Effect of Ticagrelor or Clopidogrel Treatment on 1-Year Cardiovascular Outcomes in Anemic Patients with Acute Coronary Syndrome

Effect of Ticagrelor or Clopidogrel Treatment on 1-Year Cardiovascular Outcomes in Anemic Patients with Acute Coronary Syndrome | 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 Effect of Ticagrelor or Clopidogrel Treatment on 1-Year Cardiovascular Outcomes in Anemic Patients with Acute Coronary Syndrome Tolga Onuk, Fuat Polat, Barış Yaylak, Şükrü Akyüz, Zeynep Kolak, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3397394/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 Objective This study aimed to investigate the potential impact of ticagrelor and clopidogrel treatment on cardiovascular outcomes in patients with anemia and acute coronary syndrome (ACS), and to discern the optimal therapeutic approach for this vulnerable patient population. Methods A retrospective research design was employed, involving patients diagnosed with ST-segment elevation myocardial infarction (STEMI) or non-ST-segment elevation myocardial infarction (NSTEMI) between 2014 and 2021. Inclusion criteria necessitated a hemoglobin level below 12 mg/dL and a minimum 12-month P2Y12 inhibitor treatment. Comprehensive clinical, biochemical, and echocardiographic data were collected from the hospital's electronic repository. The primary efficacy endpoint was major adverse cardiovascular events (MACE), encompassing total mortality, cardiovascular mortality, reinfarction, ischemic stroke, and hemorrhagic stroke. Major hemorrhage was the primary safety endpoint. Secondary outcomes included total mortality, CV mortality, reinfarction, ischemic stroke, and hemorrhagic stroke. Results Patients treated with ticagrelor (n = 118) and clopidogrel (n = 538) were compared. No significant difference was observed in major adverse cardiovascular events (MACE) and major bleeding between ticagrelor and clopidogrel treatment groups (MACE: clopidogrel 10.0% vs. ticagrelor 11.0%, p=0.75; major bleeding: clopidogrel 2.8%, ticagrelor 2.5%, p=0.88). Patients with hemoglobin levels ≤8 mg/dL demonstrated significantly higher MACE and major bleeding rates in the ticagrelor group (p=0.008 and p=0.002, respectively). Among patients aged ≥75 years, ticagrelor treatment was associated with a higher risk of major bleeding (p=0.04). Conclusion Ticagrelor and clopidogrel demonstrated similar efficacy and safety outcomes in anemic ACS patients over a one-year period. Ticagrelor showed superiority in reducing ischemic events in anemic ACS patients. However, specific caution is warranted in patients with hemoglobin ≤8 mg/dL and those aged ≥75 years, where ticagrelor treatment may confer a higher risk of adverse events. This study provides insights into tailoring antiplatelet therapy for anemic ACS patients and offers guidance for personalized treatment strategies. Ticagrelor clopidogrel anemia acute coronary syndrome Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION The investigation into the potential impact of ticagrelor and clopidogrel treatments on cardiovascular outcomes among patients dealing with acute coronary syndrome (ACS) and anemia assumes significant importance within the cardiology domain. Anemia, prevalent in the context of ACS, is recognized for its association with heightened susceptibility to cardiovascular events ( 1 , 2 ). Notably, the PLATelet inhibition and patient Outcomes (PLATO) study highlighted the potential benefits of ticagrelor therapy in mitigating cardiovascular mortality, myocardial infarction, or stroke, particularly within the subset of patients affected by ACS ( 3 ). This favorable therapeutic effect of ticagrelor is attributed to its superior and more consistent suppression of platelet activity compared to clopidogrel. However, the robust platelet inhibition characteristic of ticagrelor raises concerns about its appropriateness for anemic patients, as it might amplify the risk of significant cardiovascular adverse events, especially bleeding incidents. In light of this, a comprehensive evaluation of the cardiovascular outcomes associated with both ticagrelor and clopidogrel in patients afflicted with anemic ACS is crucial to discern the optimal therapeutic approach. Recent analyses have sought to delve into the potential influence of ticagrelor treatment on cardiovascular outcomes in patients diagnosed with anemic ACS. Notably, in ACS patients treated with ticagrelor and acetylsalicylic acid, lower hemoglobin levels have been linked to a heightened occurrence of major ischemic events, although no impact on survival was observed ( 4 ). Moreover, in patients at elevated ischemic risk, ticagrelor demonstrates a reduction in the incidence of ischemic events without exacerbating major bleeding when compared with clopidogrel. However, among patients with a lower ischemic risk but a higher tendency for bleeding, ticagrelor was associated with an increased likelihood of adverse events ( 5 , 6 ). Furthermore, Charpentier et al. observed a greater frequency of bleeding events with clopidogrel than with ticagrelor during intensive care unit follow-ups among ACS patients ( 7 ). Notably, individuals at heightened bleeding risk demonstrated augmented cardiovascular events and bleeding incidents associated with ticagrelor administration. Within this context, there arises a need to compare the effects of less potent P2Y12 inhibitors with that of ticagrelor specifically in anemic patients. It is crucial to subject the comparative effects of clopidogrel and ticagrelor to meticulous scrutiny, encompassing parameters such as overall mortality, cardiovascular mortality, reinfarction, ischemic stroke, hemorrhagic stroke, and major hemorrhage within this unique patient cohort. Additionally, there remains a dearth of literature investigating the relative efficacy and safety profiles of these agents in subgroups stratified by the severity of anemia, as well as in elderly anemic patients who inherently present a more vulnerable demographic ( 8 ). Consequently, this study has been meticulously devised to address these critical inquiries and contribute to a more comprehensive understanding of the optimal therapeutic strategy in this context. METHODS This study employed a retrospective research design to elucidate the effects of treatments involving ticagrelor and clopidogrel on cardiovascular outcomes over a one-year period in patients with anemia experiencing acute coronary syndrome. Between the years 2014 and 2021, individuals diagnosed with either ST-segment elevation myocardial infarction (STEMI) or non-ST-segment elevation myocardial infarction (NSTEMI) were subject to rigorous screening procedures. All enrolled patients underwent coronary angiography, and subsequent medical interventions such as medical therapy, coronary artery bypass grafting, or percutaneous coronary intervention with angioplasty and stent placement were administered as deemed appropriate based on the coronary angiography findings. Inclusion criteria for participation mandated subjects to be at least 18 years of age, undergo pre-coronary angiography blood sampling including hemogram assessment, exhibit a hemoglobin level below 12 mg/dL in the collected sample, and opt for P2Y12 inhibitor treatment for a minimum duration of 12 months. Exclusion criteria encompassed the identification of critical stenosis affecting the left main coronary artery, the presence of concomitant comorbidities such as atrial fibrillation necessitating anticoagulation therapy, alteration between P2Y12 inhibitors within a 12-month period, or premature discontinuation of the designated treatment regimen. Data derived from a comprehensive cohort of 656 patients who adhered to the study's inclusion and exclusion criteria were collated, and rigorous statistical analyses were conducted. Comprehensive datasets, incorporating clinical, biochemical, interventional, electrocardiographic (ECG), and transthoracic echocardiographic information, were culled from the hospital's electronic repository. Transthoracic echocardiography was employed to assess the left ventricular ejection fraction (LVEF). The primary efficacy endpoint of this study was the identification of major adverse cardiovascular events (MACE). MACE encompassed total mortality, cardiovascular (CV) mortality, reinfarction, ischemic stroke, and hemorrhagic stroke. CV mortality, in turn, was defined by instances of reinfarction, ischemic stroke, and hemorrhagic stroke. The study's primary safety endpoint was the characterization of major hemorrhage, clinically defined as overt bleeding culminating in fatality, symptomatic intracranial, retroperitoneal, or intraocular bleeding, overt bleeding associated with a reduction of hemoglobin levels by a minimum of 3 g/dL, or overt bleeding necessitating the transfusion of 2 units of red blood cells. Moreover, secondary outcomes included total mortality, CV mortality, reinfarction, ischemic stroke, and hemorrhagic stroke, each assessed independently. A targeted subgroup analysis aimed to evaluate the comparative efficacy and safety profiles of clopidogrel and ticagrelor in patients aged 75 years or older. Ethical endorsement for the study's design was granted by the local ethics committee, and the research was conducted in adherence to the principles delineated in the Declaration of Helsinki. Statistical Analysis The data were analyzed using SPSS software (Version 23.0, SPSS, Inc. Chicago, IL). A statistical study was performed using SPSS 23 (SPSS Inc., Chicago, IL, United States) package program. Continuous variables were expressed as mean ± standard deviation and categorical variables as frequency and percentage (%). Comparisons between groups were made with Student's t-test for normally distributed numerical variables and non-normally distributed numerical variables with Mann Whitney U test. Chi-Square or Fisher's Exact tests were used to compare categorical data. Receiver Operating Characteristic (ROC) analysis was performed to identify a critical hemoglobin level associated with an increased risk of MACE. The Area Under the Curve (AUC) along with its 95% Confidence Interval (CI) was calculated to evaluate the predictive accuracy of hemoglobin levels for MACE. Survival analysis, specifically Kaplan-Meier survival curves, was employed to analyze time-to-event outcomes such as MACE and major bleeding. These curves were compared between subgroups and treatment groups using the log-rank test. Univariate Cox regression analysis was conducted to assess the impact of individual clinical and demographic characteristics on MACE. Variables demonstrating significance in the univariate analysis were further examined using multivariate Cox regression to identify independent factors associated with MACE. Hazard Ratios (HRs) and their 95% CIs were reported. Statistical significance was determined using p-values, with a threshold of 0.05. RESULT A total of 656 patients with hemoglobin levels below 12 mg/dL and who had acute coronary syndrome between 2014 and 2021 were included in the study. In the first year after acute coronary syndrome, 82% (538) of the patients received Clopidogrel and 18% (118) Ticagrelor treatment. The mean age of patients receiving ticagrelor treatment was lower than patients receiving clopidogrel (58.5 ± 10.5, 66.4 ± 13.0, p = < 0.001). 60.8% of patients receiving clopidogrel and 70.3% of patients receiving ticagrelor were male. Diabetes, hypertension, and coronary artery disease were similar in both groups (p = 0.60, p = 0.45, p = 0.10, respectively). CRF and CHF were more common in patients receiving clopidogrel (p = 0.03 and p < 0.001, respectively). The shock rate, LVEF, and PRECISE DAPT, and Killip scores of the patients at admission were similar in both groups (p = 0.59, p = 0.57, p = 0.71, p = 0.56, respectively). In both groups, the majority of patients were NSTEMI patients (93.1% in those receiving clopidogrel, 94.1% in those receiving ticagrelor). LAD was the most common culprit vessel in both groups, and patients receiving interventional or medical therapy were similar in both groups. Other clinical and demographic characteristics are shown in Table 1 . Table 1 Clinical and Demographic Characteristics of The Study Population Patient Characteristics Clopidogrel (n=538) Ticagrelor (n=118) P value Age (year) 66.4±13.0 58.5±10.5 <0.001* Gender (male) % 60.8(327) 70.3(83) 0.052 BMI (kg/m 2 ) 28.2±5.1 29.2± 5.6 0.065 Dislipidemia % 9.9(53) 4.2(5) 0.052 DM % 39.0(210) 36.4(43) 0.600 HT % 64.7(348) 61.0(72) 0.452 History of CAD % 71.9(387) 64.4(76) 0.104 History of PCI % 31.2(168) 38.1(45) 0.147 History of CABG % 14.7(79) 9.3(11) 0.125 CRF % 16.4(88) 8.5(10) 0.030* CHF % 12.8(69) 3.4(4) 0.003* Current Smoking % 39.2(211) 50.8(60) 0.020* COPD % 5.9(32) 6.8(8) 0.732 High Precise DAPT Score 81.6(439) 83.1(98) 0.711 Killip III-IV % 5.6(30) 4.2(5) 0.558 Shock at admission % 1.5(8) 0.8(1) 0.589 Length of stay in the hospital 4.6±1.6 4.6±1.6 0.941 LVEF (%) 45.2±11.6 44.5±11.8 0.570 Type of ACS STEMI % NSTEMI % 6.9(37) 93.1(501) 5.9(7) 94.1(111) 0.710 WBC (10 3 / m L) 10.1±4.0 10.1±3.7 0.955 eGFR (ml/dk/1.78m 2 ) 60.2±27.5 59.2(27.6) 0.710 ASA % 100.0(538) 100.0(118) 1.000 Beta-Blocker % 92.4 (497) 95.8(113) 0.192 CCB % 14.1(76) 11.0(13) 0.372 ACEI/ARB % 66.2(356) 67.8(80) 0.735 MRA % 8.6(46) 6.8(8) 0.526 PPI % 95.4(513) 99.2(117) 0.055 Number of vessels with severe stenosis No-Vessel One-Vessel disease Two-Vessel disease Three-Vessel disease 17.5(94) 26.2 (141) 23.0(124) 33.3(179) 7.6(9) 32.2(38) 31.4(37) 28.8(34) 0.014* Culprit Vessel None Left anterior descending Circumflex Right coronary Graft 12.8(69) 37.5(202) 22.1(119) 22.1(119) 5.4(29) 4.2(5) 43.2(51) 22.9(27) 23.7(28) 5.9(7) 0.120 Treatment Method PCI CABG Medical follow-up 68.8(370) 16.7(90) 14.5(78) 70.3(83) 13.6(16) 16.1(19) 0.716 ACEI/ARB: Angiotensin-converting enzyme inhibitors/Angiotensin receptor blockers, ASA: Acetylsalicylic acid, BMI: Body mass index, CABG: Coronary artery By-pass grafting, CAD: Coronary artery disease, CCB: Calcium channel blocker, CHF: Congestive heart failure, COPD: Chronic obstructive pulmonary disease, DM: Diabetes mellitus, GFR: Glomerular filtration rate, HT: Hypertension, LVEF: Left ventricular ejection fraction, MACE: Major adverse cardiovascular events MI: myocardial infarction, PAD: Peripheric artery disease, PCI: Percutaneous intervention, STEMI: ST-elevation myocardial infarction, WBC: White blood cell Continuous variables are given as mean ± SD. Median, interquartile range (range, [25% percentile-75% percentile]) The lower level of hemoglobin affecting MACE was determined using ROC analysis. In anemia patients, a hemoglobin level below 9.7 mg/dL was associated with an increase in MACE with 43.3% sensitivity and 42.4% specificity (AUC: 0.427, p = 0.05) (Fig. 1 ). Patients treated with clopidogrel and ticagrelor were compared for the efficacy and safety outcomes of 1-year MACE and major bleeding. MACE and major bleeding were similar in P2Y12 treatment groups (MACE: clopidogrel 10.0% vs. ticagrelor 11.0%, p = 0.75; major bleeding: clopidogrel 2.8%, ticagrelor 2.5%, p = 0.88). Similarly, both groups had similar total mortality, cardiovascular mortality, reinfarction, and hemorrhagic stroke. While ischemic stroke was observed in 16 patients in the clopidogrel group, it was not observed in the ticagrelor group (p = 0.04) (Table 2 ). Table 2 Comparison of Patients Followed up with Clopidogrel wr Ticagrelor in Terms of 1-Year MACE and Major Hemorrhage Primary Efficacy and Safety Endpoints %(n) Study endpoints 1-Year Cardiovascular Outcomes Clopidogrel Ticagrelor P Value MACE 10.0(54) 11.0(13) 0.750 Major Bleeding 2.8(15) 2.5(3) 0.882 Secondary Endpoints %(n) Total Mortality 5.8(31) 5.9(7) 0.943 CV Mortality 4.3(23) 3.4(4) 0.661 Reinfarction 2.4(13) 1.7(2) 0.635 Ischemic Stroke 3.0(16) 0.0(0) 0.041* Hemorrhagic Stroke 0.9(5) 0.0(0) 0.293 CV: Cardiovascular, MACE: Major adverse cardiac events • Continuous variables are given as mean ± SD. • Median, interquartile range (range, [25% percentile-75% percentile]) Table 3 Comparative Analysis of Primary and Secondary Endpoints Across Different Hemoglobin Levels (≤ 8, 8–10, and 10–12 mg/dL) in Patients Receiving Clopidogrel and Ticagrelor Treatment. Primary Efficacy and Safety Endpoints %(n) Study Endpoints Clopidogrel (N = 538) P Value Ticagrelor (N = 118) P Value ≤ 8 mg/dL 8–10 mg/dL 10–12 mg/dL ≤ 8 mg/dL 8–10 mg/dL 10–12 mg/dL MACE 12.5(6) 10.2(24) 9.4(24) 0.810 36.4(4) 11.9(7) 4.2(2) 0.008* Major Bleeding 6.3(3) 2.1(5) 2.8(7) 0.286 18.2(2) 0(0) 2.1(1) 0.002* Secondary Endpoints %(n) Total Mortality 8.3(4) 5.5(13) 5.5(14) 0.727 36.4(4) 3.4(2) 2.1(1) < 0.001* CV Mortality 8.3(4) 3.8(9) 3.9(10) 0.347 27.3(3) 1.7(1) 0(0) < 0.001* Reinfarction 2.1(1) 3.4(8) 1.6(4) 0.422 9.1(1) 1.7(1) 0(0) 0.110 Ischemic Stroke 2.1(1) 3.4(8) 2.8(7) 0.855 0(0) 0(0) 0(0) - Hemorrhagic Stroke 2.1(1) 0.8(2) 0.8(2) 0.683 0(0) 0(0) 0(0) - CV: Cardiovascular, MACE: Major adverse cardiovascular events • Continuous variables are given as mean ± SD. • Median, interquartile range (range, [25% percentile-75% percentile]) Tablo 4 Analysis of the Impact of Clinical and Demographic Characteristics on MACE Using Univariate and Multivariate Cox Regression Patient Characteristics Univariate Analysis HR 95% CI Lower-Upper P value Age 1.001 0.974-1.029 0.931 Gender (male) 0.835 0.426-1.639 0.601 BMI 1.045 0.993-1.099 0.090 Dislipidemia 1.843 0.887 3.829 0.101 DM 0.810 0.428 1.531 0.516 HT 0.884 0.440-1.776 0.730 History of CAD 0.506 0.165-1.556 0.235 History of PCI 6.970 3.385-14.352 <0.001 History of CABG 7.729 3.834-15.581 <0.001 CRF 2.636 1.418-4.900 0.002 CHF 1.997 0.942-4.233 0.071 Current Smoking 0.771 0.415-1.432 0.410 COPD 2.450 0.963-6.229 0.060 High Precise DAPT Score 1.054 1.023-1.086 <0.001 Killip III-IV 1.145 0.341 3.839 0.827 Shock at admission 0.349 0.021-5.834 0.464 Length of stay in the hospital 0.820 0.684-0.983 0.032 LVEF (%) 0.956 0.932-0.980 <0.001 Type of ACS 1.135 0.024-2.246 0.345 Betablocker 1.128 0.361-4.548 0.702 ACEi/ARB 0.949 0.462-1.949 0.886 Number of vessels with severe stenosis 0.799 0.195-3.274 0.755 Culprit vessel 0.264 0.063-1.102 0.068 Treatment method 1.408 0.020-97.70 0.874 Patient Characteristics Multivariate Analysis HR 95% CI Lower-Upper P value History of PCI 3.961 2.366-6.631 <0.001 History of CABG 5.327 3.250-8.732 <0.001 CRF 2.261 1.338-3.820 0.002 High Precise DAPT Score 1.034 1.013-1.055 <0.001 Length of stay in the hospital 0.897 0.768-1.047 0.169 LVEF (%) 0.977 0.9560.999 0.037 ACEI/ARB: Angiotensin-converting enzyme inhibitors/Angiotensin receptor blockers, BMI: Body mass index, CABG: Coronary artery By-pass grafting, CAD: Coronary artery disease, CHF: Congestive heart failure, COPD: Chronic obstructive pulmonary disease, DM: Diabetes mellitus, HT: Hypertension, LVEF: Left ventricular ejection fraction, MI: myocardial infarction, PCI: Percutaneous intervention. Patients receiving clopidogrel and ticagrelor were analysed in terms of their effect on primary and secondary endpoints, divided into 3 groups according to hemoglobin levels as ≤ 8, 8–10, and 10–12 mg/dL. Hemoglobin level was ≤ 8 mg/dL in 59 (9%) patients, 8–10 mg/dL in 295 (45%) patients, and 10–12 mg/dL in 302 (46%) patients. There was no significant difference in primary efficacy and safety outcomes and secondary outcomes according to the anemia subgroups in patients receiving clopidogrel treatment. MACE and major hemorrhage were significantly higher in patients treated with ticagrelor than in patients with a hemoglobin level of ≤ 8 mg/dL (p = 0.008 and p = 0.002, respectively). In patients receiving ticagrelor treatment, MACE was observed in 36.4% of patients and major bleeding in 18.2% at 1 year. When the secondary endpoints were examined, it was observed that the difference in MACE rates was mainly due to total mortality and cardiovascular mortality. In patients with hemoglobin level ≤ 8 mg/dL, 36.4% total mortality and 27.3% cardiovascular mortality were observed at 1 year. Since fewer patients received ticagrelor treatment, reinfarction was observed in only 2 patients, while stroke was not observed in any patient (Table 2 ). Patients with and without MACE in the clopidogrel and ticagrelor treatment groups were compared according to their hemoglobin levels. Hemoglobin levels were similar according to MACE outcome in patients receiving clopidogrel treatment (MACE (-) 9.91 mg/dL, MACE (+) 9.55 mg/dL, p = 0.39). Hemoglobin levels in patients receiving ticagrelor treatment were statistically significantly lower in MACE (+) patients than in MACE (-) patients (MACE (-) 9.90 mg/dL, MACE (+) 8.60 mg/dL, p < 0.001) (Fig. 2 ). The effects of clinical and demographic characteristics of the patients on MACE were analysed by univariate and multivariate Cox Regression analysis. In the univariate analysis, PCI history, CABG history, CRF, high PRECISE DAPT score, length of stay in hospital, and LVEF were determined as factors affecting MACE (p < 0.001, p < 0.001, p = 0.002, p < 0.001 and p < 0.001, respectively). In the Multivariate Cox regression analysis, the relationship between the length of stay in hospital and MACE lost its significance, while PCI history, CABG history, CRF, high PRECISE DAPT score and LVEF were determined as factors affecting MACE (p < 0.001, p < 0.001, p = 0.002, p < 0.001 and p < 0.037, respectively) (Table 4) Survival analysis was conducted to compare patients across three hemoglobin level categories: ≤8, 8–10, and 10–12 mg/dL. Additionally, patients were stratified into two groups based on hemoglobin levels below and above 9.7 mg/dL, a threshold impacting MACE as determined by ROC analysis. MACE was more common in patients with hemoglobin levels below 8 than in the other two groups. However, MACE was observed at similar rates in the other two groups (Log Rank p = 0.11). Patients with a hemoglobin level below 9.7 had a higher MACE than patients with a hemoglobin level above 9.7 (Log Rank p = 0.03) (Fig. 3 ). In the analysis of survival according to the P2Y12 treatment group, 1-year MACE and major hemorrhage were similar in the clopidogrel and ticagrelor groups (Log Rank p = 0.76 for MACE; Log Rank p = 0.89 for major hemorrhage) (Fig. 4 ) In the study, 154 (23.5%) patients were 75 years or older. MACE was observed in 17 patients and major hemorrhage was observed in 4 patients within 1 year. In these patients, survival analysis was performed in terms of 1 year MACE and major hemorrhage compared to the P2Y12 treatment group. In patients with anemia over 75 years of age, 1st year MACE rates were found to be similar in both groups (Log Rank p = 0.74), while 1st year major hemorrhage was higher in patients who received ticagrelor treatment (Log Rank p = 0.04) (Fig. 5 ) Discussion Anemia is associated with short and long-term mortality in both stable coronary artery disease and acute coronary syndrome ( 9 ). It has been shown in various studies that this increase in mortality is associated with both adverse ischemic events and bleeding ( 10 ). In this study, we investigated the effects of clopidogrel or ticagrelor treatment in terms of adverse ischemic events and bleeding in anemic patients admitted with a diagnosis of acute coronary syndrome. Clinical and demographic characteristics were similar in both groups. We found that 1-year MACE and major bleeding were similar in P2Y12 treatment group. Similarly, both groups had similar total mortality, cardiovascular mortality, reinfarction, and hemorrhagic stroke. When we looked at the subgroup analysis, we examined the patients in 3 groups according to hemoglobin levels as ≤ 8, 8–10 and 10–12 mg/dL. There was no significant difference in primary efficacy and safety outcomes and secondary outcomes according to the anemia subgroups in patients receiving clopidogrel treatment. MACE and major hemorrhage were significantly higher in patients treated with ticagrelor than in patients with a hemoglobin level of ≤ 8 mg/dL. The PRECISE-DAPT score is a prediction algorithm for out-of-hospital bleeding in patients who have undergone elective or urgent percutaneous coronary intervention and are treated with dual antiplatelet therapy (DAPT). It includes 5 parameters: age, creatinine clearance, hemoglobin, white blood cell count (WBC), and a history of previous bleeding. Patients with a PRECISE-DAPT score of 25 or higher are considered high-risk, and it has been shown that in these patients, extended DAPT therapy is not associated with ischemic benefits and may even be linked to an increased risk of bleeding events ( 11 ). Anemia is an important component of the PRECISE-DAPT score, but its impact on the score is significant only when hemoglobin levels are between 10 and 12 mg/dL. Scores do not change when hemoglobin levels are below 10 mg/dL. In this study, when we generally compared patients with hemoglobin levels below 12 mg/dL who were receiving clopidogrel and ticagrelor, we did not observe any differences in terms of ischemic events and bleeding events. However, in the subgroup analysis, we found statistically higher rates of both MACE and major bleeding in patients with hemoglobin levels of 8 mg/dL or lower who were given ticagrelor. We believe that this finding should be considered, especially in anemic patients starting ticagrelor, when their PRECISE-DAPT score is not high. We would like to emphasize the importance of being more cautious and protective when starting ticagrelor in patients with hemoglobin levels of 8 mg/dL or lower. When we calculate the PRECISE-DAPT score for anemic patients, especially those who are young and have mild kidney insufficiency, we find that they fall into the moderate-risk category. However, based on the results of this study, we believe that this score may have limitations, especially in anemic patients who are to be given ticagrelor, and it might be prudent to consider being more cautious or starting clopidogrel instead. De-escalation studies also support this hypothesis. In the study conducted by Satoshi and colleagues, it was demonstrated that de-escalation of clopidogrel with potent antiplatelet agents reduced the risk of bleeding ( 12 ). Similarly, in the TOPIC study, patients who underwent de-escalation of DAPT with clopidogrel after 1 month of treatment with potent antiplatelet agents had a lower risk of bleeding ( 13 ). The fact that de-escalation studies reduce bleeding risk without affecting ischemic events is consistent with our study, where we did not observe a difference in ischemic events when comparing clopidogrel to ticagrelor. In fact, in our study, the greater reliability of clopidogrel in patients with hemoglobin levels of 8 or lower is also consistent with de-escalation studies. In our study, among anemic patients presenting with ACS, we did not find any differences in terms of the primary endpoint, which was MACE and bleeding between the P2Y12 inhibitor groups. Both groups had similar rates of total mortality, cardiovascular mortality, reinfarction, and hemorrhagic stroke. Only patients receiving clopidogrel had a higher incidence of ischemic stroke, while no ischemic strokes were observed in those receiving ticagrelor. In the PLATO study, the primary endpoint, which included vascular-related death, MI, or stroke, and the secondary endpoint, which included death, MI, or stroke for any reason, were found to be statistically significantly lower in patients receiving ticagrelor compared to those receiving clopidogrel ( 14 ). When analyzed individually, MI and vascular-related death were less frequent in the ticagrelor group, while there was no significant difference between the two groups in terms of stroke incidence ( 14 ). In the PLATO study, subgroup analyses for anemic patients were not reported. Therefore, it is difficult to explain why our study found no difference in ischemic events, except for ischemic stroke, compared to the PLATO study. Perhaps if such an analysis had been conducted in the PLATO study, the results we observed in our study could have been better discussed. Regarding ischemic stroke, in the PLATO study, no difference was observed between the two groups, while in our study, there was a higher incidence of ischemic stroke in patients receiving clopidogrel. Anemia is not only a well-known risk factor for bleeding but is also associated with a deficiency in the quantity and quality of platelets produced in the bone marrow, and it has been shown that these dysfunctional platelets can lead to thrombosis ( 15 , 16 ). Considering that ticagrelor is a more potent antiplatelet agent, this result may not be too surprising. When we subgrouped patients based on their hemoglobin levels, we did not find any differences in terms of primary efficacy and safety outcomes, as well as secondary endpoints, among patients receiving clopidogrel. However, in patients with hemoglobin levels of 8 mg/dL or lower who were treated with ticagrelor, we observed a statistically significant increase in MACE and major bleeding events at 1 year. When we evaluated secondary endpoints, we found that this difference in MACE was particularly associated with total mortality and cardiovascular mortality. Reinfarction occurred in only 2 patients, and there were no observed cases of stroke. These data strongly suggest that patients with hemoglobin levels of 8 mg/dL or lower are at very high risk for bleeding and cardiovascular mortality. We concluded that deep anemia, especially in patients with hemoglobin levels of 8 mg/dL or lower, leads to increased thrombogenic activity ( 15 , 16 ), and in patients with deep anemia, the more potent ticagrelor increases the risk of bleeding. CONCLUSİON In conclusion, this study offers valuable insights into the management of anemic patients with acute coronary syndrome and the choice between clopidogrel and ticagrelor for antiplatelet therapy. While overall outcomes were similar between the two medications in the broader patient population, a critical distinction emerged when analyzing patients with hemoglobin levels of 8 mg/dL or lower. In this subgroup, ticagrelor was associated with a statistically significant increase in both major adverse cardiovascular events (MACE) and major bleeding events at the one-year mark. This finding underscores the need for cautious consideration when prescribing ticagrelor to anemic patients, particularly those with severe anemia. It highlights the importance of personalized medicine in tailoring antiplatelet therapy to individual patient profiles and underscores the significance of hematologic factors in cardiovascular outcomes. Further research in this area may pave the way for more precise and effective treatment strategies for this vulnerable patient population. Declarations Funding: The authors declared that this study has received no financial support. Declaration of Interests: The authors have no conflicts of interest to declare. Informed Consent: Written informed consent was obtained from all participants who participated in this study. Availability of data and materials: Data supporting the findings of this study are available from the corresponding author, upon reasonable request, via the e-mail address [email protected] Authors' contributions: T.O. and B.Y. conceived of the presented idea. F.P. and Ş.A. developed the theory and performed the computations. F.P., Z.K. and F.D. verified the analytical methods. B.Y. and T.O. supervised the findings of this work. All authors discussed the results and contributed to the final manuscript. References Sarnak, M. J., Tighiouart, H., Manjunath, G., MacLeod, B., Griffith, J., Salem, D., & Levey, A. S. (2002). Anemia as a risk factor for cardiovascular disease in The Atherosclerosis Risk in Communities (ARIC) study. Journal of the American College of Cardiology , 40 (1), 27–33. Guerrero, C., Garay, A., Ariza-Solé, A., Formiga, F., Raposeiras-Roubín, S., Abu-Assi, E., D'Ascenzo, F., Kinnaird, T., Manzano-Fernández, S., Alegre, O., Sánchez-Salado, J. C., Lorente, V., Templin, C., Velicki, L., Xanthopoulou, I., Cerrato, E., Rognoni, A., Boccuzzi, G., Omedè, P., Montabone, A., … Cequier, Á. (2018). Anemia in patients with acute coronary syndromes treated with prasugrel or ticagrelor: Insights from the RENAMI registry. Thrombosis research , 167 , 142–148. Wallentin, L., Becker, R. C., Budaj, A., Cannon, C. P., Emanuelsson, H., Held, C., Horrow, J., Husted, S., James, S., Katus, H., Mahaffey, K. W., Scirica, B. M., Skene, A., Steg, P. G., Storey, R. F., Harrington, R. A., PLATO Investigators, Freij, A., & Thorsén, M. (2009). Ticagrelor versus clopidogrel in patients with acute coronary syndromes. The New England journal of medicine , 361 (11), 1045–1057. Verdoia, M., Rolla, R., Pergolini, P., Gioscia, R., Nardin, M., Negro, F., Viglione, F., Suryapranata, H., Kedhi, E., & Luca, G. D. (2021). Low hemoglobin predicts high-platelet reactivity and major cardiovascular ischemic events at long-term follow-up among ACS patients receiving dual antiplatelet therapy with ticagrelor. Catheterization and Cardiovascular Interventions , 98 (7), 1309-1316. Na, K., Qiu, M., Ma, S., Li, Y., Li, J., Liu, R., Zhang, J., & Han, Y. (2022). Impact of Ticagrelor vs. Clopidogrel in Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention After Risk Stratification With the CHA2DS2-VASc Score. Frontiers in Cardiovascular Medicine , 9 . Tjerkaski, J., Jernberg, T., Alfredsson, J., Erlinge, D., James, S., Lindahl, B., Mohammad, M. A., Omerovic, E., Venetsanos, D., & Szummer, K. (2022). Comparison between ticagrelor and clopidogrel in high bleeding risk patients with acute coronary syndrome. European Heart Journal , 43 (Supplement_2). Charpentier, T., Ferdynus, C., Lair, T., Cordier, C., Brulliard, C., Valance, D., Emery, M., Caron, M., Allou, N., & Allyn, J. (2020). Bleeding risk of ticagrelor compared to clopidogrel in intensive care unit patients with acute coronary syndrome: A propensity-score matching analysis. PLoS ONE , 15 (5). Szummer, K., Montez-Rath, M. E., Alfredsson, J., Erlinge, D., Lindahl, B., Hofmann, R., Ravn-Fischer, A., Svensson, P., & Jernberg, T. (2020). Comparison Between Ticagrelor and Clopidogrel in Elderly Patients With an Acute Coronary Syndrome: Insights From the SWEDEHEART Registry. Circulation , 142 (18), 1700–1708. Sabatine MS, Morrow DA, Giugliano RP, Burton PB, Murphy SA, McCabe CH, Gibson CM, Braunwald E. Association of hemoglobin levels with clinical out- comes in acute coronary syndromes. Circulation 2005;111:2042–2049. Bassand, J. P., Afzal, R., Eikelboom, J., Wallentin, L., Peters, R., Budaj, A., ... & Yusuf, S. (2010). Relationship between baseline haemoglobin and major bleeding complications in acute coronary syndromes. European heart journal, 31(1), 50-58. Costa F, van Klaveren D, James S, Heg D, Raber L, Feres F, Pilgrim T, Hong MK, Kim HS, Colombo A, Steg G, Zanchin T, Palmerini T, Wallentin L, Bhatt DL, Stone GW, Windecker S, Steyerberg EW, Valgimigli M. Derivation and valida- tion of the predicting bleeding complications in patients undergoing stent implantation and subsequent dual antiplatelet therapy (PRECISE-DAPT) score: a pooled analysis of individual-patient datasets from clinical trials. Lancet 2017;389:1025–1034. Shoji, Satoshi, et al. "De-escalation of dual antiplatelet therapy in patients with acute coronary syndromes." Journal of the American College of Cardiology 78.8 (2021): 763-777. Cuisset, Thomas, et al. "Benefit of switching dual antiplatelet therapy after acute coronary syndrome: the TOPIC (timing of platelet inhibition after acute coronary syndrome) randomized study." European heart journal 38.41 (2017): 3070-3078. Mahaffey, Kenneth W., et al. "Ticagrelor compared with clopidogrel by geographic region in the Platelet Inhibition and Patient Outcomes (PLATO) trial." Circulation 124.5 (2011): 544-554. Redfors, Björn, et al. "Quantifying ischemic risk after percutaneous coronary intervention attributable to high platelet reactivity on clopidogrel (from the assessment of dual antiplatelet therapy with drug-eluting stents study)." The American Journal of Cardiology 120.6 (2017): 917-923. Ibrahim, Homam, et al. "Association of immature platelets with adverse cardiovascular outcomes." Journal of the American College of Cardiology 64.20 (2014): 2122-2129. 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3397394","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":236839747,"identity":"efbdedb6-55a9-4242-bb5f-d726eaa639a3","order_by":0,"name":"Tolga 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Educatıon Research Hospıtal","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zeynep","middleName":"","lastName":"Kolak","suffix":""},{"id":236839756,"identity":"5b474a94-a05d-44e1-95e5-24eaf31f2c49","order_by":5,"name":"Furkan Durak","email":"","orcid":"","institution":"Prof. Dr. İlhan Varank Sancaktepe Training and Research Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Furkan","middleName":"","lastName":"Durak","suffix":""}],"badges":[],"createdAt":"2023-09-29 07:29:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3397394/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3397394/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":44208540,"identity":"43e94d0c-9978-44fe-a31c-b6dfa8660e5d","added_by":"auto","created_at":"2023-10-06 20:32:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":165543,"visible":true,"origin":"","legend":"\u003cp\u003eROC Analysis of Hemoglobin Level Affecting The MACE\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3397394/v1/9524c06456d8bb7cef8272f5.png"},{"id":44207184,"identity":"4bd0cae4-12ab-495d-b4a8-f58702259a75","added_by":"auto","created_at":"2023-10-06 20:24:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":73291,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Hemoglobin Levels in Patients with and without MACE in Clopidogrel and Ticagrelor Treatment Groups\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3397394/v1/fe66c5875d513a3086517c52.png"},{"id":44208539,"identity":"ad2b5f36-847d-410b-9cec-4f2d240ffb13","added_by":"auto","created_at":"2023-10-06 20:32:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":100317,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival Analysis of Patients Stratified by Hemoglobin Levels (≤8, 8-10, and 10-12 mg/dL) and Dichotomized Groups (Below and Above 9.7 mg/dL)\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3397394/v1/d74a075bdc121c1263aaec57.png"},{"id":44207182,"identity":"b01e528c-61bf-423b-a1e8-80b1164410fd","added_by":"auto","created_at":"2023-10-06 20:24:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":91557,"visible":true,"origin":"","legend":"\u003cp\u003eMACE and Major Hemorrhage Analysis by P2Y12 Treatment Group\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3397394/v1/55b5cae9602d109d69bc2054.png"},{"id":44207180,"identity":"601b549e-e4f8-4160-a67b-52c06b990dfa","added_by":"auto","created_at":"2023-10-06 20:24:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":107391,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Clopidogrel and Ticagrelor Therapy in Terms Of 1-Year MACE and Major Bleeding in Patients over 75 Years of Age\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-3397394/v1/2b8eaf977ea3c6a61f7bb8a9.png"},{"id":45984865,"identity":"aea6be73-9473-4acd-a5d4-d4763183b4bc","added_by":"auto","created_at":"2023-11-07 07:45:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1045085,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3397394/v1/2e0a8247-2322-4f21-bd62-a062061bcf34.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effect of Ticagrelor or Clopidogrel Treatment on 1-Year Cardiovascular Outcomes in Anemic Patients with Acute Coronary Syndrome","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe investigation into the potential impact of ticagrelor and clopidogrel treatments on cardiovascular outcomes among patients dealing with acute coronary syndrome (ACS) and anemia assumes significant importance within the cardiology domain. Anemia, prevalent in the context of ACS, is recognized for its association with heightened susceptibility to cardiovascular events (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Notably, the PLATelet inhibition and patient Outcomes (PLATO) study highlighted the potential benefits of ticagrelor therapy in mitigating cardiovascular mortality, myocardial infarction, or stroke, particularly within the subset of patients affected by ACS (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis favorable therapeutic effect of ticagrelor is attributed to its superior and more consistent suppression of platelet activity compared to clopidogrel. However, the robust platelet inhibition characteristic of ticagrelor raises concerns about its appropriateness for anemic patients, as it might amplify the risk of significant cardiovascular adverse events, especially bleeding incidents. In light of this, a comprehensive evaluation of the cardiovascular outcomes associated with both ticagrelor and clopidogrel in patients afflicted with anemic ACS is crucial to discern the optimal therapeutic approach.\u003c/p\u003e \u003cp\u003eRecent analyses have sought to delve into the potential influence of ticagrelor treatment on cardiovascular outcomes in patients diagnosed with anemic ACS. Notably, in ACS patients treated with ticagrelor and acetylsalicylic acid, lower hemoglobin levels have been linked to a heightened occurrence of major ischemic events, although no impact on survival was observed (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Moreover, in patients at elevated ischemic risk, ticagrelor demonstrates a reduction in the incidence of ischemic events without exacerbating major bleeding when compared with clopidogrel. However, among patients with a lower ischemic risk but a higher tendency for bleeding, ticagrelor was associated with an increased likelihood of adverse events (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Furthermore, Charpentier et al. observed a greater frequency of bleeding events with clopidogrel than with ticagrelor during intensive care unit follow-ups among ACS patients (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Notably, individuals at heightened bleeding risk demonstrated augmented cardiovascular events and bleeding incidents associated with ticagrelor administration. Within this context, there arises a need to compare the effects of less potent P2Y12 inhibitors with that of ticagrelor specifically in anemic patients.\u003c/p\u003e \u003cp\u003eIt is crucial to subject the comparative effects of clopidogrel and ticagrelor to meticulous scrutiny, encompassing parameters such as overall mortality, cardiovascular mortality, reinfarction, ischemic stroke, hemorrhagic stroke, and major hemorrhage within this unique patient cohort. Additionally, there remains a dearth of literature investigating the relative efficacy and safety profiles of these agents in subgroups stratified by the severity of anemia, as well as in elderly anemic patients who inherently present a more vulnerable demographic (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Consequently, this study has been meticulously devised to address these critical inquiries and contribute to a more comprehensive understanding of the optimal therapeutic strategy in this context.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThis study employed a retrospective research design to elucidate the effects of treatments involving ticagrelor and clopidogrel on cardiovascular outcomes over a one-year period in patients with anemia experiencing acute coronary syndrome. Between the years 2014 and 2021, individuals diagnosed with either ST-segment elevation myocardial infarction (STEMI) or non-ST-segment elevation myocardial infarction (NSTEMI) were subject to rigorous screening procedures. All enrolled patients underwent coronary angiography, and subsequent medical interventions such as medical therapy, coronary artery bypass grafting, or percutaneous coronary intervention with angioplasty and stent placement were administered as deemed appropriate based on the coronary angiography findings.\u003c/p\u003e \u003cp\u003eInclusion criteria for participation mandated subjects to be at least 18 years of age, undergo pre-coronary angiography blood sampling including hemogram assessment, exhibit a hemoglobin level below 12 mg/dL in the collected sample, and opt for P2Y12 inhibitor treatment for a minimum duration of 12 months. Exclusion criteria encompassed the identification of critical stenosis affecting the left main coronary artery, the presence of concomitant comorbidities such as atrial fibrillation necessitating anticoagulation therapy, alteration between P2Y12 inhibitors within a 12-month period, or premature discontinuation of the designated treatment regimen.\u003c/p\u003e \u003cp\u003eData derived from a comprehensive cohort of 656 patients who adhered to the study's inclusion and exclusion criteria were collated, and rigorous statistical analyses were conducted. Comprehensive datasets, incorporating clinical, biochemical, interventional, electrocardiographic (ECG), and transthoracic echocardiographic information, were culled from the hospital's electronic repository. Transthoracic echocardiography was employed to assess the left ventricular ejection fraction (LVEF).\u003c/p\u003e \u003cp\u003eThe primary efficacy endpoint of this study was the identification of major adverse cardiovascular events (MACE). MACE encompassed total mortality, cardiovascular (CV) mortality, reinfarction, ischemic stroke, and hemorrhagic stroke. CV mortality, in turn, was defined by instances of reinfarction, ischemic stroke, and hemorrhagic stroke. The study's primary safety endpoint was the characterization of major hemorrhage, clinically defined as overt bleeding culminating in fatality, symptomatic intracranial, retroperitoneal, or intraocular bleeding, overt bleeding associated with a reduction of hemoglobin levels by a minimum of 3 g/dL, or overt bleeding necessitating the transfusion of 2 units of red blood cells. Moreover, secondary outcomes included total mortality, CV mortality, reinfarction, ischemic stroke, and hemorrhagic stroke, each assessed independently.\u003c/p\u003e \u003cp\u003eA targeted subgroup analysis aimed to evaluate the comparative efficacy and safety profiles of clopidogrel and ticagrelor in patients aged 75 years or older. Ethical endorsement for the study's design was granted by the local ethics committee, and the research was conducted in adherence to the principles delineated in the Declaration of Helsinki.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThe data were analyzed using SPSS software (Version 23.0, SPSS, Inc. Chicago, IL). A statistical study was performed using SPSS 23 (SPSS Inc., Chicago, IL, United States) package program. Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and categorical variables as frequency and percentage (%). Comparisons between groups were made with Student's t-test for normally distributed numerical variables and non-normally distributed numerical variables with Mann Whitney U test. Chi-Square or Fisher's Exact tests were used to compare categorical data.\u003c/p\u003e \u003cp\u003eReceiver Operating Characteristic (ROC) analysis was performed to identify a critical hemoglobin level associated with an increased risk of MACE. The Area Under the Curve (AUC) along with its 95% Confidence Interval (CI) was calculated to evaluate the predictive accuracy of hemoglobin levels for MACE. Survival analysis, specifically Kaplan-Meier survival curves, was employed to analyze time-to-event outcomes such as MACE and major bleeding. These curves were compared between subgroups and treatment groups using the log-rank test. Univariate Cox regression analysis was conducted to assess the impact of individual clinical and demographic characteristics on MACE. Variables demonstrating significance in the univariate analysis were further examined using multivariate Cox regression to identify independent factors associated with MACE. Hazard Ratios (HRs) and their 95% CIs were reported. Statistical significance was determined using p-values, with a threshold of 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULT","content":"\u003cp\u003eA total of 656 patients with hemoglobin levels below 12 mg/dL and who had acute coronary syndrome between 2014 and 2021 were included in the study. In the first year after acute coronary syndrome, 82% (538) of the patients received Clopidogrel and 18% (118) Ticagrelor treatment. The mean age of patients receiving ticagrelor treatment was lower than patients receiving clopidogrel (58.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5, 66.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.0, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001). 60.8% of patients receiving clopidogrel and 70.3% of patients receiving ticagrelor were male. Diabetes, hypertension, and coronary artery disease were similar in both groups (p\u0026thinsp;=\u0026thinsp;0.60, p\u0026thinsp;=\u0026thinsp;0.45, p\u0026thinsp;=\u0026thinsp;0.10, respectively). CRF and CHF were more common in patients receiving clopidogrel (p\u0026thinsp;=\u0026thinsp;0.03 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively). The shock rate, LVEF, and PRECISE DAPT, and Killip scores of the patients at admission were similar in both groups (p\u0026thinsp;=\u0026thinsp;0.59, p\u0026thinsp;=\u0026thinsp;0.57, p\u0026thinsp;=\u0026thinsp;0.71, p\u0026thinsp;=\u0026thinsp;0.56, respectively). In both groups, the majority of patients were NSTEMI patients (93.1% in those receiving clopidogrel, 94.1% in those receiving ticagrelor). LAD was the most common culprit vessel in both groups, and patients receiving interventional or medical therapy were similar in both groups. Other clinical and demographic characteristics are shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003eClinical and Demographic Characteristics of The Study Population\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eClopidogrel\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=538)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTicagrelor\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=118)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e66.4\u0026plusmn;13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e58.5\u0026plusmn;10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender (male) %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e60.8(327)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e70.3(83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e28.2\u0026plusmn;5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e29.2\u0026plusmn;\u0026nbsp;5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDislipidemia %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e9.9(53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e4.2(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDM %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e39.0(210)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e36.4(43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHT %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e64.7(348)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e61.0(72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of CAD %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e71.9(387)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e64.4(76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of PCI %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e31.2(168)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e38.1(45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of CABG %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e14.7(79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e9.3(11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRF %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e16.4(88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e8.5(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.030*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHF %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e12.8(69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e3.4(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent Smoking\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e39.2(211)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e50.8(60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.020*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOPD %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e5.9(32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e6.8(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh Precise DAPT Score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e81.6(439)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e83.1(98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.711\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eKillip III-IV %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e5.6(30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e4.2(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.558\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eShock at admission %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e1.5(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e0.8(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.589\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength of stay in the hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e4.6\u0026plusmn;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e4.6\u0026plusmn;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.941\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLVEF (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e45.2\u0026plusmn;11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e44.5\u0026plusmn;11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.570\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of ACS\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eSTEMI %\u003c/p\u003e\n \u003cp\u003eNSTEMI %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.9(37)\u003c/p\u003e\n \u003cp\u003e93.1(501)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.9(7)\u003c/p\u003e\n \u003cp\u003e94.1(111)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.710\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWBC (10\u003csup\u003e3\u003c/sup\u003e/\u003c/strong\u003e\u003cstrong\u003em\u003c/strong\u003e\u003cstrong\u003eL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e10.1\u0026plusmn;4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e10.1\u0026plusmn;3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eeGFR\u0026nbsp;(ml/dk/1.78m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e60.2\u0026plusmn;27.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e59.2(27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.710\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eASA %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e100.0(538)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e100.0(118)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeta-Blocker %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e92.4 (497)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e95.8(113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.192\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCCB %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e14.1(76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e11.0(13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.372\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eACEI/ARB %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e66.2(356)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e67.8(80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.735\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMRA %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e8.6(46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e6.8(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPI %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e95.4(513)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e99.2(117)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of vessels with severe stenosis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNo-Vessel\u003c/p\u003e\n \u003cp\u003eOne-Vessel disease\u003c/p\u003e\n \u003cp\u003eTwo-Vessel disease\u003c/p\u003e\n \u003cp\u003eThree-Vessel disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17.5(94)\u003c/p\u003e\n \u003cp\u003e26.2 (141)\u003c/p\u003e\n \u003cp\u003e23.0(124)\u003c/p\u003e\n \u003cp\u003e33.3(179)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7.6(9)\u003c/p\u003e\n \u003cp\u003e32.2(38)\u003c/p\u003e\n \u003cp\u003e31.4(37)\u003c/p\u003e\n \u003cp\u003e28.8(34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.014*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCulprit Vessel\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003cp\u003eLeft anterior descending\u003c/p\u003e\n \u003cp\u003eCircumflex\u003c/p\u003e\n \u003cp\u003eRight coronary\u003c/p\u003e\n \u003cp\u003eGraft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12.8(69)\u003c/p\u003e\n \u003cp\u003e37.5(202)\u003c/p\u003e\n \u003cp\u003e22.1(119)\u003c/p\u003e\n \u003cp\u003e22.1(119)\u003c/p\u003e\n \u003cp\u003e5.4(29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.2(5)\u003c/p\u003e\n \u003cp\u003e43.2(51)\u003c/p\u003e\n \u003cp\u003e22.9(27)\u003c/p\u003e\n \u003cp\u003e23.7(28)\u003c/p\u003e\n \u003cp\u003e5.9(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment Method\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePCI\u003c/p\u003e\n \u003cp\u003eCABG\u003c/p\u003e\n \u003cp\u003eMedical follow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.85430463576159%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e68.8(370)\u003c/p\u003e\n \u003cp\u003e16.7(90)\u003c/p\u003e\n \u003cp\u003e14.5(78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e70.3(83)\u003c/p\u003e\n \u003cp\u003e13.6(16)\u003c/p\u003e\n \u003cp\u003e16.1(19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.8476821192053%\" valign=\"top\"\u003e\n \u003cp\u003e0.716\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eACEI/ARB: Angiotensin-converting enzyme inhibitors/Angiotensin receptor blockers, ASA: Acetylsalicylic acid, BMI: Body mass index, CABG: Coronary artery By-pass grafting, CAD: Coronary artery disease, CCB: Calcium channel blocker, CHF: Congestive heart failure, COPD: Chronic obstructive pulmonary disease, DM: Diabetes mellitus, GFR: Glomerular filtration rate, HT: Hypertension, LVEF: Left ventricular ejection fraction, MACE:\u0026nbsp;Major adverse\u0026nbsp;cardiovascular\u0026nbsp;events\u0026nbsp; MI: myocardial infarction, PAD: Peripheric artery disease, PCI: Percutaneous intervention, STEMI: ST-elevation myocardial infarction,\u0026nbsp;WBC: White blood cell\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eContinuous variables are given as mean \u0026plusmn; SD.\u003c/li\u003e\n \u003cli\u003eMedian, interquartile range (range, [25% percentile-75% percentile])\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe lower level of hemoglobin affecting MACE was determined using ROC analysis. In anemia patients, a hemoglobin level below 9.7 mg/dL was associated with an increase in MACE with 43.3% sensitivity and 42.4% specificity (AUC: 0.427, p\u0026thinsp;=\u0026thinsp;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003ePatients treated with clopidogrel and ticagrelor were compared for the efficacy and safety outcomes of 1-year MACE and major bleeding. MACE and major bleeding were similar in P2Y12 treatment groups (MACE: clopidogrel 10.0% vs. ticagrelor 11.0%, p\u0026thinsp;=\u0026thinsp;0.75; major bleeding: clopidogrel 2.8%, ticagrelor 2.5%, p\u0026thinsp;=\u0026thinsp;0.88). Similarly, both groups had similar total mortality, cardiovascular mortality, reinfarction, and hemorrhagic stroke. While ischemic stroke was observed in 16 patients in the clopidogrel group, it was not observed in the ticagrelor group (p\u0026thinsp;=\u0026thinsp;0.04) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of Patients Followed up with Clopidogrel wr Ticagrelor in Terms of 1-Year MACE and Major Hemorrhage\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003ePrimary Efficacy and Safety Endpoints %(n)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eStudy endpoints\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e1-Year Cardiovascular Outcomes\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eClopidogrel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTicagrelor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMACE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.0(54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.0(13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMajor Bleeding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8(15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecondary Endpoints %(n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8(31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.9(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCV Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3(23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.4(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.661\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReinfarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4(13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.635\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIschemic Stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0(16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.041*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHemorrhagic Stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.293\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eCV: Cardiovascular, MACE: Major adverse cardiac events\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\u0026bull; Continuous variables are given as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\u0026bull; Median, interquartile range (range, [25% percentile-75% percentile])\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparative Analysis of Primary and Secondary Endpoints Across Different Hemoglobin Levels (\u0026le;\u0026thinsp;8, 8\u0026ndash;10, and 10\u0026ndash;12 mg/dL) in Patients Receiving Clopidogrel and Ticagrelor Treatment.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003ePrimary Efficacy and Safety Endpoints %(n)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eStudy Endpoints\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eClopidogrel (N\u0026thinsp;=\u0026thinsp;538)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTicagrelor (N\u0026thinsp;=\u0026thinsp;118)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;8 mg/dL\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e8\u0026ndash;10 mg/dL\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e10\u0026ndash;12 mg/dL\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;8 mg/dL\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e8\u0026ndash;10 mg/dL\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e10\u0026ndash;12 mg/dL\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMACE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.5(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.2(24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.4(24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.4(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.9(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.2(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.008*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMajor Bleeding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.3(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.2(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecondary Endpoints %(n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.3(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5(13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5(14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.4(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.4(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCV Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.3(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.9(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.3(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReinfarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.4(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.422\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.1(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIschemic Stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.4(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.855\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHemorrhagic Stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003eCV: Cardiovascular, MACE: Major adverse cardiovascular events\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u0026bull; Continuous variables are given as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u0026bull; Median, interquartile range (range, [25% percentile-75% percentile])\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTablo 4\u0026nbsp;\u003c/strong\u003eAnalysis of the Impact of Clinical and Demographic Characteristics on MACE Using Univariate and Multivariate Cox Regression\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.53763440860215%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eUnivariate Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.659574468085108%\" valign=\"top\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.5531914893617%\" valign=\"top\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003cp\u003eLower-Upper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.78723404255319%\" valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e1.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.974-1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.931\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender (male)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.426-1.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e1.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.993-1.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDislipidemia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e1.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.887 \u0026nbsp; 3.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.428 \u0026nbsp; 1.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.516\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.884\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.440-1.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.730\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of CAD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.165-1.556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of PCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e6.970\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e3.385-14.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of CABG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e7.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e3.834-15.581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e2.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e1.418-4.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e1.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.942-4.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent Smoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.415-1.432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.410\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOPD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e2.450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.963-6.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh Precise DAPT Score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e1.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e1.023-1.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eKillip III-IV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e1.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.341 \u0026nbsp; 3.839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eShock at admission\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.021-5.834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength of stay in the hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.684-0.983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.032\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLVEF (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.932-0.980\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of ACS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e1.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.024-2.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.345\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBetablocker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e1.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.361-4.548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.702\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eACEi/ARB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.462-1.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.886\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of vessels with severe stenosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.195-3.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.755\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCulprit vessel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.063-1.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e1.408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.020-97.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.874\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.53763440860215%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eMultivariate Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.659574468085108%\" valign=\"top\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.5531914893617%\" valign=\"top\"\u003e\n \u003cp\u003e95% CI\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eLower-Upper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.78723404255319%\" valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of PCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e3.961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e2.366-6.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of CABG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e5.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e3.250-8.732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e2.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e1.338-3.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh Precise DAPT Score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e1.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e1.013-1.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength of stay in the hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.768-1.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.46236559139785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLVEF (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.978494623655914%\" valign=\"top\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50537634408602%\" valign=\"top\"\u003e\n \u003cp\u003e0.9560.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.053763440860216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eACEI/ARB: Angiotensin-converting enzyme inhibitors/Angiotensin receptor blockers, BMI: Body mass index, CABG: Coronary artery By-pass grafting, CAD: Coronary artery disease, CHF: Congestive heart failure, COPD: Chronic obstructive pulmonary disease, DM: Diabetes mellitus, HT: Hypertension, LVEF: Left ventricular ejection fraction, MI: myocardial infarction, PCI: Percutaneous intervention.\u003c/p\u003e\n\u003cp\u003ePatients receiving clopidogrel and ticagrelor were analysed in terms of their effect on primary and secondary endpoints, divided into 3 groups according to hemoglobin levels as \u0026le;\u0026thinsp;8, 8\u0026ndash;10, and 10\u0026ndash;12 mg/dL. Hemoglobin level was \u0026le;\u0026thinsp;8 mg/dL in 59 (9%) patients, 8\u0026ndash;10 mg/dL in 295 (45%) patients, and 10\u0026ndash;12 mg/dL in 302 (46%) patients. There was no significant difference in primary efficacy and safety outcomes and secondary outcomes according to the anemia subgroups in patients receiving clopidogrel treatment. MACE and major hemorrhage were significantly higher in patients treated with ticagrelor than in patients with a hemoglobin level of \u0026le;\u0026thinsp;8 mg/dL (p\u0026thinsp;=\u0026thinsp;0.008 and p\u0026thinsp;=\u0026thinsp;0.002, respectively). In patients receiving ticagrelor treatment, MACE was observed in 36.4% of patients and major bleeding in 18.2% at 1 year. When the secondary endpoints were examined, it was observed that the difference in MACE rates was mainly due to total mortality and cardiovascular mortality. In patients with hemoglobin level\u0026thinsp;\u0026le;\u0026thinsp;8 mg/dL, 36.4% total mortality and 27.3% cardiovascular mortality were observed at 1 year. Since fewer patients received ticagrelor treatment, reinfarction was observed in only 2 patients, while stroke was not observed in any patient (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003ePatients with and without MACE in the clopidogrel and ticagrelor treatment groups were compared according to their hemoglobin levels. Hemoglobin levels were similar according to MACE outcome in patients receiving clopidogrel treatment (MACE (-) 9.91 mg/dL, MACE (+) 9.55 mg/dL, p\u0026thinsp;=\u0026thinsp;0.39). Hemoglobin levels in patients receiving ticagrelor treatment were statistically significantly lower in MACE (+) patients than in MACE (-) patients (MACE (-) 9.90 mg/dL, MACE (+) 8.60 mg/dL, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eThe effects of clinical and demographic characteristics of the patients on MACE were analysed by univariate and multivariate Cox Regression analysis. In the univariate analysis, PCI history, CABG history, CRF, high PRECISE DAPT score, length of stay in hospital, and LVEF were determined as factors affecting MACE (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, p\u0026thinsp;=\u0026thinsp;0.002, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively). In the Multivariate Cox regression analysis, the relationship between the length of stay in hospital and MACE lost its significance, while PCI history, CABG history, CRF, high PRECISE DAPT score and LVEF were determined as factors affecting MACE (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, p\u0026thinsp;=\u0026thinsp;0.002, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.037, respectively) (Table\u0026nbsp;4)\u003c/p\u003e\n\u003cp\u003eSurvival analysis was conducted to compare patients across three hemoglobin level categories: \u0026le;8, 8\u0026ndash;10, and 10\u0026ndash;12 mg/dL. Additionally, patients were stratified into two groups based on hemoglobin levels below and above 9.7 mg/dL, a threshold impacting MACE as determined by ROC analysis. MACE was more common in patients with hemoglobin levels below 8 than in the other two groups. However, MACE was observed at similar rates in the other two groups (Log Rank p\u0026thinsp;=\u0026thinsp;0.11). Patients with a hemoglobin level below 9.7 had a higher MACE than patients with a hemoglobin level above 9.7 (Log Rank p\u0026thinsp;=\u0026thinsp;0.03) (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eIn the analysis of survival according to the P2Y12 treatment group, 1-year MACE and major hemorrhage were similar in the clopidogrel and ticagrelor groups (Log Rank p\u0026thinsp;=\u0026thinsp;0.76 for MACE; Log Rank p\u0026thinsp;=\u0026thinsp;0.89 for major hemorrhage) (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\n\u003cp\u003eIn the study, 154 (23.5%) patients were 75 years or older. MACE was observed in 17 patients and major hemorrhage was observed in 4 patients within 1 year. In these patients, survival analysis was performed in terms of 1 year MACE and major hemorrhage compared to the P2Y12 treatment group. In patients with anemia over 75 years of age, 1st year MACE rates were found to be similar in both groups (Log Rank p\u0026thinsp;=\u0026thinsp;0.74), while 1st year major hemorrhage was higher in patients who received ticagrelor treatment (Log Rank p\u0026thinsp;=\u0026thinsp;0.04) (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAnemia is associated with short and long-term mortality in both stable coronary artery disease and acute coronary syndrome (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). It has been shown in various studies that this increase in mortality is associated with both adverse ischemic events and bleeding (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, we investigated the effects of clopidogrel or ticagrelor treatment in terms of adverse ischemic events and bleeding in anemic patients admitted with a diagnosis of acute coronary syndrome. Clinical and demographic characteristics were similar in both groups.\u003c/p\u003e \u003cp\u003eWe found that 1-year MACE and major bleeding were similar in P2Y12 treatment group. Similarly, both groups had similar total mortality, cardiovascular mortality, reinfarction, and hemorrhagic stroke.\u003c/p\u003e \u003cp\u003eWhen we looked at the subgroup analysis, we examined the patients in 3 groups according to hemoglobin levels as \u0026le;\u0026thinsp;8, 8\u0026ndash;10 and 10\u0026ndash;12 mg/dL. There was no significant difference in primary efficacy and safety outcomes and secondary outcomes according to the anemia subgroups in patients receiving clopidogrel treatment. MACE and major hemorrhage were significantly higher in patients treated with ticagrelor than in patients with a hemoglobin level of \u0026le;\u0026thinsp;8 mg/dL.\u003c/p\u003e \u003cp\u003eThe PRECISE-DAPT score is a prediction algorithm for out-of-hospital bleeding in patients who have undergone elective or urgent percutaneous coronary intervention and are treated with dual antiplatelet therapy (DAPT). It includes 5 parameters: age, creatinine clearance, hemoglobin, white blood cell count (WBC), and a history of previous bleeding. Patients with a PRECISE-DAPT score of 25 or higher are considered high-risk, and it has been shown that in these patients, extended DAPT therapy is not associated with ischemic benefits and may even be linked to an increased risk of bleeding events (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Anemia is an important component of the PRECISE-DAPT score, but its impact on the score is significant only when hemoglobin levels are between 10 and 12 mg/dL. Scores do not change when hemoglobin levels are below 10 mg/dL.\u003c/p\u003e \u003cp\u003eIn this study, when we generally compared patients with hemoglobin levels below 12 mg/dL who were receiving clopidogrel and ticagrelor, we did not observe any differences in terms of ischemic events and bleeding events. However, in the subgroup analysis, we found statistically higher rates of both MACE and major bleeding in patients with hemoglobin levels of 8 mg/dL or lower who were given ticagrelor. We believe that this finding should be considered, especially in anemic patients starting ticagrelor, when their PRECISE-DAPT score is not high. We would like to emphasize the importance of being more cautious and protective when starting ticagrelor in patients with hemoglobin levels of 8 mg/dL or lower. When we calculate the PRECISE-DAPT score for anemic patients, especially those who are young and have mild kidney insufficiency, we find that they fall into the moderate-risk category. However, based on the results of this study, we believe that this score may have limitations, especially in anemic patients who are to be given ticagrelor, and it might be prudent to consider being more cautious or starting clopidogrel instead. De-escalation studies also support this hypothesis. In the study conducted by Satoshi and colleagues, it was demonstrated that de-escalation of clopidogrel with potent antiplatelet agents reduced the risk of bleeding (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Similarly, in the TOPIC study, patients who underwent de-escalation of DAPT with clopidogrel after 1 month of treatment with potent antiplatelet agents had a lower risk of bleeding (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The fact that de-escalation studies reduce bleeding risk without affecting ischemic events is consistent with our study, where we did not observe a difference in ischemic events when comparing clopidogrel to ticagrelor. In fact, in our study, the greater reliability of clopidogrel in patients with hemoglobin levels of 8 or lower is also consistent with de-escalation studies.\u003c/p\u003e \u003cp\u003eIn our study, among anemic patients presenting with ACS, we did not find any differences in terms of the primary endpoint, which was MACE and bleeding between the P2Y12 inhibitor groups. Both groups had similar rates of total mortality, cardiovascular mortality, reinfarction, and hemorrhagic stroke. Only patients receiving clopidogrel had a higher incidence of ischemic stroke, while no ischemic strokes were observed in those receiving ticagrelor. In the PLATO study, the primary endpoint, which included vascular-related death, MI, or stroke, and the secondary endpoint, which included death, MI, or stroke for any reason, were found to be statistically significantly lower in patients receiving ticagrelor compared to those receiving clopidogrel (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). When analyzed individually, MI and vascular-related death were less frequent in the ticagrelor group, while there was no significant difference between the two groups in terms of stroke incidence (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In the PLATO study, subgroup analyses for anemic patients were not reported. Therefore, it is difficult to explain why our study found no difference in ischemic events, except for ischemic stroke, compared to the PLATO study. Perhaps if such an analysis had been conducted in the PLATO study, the results we observed in our study could have been better discussed. Regarding ischemic stroke, in the PLATO study, no difference was observed between the two groups, while in our study, there was a higher incidence of ischemic stroke in patients receiving clopidogrel. Anemia is not only a well-known risk factor for bleeding but is also associated with a deficiency in the quantity and quality of platelets produced in the bone marrow, and it has been shown that these dysfunctional platelets can lead to thrombosis (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Considering that ticagrelor is a more potent antiplatelet agent, this result may not be too surprising.\u003c/p\u003e \u003cp\u003eWhen we subgrouped patients based on their hemoglobin levels, we did not find any differences in terms of primary efficacy and safety outcomes, as well as secondary endpoints, among patients receiving clopidogrel. However, in patients with hemoglobin levels of 8 mg/dL or lower who were treated with ticagrelor, we observed a statistically significant increase in MACE and major bleeding events at 1 year. When we evaluated secondary endpoints, we found that this difference in MACE was particularly associated with total mortality and cardiovascular mortality. Reinfarction occurred in only 2 patients, and there were no observed cases of stroke. These data strongly suggest that patients with hemoglobin levels of 8 mg/dL or lower are at very high risk for bleeding and cardiovascular mortality. We concluded that deep anemia, especially in patients with hemoglobin levels of 8 mg/dL or lower, leads to increased thrombogenic activity (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), and in patients with deep anemia, the more potent ticagrelor increases the risk of bleeding.\u003c/p\u003e"},{"header":"CONCLUSİON","content":"\u003cp\u003eIn conclusion, this study offers valuable insights into the management of anemic patients with acute coronary syndrome and the choice between clopidogrel and ticagrelor for antiplatelet therapy. While overall outcomes were similar between the two medications in the broader patient population, a critical distinction emerged when analyzing patients with hemoglobin levels of 8 mg/dL or lower. In this subgroup, ticagrelor was associated with a statistically significant increase in both major adverse cardiovascular events (MACE) and major bleeding events at the one-year mark. This finding underscores the need for cautious consideration when prescribing ticagrelor to anemic patients, particularly those with severe anemia. It highlights the importance of personalized medicine in tailoring antiplatelet therapy to individual patient profiles and underscores the significance of hematologic factors in cardiovascular outcomes. Further research in this area may pave the way for more precise and effective treatment strategies for this vulnerable patient population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe authors declared that this study has received no financial support.\u003c/p\u003e\n\u003cp\u003eDeclaration of Interests: The authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eInformed Consent:\u0026nbsp;\u003c/strong\u003eWritten informed consent was obtained from all participants who participated in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eData supporting the findings of this study are available from the corresponding author, upon reasonable request, via the e-mail address\u0026nbsp;[email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003eT.O. and B.Y. conceived of the presented idea. F.P. and Ş.A. developed the theory and performed the computations. \u0026nbsp;F.P., Z.K. and F.D. verified the analytical methods. B.Y. and T.O. supervised the findings of this work. All authors discussed the results and contributed to the final manuscript.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSarnak, M. J., Tighiouart, H., Manjunath, G., MacLeod, B., Griffith, J., Salem, D., \u0026amp; Levey, A. S. (2002). Anemia as a risk factor for cardiovascular disease in The Atherosclerosis Risk in Communities (ARIC) study. \u003cem\u003eJournal of the American College of Cardiology\u003c/em\u003e, \u003cem\u003e40\u003c/em\u003e(1), 27\u0026ndash;33.\u003c/li\u003e\n\u003cli\u003eGuerrero, C., Garay, A., Ariza-Sol\u0026eacute;, A., Formiga, F., Raposeiras-Roub\u0026iacute;n, S., Abu-Assi, E., D\u0026apos;Ascenzo, F., Kinnaird, T., Manzano-Fern\u0026aacute;ndez, S., Alegre, O., S\u0026aacute;nchez-Salado, J. C., Lorente, V., Templin, C., Velicki, L., Xanthopoulou, I., Cerrato, E., Rognoni, A., Boccuzzi, G., Omed\u0026egrave;, P., Montabone, A., \u0026hellip; Cequier, \u0026Aacute;. (2018). Anemia in patients with acute coronary syndromes treated with prasugrel or ticagrelor: Insights from the RENAMI registry. \u003cem\u003eThrombosis research\u003c/em\u003e, \u003cem\u003e167\u003c/em\u003e, 142\u0026ndash;148. \u003c/li\u003e\n\u003cli\u003eWallentin, L., Becker, R. C., Budaj, A., Cannon, C. P., Emanuelsson, H., Held, C., Horrow, J., Husted, S., James, S., Katus, H., Mahaffey, K. W., Scirica, B. M., Skene, A., Steg, P. G., Storey, R. F., Harrington, R. A., PLATO Investigators, Freij, A., \u0026amp; Thors\u0026eacute;n, M. (2009). Ticagrelor versus clopidogrel in patients with acute coronary syndromes. \u003cem\u003eThe New England journal of medicine\u003c/em\u003e, \u003cem\u003e361\u003c/em\u003e(11), 1045\u0026ndash;1057.\u003c/li\u003e\n\u003cli\u003eVerdoia, M., Rolla, R., Pergolini, P., Gioscia, R., Nardin, M., Negro, F., Viglione, F., Suryapranata, H., Kedhi, E., \u0026amp; Luca, G. D. (2021). Low hemoglobin predicts high-platelet reactivity and major cardiovascular ischemic events at long-term follow-up among ACS patients receiving dual antiplatelet therapy with ticagrelor. \u003cem\u003eCatheterization and Cardiovascular Interventions\u003c/em\u003e, \u003cem\u003e98\u003c/em\u003e(7), 1309-1316.\u003c/li\u003e\n\u003cli\u003eNa, K., Qiu, M., Ma, S., Li, Y., Li, J., Liu, R., Zhang, J., \u0026amp; Han, Y. (2022). Impact of Ticagrelor vs. Clopidogrel in Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention After Risk Stratification With the CHA2DS2-VASc Score. \u003cem\u003eFrontiers in Cardiovascular Medicine\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eTjerkaski, J., Jernberg, T., Alfredsson, J., Erlinge, D., James, S., Lindahl, B., Mohammad, M. A., Omerovic, E., Venetsanos, D., \u0026amp; Szummer, K. (2022). Comparison between ticagrelor and clopidogrel in high bleeding risk patients with acute coronary syndrome. \u003cem\u003eEuropean Heart Journal\u003c/em\u003e, \u003cem\u003e43\u003c/em\u003e(Supplement_2).\u003c/li\u003e\n\u003cli\u003eCharpentier, T., Ferdynus, C., Lair, T., Cordier, C., Brulliard, C., Valance, D., Emery, M., Caron, M., Allou, N., \u0026amp; Allyn, J. (2020). Bleeding risk of ticagrelor compared to clopidogrel in intensive care unit patients with acute coronary syndrome: A propensity-score matching analysis. \u003cem\u003ePLoS ONE\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(5).\u003c/li\u003e\n\u003cli\u003eSzummer, K., Montez-Rath, M. E., Alfredsson, J., Erlinge, D., Lindahl, B., Hofmann, R., Ravn-Fischer, A., Svensson, P., \u0026amp; Jernberg, T. (2020). Comparison Between Ticagrelor and Clopidogrel in Elderly Patients With an Acute Coronary Syndrome: Insights From the SWEDEHEART Registry. \u003cem\u003eCirculation\u003c/em\u003e, \u003cem\u003e142\u003c/em\u003e(18), 1700\u0026ndash;1708.\u003c/li\u003e\n\u003cli\u003eSabatine MS, Morrow DA, Giugliano RP, Burton PB, Murphy SA, McCabe CH, Gibson CM, Braunwald E. Association of hemoglobin levels with clinical out- comes in acute coronary syndromes. Circulation 2005;111:2042\u0026ndash;2049. \u003c/li\u003e\n\u003cli\u003eBassand, J. P., Afzal, R., Eikelboom, J., Wallentin, L., Peters, R., Budaj, A., ... \u0026amp; Yusuf, S. (2010). Relationship between baseline haemoglobin and major bleeding complications in acute coronary syndromes. European heart journal, 31(1), 50-58.\u003c/li\u003e\n\u003cli\u003eCosta F, van Klaveren D, James S, Heg D, Raber L, Feres F, Pilgrim T, Hong MK, Kim HS, Colombo A, Steg G, Zanchin T, Palmerini T, Wallentin L, Bhatt DL, Stone GW, Windecker S, Steyerberg EW, Valgimigli M. Derivation and valida- tion of the predicting bleeding complications in patients undergoing stent implantation and subsequent dual antiplatelet therapy (PRECISE-DAPT) score: a pooled analysis of individual-patient datasets from clinical trials. Lancet 2017;389:1025\u0026ndash;1034.\u003c/li\u003e\n\u003cli\u003eShoji, Satoshi, et al. \u0026quot;De-escalation of dual antiplatelet therapy in patients with acute coronary syndromes.\u0026quot; Journal of the American College of Cardiology 78.8 (2021): 763-777.\u003c/li\u003e\n\u003cli\u003eCuisset, Thomas, et al. \u0026quot;Benefit of switching dual antiplatelet therapy after acute coronary syndrome: the TOPIC (timing of platelet inhibition after acute coronary syndrome) randomized study.\u0026quot; European heart journal 38.41 (2017): 3070-3078.\u003c/li\u003e\n\u003cli\u003eMahaffey, Kenneth W., et al. \u0026quot;Ticagrelor compared with clopidogrel by geographic region in the Platelet Inhibition and Patient Outcomes (PLATO) trial.\u0026quot; Circulation 124.5 (2011): 544-554.\u003c/li\u003e\n\u003cli\u003eRedfors, Bj\u0026ouml;rn, et al. \u0026quot;Quantifying ischemic risk after percutaneous coronary intervention attributable to high platelet reactivity on clopidogrel (from the assessment of dual antiplatelet therapy with drug-eluting stents study).\u0026quot; The American Journal of Cardiology 120.6 (2017): 917-923.\u003c/li\u003e\n\u003cli\u003eIbrahim, Homam, et al. \u0026quot;Association of immature platelets with adverse cardiovascular outcomes.\u0026quot; Journal of the American College of Cardiology 64.20 (2014): 2122-2129.\u003c/li\u003e\n\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":"Ticagrelor, clopidogrel, anemia, acute coronary syndrome","lastPublishedDoi":"10.21203/rs.3.rs-3397394/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3397394/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e This study aimed to investigate the potential impact of ticagrelor and clopidogrel treatment on cardiovascular outcomes in patients with anemia and acute coronary syndrome (ACS), and to discern the optimal therapeutic approach for this vulnerable patient population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eA retrospective research design was employed, involving patients diagnosed with ST-segment elevation myocardial infarction (STEMI) or non-ST-segment elevation myocardial infarction (NSTEMI) between 2014 and 2021. Inclusion criteria necessitated a hemoglobin level below 12 mg/dL and a minimum 12-month P2Y12 inhibitor treatment. Comprehensive clinical, biochemical, and echocardiographic data were collected from the hospital's electronic repository. The primary efficacy endpoint was major adverse cardiovascular events (MACE), encompassing total mortality, cardiovascular mortality, reinfarction, ischemic stroke, and hemorrhagic stroke. Major hemorrhage was the primary safety endpoint. Secondary outcomes included total mortality, CV mortality, reinfarction, ischemic stroke, and hemorrhagic stroke.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003ePatients treated with ticagrelor (n = 118) and clopidogrel (n = 538) were compared. No significant difference was observed in major adverse cardiovascular events (MACE) and major bleeding between ticagrelor and clopidogrel treatment groups (MACE: clopidogrel 10.0% vs. ticagrelor 11.0%, p=0.75; major bleeding: clopidogrel 2.8%, ticagrelor 2.5%, p=0.88). Patients with hemoglobin levels ≤8 mg/dL demonstrated significantly higher MACE and major bleeding rates in the ticagrelor group (p=0.008 and p=0.002, respectively). Among patients aged ≥75 years, ticagrelor treatment was associated with a higher risk of major bleeding (p=0.04).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion \u003c/strong\u003eTicagrelor and clopidogrel demonstrated similar efficacy and safety outcomes in anemic ACS patients over a one-year period. Ticagrelor showed superiority in reducing ischemic events in anemic ACS patients. However, specific caution is warranted in patients with hemoglobin ≤8 mg/dL and those aged ≥75 years, where ticagrelor treatment may confer a higher risk of adverse events. This study provides insights into tailoring antiplatelet therapy for anemic ACS patients and offers guidance for personalized treatment strategies.\u003c/p\u003e","manuscriptTitle":"Effect of Ticagrelor or Clopidogrel Treatment on 1-Year Cardiovascular Outcomes in Anemic Patients with Acute Coronary Syndrome","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-10-06 20:24:08","doi":"10.21203/rs.3.rs-3397394/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":"a7e5a8c7-c011-4174-aa11-407da96cd94b","owner":[],"postedDate":"October 6th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-11-07T07:44:54+00:00","versionOfRecord":[],"versionCreatedAt":"2023-10-06 20:24:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3397394","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3397394","identity":"rs-3397394","version":["v1"]},"buildId":"ApUGefWb6u5IBVtyqm6d5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}