years).15,16 Thus, guidelines recommended it a superior tool for risk stratification as soon as at admission. Of note, some factors limit its utility and accuracy. The GRACE Registry included mostly white patients of European descent, and procedural and medical management has advanced beyond the clinical environment of the 2000s. Our previous study showed its limited discriminative accuracy of long-term outcomes in patients after PCI: AUROCs of death and MACCE were 0.661 (95% CI, 0.586-0.736; p < 0.001) and 0.520 (95% CI, 0.496-0.545; p = 0.101), respectively.17 Recently, a revised version (GRACE score 2.0) was available online to provide a better tool for 1 or 3-year prognoses and some researchers have launched evaluation about it.18,19 In the present study, we simply evaluated the updated GRACE score and compared it with EPICOR. Although containing different items, the EPICOR score was noninferior to the GRACE score 2.0 whenever applied to ACS, STEMI, or NSTE-ACS patients.
The EPICOR and EPICOR Asia studies also enrolled a large cohort of registry patients from different geographic regions and healthcare systems, aiming to conduct a novel scoring model to predict long-term mortality.10,20 Different from what is involved in the GRACE model, it extended variables such as hemoglobin, fasting glucose, COPD, interventional strategy, and, especially, educational degree and living quality. As already mentioned, sex is not incorporated in the GRACE model. Despite a sex disparity in mortality, some researchers believe that higher mortality rates in females might result in higher baseline risk profiles.21 However, whether male or female sex should be considered as a risk predictor has long been debated.22,23 Unlike most of the previous results, the EPICOR study demonstrated that male sex independently predicted a 32% higher risk. In addition to some traditional risk factors (eg, ejection fraction value and previous history of cardiac disease), it is reported that some parameters that do not apparently reflect cardiac conditions might add risk probability for ACS patients. Stefan et al pointed out that patients with COPD hospitalized with acute MI were at higher risk for dying during hospitalization (13.5% vs 10.1%) and at 30 days after discharge (18.7% vs 13.2%).24 Su et al found that patients with acute MI and a history of COPD were less likely to receive evidence-based pharmacological or interventional treatments and that 1-year mortality rates were increased by 20%.25 Previous studies found that elevated glucose level at admission was associated with both short- and long-term mortality.26,27 Although underlying mechanisms have not been fully clarified, some scholars suggested that hyperglycemia may lead to oxidative stress, platelet activation, or enhanced thrombin formation.28 Reduced hemoglobin at admission is another index in the EPICOR model and has been promoted as a statistically significant predictor of adverse events in several studies possibly due to the impairment of balance between oxygen delivery and demand.29,30
Our study included unselected clinical patients in a single Chinese center representing real-world and consistent practice experience. It showed only a moderate discriminatory ability for long-term mortality prediction in the entire cohort but was more accurate with regard to the STEMI subgroup. When setting estimated risk into a categorical variable, the model distinguished itself for discrimination of patients at a higher tendency of worse outcomes. Two-fold and 12-fold hazards of death for patients in medium- and high-risk groups warrant more positive medical management and frequent follow-up visits to improve their prognoses.
Obviously, a relatively poorer performance of the simplified EPICOR score was observed in our population than in the original cohort. A possible explanation for this may be discrepancies in baseline characteristics, clinical practice, and mortality rates. To be specific, the proportion of STEMI participants (22.5%) in this study was relatively lower, distinct from that in the EPICORs (49.2%). And subgroup analysis confirmed that when applied to STEMI patients, the model performed nearly as well as in the EPICOR studies. Although COPD predicted a 57% higher risk for mortality in the EPICOR model, a relatively lower prevalence in our cohort was observed (2.3% vs 4.5% of EPICORs) and univariate Cox regression failed to find its association with mortality. In terms of medical therapy, all of our participants received PCI, most of them being implanted with drug-eluting stents, while that figure in EPICORs was below 70%. Therefore, all of these aforementioned factors considered the subjects we studied more likely to be at low risk, which was in accord with the lower mortality rates. In addition, EQ-5D was unavailable in our database, making it possible to underestimate mortality risk given that the choice of “Unknown” is equivalent to “0” in the algorithm. Nevertheless, no evident differences were observed between the EPICOR and GRACE scores despite of lack of EQ-5D data. Thus, it calls for the further research with more detailed materials to validate the EPICOR score.
Analogous to the EPICORs, multivariate Cox regression modeling revealed that diuretic at discharge was an independent predictor of 2-year mortality (which is incorporated in the full model). Meanwhile, a 2-fold’s hazard for patients with previous history of cerebrovascular disease was seen in the analysis. Insufficient treatment of evidence-based medicine and intervention might in part explain this phenomenon, while pathophysiological interactions remain to be elucidated. Therefore, despite a wide spectrum of variables, it is clear that not all factors that might have an impact on prognosis are included. For example, some recent research has reported that angiographic information might provide incremental prognostic value for patients after PCI in the long term.9,31
There are some limitations to our study. First, it is a single-center observational study enrolling only those undergoing PCI treatment, and thus not representative of real-world clinical practice nationwide. Second, patients enrolled in this study had a lower incidence of mortality compared with the EPICOR and EPICOR Asia studies. As described earlier, active intervention with extensive use of drug-eluting stents, relatively lower proportion of acute MI, and preserved cardiac function as normal ejection fraction may contribute to this result. Finally, we were unable to conduct the full model calculation because some variables required in that score were not systematically collected, and the absence of EQ-5D underestimated the accuracy of the simplified model.
In conclusion, the simplified EPICOR score is a valid predictor of long-term mortality in ACS patients undergoing PCI treatment, and shows its strength in discriminating high-risk patients.
This study was supported by the National Key Research and Development Program of China (2016YFC1301301) and the National Natural Science Foundation of China (81770365).
We thank all the colleagues in the Department of Cardiology, Catheterization Laboratory and Follow-up Center, Fu Wai Hospital for their contributions. We also appreciate Liwen Bianji, Edanz Group China (www.liwenbianji.cn/ac), for editing the English text of a draft of the article.
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Keywords:© 2019 by Lippincott Williams & Wilkins, Inc.
Acute coronary syndrome; Mortality; Percutaneous coronary intervention