The new classification method in ACEF score is more useful in patients with acute coronary syndrome without ST segment elevation

creatinine, and ejection fraction (ACEF) score [age (years) / ejection fraction (%) +1 (if creatinine >2 mg / dL)] could predict in-hospital mortality in patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) and its relationship with the Global Record of Acute Coronary Events (GRACE) risk score were investigated. The study enrolled 658 NSTE-ACS patients from January 2016 to August 2020. The patients were divided into two groups according to the ACEF score with an optimum cut-off value of 1.283 who were divided into two groups according to the ACEF score: low ACEF (≤1.283, n:382) and high ACEF (>1.283, n: 276). The primary outcome of the study was in-hospital all-cause mortality. The primary outcome of the study was in-hospital all-cause mortality. Statistically accuracy was defined with area under the curve by receiver-operating characteristic curve analysis. Results for predicting in-hospital mortality was 0.849 (95 % CI, 0.820 to 0.876; p<0.0001); sensitivity, 92.3 %; specificity, 59.2 %, and the optimum cut-off value was >1.283. The ACEF score presented excellent discrimination in predicting in-hospital mortality. We obtained an easier and more useful result by dividing the ACEF score into two groups instead of three in NSTE-ACS patients. As a simple, useful, and easily applicable risk stratification in the evaluation of an emergency event such as the ACEF score, it can significantly contribute to the identification of patients at high risk.


Introduction
Non-ST segment elevation acute coronary syndrome (NSTE-ACS) remains an important cause of mortality among ischemic heart diseases [1]. Patients with NSTE-ACS represent a heterogeneous subgroup consisting of non-ST segment elevation myocardial infarction (NSTEMI) and unstable angina pectoris (USAP) in acute coronary syndrome (ACS) [2,3]. NSTE-ACS is the most common and increasingly common cause of coronary events in patients with previous heart disease [3]. In NSTE-ACS patients, it is important to undertake a risk assessment in patients when deciding on different therapeutic strategies that can significantly affect short-term and longterm outcomes such as conservative or invasive therapy. Determining the appropriate treatment according to the risk classification in these patients has the potential to improve clinical results [4,5]. In order to evaluate these patients over time, various risk classification systems with simpler, less time-consuming and easily evaluable risk scores have been developed. One of these scores is the age, creatinine, and left ventricular ejection fraction (LVEF) (ACEF) score, which is a simple and extremely easy to calculate a cardiovascular risk score, consists of three independent factors such as age, creatinine, and LVEF. The ACEF score was first used by Ranucci et al, in patients undergoing elective coronary artery bypass surgery (CABG), it has been reported to show similar or better predictive value for mortality compared to more complex risk scores [6]. The ACEF score was stated to be the predictor of mortality in patients undergoing percutaneous coronary intervention (PCI) [7]. Similarly, different studies have been reported to provide a good prognostic contribution to the identification of high-risk patients undergoing PCI due to serious coronary lesions such as bifurcation lesions and chronic total occlusion [8,9]. ОРИГИНАЛЬНЫЕ СТАТЬИ § Data on the predictive value of the ACEF score in patients presenting with NSTE-ACS are scarce.
We aimed to investigate the association between ACEF score and the Global Record of Acute Coronary Events (GRACE) risk score and in-hospital mortality in patients with NSTE-ACS.

Material and Methods
Data of 658 NSTE-ACS patients over 18 years of age who were identified as 74 USAP and 584 NSTE-myocardial infarction (MI) hospitalized in a coronary care unit (CICU) between January 2016 and August 2020 were retrospectively recorded by the physician in the CICU. In total, the age range of patients was 28-91 years, an average of 61.7±12. 8  The diagnosis of NSTEMI was defined as patients with typical angina and increased cardiac biomarker level (troponin-I >0.06 ng/mL) without ST-segment elevation criteria on electrocardiography (ECG). The USAP diagnosis was defined as patients with normal cardiac biomarker level (troponin-I <0.06 ng/mL), without ST-segment elevation criteria on ECG, and with typical angina [10]. When the patients were admitted to the CICU, they were immediately monitored, ECG was taken and blood samples were taken for biochemical analysis. The treatments of the patients were organized according to the guidelines of the European Society of Cardiology (ESC) and antiaggregant was started. Angiotensin converting enzyme inhibitors, beta blockers and statins were started within the first 24 hours after hospital admission without contraindications. All patients underwent coronary angiography and were referred to PCI or CABG as indicated. Later, transthoracic echocardiographic examination was performed before coronary angiography in all patients using Philips Epic 5 (Philips Healthcare, Andover, Massachusetts) device with a 1-5 MHz converter. Standard 2-dimensional and Doppler echocardiographic measurements were made to the patients included in the study according to the American Echocardiography Association / European Echocardiography Association guidelines [11]. LVEF was calculated using the modified Simpson's method and LVEF was considered <50 % decreased and LVEF ≥50 % was considered normal.
Exclusion criteria from the study; 1) acute ST-segment elevation myocardial infarction, 2) patients without serum creatinine value or LVEF records. 42 patients whose ACEF score could not be calculated due to lack knowledge of LVEF and creatinine were excluded from the study.
The medical records of the patients were examined retrospectively. Data of demographic and clinical features, such as age, gender, history of hypertension (HT), diabetes mellitus (DM), smoking, family coronary artery disease (CAD) history, hyperlipidemia, previous CAD, vital signs, laboratory results (glucose, creatinine, troponin I, etc.) and echocardiographic results were collected by the CICU doctor and recorded on standard patient data collection pages.
Besides, DM was defined as a previous history of DM, or a fasting blood glucose level ≥126 mg/dl, or above 200 mg/dl at any measurement, or use of oral hypoglycemic agents and/ or insulin, or HbA 1c > 6.5% [12]. Existing or for mer smokers were recorded as 'smokers' . HT was de fined as having blood pressure ≥140 / 90 mmHg and / or anti hy per tensive drug use.
For the GRACE risk score, patients' age, heart rate, systolic blood pressure (SBP), creatinine value, Killip degree, pre-hospital cardiac arrest, ST-segment deviation on ECG, and increase in troponin I were recorded and GRACE risk scores were calculated [13].
The ACEF score calculated without treatment (PCI or drug treatment) of patients yet. The The ACEF score was calculated as follows: formula age (years) / LVEF (%) +1 sco re for serum creatinine >2 mg / dL [6]. The patients were divided into two groups according to the ACEF score with an optimum cut-off value of 1.283; low ACEF (≤1.283, n:382), and high ACEF (>1.283, n:276). During their hospital stay, all clinical data of the patients were examined and analyzed, and death due to all causes before discharge was accepted as in-hospital mortality. The primary outcome of the study was in-hospital all-cause mortality.
The study protocol was prepared after the local ethical committee approval. The study was designed and conducted under the principles of the Helsinki Declaration.

Statistical analysis
The required sample size power analysis results, including at least 647 individuals were determined. In this case, 82.96 % of the power test is expected to be obtained. SPPS 25 (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.) statistical package program was used to evaluate the data. Variables were determined as mean±standard deviation and percentage and frequency values. Variables were evaluated after controlling the preconditions for normality and homogeneity of variances (Shapiro Wilk and Levene Test). While analyzing the data, Independent 2 group t test (Student's t test) was used for the comparison of two groups, and Mann Whitney-U test was used if the prerequisites were not met. The relationship between two continuous variables was evaluated with the Pearson correlation coefficient and the Spearman correlation coefficient if the parametric test did not meet the prerequisites. Multivariate logistic regression analysis was used to see the effect of other variables when the ACEF score value is categorically ОРИГИНАЛЬНЫЕ СТАТЬИ §

Results
The distribution of demographic findings and bio chemicals according to ACEF risk groups is shown in Table 1. In addition to age, kidney function, and LVEF, which are components of the ACEF score, in the higher ACEF score group were found higher glucose, lower hemoglobin value, lower platelet value, higher leukocyte value, higher troponin I value and higher GRACE risk score (Table 1). Patients in the higher ACEF score group had a higher prevalence of cardiovascular comorbidity, as did previous CAD and DM (Table 2).
When the patients were compared in two groups as those with and without mortality; the ACEF score was significantly higher in the group with mortality than the group without mortality (2.1±0.53 vs. 1.34±0.56, p=0.001) ( Table 3). The group with mortality had higher age, higher GRACE risk score, low LVEF value, low hemoglobin value, high glucose value, and high leukocyte count compared to the group without mortality (Table 3-
NSTE-ACS patients with high ACEF score are highly selective group with in-hospital mortality of 4.71 % ( Table 4). In ROC curve analysis, ACEF score presented excellent discrimination in predicting in-hospital mortality: The AUC of ACEF score for predicting in-hospital mortality was 0.849 (95 % CI, 0.820 to 0.876; p <0.0001); sensitivity 92.3 %; specificity 59.2 %, and the optimum cut-off value was >1.283 ( Figure 2).
Predictive predictors for values below and above 1.283 (cut off value) of the ACEF risk score were determined in logistic regression analysis. In the regression analysis, age, creatinine and LVEF which are components of the ACEF score are not included. Decreased hemoglobin (OR=0.7, p=0.003), decreased platelet count (OR=0.99, p=0.02), increased leukocyte count (OR=1.1, p=0.01), increased troponin I (OR=1.0001, p=0.03), GRACE risk score (OR=1.09, p=0.003) and smoking (OR=0.4, p=0.01) are independent determinants of the high ACEF score in the multivariate regression (Table 5).

Discussion
In this study, we analyzed the association between ACEF score and GRACE risk score and in-hospital mortality in patients with NSTE-ACS. We found that the ACEF score has a good predictive ability for in-hospital mortality. The ACEF score was positively correlated with GRACE risk score.
According to the ACEF score, two different risk groups can be defined. The ACEF score can provide a very simple and easy-to-calculate tool to classify the daily clinical practice risk of NSTE-ACS patients.
There are pathophysiological differences between NSTE-ACS and ST-segment elevation myocardial infarction. In  ОРИГИНАЛЬНЫЕ СТАТЬИ § NSTE-ACS, it usually involves situations in which coronary blood flow is reduced, such as incomplete (partial) or temporary total coronary occlusion, rather than complete coronary artery occlusion. This difference is important when determining the treatment of patients with NSTE-ACS [14,15]. In NSTE-ACS, treatment plan is made according to the patient's risk. Although mortality rates have decreased significantly compared to the pre-PCI period, a significant number of patients with NSTE-ACS still suffer from death. Therefore, there is an urgent need to identify patients at high risk of mortality. Moreover, we can say that a risk assessment is the most important step to organize the treatment of each patient with NSTE-ACS (early invasive or conservative) after hospitalization and to determine the short and long term prognosis. Because the success of the treatment of patients who apply with NSTE-ACS is often directly related to the risk of the patients [16]. Since risk stratification in NSTE-ACS patients is a very important step in directing treatment, different risk assessment strategies have been developed over time. The 2018 ESC myocardial revascularization guidelines highlight the role of the NSTE-ACS risk classification in the decision-making process (especially invasive strategy) for the treatment of patients [17]. It is recommended to calculate the GRACE risk score in nowadays international guidelines for risk stratification in patients with NSTE-ACS [15]. In addition, it has been reported that the GRACE risk score has a superior discriminating performance compared to other ACS risk scores [18]. Our study is the study to examine the relationship between GRACE risk score and ACEF score in patients with NSTE-ACS. A positive correlation was found between the GRACE risk score and ACEF score (p<0.001). Included the ACEF score in the ESC myocardial revascularization guidelines (Class IIB) in 2010 [19] and the 2018 update was similarly done [17]. In previous studies, in-hospital mortality rate of NSTE-ACS was found to be approximately 4.9-5.2 % [20]. In our study, in-hospital mortality was 4.71 %, and this is very similar to in-hospital mortality data of the GRACE risk score and data from previous studies [2,21). Data on the predictive value of the ACEF score in patients presenting with NSTE-ACS are scarce. In an Acute Catheterization and Emergency Response Triage Strategy (ACUITY) study conducted in patients with NSTE-ACS, we retrospectively compared the existing 6 risk scores and analyzed the ACEF score as a subgroup, but as a result of the study, a very good distinction was not determined for the ACEF score [21]. In previous studies evaluating ACEF scores in various patient groups, ACEF was generally divided into three groups as low, medium and high. Unlike previous studies, it is a simpler classification to divide patients into two groups based on the cut-off value of 1.23 instead of three groups based on ACEF value and it may be more advantageous for this [21][22][23]. We also found that NSTE-ACS patients had very good predictive accuracy in ACEF score for in-hospital mortality (AUC 0.849). Therefore, our classification method could be a practical and simple solution for grouping these patients. In our study, it was determined that ACEF scores of patients before taking coronary angiography or PCI had strong accuracy in predicting in-hospital mortality (AUC 0.849). Determination of the ACEF score before coronary angiography or PCI may have eliminated possible effects on creatinine value and LVEF.
Similar to the data in previous studies, the proportion of patients with DM and previously CAD was higher in the high ACEF score group [7]. Also, in our study, a high ACEF score group was found to be associated with worse clinical markers, such as higher troponin value, lower hemoglobin value, higher leukocyte, lower platelet, etc. Therefore, the ACEF score accurately reflects the comorbidities that can be encountered in patients with NSTE-ACS by correctly including three variables.
Our study has some limitations. This study is a singlecenter retrospective study and may be small in number and needs further validation with multicenter and larger cohort studies. Multivariate analysis was done to adjust possible risk factors, but confounding factors may affect clinical outcomes. The ACEF score was calculated only when patients were hospitalized. Because we do not have long-term follow-up results, so we do not know the prognostic value of this score in the long-term follow-up.

Conclusions
The ACEF score could be considered as a simple, easy to calculate, highly useful risk classification tool for the initial assessment of patients with NSTE-ACS. Also, this score includes 3 independent variables such as age, creatine, and LVEF, and they are constantly variable. Besides, the ACEF score may provide a more objective assessment compared to other more complex risk scores, since it does not contain any categorical variable such as Killip classification or any variables that may include inter-observer variability in comments such as coronary angiography [13,24,25]. We found that the ACEF score correlates with the GRACE risk score and the ACEF score has a very strong ability to assess in-hospital mortality. We think that the ACEF score may be more useful in identifying high-risk patients very quickly and in referring patients to urgent or early invasive treatment, or in the detection and follow-up of patients who need close monitoring, especially in clinical practice, compared to other complex risk scores.

Funding
No funding was received for our study. Authors declared no financial support.

No conflict of interest is reported.
The article was received on 11/10/2020