Plasma CA125 Levels as a Predictor of Major Adverse Cardiac Events in Acute Coronary Syndrome Patients: A Six-Month Follow-Up Study 

Plasma CA125 Levels as a Predictor of Major Adverse Cardiac Events in Acute Coronary Syndrome Patients: A Six-Month Follow-Up Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Plasma CA125 Levels as a Predictor of Major Adverse Cardiac Events in Acute Coronary Syndrome Patients: A Six-Month Follow-Up Study Nazlı Dilek Çolak, Turgut Karabağ, Onuralp Çalışkan, Songül Tezcan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6196032/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives : Carbohydrate antigen 125 (CA125) is associated with different heart conditions. The study aims to determine CA125 levels in patients with ACS and the potential relationship between major adverse cardiac events (MACE) in a short-term following. Methods : This was a prospective and cross-sectional study conducted in the cardiology clinic between May and August 2022. Plasma CA125 levels were measured only once on hospital admission. Patients were followed for six months. The presence of MACE (cardiac death, recurrent ACS, need for revascularization, decompensated heart failure, hypertensive cardiogenic pulmonary edema) was recorded. Results : A total of 127 patients were included in the study. The mean left ventricular ejection fraction (LVEF) was 50.5%. The plasma CA125 median value was 14.6 KU/L. It was determined that there was a positive, significant relationship between CA125 value and hsTroponinT (r=0.315, p<0.001) and proBNP (r=0.423, p<0.001), and a negative relationship between LVEF (r=-0.186, p=0.037) value. Conclusions : It was found that plasma CA125 levels were correlated with ACS biomarkers (proBNP and hs-cTnT). Another interesting result was the correlation with the predictive value LVEF. Elevated plasma CA125 levels might be used to identify patients with ACS with a higher risk of MACE at 6 months. Acute coronary syndrome major cardiac adverse event carbohydrate antigen 125 biomarker cardiovascular diseases Figures Figure 1 What is already known on this topic Carbohydrate antigen 125 (CA125), a glycoprotein belonging to the mucin family, has been accepted as a diagnostic and prognostic marker in CVD. What this study adds – Significantly increased levels of CA125 (23.50 U/L), proBNP, and hsTroponinT were observed in patients who experienced major adverse cardiac events (MACE) during the 6-month follow-up. The study found that CA125 and proBNP levels were significantly higher in the MACE group. A statistically significant negative correlation was identified between CA125 levels and left ventricular ejection fraction (LVEF) in patients with acute coronary syndrome (ACS). How this study might affect research, practice or policy – ROC analyses demonstrated that CA125, hsTroponinT, LVEF, and proBNP are all statistically significant predictors of MACE, showing strong positive correlations among these biomarkers. 1. Introduction Biomarkers have been important in predicting cardiovascular (CV) risks in recent years. 1 – 3 Risk stratification of patients with CVD, especially ACS, in terms of short- and long-term adverse events and identifying high-risk patients is essential for optimal management. Since atherosclerosis is a multifactorial process, using several markers simultaneously can improve the performance of risk strategies. Obstructive and inflammation markers such as natriuretic peptides (NP) and high-sensitivity C reactive protein (hs-CRP) are prognostic markers. However, currently available biomarkers are imperfect, and their correct interpretation requires careful evaluation of the specific clinical scenario. 4 , 5 Carbohydrate antigen 125 (CA125), a glycoprotein belonging to the mucin family, has been accepted as a diagnostic and prognostic marker in CVD such as pericarditis, atrial fibrillation, heart failure and coronary artery disease (CAD), and various studies have emphasized the prognostic role of increased CA125 levels in different heart diseases. 5 – 7 Since mechanical stress and inflammation can induce CA125 synthesis from mesothelial cells of the peritoneum, pleura, and pericardium, it is a prognostic marker for mortality and rehospitalization in patients with heart failure. 4 In addition, a recent meta-analysis showed that high CA125 levels were also associated with hospital readmissions and all-cause mortality in patients presenting with acute heart failure, although none of the studies included in this meta-analysis evaluated ACS patients. 4 , 8 Exacerbation of the inflammatory process occurs, which leads to instability of coronary atherosclerotic plaques and can result in arterial thrombotic occlusion in ACS. 9 , 10 It is suggested that mechanical stress and inflammatory stimuli are transmitted to the cytoplasm, leading to a morphological and membrane stability change that activates CA125 release from mesothelial cells. 6 , 8 In this sense, congestion and inflammation occur with each other. Therefore, CA125 may be a marker for both. 6 The primary aim of this study is to investigate the potential relationship between CA125 levels and ACS. The second aim is to evaluate its prognostic role in predicting short-term outcomes in ACS patients. 2. Methods This prospective and cross-sectional study was out in the cardiology clinic of a training and research hospital in Istanbul (Turkey). Ethical approval for the study was received from the local ethics committee (Ethics approval NO:146/Date: 06.05.2022). A total of 127 patients over 18 years and diagnosed with ACS between 01.05.2022 and 01.08.2022 were included in the study. ACS was diagnosed according to the fourth universal definition and also shown angiographically [11]. The study did not involve individuals below the age of 18, as well as female patients who were pregnant or breastfeeding, individuals who did not provide written consent, and those who were unable to communicate due to cognitive impairment. Patients’ sociodemographic characteristics were recorded and plasma CA125 levels were measured only once on hospital admission. Patients were followed for six months. The presence of major adverse cardiac events (MACE) (including cardiac death, recurrent ACS, need for revascularization, decompensated heart failure, hypertensive cardiogenic pulmonary edema) in patients within 6 months was determined and the potential relationship between CA125 levels during hospitalization was evaluated. 4 , 7 , 12 The CA125 serum levels were determined using a commercial electrochemiluminescence immunoassay (ECLIA) kit (Roche® Diagnostics). The manufacturer’s cutoff point for CA125 is 35 KU/L. We did not use artificial intelligence (AI)– assisted technologies (such as Large Language Models [LLMs], chatbots, or image creators) in the production of submitted work. 2.1 Statistical analysis : Mean, standard deviation, median, lowest, highest, frequency and ratio values were used in the descriptive statistics of the data. The distribution of variables was measured with the Kolmogorov-Smirnov test. Independent samples t-test and Mann-Whitney u-test were used in the analysis of quantitative independent data. The chi-square test was used in the analysis of qualitative independent data, and the Fischer test was used when chi-square test conditions were not met. The effect level and cut-off value were investigated with the ROC curve. The effect level was investigated by univariate and multivariate logistic regression. SPSS 28.0 program was used in the analyses. A p -value of less than 0.05 was considered statically significant 3. Results The mean age of the participants was 61.09 ± 10.87 years and 78.7% of the patients were male. While 75.6% of patients were found to have at least one comorbid disease, the most common cardiovascular (CV) risk factor was found to be the family history of CVD (81.9%). After 6 months of follow-up, a total of 60 MACEs occurred in 33.9% of patients and 9 patients died. No statistically significant difference was detected in terms of systolic blood pressure and diastolic blood pressure according to the presence of MACE (p > 0.05). It was determined that there was a statistically significant difference in terms of age, number of comorbidities, number of CV risk factors, left ventricular ejection fraction (LVEF), CA125, high sensitivity Troponin T (hsTroponinT), and pro-brain natriuretic peptide (proBNP) according to the presence of MACE (p = 0.026, p < 0.001, p = 0.003, p = 0.004, p = 0.009, p = 0.014, p = 0.035, respectively). There was no statistically significant difference in the MACE according to type of ACS, hyperlipidemia (HL), obesity, diabetes mellitus (DM), smoking, alcohol use, family CVD history, and presence of stent (p > 0.05). It was determined that there was a statistically significant difference in the MACE according to gender, presence of comorbidity, and presence of hypertension (HT) (p = 0.007, p = 0.005, p = 0.001, respectively). The MACE was found to be higher in females, patients with comorbidities, and patients with HT. The clinical characteristics of the patients according to the presence of MACE are presented in Table 1 . Table 1 Clinical characteristics of patients according to the presence of MACE Presence of MACE Total (n = 127) No (n = 84) Yes (n = 43) a p Mean ± SD Mean ± SD Mean ± SD Age 61.09 ± 10.87 59.56 ± 11.29 64.09 ± 9.42 0.026* Number of comorbidities 2.66 ± 2.1 2.20 ± 2.00 3.56 ± 2.03 < 0.001* Total number of CV risk factors 3.6 ± 1.43 3.33 ± 1.47 4.12 ± 1.22 0.003* LVEF (%) 50.17 ± 10.84 52.12 ± 9.89 46.37 ± 11.69 0.004* Systolic BP 146.93 ± 24.19 146.65 ± 25.17 147.47 ± 22.43 0.859 Diastolic BP 80.99 ± 14.75 80.79 ± 14.69 81.40 ± 15.03 0.827 CA125 (KU/L) 14.59 ± 20.28 10.03 ± 6.33 23.50 ± 32.12 0.009* hsTroponinT (ng/L) 316.69 ± 766.58 155.36 ± 271.33 631.83 ± 1209.85 0.014* proBNP (ng/L) 2963.72 ± 6227.56 1927.72 ± 4048.78 4987.54 ± 8809.79 0.035* n (%) n (%) n (%) b p Gender 0.007* Female Male 27 (21.3) 12 (44.4) 15 (55.6) 100 (78.7) 72 (72) 28 (28) Comorbidity 96 (75.6) 57 (59.4) 39 (40.6) 0.005* Type of ACS 0.682 STEMI NSTEMI Unstable Angina 38 (29.9) 23 (60.5) 15 (39.5) 67 (52.8) 46 (68.7) 21 (31.3) 22 (17.3) 15 (68.2) 7 (31.8) CV risk factors H.T. H.L. Obesity DM smoking alcohol use 79 (62.2) 44 (55.7) 35 (44.3) 0.001* 78 (61.4) 50 (64.1) 28 (35.9) 0.54 32 (25.2) 19 (59.4) 13 (40.6) 0.35 42 (33.1) 23 (54.8) 19 (45.2) 0.057 95 (74.8) 59 (62.1) 36 (37.9) 0.098 28 (22) 19 (67.9) 9 (32.1) 0.828 Family history of CV disease 104 (81.9) 66 (63.5) 38 (36.5) 0.175 Presence of stent 76 (59.8) 54 (71.1) 22 (28.9) 0.153 MACE: major adverse cardiac event, CV: cardiovascular, LVEF: left ventricular ejection fraction, BP: blood pressure, CA125: carbohydrate antigen 125, hsTroponinT: high sensitivity troponin T, proBNP: pro brain natriuretic peptide, ACS: acute coronary syndrome, STEMI ST: segment elevation myocardial infarction, NSTEMI ST: myocardial infarction without segment elevation, HT: hypertension, HL: hyperlipidemia, DM: diabetes mellitus,* p < 0.05 statistically significant a : Independent groups t test b : Pearson chi-square test While the serum CA125 median value was 14.59±20.28 in all patients, it was 23.50±32.12 in the patients with MACE and was found to be significantly higher (p:0.009). No statistically significant relationship was found between CA125 value and age, number of comorbidities, number of CV risk factors, systolic blood pressure, and diastolic blood pressure (p>0.05). It was determined that there was a positive, statistically significant relationship between CA125 value and hsTroponinT (r=0.315, p<0.001) and proBNP (r=0.423, p<0.001), and a negative relationship between LVEF (r=-0.186, p=0.037) value. There was no statistically significant difference found in terms of CA125 value according to gender, number of comorbidities, type of ACS, HT, HL, obesity, DM, smoking, alcohol use, family history of CVD, and presence of stent (p>0.05). The clinical characteristics of the patients according to CA125 levels are presented in Table 2. Table 2 Clinical characteristics of patients according to CA125 levels. CA125 r p Age 0.118 0.185 Number of comorbidities 0.043 0.635 Total number of CV risk factors 0.085 0.344 LVEF (%) -0.186 0.037* Systolic BP -0.109 0.221 Diastolic BP -0.060 0.503 hsTroponinT (ng/L) 0.315 < 0.001* proBNP (ng/L) 0.423 < 0.001* Mean ± SD a p Gender 0.369 Female Male 19.67 ± 36.06 13.22 ± 13.14 Comorbidity 0.795 No Yes 15.42 ± 32.11 14.33 ± 14.81 Type of ACS d 0.401 STEMI NSTEMI Unstable Angina 17.70 ± 30.33 14.19 ± 15.49 10.44 ± 7.43 CV risk factor (HT) 0.671 No Yes 13.61 ± 26.04 15.19 ± 15.96 CV risk factor (HL) 0.413 No Yes 16.46 ± 27.24 13.42 ± 14.37 CV risk factor (Obesity) 0.455 No Yes 13.81 ± 15.21 16.92 ± 31.01 CV risk factor (DM) 0.821 No Yes 14.30 ± 21.18 15.18 ± 18.55 CV risk factor (Smoking) 0.131 No Yes 9.90 ± 5.83 16.17 ± 23.02 CV risk factor (Alcohol use) 0.569 No Yes 14.04 ± 19.97 16.53 ± 21.57 CV risk factor (Family history of CV disease) 0.606 No Yes 12.61 ± 9.18 15.03 ± 22.00 Presence of stent 0.963 No Yes 14.49 ± 14.91 14.66 ± 23.29 CV: cardiovascular, LVEF: left ventricular ejection fraction, BP: blood pressure, CA125: carbohydrate antigen 125, hsTroponinT: high sensitivity troponin T, proBNP: pro brain natriuretic peptide, ACS:acute coronary syndrome, STEMI ST:segment elevation myocardial infarction, NSTEMI non-ST-segment elevation myocardial infarction, HT: hypertension, HL: hyperlipidemia, DM: diabetes mellitus, * p < 0.05 statistically significant r: Pearson correlation coefficient a:Independent groups t test d:One-way analysis of variance It was found that there was no statistically significant relationship between the number of CV risk factors and CA125, hsTroponinT and proBNP (p>0.05). A statistically significant negative relationship was found between the number of CV risk factors and LVEF (r = -0.194, p = 0.029) value (Table 3). Table 3 Correlation of different biomarkers with the total number of cardiovascular risk factors. Total number of cardiovascular risk factors r p LVEF (%) -0.194 0.029* CA125 (KU/L) 0.085 0.344 hsTroponinT (ng/L) 0.106 0.235 proBNP (ng/L) 0.024 0.786 CV: cardiovascular, LVEF: left ventricular ejection fraction, CA125: carbohydrate antigen 125, hsTroponinT: high sensitivity troponin T, proBNP: pro brain natriuretic peptide, * p < 0.05 statistically significant r: Pearson correlation coefficient In the ROC analyzes performed to test the usability of CA125, hsTroponinT, LVEF and proBNP values in predicting the presence of MACE, the results obtained for all variables were found to be statistically significant (p<0.05). Optimal cut-off values for the variables and AUC, sensitivity, specificity, PPV, NPV values with 95% confidence intervals are presented in Table 4. ROC curves of the variables are presented in Figure 1. Table 4 AUC characteristics of different biomarkers AUC (95% CI) p Optimal cut-off Sensitivity (95% CI) Specificity (95% CI) PPV (95% CI) NPV (95% CI) CA125 0.756 (0.667, 0.845) 12.56 58.14 (42.1, 73.0) 84.52 (75.0, 91.5) 65.8 (48.6, 80.4) 79.8 (69.9, 87.6) hsTroponinT 0.674 (0.575, 0.774) 353.5 37.21 (23.0, 53.3) 89.29 (80.6, 95.0) 64 (42.5, 82.0) 73.5 (63.9, 81.8) LVEF 0.644 (0.544, 0.745) 0.005* ≤ 30 16.28 (6.8, 30.7) 97.62 (91.7, 99.7) 77.8 (40.0, 97.2) 69.5 (60.3, 77.6) proBNP 0.654 (0.551, 0.757) 0.003* > 4191 32.56 (19.1, 48.5) 89.29 (80.6, 95.0) 60.9 (38.5, 80.3) 72.1 (62.5, 80.5) AUC: area under the curve, 95% CI: confidence interval 95%, PPV: positive predictive value, NPV: negative predictive value, LVEF: left ventricular ejection fraction, CA125: carbohydrate antigen 125, hsTroponinT: high sensitivity troponin T, proBNP: pro brain natriuretic peptide, * p < 0.05 is statistically significant ROC curves of the variables were compared using the DeLong method. It was determined that the area related to CA125 was statistically significantly larger/higher than the area related to proBNP (p = 0.006). No statistically significant difference was detected between the areas under the ROC curves of other variables (p > 0.05). Multivariate logistic regression analysis was performed using the backward elimination method to determine the factors affecting MACE. In this context, age, gender, number of comorbidities, number of CV risk factors, CA125, hsTroponinT, proBNP variables were included in the model in the first stage. In the final stage, gender, number of CV risk factors, CA125 and hsTroponinT variables were included in the model, while age, number of comorbidities and proBNP variables were eliminated because they were not meaningful. It was determined that the resulting model was statistically significant and correctly identified the cases in 77.2% of cases [χ2 = 41.156, p < 0.001] (Table 5 ). Table 5 Factors affecting the presence of MACE. OR (95% CI) p Gender Female Male 3.958 (1.449, 10.807) 0.007* 1 Number of CV risk factors 1.452 (1.054, 2.001) 0.023* CA125 1.099 (1.033, 1.170) 0.003* hsTroponinT 1.001 (1.001, 1.003) 0.036* OR: odds ratio, 95% CI: confidence interval 95%, CV: cardiovascular, CA125: carbohydrate antigen 125, hsTroponinT: high sensitivity troponin T, * p < 0.05 statistically significant It was determined that the risk of MACE in females was 3.958 times that of males [OR (95% CI) = 3.958 (1.449, 10.807), p = 0.007]. It was determined that a 1-unit increase in the number of CV risk factors increased the risk of MACE by 1.452 times [OR (95% CI) = 1.452 (1.054, 2.001), p = 0.023]. It was determined that a 1-unit increase in CA125 value increased the risk of MACE by 1.452 times [OR (95% CI) = 1.099 (1.033, 1.170), p = 0.003]. It was determined that a 1-unit increase in hsTroponinT value increased the risk of MACE by 1.001 times [OR (95% CI) = 1.001 (1.001, 1.003), p = 0.036]. 4. Discussion CA125 is a glycoprotein associated with the mucin family, produced by mesothelial cells in the pericardium, pleura, peritoneum, and Müllerian epithelium, possibly as a response to mechanical (occlusion) or inflammatory stress. 6 CA125 has more recently been recognized as a diagnostic and prognostic marker in cardiovascular diseases such as pericarditis, atrial fibrillation, heart failure, and CAD. 5 – 10 Numerous studies have focused on investigating the prognostic role of elevated CA125 levels in various heart diseases. 5–7,12−23 Breakdown of CA125 reveals characteristics that make it a promising prognostic tool in ACS: it is readily available and more cost-effective compared to other biomarkers, and it is a stable molecule with a prolonged half-life (lasting longer than 1 week). This extended half-life enables its association with the clinical status and prognosis of the disease, enhancing its value in predicting patients at high risk of adverse outcomes. 7 In the existing literature, the standard measurement unit for CA125 levels is U/mL. However, for our study, the laboratory measured the levels in KU/L, which is equivalent to U/mL. Therefore, we have chosen to present our data using the U/mL unit in this section. Our study found that the average CA125 level in patients diagnosed with ACS was 12.56 U/mL. Previous studies have shown CA125 levels ranging from 12–24 U/mL in ACS patients [12,14,15]. Additionally, another research reported an average CA125 value of 13.85 U/mL in their investigation of the association between CA125 levels and mortality in female ACS patients. 18 In a study that assessed the predictive value of CA125 levels for PCI outcomes after ACS in male patients, the reported CA125 level in ACS patients was 7.99 U/mL. 7 Although our study found higher CA125 levels in female patients compared to male patients, this difference was not statistically significant (19.67 U/mL vs 13.22 U/mL). Falcao et al. 4 identified 11.48 IU/mL as the optimal CA125 cutoff value, while Luo et al. 18 reported it as 16.4 U/mL. In our study, we determined the threshold for MACE development to be 12.56 U/mL. Separham et al. 7 demonstrated that patients diagnosed with ACS who later developed MACE showed significantly elevated levels of CA125 and cardiac troponin I (CTnI) and a notably lower LVEF value. Their study also confirmed the role of CA125 level as an independent predictor for the onset of MACE, with an average CA125 level of 18.92 U/mL in patients who experienced MACE. In another study, Falcao et al. 4 reported an average CA125 value of 9.2 U/mL among patients with high mortality rates, emphasizing the strong statistical correlation between CA125 and mortality. Additionally, in our study, we observed significantly increased levels of CA125, proBNP, and hsTroponinT in the group that experienced MACE during the 6-month follow-up, with CA125 levels measured at 23.50 U/L in this cohort. These findings are aligned with existing literature, which also suggests that higher CA125 levels are prevalent in patients experiencing MACE. Falcao et al. 4 found HT (74.4%), smoking (45.4%), and DM (34.9%) to be significant risk factors for mortality in ACS patients. However, our study observed a different order of prevalence for these factors in MACE cases: HT (44.3%), DM (45.2%), and obesity (40.6%). In a recent study, it was found that CA125 showed similar ROC curves to NTproBNP and hs-CRP in predicting mortality among STEMI patients, suggesting that CA125 could be utilized either alongside or instead of NTproBNP or hs-CRP. 4 In our study, the ROC analyses conducted to assess the efficacy of CA125, hsTroponinT, LVEF, and proBNP values in predicting MACE showed that all variables yielded statistically significant results, and a significant positive correlation was observed among these biomarkers. Therefore, it is reasonable to propose that CA125 might have a role in the early risk evaluation of ACS patients, and its assessment in conjunction with BNP levels could assist in identifying patients diagnosed with ACS. Impaired left ventricular function often follows ACS and significantly increases the risk of mortality. This complication can develop asymptomatically in ACS patients and frequently leads to heart failure, resulting in subsequent hospital readmissions. Duman et al. 13 found elevated CA125 levels in patients with symptomatic advanced mitral stenosis, even when their LVEF and left ventricular dimensions were within normal range. This discovery may offer insights into the physiological factors triggering CA125 production in ACS patients who later develop heart failure. Yalta et al. 14 reported a substantial increase in CA125 levels and an inverse relationship between CA125 and LVEF in ACS patients with an LVEF below 55%. Likewise, Luo et al. 18 identified higher CA125 levels in ACS patients experiencing acute heart failure during hospitalization, with a weak negative correlation with LVEF values. In another study, Kouris et al. 24 found elevated CA125 levels in ACS patients with decompensated heart failure, particularly in those presenting with pulmonary congestion and peripheral edema. Our study also showed a statistically significant negative correlation between CA125 levels and LVEF values in ACS patients. These collective findings suggest that ACS patients with elevated CA125 levels may have an increased risk of heart failure-related hospitalizations, indicating that CA125 could serve as an independent prognostic indicator for this risk. De Gennaro et al. 15 measured CA125 and BNP levels in patients diagnosed with ACS within the first 24 hours and 72 hours after hospitalization and evaluated the patients' left ventricular functions and the incidence of acute heart failure during the hospital stay. It revealed that CA125 and BNP levels were significantly higher in patients diagnosed with ACS. In the same study, it was found that the CA125 levels of patients with clinical improvement decreased, while the CA125 levels of patients whose clinical condition did not improve despite drug treatment did not decrease or even increase. It has been stated that CA125 levels alone have higher specificity and sensitivity compared to BNP levels in predicting the incidence of acute heart failure. In our study, CA125 and proBNP levels were found to be significantly higher in the group that developed MACE, and CA125 was found to be significantly more powerful than proBNP in predicting the incidence of MACE. 4.1 Limitations : This study was a cross-sectional study conducted in a single center and consisted of a small number of patients. This may limit the adaptation of our results to all populations. Additionally, the biomarkers evaluated in the study were measured only with samples obtained during hospitalization, and these values may vary from symptom onset to time. For this reason, serial measurements will allow more precise prognostic data to be provided. Also, other factors that may allow patients to develop MACE in the post-discharge period (e.g., type of stent, access to treatment, and patient adherence) are not included in our analyses and cannot be ignored. Finally, the follow-up period of our study was limited to 6 months. Follow-up of patients for MACE for a longer time after discharge may also determine a more precise relationship with survival rates. Conclusions The results of our study showed that there is a potential association between increased CA125 levels in patients diagnosed with ACS and the risk of developing MACE at a 6-month follow-up after discharge. At the same time, it can be concluded that CA125 has a similar predictor value with other cardiac parameters (hsTroponinT, LVEF, proBNP) in terms of MACE development. As a result of our study, the factors affecting the presence of MACE are CA125 levels, female gender, number of CV risk factors, and hsTroponinT. Declarations Acknowledgment This study was presented as a poster at the 51st ESCP symposium on clinical pharmacy 31 October–02 November 2023, Aberdeen, Scotland. We want to thank all patients who participated in the study and the physicians in the department. Funding This research received no funding. Conflict of Interest The authors declare no conflict of interest. Authors' contributions N.D. Caliskan and S. Tezcan conceived and designed the research; N.D. Caliskan and O. Caliskan performed the research and acquired the data; N.D. Caliskan and S. Tezcan analyzed and interpreted the data; N.D. Caliskan and S. Tezcan wrote the paper. All authors were involved in drafting and revising the manuscript. References Benjamin EJ, Muntner P, Alonso A, et al. Heart disease and stroke statistics—2019 update: a report from the American Heart Association. Circulation. 2020;141. 10.1161/CIR.0000000000000746 . Lopez AD, Mathers CD, Ezzati M, et al. 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Role of plasma levels of CA-125 in predicting outcome of primary PCI after acute myocardial infarction in male patients. J Cardiovasc Thorac Res. 2018;10:109–12. 10.15171/jcvtr.2018.17 . Li X, He M, Zhu J, et al. Higher carbohydrate antigen 125 levels are associated with increased risk of coronary heart disease in elderly Chinese: a population-based case-control study. PLoS ONE. 2013;8. 10.1371/journal.pone.0081328 . Yuan D, Chu J, Qian J, et al. New concepts on the pathophysiology of acute coronary syndrome. Rev Cardiovasc Med. 2023;24:112. 10.31083/j.rcm2404112 . Theofilis P, Oikonomou E, Chasikidis C, et al. Pathophysiology of acute coronary syndromes—diagnostic and treatment considerations. Life. 2023;13:1543. 10.3390/life13071543 . Thygesen K, Alpert JS, Jaffe AS, et al. Fourth universal definition of myocardial infarction (2018). J Am Coll Cardiol. 2018;72:2231–64. 10.1016/j.jacc.2018.08.1038 . Rong X, Yunke Z, Guoping L, et al. Clinical and prognostic value of elevated CA125 levels in patients with coronary heart disease. Herz. 2015;40:690–4. 10.1007/s00059-014-4109-y . Duman C, Ercan E, Tengiz I, et al. Elevated serum CA 125 levels in mitral stenotic patients with heart failure. Cardiology. 2003;100:7–10. 10.1159/000072385 . Yalta K, Yilmaz A, Turgut OO, et al. Evaluation of tumor markers CA-125 and CEA in acute myocardial infarction. Adv Ther. 2006;23:1052–9. 10.1007/BF02850225 . De Gennaro L, Brunetti ND, Bungaro R, et al. Carbohydrate antigen-125: additional accuracy in identifying patients at risk of acute heart failure in acute coronary syndrome. Coron Artery Dis. 2009;20:274–80. 10.1097/MCA.0b013e3283229d82 . Xie YT, Dang Y, Zhang FF, et al. Combination of serum TIMP-3, CA125, and NT-proBNP in predicting ventricular remodeling in patients with heart failure following acute myocardial infarction. Cardiovasc Diagn Ther. 2020;10:1184–91. 10.21037/cdt-20-399 . Eggers KM, Lindhagen L, Baron T, et al. Predicting outcome in acute myocardial infarction: an analysis investigating 175 circulating biomarkers. Eur Heart J Acute Cardiovasc Care. 2022;11:88. 10.1093/ehjacc/zuaa014 . Luo Y, Cheng Y, Zhang X, et al. Prognostic value of CA125 serum levels in female patients with acute coronary syndrome. Res Square. 2021. 10.21203/rs.3.rs-395092/v1 . Li M, Wu Z, Tudahun I, et al. High serum carbohydrate antigen (CA) 125 level is associated with poor prognosis in patients with light-chain cardiac amyloidosis. Front Cardiovasc Med. 2021;8:692083. 10.3389/fcvm.2021.692083 . Hu X, Zhang J, Cao Y. Factors associated with serum CA125 level in women without ovarian cancer in the United States: a population-based study. BMC Cancer. 2022;22:544. 10.1186/s12885-022-09637-7 . Xu K, Wu M, Huang M, et al. Carbohydrate antigen 125 combined with N-terminal pro-B-type natriuretic peptide in the prediction of acute heart failure following ST-elevation myocardial infarction. Med (Baltim). 2022;101. 10.1097/MD.0000000000032129 . Wu B, Shi J, Yu F, et al. Association of cancer antigen 125 with long-term prognosis in light-chain cardiorenal amyloidosis. Cardiorenal Med. 2023;13:19–25. 10.1159/000527442 . Chua W, Cardoso VR, Guasch E, et al. An angiopoietin 2, FGF23, and BMP10 biomarker signature differentiates atrial fibrillation from other concomitant cardiovascular conditions. Sci Rep. 2023;13:16743. 10.1038/s41598-023-42331-7 . Kouris NT, Kontogianni DD, Papoulia EP, et al. Clinical and prognostic value of elevated CA125 levels in patients with congestive heart failure. Hellenic J Cardiol. 2006;47(5):269–74. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6196032","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":427772649,"identity":"214ee289-082d-4b6c-9448-daf2b1cd4c4c","order_by":0,"name":"Nazlı Dilek Çolak","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIiWNgGAWjYDCCw8wNjA0MDDJsDGxAXgVMmA2fFkawFh6IljNIWnhwaTkA1QJWxdhGhBa+44yND2fU2PHw8R9L/Fw4b5u8+YzcAwwfyg4z2EsfwKpF8jBjs+GGY8k8bBJph6VnbrttOOdGXgLjjHOHGXj4ErBqMTjM2Cb5sIEZqIW9QZp3223GGRI5Bsy8bUAtOFwG1NL+82FDPQ8b//Hm37xzbtuDtfzFr6WNcWPDYWCIpR2T5m24nQjWwohHC8gvkjOOHQf5Jc2a59jt5Bk8bwwO9pxL5+E5g10L3/nDBz/21FTLyfcfM77NU3PbdgZ7juGDH2XWcuw92LVgBwcY8MTkKBgFo2AUjALCAAD2nViGzJsGyQAAAABJRU5ErkJggg==","orcid":"","institution":"Marmara University","correspondingAuthor":true,"prefix":"","firstName":"Nazlı","middleName":"Dilek","lastName":"Çolak","suffix":""},{"id":427772650,"identity":"6a7188bc-b473-4603-b35a-07d3e9c0e91a","order_by":1,"name":"Turgut Karabağ","email":"","orcid":"","institution":"University of Health Sciences, Istanbul Education and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Turgut","middleName":"","lastName":"Karabağ","suffix":""},{"id":427772651,"identity":"441fe404-a64f-4c1f-acc4-fc149e5c0c9b","order_by":2,"name":"Onuralp Çalışkan","email":"","orcid":"","institution":"Istinye University","correspondingAuthor":false,"prefix":"","firstName":"Onuralp","middleName":"","lastName":"Çalışkan","suffix":""},{"id":427772652,"identity":"d991a389-f22b-4a13-ab0b-18e77860db6b","order_by":3,"name":"Songül Tezcan","email":"","orcid":"","institution":"Marmara University","correspondingAuthor":false,"prefix":"","firstName":"Songül","middleName":"","lastName":"Tezcan","suffix":""}],"badges":[],"createdAt":"2025-03-10 13:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6196032/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6196032/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78691351,"identity":"a794d331-8875-4211-9d05-e473e51ab86f","added_by":"auto","created_at":"2025-03-17 16:19:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":111974,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC curves comparing carbohydrate antigen 125 (CA125), high sensitivity troponin T (hsTroponinT), left ventricular ejection fraction (LVEF), and pro-brain natriuretic peptide (proBNP) biomarkers in predicting the rate of development of major adverse cardiac events at 6-month follow-up.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6196032/v1/fa44486fdcb4815b2c8f40e2.png"},{"id":80988970,"identity":"e0f130f4-cc4b-41db-915d-1fa78f3d82d7","added_by":"auto","created_at":"2025-04-21 02:16:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1868095,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6196032/v1/1922ee71-e177-456c-adf1-ee14d63a9c40.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Plasma CA125 Levels as a Predictor of Major Adverse Cardiac Events in Acute Coronary Syndrome Patients: A Six-Month Follow-Up Study ","fulltext":[{"header":"What is already known on this topic ","content":"\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003eCarbohydrate antigen 125 (CA125), a glycoprotein belonging to the mucin family, has been accepted as a diagnostic and prognostic marker in CVD.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eWhat this study adds\u003c/strong\u003e \u0026ndash;\u0026nbsp;\u003cul\u003e\n \u003cli\u003eSignificantly increased levels of CA125 (23.50 U/L), proBNP, and hsTroponinT were observed in patients who experienced major adverse cardiac events (MACE) during the 6-month follow-up.\u003c/li\u003e\n \u003cli\u003eThe study found that CA125 and proBNP levels were significantly higher in the MACE group.\u003c/li\u003e\n \u003cli\u003eA statistically significant negative correlation was identified between CA125 levels and left ventricular ejection fraction (LVEF) in patients with acute coronary syndrome (ACS).\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eHow this study might affect research, practice or policy\u003c/strong\u003e \u0026ndash;\u0026nbsp;\u003cul\u003e\n \u003cli\u003eROC analyses demonstrated that CA125, hsTroponinT, LVEF, and proBNP are all statistically significant predictors of MACE, showing strong positive correlations among these biomarkers.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eBiomarkers have been important in predicting cardiovascular (CV) risks in recent years.\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Risk stratification of patients with CVD, especially ACS, in terms of short- and long-term adverse events and identifying high-risk patients is essential for optimal management. Since atherosclerosis is a multifactorial process, using several markers simultaneously can improve the performance of risk strategies. Obstructive and inflammation markers such as natriuretic peptides (NP) and high-sensitivity C reactive protein (hs-CRP) are prognostic markers. However, currently available biomarkers are imperfect, and their correct interpretation requires careful evaluation of the specific clinical scenario.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eCarbohydrate antigen 125 (CA125), a glycoprotein belonging to the mucin family, has been accepted as a diagnostic and prognostic marker in CVD such as pericarditis, atrial fibrillation, heart failure and coronary artery disease (CAD), and various studies have emphasized the prognostic role of increased CA125 levels in different heart diseases.\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Since mechanical stress and inflammation can induce CA125 synthesis from mesothelial cells of the peritoneum, pleura, and pericardium, it is a prognostic marker for mortality and rehospitalization in patients with heart failure.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e In addition, a recent meta-analysis showed that high CA125 levels were also associated with hospital readmissions and all-cause mortality in patients presenting with acute heart failure, although none of the studies included in this meta-analysis evaluated ACS patients.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eExacerbation of the inflammatory process occurs, which leads to instability of coronary atherosclerotic plaques and can result in arterial thrombotic occlusion in ACS.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e It is suggested that mechanical stress and inflammatory stimuli are transmitted to the cytoplasm, leading to a morphological and membrane stability change that activates CA125 release from mesothelial cells.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e In this sense, congestion and inflammation occur with each other. Therefore, CA125 may be a marker for both.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e The primary aim of this study is to investigate the potential relationship between CA125 levels and ACS. The second aim is to evaluate its prognostic role in predicting short-term outcomes in ACS patients.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eThis prospective and cross-sectional study was out in the cardiology clinic of a training and research hospital in Istanbul (Turkey). Ethical approval for the study was received from the local ethics committee (Ethics approval NO:146/Date: 06.05.2022).\u003c/p\u003e \u003cp\u003eA total of 127 patients over 18 years and diagnosed with ACS between 01.05.2022 and 01.08.2022 were included in the study. ACS was diagnosed according to the fourth universal definition and also shown angiographically [11]. The study did not involve individuals below the age of 18, as well as female patients who were pregnant or breastfeeding, individuals who did not provide written consent, and those who were unable to communicate due to cognitive impairment.\u003c/p\u003e \u003cp\u003ePatients\u0026rsquo; sociodemographic characteristics were recorded and plasma CA125 levels were measured only once on hospital admission. Patients were followed for six months. The presence of major adverse cardiac events (MACE) (including cardiac death, recurrent ACS, need for revascularization, decompensated heart failure, hypertensive cardiogenic pulmonary edema) in patients within 6 months was determined and the potential relationship between CA125 levels during hospitalization was evaluated.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe CA125 serum levels were determined using a commercial electrochemiluminescence immunoassay (ECLIA) kit (Roche\u0026reg; Diagnostics). The manufacturer\u0026rsquo;s cutoff point for CA125 is 35 KU/L.\u003c/p\u003e \u003cp\u003eWe did not use artificial intelligence (AI)\u0026ndash; assisted technologies (such as Large Language Models [LLMs], chatbots, or image creators) in the production of submitted work.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.1 Statistical analysis\u003c/b\u003e: Mean, standard deviation, median, lowest, highest, frequency and ratio values were used in the descriptive statistics of the data. The distribution of variables was measured with the Kolmogorov-Smirnov test. Independent samples t-test and Mann-Whitney u-test were used in the analysis of quantitative independent data. The chi-square test was used in the analysis of qualitative independent data, and the Fischer test was used when chi-square test conditions were not met. The effect level and cut-off value were investigated with the ROC curve. The effect level was investigated by univariate and multivariate logistic regression. SPSS 28.0 program was used in the analyses. A \u003cem\u003ep\u003c/em\u003e-value of less than 0.05 was considered statically significant\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe mean age of the participants was 61.09\u0026thinsp;\u0026plusmn;\u0026thinsp;10.87 years and 78.7% of the patients were male. While 75.6% of patients were found to have at least one comorbid disease, the most common cardiovascular (CV) risk factor was found to be the family history of CVD (81.9%). After 6 months of follow-up, a total of 60 MACEs occurred in 33.9% of patients and 9 patients died. No statistically significant difference was detected in terms of systolic blood pressure and diastolic blood pressure according to the presence of MACE (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eIt was determined that there was a statistically significant difference in terms of age, number of comorbidities, number of CV risk factors, left ventricular ejection fraction (LVEF), CA125, high sensitivity Troponin T (hsTroponinT), and pro-brain natriuretic peptide (proBNP) according to the presence of MACE (p\u0026thinsp;=\u0026thinsp;0.026, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, p\u0026thinsp;=\u0026thinsp;0.003, p\u0026thinsp;=\u0026thinsp;0.004, p\u0026thinsp;=\u0026thinsp;0.009, p\u0026thinsp;=\u0026thinsp;0.014, p\u0026thinsp;=\u0026thinsp;0.035, respectively). There was no statistically significant difference in the MACE according to type of ACS, hyperlipidemia (HL), obesity, diabetes mellitus (DM), smoking, alcohol use, family CVD history, and presence of stent (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). It was determined that there was a statistically significant difference in the MACE according to gender, presence of comorbidity, and presence of hypertension (HT) (p\u0026thinsp;=\u0026thinsp;0.007, p\u0026thinsp;=\u0026thinsp;0.005, p\u0026thinsp;=\u0026thinsp;0.001, respectively). The MACE was found to be higher in females, patients with comorbidities, and patients with HT. The clinical characteristics of the patients according to the presence of MACE are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eClinical characteristics of patients according to the presence of MACE\u003c/b\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ePresence of MACE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;127)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo (n\u0026thinsp;=\u0026thinsp;84)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes (n\u0026thinsp;=\u0026thinsp;43)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.09\u0026thinsp;\u0026plusmn;\u0026thinsp;10.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.56\u0026thinsp;\u0026plusmn;\u0026thinsp;11.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.09\u0026thinsp;\u0026plusmn;\u0026thinsp;9.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.026*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of comorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.20\u0026thinsp;\u0026plusmn;\u0026thinsp;2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number of CV risk factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.003*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.17\u0026thinsp;\u0026plusmn;\u0026thinsp;10.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.12\u0026thinsp;\u0026plusmn;\u0026thinsp;9.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.37\u0026thinsp;\u0026plusmn;\u0026thinsp;11.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.004*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146.93\u0026thinsp;\u0026plusmn;\u0026thinsp;24.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e146.65\u0026thinsp;\u0026plusmn;\u0026thinsp;25.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e147.47\u0026thinsp;\u0026plusmn;\u0026thinsp;22.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.859\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiastolic BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.99\u0026thinsp;\u0026plusmn;\u0026thinsp;14.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.79\u0026thinsp;\u0026plusmn;\u0026thinsp;14.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.40\u0026thinsp;\u0026plusmn;\u0026thinsp;15.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.827\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA125 (KU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.59\u0026thinsp;\u0026plusmn;\u0026thinsp;20.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.03\u0026thinsp;\u0026plusmn;\u0026thinsp;6.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.50\u0026thinsp;\u0026plusmn;\u0026thinsp;32.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.009*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehsTroponinT (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e316.69\u0026thinsp;\u0026plusmn;\u0026thinsp;766.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155.36\u0026thinsp;\u0026plusmn;\u0026thinsp;271.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e631.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1209.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.014*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eproBNP (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2963.72\u0026thinsp;\u0026plusmn;\u0026thinsp;6227.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1927.72\u0026thinsp;\u0026plusmn;\u0026thinsp;4048.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4987.54\u0026thinsp;\u0026plusmn;\u0026thinsp;8809.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.035*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.007*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (78.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96 (75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (59.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of ACS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.682\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSTEMI\u003c/p\u003e \u003cp\u003eNSTEMI\u003c/p\u003e \u003cp\u003eUnstable Angina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (60.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (39.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (52.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (68.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (68.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCV risk factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eH.T.\u003c/p\u003e \u003cp\u003eH.L.\u003c/p\u003e \u003cp\u003eObesity\u003c/p\u003e \u003cp\u003eDM\u003c/p\u003e \u003cp\u003esmoking\u003c/p\u003e \u003cp\u003ealcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 (62.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (55.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35 (44.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 (61.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (64.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.54\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (59.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.057\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (74.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (62.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.098\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (67.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.828\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history of CV disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104 (81.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (63.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (36.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.175\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresence of stent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (59.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (71.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.153\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMACE: major adverse cardiac event, CV: cardiovascular, LVEF: left ventricular ejection fraction, BP: blood pressure, CA125: carbohydrate antigen 125, hsTroponinT: high sensitivity troponin T, proBNP: pro brain natriuretic peptide, ACS: acute coronary syndrome, STEMI ST: segment elevation myocardial infarction, NSTEMI ST: myocardial infarction without segment elevation, HT: hypertension, HL: hyperlipidemia, DM: diabetes mellitus,* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 statistically significant\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e: \u003cb\u003eIndependent groups t test\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e: \u003cb\u003ePearson chi-square test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhile the serum CA125 median value was 14.59\u0026plusmn;20.28 in all patients, it was 23.50\u0026plusmn;32.12 in the patients with MACE and was found to be significantly higher (p:0.009). No statistically significant relationship was found between CA125 value and age, number of comorbidities, number of CV risk factors, systolic blood pressure, and diastolic blood pressure (p\u0026gt;0.05). It was determined that there was a positive, statistically significant relationship between CA125 value and hsTroponinT (r=0.315, p\u0026lt;0.001) and proBNP (r=0.423, p\u0026lt;0.001), and a negative relationship between LVEF (r=-0.186, p=0.037) value. There was no statistically significant difference found in terms of CA125 value according to gender, number of comorbidities, type of ACS, HT, HL, obesity, DM, smoking, alcohol use, family history of CVD, and presence of stent (p\u0026gt;0.05). The clinical characteristics of the patients according to CA125 levels are presented in Table 2.\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eClinical characteristics of patients according to CA125 levels.\u003c/b\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCA125\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.185\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of comorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.635\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number of CV risk factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.344\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.037*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.221\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiastolic BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.503\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehsTroponinT (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eproBNP (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.369\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.67\u0026thinsp;\u0026plusmn;\u0026thinsp;36.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.22\u0026thinsp;\u0026plusmn;\u0026thinsp;13.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.795\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.42\u0026thinsp;\u0026plusmn;\u0026thinsp;32.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.33\u0026thinsp;\u0026plusmn;\u0026thinsp;14.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of ACS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003csup\u003e\u003cb\u003ed\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e0.401\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSTEMI\u003c/p\u003e \u003cp\u003eNSTEMI\u003c/p\u003e \u003cp\u003eUnstable Angina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.70\u0026thinsp;\u0026plusmn;\u0026thinsp;30.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.19\u0026thinsp;\u0026plusmn;\u0026thinsp;15.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.44\u0026thinsp;\u0026plusmn;\u0026thinsp;7.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCV risk factor (HT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.671\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.61\u0026thinsp;\u0026plusmn;\u0026thinsp;26.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.19\u0026thinsp;\u0026plusmn;\u0026thinsp;15.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCV risk factor (HL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.413\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.46\u0026thinsp;\u0026plusmn;\u0026thinsp;27.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.42\u0026thinsp;\u0026plusmn;\u0026thinsp;14.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCV risk factor (Obesity)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.455\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.81\u0026thinsp;\u0026plusmn;\u0026thinsp;15.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.92\u0026thinsp;\u0026plusmn;\u0026thinsp;31.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCV risk factor (DM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.821\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.30\u0026thinsp;\u0026plusmn;\u0026thinsp;21.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.18\u0026thinsp;\u0026plusmn;\u0026thinsp;18.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCV risk factor (Smoking)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.131\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.90\u0026thinsp;\u0026plusmn;\u0026thinsp;5.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.17\u0026thinsp;\u0026plusmn;\u0026thinsp;23.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCV risk factor (Alcohol use)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.569\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.04\u0026thinsp;\u0026plusmn;\u0026thinsp;19.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.53\u0026thinsp;\u0026plusmn;\u0026thinsp;21.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCV risk factor (Family history of CV disease)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.606\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.61\u0026thinsp;\u0026plusmn;\u0026thinsp;9.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.03\u0026thinsp;\u0026plusmn;\u0026thinsp;22.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresence of stent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.963\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.49\u0026thinsp;\u0026plusmn;\u0026thinsp;14.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.66\u0026thinsp;\u0026plusmn;\u0026thinsp;23.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCV: cardiovascular, LVEF: left ventricular ejection fraction, BP: blood pressure, CA125: carbohydrate antigen 125, hsTroponinT: high sensitivity troponin T, proBNP: pro brain natriuretic peptide, ACS:acute coronary syndrome, STEMI ST:segment elevation myocardial infarction, NSTEMI non-ST-segment elevation myocardial infarction, HT: hypertension, HL: hyperlipidemia, DM: diabetes mellitus, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 statistically significant\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003er: Pearson correlation coefficient\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ea:Independent groups t test\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ed:One-way analysis of variance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \n\u003cp\u003eIt was found that there was no statistically significant relationship between the number of CV risk factors and CA125, hsTroponinT and proBNP (p\u0026gt;0.05). A statistically significant negative relationship was found between the number of CV risk factors and LVEF (r = -0.194, p = 0.029) value (Table 3).\u003c/p\u003e\n\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eCorrelation of different biomarkers with the total number of cardiovascular risk factors.\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTotal number of cardiovascular risk factors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.029*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA125 (KU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.344\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehsTroponinT (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.235\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eproBNP (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.786\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCV: cardiovascular, LVEF: left ventricular ejection fraction, CA125: carbohydrate antigen 125, hsTroponinT: high sensitivity troponin T, proBNP: pro brain natriuretic peptide, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 statistically significant\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003er: Pearson correlation coefficient\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \n\u003cp\u003eIn the ROC analyzes performed to test the usability of CA125, hsTroponinT, LVEF and proBNP values in predicting the presence of MACE, the results obtained for all variables were found to be statistically significant (p\u0026lt;0.05). Optimal cut-off values for the variables and AUC, sensitivity, specificity, PPV, NPV values with 95% confidence intervals are presented in Table 4. ROC curves of the variables are presented in Figure 1.\u003c/p\u003e\n\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAUC characteristics of different biomarkers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOptimal cut-off\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpecificity (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePPV (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNPV (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.756 (0.667, 0.845)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.14 (42.1, 73.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84.52 (75.0, 91.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65.8 (48.6, 80.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e79.8 (69.9, 87.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehsTroponinT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.674 (0.575, 0.774)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;353.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.21 (23.0, 53.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e89.29 (80.6, 95.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64 (42.5, 82.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e73.5 (63.9, 81.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.644 (0.544, 0.745)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.005*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.28 (6.8, 30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.62 (91.7, 99.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e77.8 (40.0, 97.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e69.5 (60.3, 77.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eproBNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.654 (0.551, 0.757)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.003*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;4191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.56 (19.1, 48.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e89.29 (80.6, 95.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.9 (38.5, 80.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e72.1 (62.5, 80.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAUC: area under the curve, 95% CI: confidence interval 95%, PPV: positive predictive value, NPV: negative predictive value, LVEF: left ventricular ejection fraction, CA125: carbohydrate antigen 125, hsTroponinT: high sensitivity troponin T, proBNP: pro brain natriuretic peptide, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 is statistically significant\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eROC curves of the variables were compared using the DeLong method. It was determined that the area related to CA125 was statistically significantly larger/higher than the area related to proBNP (p\u0026thinsp;=\u0026thinsp;0.006). No statistically significant difference was detected between the areas under the ROC curves of other variables (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eMultivariate logistic regression analysis was performed using the backward elimination method to determine the factors affecting MACE. In this context, age, gender, number of comorbidities, number of CV risk factors, CA125, hsTroponinT, proBNP variables were included in the model in the first stage. In the final stage, gender, number of CV risk factors, CA125 and hsTroponinT variables were included in the model, while age, number of comorbidities and proBNP variables were eliminated because they were not meaningful. It was determined that the resulting model was statistically significant and correctly identified the cases in 77.2% of cases [χ2\u0026thinsp;=\u0026thinsp;41.156, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001] (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors affecting the presence of MACE.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.958 (1.449, 10.807)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of CV risk factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.452 (1.054, 2.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.023*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.099 (1.033, 1.170)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehsTroponinT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.001 (1.001, 1.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.036*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOR: odds ratio, 95% CI: confidence interval 95%, CV: cardiovascular, CA125: carbohydrate antigen 125, hsTroponinT: high sensitivity troponin T, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 statistically significant\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIt was determined that the risk of MACE in females was 3.958 times that of males [OR (95% CI)\u0026thinsp;=\u0026thinsp;3.958 (1.449, 10.807), p\u0026thinsp;=\u0026thinsp;0.007]. It was determined that a 1-unit increase in the number of CV risk factors increased the risk of MACE by 1.452 times [OR (95% CI)\u0026thinsp;=\u0026thinsp;1.452 (1.054, 2.001), p\u0026thinsp;=\u0026thinsp;0.023]. It was determined that a 1-unit increase in CA125 value increased the risk of MACE by 1.452 times [OR (95% CI)\u0026thinsp;=\u0026thinsp;1.099 (1.033, 1.170), p\u0026thinsp;=\u0026thinsp;0.003]. It was determined that a 1-unit increase in hsTroponinT value increased the risk of MACE by 1.001 times [OR (95% CI)\u0026thinsp;=\u0026thinsp;1.001 (1.001, 1.003), p\u0026thinsp;=\u0026thinsp;0.036].\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eCA125 is a glycoprotein associated with the mucin family, produced by mesothelial cells in the pericardium, pleura, peritoneum, and M\u0026uuml;llerian epithelium, possibly as a response to mechanical (occlusion) or inflammatory stress.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e CA125 has more recently been recognized as a diagnostic and prognostic marker in cardiovascular diseases such as pericarditis, atrial fibrillation, heart failure, and CAD.\u003csup\u003e\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Numerous studies have focused on investigating the prognostic role of elevated CA125 levels in various heart diseases.\u003csup\u003e5\u0026ndash;7,12\u0026minus;23\u003c/sup\u003e Breakdown of CA125 reveals characteristics that make it a promising prognostic tool in ACS: it is readily available and more cost-effective compared to other biomarkers, and it is a stable molecule with a prolonged half-life (lasting longer than 1 week). This extended half-life enables its association with the clinical status and prognosis of the disease, enhancing its value in predicting patients at high risk of adverse outcomes.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn the existing literature, the standard measurement unit for CA125 levels is U/mL. However, for our study, the laboratory measured the levels in KU/L, which is equivalent to U/mL. Therefore, we have chosen to present our data using the U/mL unit in this section. Our study found that the average CA125 level in patients diagnosed with ACS was 12.56 U/mL. Previous studies have shown CA125 levels ranging from 12\u0026ndash;24 U/mL in ACS patients [12,14,15]. Additionally, another research reported an average CA125 value of 13.85 U/mL in their investigation of the association between CA125 levels and mortality in female ACS patients.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e In a study that assessed the predictive value of CA125 levels for PCI outcomes after ACS in male patients, the reported CA125 level in ACS patients was 7.99 U/mL.\u003csup\u003e7\u003c/sup\u003e Although our study found higher CA125 levels in female patients compared to male patients, this difference was not statistically significant (19.67 U/mL vs 13.22 U/mL).\u003c/p\u003e \u003cp\u003eFalcao et al.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e identified 11.48 IU/mL as the optimal CA125 cutoff value, while Luo et al.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e reported it as 16.4 U/mL. In our study, we determined the threshold for MACE development to be 12.56 U/mL.\u003c/p\u003e \u003cp\u003eSeparham et al.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e demonstrated that patients diagnosed with ACS who later developed MACE showed significantly elevated levels of CA125 and cardiac troponin I (CTnI) and a notably lower LVEF value. Their study also confirmed the role of CA125 level as an independent predictor for the onset of MACE, with an average CA125 level of 18.92 U/mL in patients who experienced MACE. In another study, Falcao et al.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e reported an average CA125 value of 9.2 U/mL among patients with high mortality rates, emphasizing the strong statistical correlation between CA125 and mortality. Additionally, in our study, we observed significantly increased levels of CA125, proBNP, and hsTroponinT in the group that experienced MACE during the 6-month follow-up, with CA125 levels measured at 23.50 U/L in this cohort. These findings are aligned with existing literature, which also suggests that higher CA125 levels are prevalent in patients experiencing MACE.\u003c/p\u003e \u003cp\u003eFalcao et al.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e found HT (74.4%), smoking (45.4%), and DM (34.9%) to be significant risk factors for mortality in ACS patients. However, our study observed a different order of prevalence for these factors in MACE cases: HT (44.3%), DM (45.2%), and obesity (40.6%).\u003c/p\u003e \u003cp\u003eIn a recent study, it was found that CA125 showed similar ROC curves to NTproBNP and hs-CRP in predicting mortality among STEMI patients, suggesting that CA125 could be utilized either alongside or instead of NTproBNP or hs-CRP.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e In our study, the ROC analyses conducted to assess the efficacy of CA125, hsTroponinT, LVEF, and proBNP values in predicting MACE showed that all variables yielded statistically significant results, and a significant positive correlation was observed among these biomarkers. Therefore, it is reasonable to propose that CA125 might have a role in the early risk evaluation of ACS patients, and its assessment in conjunction with BNP levels could assist in identifying patients diagnosed with ACS.\u003c/p\u003e \u003cp\u003eImpaired left ventricular function often follows ACS and significantly increases the risk of mortality. This complication can develop asymptomatically in ACS patients and frequently leads to heart failure, resulting in subsequent hospital readmissions. Duman et al.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e found elevated CA125 levels in patients with symptomatic advanced mitral stenosis, even when their LVEF and left ventricular dimensions were within normal range. This discovery may offer insights into the physiological factors triggering CA125 production in ACS patients who later develop heart failure. Yalta et al.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e reported a substantial increase in CA125 levels and an inverse relationship between CA125 and LVEF in ACS patients with an LVEF below 55%. Likewise, Luo et al.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e identified higher CA125 levels in ACS patients experiencing acute heart failure during hospitalization, with a weak negative correlation with LVEF values. In another study, Kouris et al.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e found elevated CA125 levels in ACS patients with decompensated heart failure, particularly in those presenting with pulmonary congestion and peripheral edema. Our study also showed a statistically significant negative correlation between CA125 levels and LVEF values in ACS patients. These collective findings suggest that ACS patients with elevated CA125 levels may have an increased risk of heart failure-related hospitalizations, indicating that CA125 could serve as an independent prognostic indicator for this risk.\u003c/p\u003e \u003cp\u003eDe Gennaro et al.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e measured CA125 and BNP levels in patients diagnosed with ACS within the first 24 hours and 72 hours after hospitalization and evaluated the patients' left ventricular functions and the incidence of acute heart failure during the hospital stay. It revealed that CA125 and BNP levels were significantly higher in patients diagnosed with ACS. In the same study, it was found that the CA125 levels of patients with clinical improvement decreased, while the CA125 levels of patients whose clinical condition did not improve despite drug treatment did not decrease or even increase. It has been stated that CA125 levels alone have higher specificity and sensitivity compared to BNP levels in predicting the incidence of acute heart failure. In our study, CA125 and proBNP levels were found to be significantly higher in the group that developed MACE, and CA125 was found to be significantly more powerful than proBNP in predicting the incidence of MACE.\u003c/p\u003e\u003cp\u003e \u003cb\u003e4.1 Limitations\u003c/b\u003e: This study was a cross-sectional study conducted in a single center and consisted of a small number of patients. This may limit the adaptation of our results to all populations. Additionally, the biomarkers evaluated in the study were measured only with samples obtained during hospitalization, and these values may vary from symptom onset to time. For this reason, serial measurements will allow more precise prognostic data to be provided. Also, other factors that may allow patients to develop MACE in the post-discharge period (e.g., type of stent, access to treatment, and patient adherence) are not included in our analyses and cannot be ignored. Finally, the follow-up period of our study was limited to 6 months. Follow-up of patients for MACE for a longer time after discharge may also determine a more precise relationship with survival rates.\u003c/p\u003e "},{"header":"Conclusions","content":"\u003cp\u003eThe results of our study showed that there is a potential association between increased CA125 levels in patients diagnosed with ACS and the risk of developing MACE at a 6-month follow-up after discharge. At the same time, it can be concluded that CA125 has a similar predictor value with other cardiac parameters (hsTroponinT, LVEF, proBNP) in terms of MACE development. As a result of our study, the factors affecting the presence of MACE are CA125 levels, female gender, number of CV risk factors, and hsTroponinT.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was presented as a poster at the 51st ESCP symposium on clinical pharmacy 31 October–02 November 2023, Aberdeen, Scotland.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe want to thank all patients who participated in the study and the physicians in the department.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN.D. Caliskan and S. 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Hellenic J Cardiol. 2006;47(5):269\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acute coronary syndrome, major cardiac adverse event, carbohydrate antigen 125, biomarker, cardiovascular diseases","lastPublishedDoi":"10.21203/rs.3.rs-6196032/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6196032/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e: Carbohydrate antigen 125 (CA125) is associated with different heart conditions. \u0026nbsp;The study aims to determine CA125 levels in patients with ACS and the potential relationship between major adverse cardiac events (MACE) in a short-term following.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This was a prospective and cross-sectional study conducted in the cardiology clinic between May and August 2022. Plasma CA125 levels were measured only once on hospital admission. Patients were followed for six months. The presence of MACE (cardiac death, recurrent ACS, need for revascularization, decompensated heart failure, hypertensive cardiogenic pulmonary edema) was recorded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: A total of 127 patients were included in the study. The mean left ventricular ejection fraction (LVEF) was 50.5%. The plasma CA125 median value was 14.6 KU/L. It was determined that there was a positive, significant relationship between CA125 value and hsTroponinT (r=0.315, p\u0026lt;0.001) and proBNP (r=0.423, p\u0026lt;0.001), and a negative relationship between LVEF (r=-0.186, p=0.037) value.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: It was found that plasma CA125 levels were correlated with ACS biomarkers (proBNP and hs-cTnT). Another interesting result was the correlation with the predictive value LVEF. Elevated plasma CA125 levels might be used to identify patients with ACS with a higher risk of MACE at 6 months.\u003c/p\u003e","manuscriptTitle":"Plasma CA125 Levels as a Predictor of Major Adverse Cardiac Events in Acute Coronary Syndrome Patients: A Six-Month Follow-Up Study ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-17 16:18:59","doi":"10.21203/rs.3.rs-6196032/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7e095cdc-5425-4047-bd56-6186f40e1082","owner":[],"postedDate":"March 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-04T13:53:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-17 16:18:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6196032","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6196032","identity":"rs-6196032","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}