The Impact of Coronary Artery Ectasia on the Prognosis of Patients with Acute Coronary Syndrome

The Impact of Coronary Artery Ectasia on the Prognosis of 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 The Impact of Coronary Artery Ectasia on the Prognosis of Patients with Acute Coronary Syndrome Xing Wang, Mengqu Yang, Libo Sheng, Qian Yang, Qichang Zhu, Hongwei Tian This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6999116/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 To investigate the impact of coronary artery ectasia (CAE) on the prognosis of patients with acute coronary syndrome (ACS). Methods A retrospective cohort study was conducted, including 266 patients diagnosed with ACS who underwent coronary angiography at the People’s Hospital of Ningxia Hui Autonomous Region between January 1, 2019, and January 31, 2020. Clinical data were collected, and the prognostic outcomes were analyzed. Major adverse cardiovascular events (MACE), defined as a composite of all-cause mortality, non-fatal acute myocardial infarction, unplanned revascularization, and cerebrovascular accidents, along with acute heart failure, were utilized as endpoint events. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent risk factors associated with these outcomes. Results Multivariate Cox analysis demonstrated that the presence of CAE (HR 3.75, 95% CI 1.63–8.60, P < 0.01), reduced left ventricular ejection fraction (LVEF) (HR 0.90, 95% CI 0.86–0.94, P < 0.01), and an increased number of diseased vessels (HR 1.75, 95% CI 1.06–2.87, P = 0.03) were independently associated with a significantly elevated risk of MACE in ACS patients. Furthermore, the presence of CAE (HR 17.17, 95% CI 2.60-113.27, P < 0.01) and reduced LVEF (HR 0.84, 95% CI 0.75–0.95, P = 0.01) were identified as robust predictors of an increased risk of acute heart failure in this patient population. Conclusion CAE is an independent risk factor for the occurrence of both MACE and acute heart failure in ACS patients. Additionally, reduced LVEF and an increased number of diseased vessels are independent risk factors for MACE in this population. These findings highlight the critical role of CAE and impaired left ventricular function in predicting adverse cardiovascular outcomes in ACS patients, underscoring the need for targeted therapeutic strategies and close monitoring in this high-risk subgroup. Coronary artery ectasia Acute coronary syndrome Prognosis Figures Figure 1 Figure 2 Introduction Coronary artery ectasia (CAE) is a rare cardiovascular disorder characterized by the abnormal dilation of a coronary artery segment, defined as a diameter exceeding 1.5 times that of the adjacent normal segment [ 1 ]. Its reported incidence ranges from 1.2–4.9% [ 2 ]. Although the precise pathogenesis of CAE remains incompletely understood, studies indicate that approximately 50% of adult cases are associated with atherosclerosis, sharing overlapping pathogenic mechanisms with coronary artery disease (CAD)[ 3 ] [ 2 ]. In recent years, the rising prevalence of CAD has paralleled an increased detection rate of CAE. This study aims to investigate the impact of CAE on the prognosis of patients with acute coronary syndrome (ACS). Subjects and Methods Study Population A total of 300 patients diagnosed with acute coronary syndrome (ACS) who underwent coronary angiography at the People’s Hospital of Ningxia Hui Autonomous Region between January 1, 2019, and January 31, 2020, were initially enrolled in this study. Inclusion criteria comprised: (1) age ≥ 18 years; (2) availability of complete coronary angiography imaging data; and (3) confirmed diagnosis of ACS, including ST-segment elevation myocardial infarction (STEMI), non-ST-segment elevation myocardial infarction (NSTEMI), or unstable angina (UA). Exclusion criteria were defined as follows: (1) patients with stable angina, severe valvular heart disease (n = 10), arrhythmia, or a history of severe heart failure (n = 14); (2) severe renal insufficiency (eGFR < 30 mL/min/m², n = 7) or severe hepatic dysfunction; (3) prior coronary artery bypass grafting (CABG, n = 3); and (4) a history of malignant tumors. After applying the exclusion criteria, 266 patients were included in the final analysis. Based on coronary angiography findings, the study population was stratified into two groups according to the criterion of a coronary artery segment diameter exceeding 1.5 times that of the adjacent normal segment: the coronary artery ectasia positive group (CAE (+), n = 75) and the coronary artery ectasia negative group (CAE (-), n = 191), Fig. 1 ). This stratification enabled a comparative analysis of clinical characteristics and outcomes between patients with and without CAE, providing valuable insights into the impact of CAE on ACS management and prognosis. Data Collection and Variables Comprehensive hospitalization data were collected, encompassing demographic characteristics (age, gender), comorbidities (hypertension, diabetes), smoking history, and post-discharge medication use (antiplatelet agents, anticoagulants, lipid-lowering drugs, renin-angiotensin system inhibitors, and beta-blockers). Laboratory parameters included total cholesterol, triglycerides, and low-density lipoprotein cholesterol (LDL-C). Transthoracic echocardiography was employed to measure left ventricular ejection fraction (LVEF). Additional angiographic data included the presence of coronary artery dilation, the number of diseased vessels, whether percutaneous coronary intervention (PCI) was performed, and the number of stents implanted. Follow-up data were obtained via telephone interviews or review of rehospitalization records to assess clinical outcomes, including major adverse cardiovascular events (MACE)—defined as a composite of all-cause mortality, non-fatal acute myocardial infarction, unplanned revascularization, and cerebrovascular accidents—as well as the occurrence of acute heart failure. Statistical Analysis Statistical analyses were performed using SPSS 26.0 software. Continuous variables following a normal distribution were expressed as mean ± standard deviation and compared using independent samples t-tests. Non-normally distributed continuous variables were expressed as median (Q₁, Q₃) and compared using the Wilcoxon rank-sum test. Categorical variables were expressed as frequencies (percentages) and compared using the chi-square test or Fisher’s exact test, as appropriate. Kaplan-Meier survival analysis was conducted to evaluate long-term outcomes, and univariate and multivariate Cox proportional hazards regression models were utilized to compare survival curves and adjust for potential confounding factors. A two-sided P-value < 0.05 was considered statistically significant. Results Comparison of Baseline Characteristics Between Groups Significant differences were observed between the CAE (+) and CAE (-) groups in the number of diseased vessels, number of stents implanted, utilization of percutaneous coronary intervention (PCI), and the use of antiplatelet drugs, beta-blockers, ACEI/ARB, and anticoagulants (P < 0.05). No statistically significant differences were noted in age, gender, comorbidities, laboratory parameters, left ventricular ejection fraction (LVEF), or the occurrence of endpoint events (P ≥ 0.05). Detailed results are presented in Table 1 . Table 1 Comparison of Baseline Characteristics Between the Two Groups Variable Overall (n = 266) No Coronary Dilation (n = 191) Coronary Dilation (n = 75) P-value Age, Mean ± SD 60.68 ± 11.44 60.82 ± 11.29 60.33 ± 11.87 0.75 Male, n(%) 182 (68.42) 126 (65.97) 56 (74.67) 0.17 Smoking history, n(%) 131 (49.25) 92 (48.17) 39 (52.00) 0.57 Hypertension, n(%) 168 (63.16) 119 (62.30) 49 (65.33) 0.64 Diabetes history, n(%) 74 (27.82) 53 (27.75) 21 (28.00) 0.97 Cholesterol, M (Q₁, Q₃) 4.22 (3.43, 4.96) 4.30 (3.42, 4.97) 3.99 (3.57, 4.70) 0.68 Triglycerides, M (Q₁, Q₃) 1.56 (1.10, 2.28) 1.64 (1.04, 2.30) 1.49 (1.19, 2.17) 0.95 LDL, M (Q₁, Q₃) 2.35 (1.82, 2.94) 2.37 (1.83, 2.96) 2.28 (1.82, 2.78) 0.68 LVEF, M (Q₁, Q₃) 62.40 (59.00, 65.03) 62.40 (59.75, 65.00) 62.40 (58.60, 65.10) 0.85 Number of diseased vessels, M (Q₁, Q₃) 2.00 (1.00, 3.00) 2.00 (2.00, 3.00) 2.00 (0.00, 3.00) < 0.01 Number of stents, M (Q₁, Q₃) 1.00 (0.00, 2.00) 1.00 (1.00, 2.00) 0.00 (0.00, 1.00) < 0.01 PCI performed, n(%) 205 (77.36) 169 (88.48) 36 (48.65) < 0.01 Antiplatelet drugs, n(%) < 0.01 Single antiplatelet use 41 (15.41) 13 (6.81) 28 (37.33) Dual antiplatelet use 214 (80.45) 177 (92.67) 37 (49.33) Lipid-lowering drugs, n(%) 259 (97.37) 188 (98.43) 71 (94.67) 0.19 ACEI/ARB, n(%) 178 (67.17) 137 (71.73) 41 (55.41) 0.01 Beta-blockers, n(%) 182 (68.42) 143 (74.87) 39 (52.00) < 0.01 Anticoagulants, n(%) 18 (6.77) 6 (3.14) 12 (16.00) < 0.01 Positive events, n(%) 42 (15.79) 26 (13.61) 16 (21.33) 0.12 MACE, n(%) 36 (13.53) 24 (12.57) 12 (16.00) 0.46 Acute heart failure, n(%) 6 (2.26) 2 (1.05) 4 (5.33) 0.10 All-cause death, n(%) 4 (1.50) 2 (1.05) 2 (2.67) 0.68 Non-fatal MI, n(%) 12 (4.51) 7 (3.66) 5 (6.67) 0.46 Cerebrovascular accident, n(%) 5 (1.88) 4 (2.09) 1 (1.33) 1.00 Unplanned revascularization, n(%) 15 (5.64) 11 (5.76) 4 (5.33) 1.00 Comparison of Prognosis Between Groups During the follow-up period, 36 patients (13.53%) experienced major adverse cardiovascular events (MACE), including 12 cases (16.00%) in the CAE (+) group and 24 cases (12.57%) in the CAE (-) group. All-cause mortality occurred in 4 patients (1.50%), with 2 cases (2.67%) in the CAE (+) group and 2 cases (1.05%) in the CAE (-) group. Non-fatal acute myocardial infarction was observed in 12 patients (4.51%), with 5 cases (6.67%) in the CAE (+) group and 7 cases (3.66%) in the CAE (-) group. Unplanned revascularization was performed in 15 patients (5.64%), including 4 cases (5.33%) in the CAE (+) group and 11 cases (5.76%) in the CAE (-) group. Cerebrovascular accidents occurred in 5 patients (2.05%), with 1 case (1.33%) in the CAE (+) group and 4 cases (2.09%) in the CAE (-) group. Acute heart failure was documented in 6 patients, with 4 cases (5.33%) in the CAE (+) group and 2 cases (1.05%) in the CAE (-) group. Kaplan-Meier analysis revealed significant differences in survival time distribution between the two groups when MACE (Log-rank P = 0.02), acute heart failure (Log-rank P < 0.01), and non-fatal myocardial infarction (Log-rank P = 0.03) were used as outcome indicators. No significant differences were observed for all-cause mortality, unplanned revascularization, or cerebrovascular accidents (P > 0.05). The Kaplan-Meier curves are illustrated in Fig. 2 . Analysis of Risk Factors for Prognosis in ACS Patients Univariate and multivariate Cox regression analyses were performed to identify risk factors for MACE in ACS patients. The presence of CAE (HR 3.75, 95% CI 1.63–8.60, P < 0.01), reduced left ventricular ejection fraction (HR 0.90, 95% CI 0.86–0.94, P < 0.01), and an increased number of diseased vessels (HR 1.75, 95% CI 1.06–2.87, P = 0.03) were independently associated with an elevated risk of MACE. Detailed results are presented in Table 2 . Table 2 Univariate and Multivariate Cox Regression Analysis for MACE Variable Univariate Analysis Multivariate Analysis HR (95%CI) P HR (95%CI) P Coronary Artery Ectasia 2.26(1.10 ~ 4.63) 0.03 3.75(1.63 ~ 8.60) < 0.01 Age 1.00 (0.97 ~ 1.03) 1.00 Male 1.12(0.53 ~ 2.34) 0.77 Smoking History 1.03 (0.54 ~ 1.99) 0.92 Cholesterol 1.18 (0.95 ~ 1.46) 0.14 Triglycerides 1.16 (1.05 ~ 1.28) < 0.01 1.11(1.00 ~ 1.23) 0.05 LDL Cholesterol 1.00 (0.69 ~ 1.47) 0.99 Left Ventricular Ejection Fraction 0.91 (0.87 ~ 0.94) < 0.01 0.90(0.86 ~ 0.94) < 0.01 Number of Diseased Vessels 1.94 (1.22 ~ 3.08) < 0.01 1.75(1.06 ~ 2.87) 0.03 Number of Stents Implanted 1.25 (0.88 ~ 1.79) 0.21 Antiplatelet Therapy - Monotherapy 0.21 (0.03 ~ 1.32) 0.10 - Dual Therapy 0.33 (0.08 ~ 1.40) 0.13 Lipid-Lowering Drugs 0.71 (0.10 ~ 5.18) 0.73 RAS Inhibitors 0.84 (0.42 ~ 1.70) 0.63 Beta-Blockers 1.32 (0.60 ~ 2.93) 0.49 Anticoagulation Therapy 1.81 (0.55 ~ 5.94) 0.33 Further analysis identified CAE (HR 17.17, 95% CI 2.60-113.27, P < 0.01) and reduced left ventricular ejection fraction (HR 0.84, 95% CI 0.75–0.95, P = 0.01) as independent risk factors for acute heart failure in ACS patients. Detailed results are presented in Table 3 . Table 3 Univariate and Multivariate COX Regression Analysis for Acute Heart Failure Variable Univariate Analysis Multivariate Analysis p HR (95% CI) Coronary Artery Ectasia 0.01 10.30 (1.88 ~ 56.49) Age 0.04 1.10 (1.01 ~ 1.20) Male 0.10 0.24 (0.04 ~ 1.29) Hypertension 0.33 2.89 (0.34 ~ 24.76) Diabetes 0.77 1.28 (0.23 ~ 7.00) Smoking History 0.16 0.21 (0.02 ~ 1.83) Cholesterol 0.25 1.28 (0.84 ~ 1.97) Triglycerides 0.68 1.08 (0.76 ~ 1.54) LDL Cholesterol 0.33 1.39 (0.72 ~ 2.67) Left Ventricular Ejection Fraction 0.02 0.90 (0.81 ~ 0.98) Number of Diseased Vessels 0.98 1.01 (0.41 ~ 2.50) Number of Stents Implanted 0.91 0.95 (0.37 ~ 2.44) Antiplatelet Therapy 1.00 - Lipid-Lowering Drugs 1.00 - RAS Inhibitors 0.90 0.90 (0.16 ~ 4.92) Beta-Blockers 0.80 0.80 (0.15 ~ 4.36) Anticoagulation Therapy 1.00 - Discussion The prognostic implications of coronary artery ectasia (CAE) in patients with acute coronary syndrome (ACS) remain a subject of considerable debate, with heterogeneous findings reported across various studies. Our investigation revealed a statistically significant divergence in clinical outcomes between the CAE-positive (CAE [+]) and CAE-negative (CAE [-]) cohorts (P < 0.05). Specifically, when major adverse cardiovascular events (MACE) were employed as the primary endpoint, the CAE (+) group demonstrated a markedly elevated risk of MACE compared to the CAE (-) group. Kaplan-Meier survival analysis corroborated this finding, with the CAE (+) cohort exhibiting significantly inferior survival rates (Log-rank P = 0.02). Subsequent univariate and multivariate Cox regression analyses confirmed CAE as an independent predictor of MACE in ACS patients (HR 3.75, 95% CI 1.63–8.60, P < 0.01). These findings align with prior large-scale cohort studies. For instance, a study involving 1,698 acute myocardial infarction (AMI) patients reported that CAE increased the risk of future major cardiac events (including cardiac death and non-fatal myocardial infarction) by 3.25-fold, a relationship that persisted after multivariate and propensity-matched analyses[ 4 ]. Similarly, Wang et al[ 5 ]observed consistent results in a cohort of 4,788 AMI patients, identifying CAE as an independent predictor of MACE (HR 1.597, 95% CI 1.238–2.060, P < 0.001). However, conflicting evidence exists, as some studies have failed to establish CAE as an additional risk factor in patients with coronary artery disease (CAD)[ 6 ]. For example, a retrospective cohort study comparing 203 CAE patients with 173 obstructive CAD patients found no significant difference in MACE incidence (12.4% vs. 10.4%) or cardiac mortality risk (3.3% vs. 5.2%)[ 7 ]. To elucidate the pathophysiological mechanisms underlying the heightened MACE risk in CAE patients, we conducted a detailed review of coronary angiography images. These analyses revealed a transition from laminar to turbulent blood flow in ectatic segments, a hemodynamic alteration that promotes erythrocyte aggregation and increases blood viscosity. Furthermore, emerging evidence suggests that CAE patients frequently exhibit platelet activation and coagulation system activation, both of which predispose to thrombus formation. Collectively, these factors render CAE patients more susceptible to local thrombus formation, distal microvascular obstruction, and myocardial perfusion impairment, potentially culminating in acute myocardial infarction[ 8 ]. Additionally, multiple studies[ 8 ]have documented that CAE patients often present with coronary slow flow, reduced TIMI flow grades, and increased thrombus burden. For instance, among STEMI patients undergoing primary percutaneous coronary intervention (PCI), only 64.8% of CAE patients achieved TIMI flow grade 3, significantly lower than the 88.2% observed in non-CAE patients (P < 0.001)[ 13 ]. A comprehensive evaluation of coronary angiography in 667 STEMI patients further demonstrated that CAE patients had fewer instances of TIMI flow grade II or III pre-PCI (7.4% vs. 27.5%, P = 0.001) and post-PCI (49.4% vs. 68.4%, P = 0.001). Multivariate analysis revealed that CAE increased the risk of post-PCI TIMI flow grade II by 2.239-fold (OR: 2.239; 95% CI: 1.392–3.599; P = 0.001)[ 14 ]. Moreover, a longitudinal study following 64 patients with coronary slow flow for 21 months reported that 84% experienced recurrent angina pectoris, substantiating the association between coronary slow flow and myocardial ischemia, acute coronary syndrome, and acute myocardial infarction[ 15 ]. In summary, we postulate that the elevated MACE risk (encompassing all-cause mortality, non-fatal myocardial infarction, unplanned revascularization, and cerebrovascular events) in CAE (+) patients may be attributable to altered hemodynamics, platelet activation, coagulation system activation, and coronary slow flow. Notably, few survival analyses have incorporated heart failure as an endpoint in CAE patients. Our study identified a statistically significant difference in Kaplan-Meier curves between CAE (+) and CAE (-) groups when acute heart failure was employed as the endpoint (Log-rank P < 0.01). Subsequent univariate and multivariate Cox regression analyses established CAE as an independent risk factor for acute heart failure in ACS patients (HR 17.17, 95% CI 2.60-113.27, P < 0.01). We hypothesize that the increased heart failure risk in CAE patients may be secondary to myocardial ischemia. As previously discussed, multiple studies have identified coronary slow flow in CAE patients, with some scholars proposing that slow flow may represent a novel mechanism of ischemic heart disease[ 16 ]. This hypothesis is supported by findings that CAE patients with AMI had fewer instances of TIMI flow grade III post-PCI compared to non-CAE patients. Furthermore, significantly reduced coronary flow reserve has been documented in CAE patients relative to controls. These observations collectively suggest that CAE patients experience suboptimal coronary perfusion compared to non-CAE patients, potentially predisposing to ischemic cardiomyopathy (ICM) in ACS patients with concomitant CAE[ 17 ]. Limitations Several limitations of this study warrant consideration. First, this single-center retrospective cohort study is constrained by a relatively modest sample size, which may limit its generalizability. The low prevalence of CAE and restricted sample size may compromise statistical power, potentially yielding spurious results. Second, as with many retrospective investigations, residual confounding factors may persist despite statistical adjustments, necessitating prospective studies to validate these observations. Third, the current evidence remains insufficient to definitively establish CAE as a risk factor for acute heart failure in ACS patients, underscoring the need for larger-scale clinical trials to substantiate this hypothesis. Conclusion In conclusion, our findings indicate that CAE serves as an independent risk factor for both MACE and acute heart failure in ACS patients, while left ventricular ejection fraction and the number of diseased vessels emerge as independent risk factors for MACE. These results highlight the need for heightened clinical vigilance in managing CAE patients, particularly in the context of ACS, and emphasize the importance of further research to elucidate the underlying mechanisms and optimize therapeutic strategies. Declarations Acknowledgements The authors thank all the participants for their time and effort. Authors’ contributions Study concept and design: Hongwei Tian and Xin Wang; acquisition of data: Libo Sheng and Qian Yang; analysis and interpretation of data: Qichang Zhu; drafting of the manuscript: Xing Wang; critical revision of the manuscript: Hongwei Tian. All the authors read approved the fnal manuscript. Funding This study was supported by the Special Talent Start-up Program of Ningxia Medical University (NO. XZ20200012) and the Key Research and Development Plan - Talent Introduction Special Project Foundation of Ningxia, China (NO. 2024BEH04079). Data availability The datasets generated and/or analyzed during the current study are not publicly available due to the strict management and protection requirements for patient data under hospital policies, but are available from the corresponding author upon reasonable request. Ethics approval and consent to participate All methods were carried out in accordance with the Declaration of Helsinki. This study involves human participants and was approved by the Ethics Committee of the People’s Hospital of Ningxia Hui Autonomous Region. Due to the retrospective nature of this study, written informed consent was waived by the Ethics Committee of the People’s Hospital of Ningxia Hui Autonomous Region. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Clinical trial number Not applicable Author details 1 Department of Cardiology, People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University, Yinchuan, 750002, China. 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Difference in inflammation, atherosclerosis, and platelet activation between coronary artery aneurysm and coronary artery ectasia. J THORAC DIS 2020, 12(10):5811-5821. Eitan A, Roguin A. Coronary artery ectasia: new insights into pathophysiology, diagnosis, and treatment. Coron Artery Dis 2016, 27(5):420-428. Luo Y, et al. Coronary Artery Aneurysm Differs From Coronary Artery Ectasia: Angiographic Characteristics and Cardiovascular Risk Factor Analysis in Patients Referred for Coronary Angiography. ANGIOLOGY 2016. Mood EP, et al. Ectasia and slow flow phenomena of coronary artery related to apical hypertrophic cardiomyopathy. Clinical Case Reports 2023, 11(9):6. Kaplan M, et al. Slow Flow Phenomenon Impairs the Prognosis of Coronary Artery Ectasia as Well as Coronary Atherosclerosis. BRAZ J CARDIOV SURG 2021(3). Schram H, et al. Coronary artery ectasia, an independent predictor of no-reflow after primary PCI for ST-elevation myocardial infarction. INT J CARDIOL 2018, 265:12-17. Geraiely B, et al. Angiographic Characteristics of ST-Elevation Myocardial Infarction Patients With Infarct-related Coronary Artery Ectasia Undergoing Primary Percutaneous Coronary Intervention. Critical pathways in cardiology 2018, 17(2):95-97. Beltrame J, Ganz P. The Coronary Slow Flow Phenomenon. Springer London 2013. Kaplan M, et al. Slow Flow Phenomenon Impairs the Prognosis of Coronary Artery Ectasia as Well as Coronary Atherosclerosis. Braz J Cardiovasc Surg 2021, 36(3):346-353. Akyürek M, et al. Altered coronary flow properties in diffuse coronary artery ectasia. AM HEART J 2003, 145(1):66-72. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6999116","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498340067,"identity":"fcfadbc2-5b50-4e9d-a3b6-dfcb40aaeb8d","order_by":0,"name":"Xing Wang","email":"","orcid":"","institution":"People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xing","middleName":"","lastName":"Wang","suffix":""},{"id":498340068,"identity":"8f735f60-d09d-4378-aab4-ee8642462c09","order_by":1,"name":"Mengqu Yang","email":"","orcid":"","institution":"People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mengqu","middleName":"","lastName":"Yang","suffix":""},{"id":498340069,"identity":"76ce4693-0ca8-4df2-b2ee-670fd9715be9","order_by":2,"name":"Libo Sheng","email":"","orcid":"","institution":"People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Libo","middleName":"","lastName":"Sheng","suffix":""},{"id":498340070,"identity":"99969157-4d8b-4c5f-84ac-370c3ba9cd2a","order_by":3,"name":"Qian Yang","email":"","orcid":"","institution":"People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Yang","suffix":""},{"id":498340071,"identity":"6436850c-2c66-4a63-99c7-a5de2b5d66c7","order_by":4,"name":"Qichang Zhu","email":"","orcid":"","institution":"People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qichang","middleName":"","lastName":"Zhu","suffix":""},{"id":498340072,"identity":"cdeee7b2-e40b-4322-914c-dabc41ebc158","order_by":5,"name":"Hongwei Tian","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYLACHgYJBgb2xsaHH4jXkgDUwnO42ViCBC1AQiK9TYCHGNXy0YefPXj7w0LeXPJhG9B9dnK6DQS0GJ5LMzeckyBhuHN2YtuDAoZkY7MDhLT0MJhJA/3CuOF2YruBBMOBxG2EtbB/A2mx33DzYJsEDzFa5Hl4wLYkbrjBSKQWAx6eMsk5aRLJG84kAgPZgAi/yPewb5N4Y1Nnu+H48YcPP1TYyRHUYoCqwICAcrAtDUQoGgWjYBSMghEOAKpjPsOaYTf6AAAAAElFTkSuQmCC","orcid":"","institution":"People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University","correspondingAuthor":true,"prefix":"","firstName":"Hongwei","middleName":"","lastName":"Tian","suffix":""}],"badges":[],"createdAt":"2025-06-28 17:08:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6999116/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6999116/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89066920,"identity":"0dc2bcfd-aeee-468c-aaae-0c54c12fcb3d","added_by":"auto","created_at":"2025-08-14 10:42:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":139541,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of patient inclusion in the current study. ACS, acute coronary syndrome; CAE, Coronary artery ectasia.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6999116/v1/c2693839cbf875d57376f9a8.png"},{"id":89066990,"identity":"0fdf5b0d-350f-439b-85c2-8901af28c225","added_by":"auto","created_at":"2025-08-14 10:43:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":189206,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier Survival Curves for Major Adverse Cardiovascular Events (MACE) A, Acute Heart Failure (AHF) B, Non-fatal Myocardial Infarction C, All-cause Death D, Unplanned Revascularization E, and Cerebrovascular Accident F in Patients with Coronary Artery Ectasia (CAE) vs. Those Without CAE.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6999116/v1/398ef46ba30747de18c5bc53.png"},{"id":97370762,"identity":"199fc6df-0ab4-4af2-8088-232744e48f4c","added_by":"auto","created_at":"2025-12-03 16:27:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1090479,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6999116/v1/72ca1dc8-45d9-44d9-ba6a-039cc09230c9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of Coronary Artery Ectasia on the Prognosis of Patients with Acute Coronary Syndrome","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoronary artery ectasia (CAE) is a rare cardiovascular disorder characterized by the abnormal dilation of a coronary artery segment, defined as a diameter exceeding 1.5 times that of the adjacent normal segment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Its reported incidence ranges from 1.2–4.9% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although the precise pathogenesis of CAE remains incompletely understood, studies indicate that approximately 50% of adult cases are associated with atherosclerosis, sharing overlapping pathogenic mechanisms with coronary artery disease (CAD)[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In recent years, the rising prevalence of CAD has paralleled an increased detection rate of CAE. This study aims to investigate the impact of CAE on the prognosis of patients with acute coronary syndrome (ACS).\u003c/p\u003e"},{"header":"Subjects and Methods","content":"\u003cp\u003e\u003cb\u003eStudy Population\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 300 patients diagnosed with acute coronary syndrome (ACS) who underwent coronary angiography at the People’s Hospital of Ningxia Hui Autonomous Region between January 1, 2019, and January 31, 2020, were initially enrolled in this study. Inclusion criteria comprised: (1) age ≥ 18 years; (2) availability of complete coronary angiography imaging data; and (3) confirmed diagnosis of ACS, including ST-segment elevation myocardial infarction (STEMI), non-ST-segment elevation myocardial infarction (NSTEMI), or unstable angina (UA). Exclusion criteria were defined as follows: (1) patients with stable angina, severe valvular heart disease (n = 10), arrhythmia, or a history of severe heart failure (n = 14); (2) severe renal insufficiency (eGFR \u0026lt; 30 mL/min/m², n = 7) or severe hepatic dysfunction; (3) prior coronary artery bypass grafting (CABG, n = 3); and (4) a history of malignant tumors.\u003c/p\u003e\u003cp\u003eAfter applying the exclusion criteria, 266 patients were included in the final analysis. Based on coronary angiography findings, the study population was stratified into two groups according to the criterion of a coronary artery segment diameter exceeding 1.5 times that of the adjacent normal segment: the coronary artery ectasia positive group (CAE (+), n = 75) and the coronary artery ectasia negative group (CAE (-), n = 191), Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This stratification enabled a comparative analysis of clinical characteristics and outcomes between patients with and without CAE, providing valuable insights into the impact of CAE on ACS management and prognosis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Collection and Variables\u003c/b\u003e\u003c/p\u003e\u003cp\u003eComprehensive hospitalization data were collected, encompassing demographic characteristics (age, gender), comorbidities (hypertension, diabetes), smoking history, and post-discharge medication use (antiplatelet agents, anticoagulants, lipid-lowering drugs, renin-angiotensin system inhibitors, and beta-blockers). Laboratory parameters included total cholesterol, triglycerides, and low-density lipoprotein cholesterol (LDL-C). Transthoracic echocardiography was employed to measure left ventricular ejection fraction (LVEF). Additional angiographic data included the presence of coronary artery dilation, the number of diseased vessels, whether percutaneous coronary intervention (PCI) was performed, and the number of stents implanted. Follow-up data were obtained via telephone interviews or review of rehospitalization records to assess clinical outcomes, including major adverse cardiovascular events (MACE)—defined as a composite of all-cause mortality, non-fatal acute myocardial infarction, unplanned revascularization, and cerebrovascular accidents—as well as the occurrence of acute heart failure.\u003c/p\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were performed using SPSS 26.0 software. Continuous variables following a normal distribution were expressed as mean ± standard deviation and compared using independent samples t-tests. Non-normally distributed continuous variables were expressed as median (Q₁, Q₃) and compared using the Wilcoxon rank-sum test. Categorical variables were expressed as frequencies (percentages) and compared using the chi-square test or Fisher’s exact test, as appropriate. Kaplan-Meier survival analysis was conducted to evaluate long-term outcomes, and univariate and multivariate Cox proportional hazards regression models were utilized to compare survival curves and adjust for potential confounding factors. A two-sided P-value \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eComparison of Baseline Characteristics Between Groups\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSignificant differences were observed between the CAE (+) and CAE (-) groups in the number of diseased vessels, number of stents implanted, utilization of percutaneous coronary intervention (PCI), and the use of antiplatelet drugs, beta-blockers, ACEI/ARB, and anticoagulants (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No statistically significant differences were noted in age, gender, comorbidities, laboratory parameters, left ventricular ejection fraction (LVEF), or the occurrence of endpoint events (P\u0026thinsp;\u0026ge;\u0026thinsp;0.05). Detailed results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of Baseline Characteristics Between the Two Groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall (n\u0026thinsp;=\u0026thinsp;266)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo Coronary Dilation (n\u0026thinsp;=\u0026thinsp;191)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCoronary Dilation (n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60.68\u0026thinsp;\u0026plusmn;\u0026thinsp;11.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60.82\u0026thinsp;\u0026plusmn;\u0026thinsp;11.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60.33\u0026thinsp;\u0026plusmn;\u0026thinsp;11.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e182 (68.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e126 (65.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56 (74.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking history, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e131 (49.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92 (48.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39 (52.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e168 (63.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e119 (62.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49 (65.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes history, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e74 (27.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53 (27.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21 (28.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCholesterol, M (Q₁, Q₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.22 (3.43, 4.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.30 (3.42, 4.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.99 (3.57, 4.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglycerides, M (Q₁, Q₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.56 (1.10, 2.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.64 (1.04, 2.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.49 (1.19, 2.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL, M (Q₁, Q₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.35 (1.82, 2.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.37 (1.83, 2.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.28 (1.82, 2.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLVEF, M (Q₁, Q₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.40 (59.00, 65.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62.40 (59.75, 65.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62.40 (58.60, 65.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of diseased vessels, M (Q₁, Q₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.00 (1.00, 3.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.00 (2.00, 3.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.00 (0.00, 3.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of stents, M (Q₁, Q₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00 (0.00, 2.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00 (1.00, 2.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.00 (0.00, 1.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCI performed, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e205 (77.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e169 (88.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36 (48.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntiplatelet drugs, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle antiplatelet use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41 (15.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (6.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (37.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDual antiplatelet use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e214 (80.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e177 (92.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37 (49.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLipid-lowering drugs, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e259 (97.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e188 (98.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71 (94.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACEI/ARB, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e178 (67.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e137 (71.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41 (55.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBeta-blockers, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e182 (68.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e143 (74.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39 (52.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnticoagulants, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (6.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (3.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (16.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive events, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42 (15.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (13.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (21.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMACE, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36 (13.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (12.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (16.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcute heart failure, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (2.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (5.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAll-cause death, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (1.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (2.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-fatal MI, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (4.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (3.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (6.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebrovascular accident, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (1.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (2.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnplanned revascularization, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (5.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (5.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (5.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eComparison of Prognosis Between Groups\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDuring the follow-up period, 36 patients (13.53%) experienced major adverse cardiovascular events (MACE), including 12 cases (16.00%) in the CAE (+) group and 24 cases (12.57%) in the CAE (-) group. All-cause mortality occurred in 4 patients (1.50%), with 2 cases (2.67%) in the CAE (+) group and 2 cases (1.05%) in the CAE (-) group. Non-fatal acute myocardial infarction was observed in 12 patients (4.51%), with 5 cases (6.67%) in the CAE (+) group and 7 cases (3.66%) in the CAE (-) group. Unplanned revascularization was performed in 15 patients (5.64%), including 4 cases (5.33%) in the CAE (+) group and 11 cases (5.76%) in the CAE (-) group. Cerebrovascular accidents occurred in 5 patients (2.05%), with 1 case (1.33%) in the CAE (+) group and 4 cases (2.09%) in the CAE (-) group. Acute heart failure was documented in 6 patients, with 4 cases (5.33%) in the CAE (+) group and 2 cases (1.05%) in the CAE (-) group.\u003c/p\u003e\u003cp\u003eKaplan-Meier analysis revealed significant differences in survival time distribution between the two groups when MACE (Log-rank P\u0026thinsp;=\u0026thinsp;0.02), acute heart failure (Log-rank P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and non-fatal myocardial infarction (Log-rank P\u0026thinsp;=\u0026thinsp;0.03) were used as outcome indicators. No significant differences were observed for all-cause mortality, unplanned revascularization, or cerebrovascular accidents (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The Kaplan-Meier curves are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnalysis of Risk Factors for Prognosis in ACS Patients\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUnivariate and multivariate Cox regression analyses were performed to identify risk factors for MACE in ACS patients. The presence of CAE (HR 3.75, 95% CI 1.63\u0026ndash;8.60, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), reduced left ventricular ejection fraction (HR 0.90, 95% CI 0.86\u0026ndash;0.94, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and an increased number of diseased vessels (HR 1.75, 95% CI 1.06\u0026ndash;2.87, P\u0026thinsp;=\u0026thinsp;0.03) were independently associated with an elevated risk of MACE. Detailed results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUnivariate and Multivariate Cox Regression Analysis for MACE\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eUnivariate Analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMultivariate Analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHR (95%CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHR (95%CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoronary Artery Ectasia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.26(1.10\u0026thinsp;~\u0026thinsp;4.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.75(1.63\u0026thinsp;~\u0026thinsp;8.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00 (0.97\u0026thinsp;~\u0026thinsp;1.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.12(0.53\u0026thinsp;~\u0026thinsp;2.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking History\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.03 (0.54\u0026thinsp;~\u0026thinsp;1.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCholesterol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.18 (0.95\u0026thinsp;~\u0026thinsp;1.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglycerides\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.16 (1.05\u0026thinsp;~\u0026thinsp;1.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.11(1.00\u0026thinsp;~\u0026thinsp;1.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL Cholesterol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00 (0.69\u0026thinsp;~\u0026thinsp;1.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeft Ventricular Ejection Fraction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.91 (0.87\u0026thinsp;~\u0026thinsp;0.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.90(0.86\u0026thinsp;~\u0026thinsp;0.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of Diseased Vessels\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.94 (1.22\u0026thinsp;~\u0026thinsp;3.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.75(1.06\u0026thinsp;~\u0026thinsp;2.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of Stents Implanted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.25 (0.88\u0026thinsp;~\u0026thinsp;1.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntiplatelet Therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e- Monotherapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.21 (0.03\u0026thinsp;~\u0026thinsp;1.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e- Dual Therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.33 (0.08\u0026thinsp;~\u0026thinsp;1.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLipid-Lowering Drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.71 (0.10\u0026thinsp;~\u0026thinsp;5.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRAS Inhibitors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.84 (0.42\u0026thinsp;~\u0026thinsp;1.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBeta-Blockers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.32 (0.60\u0026thinsp;~\u0026thinsp;2.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnticoagulation Therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.81 (0.55\u0026thinsp;~\u0026thinsp;5.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFurther analysis identified CAE (HR 17.17, 95% CI 2.60-113.27, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and reduced left ventricular ejection fraction (HR 0.84, 95% CI 0.75\u0026ndash;0.95, P\u0026thinsp;=\u0026thinsp;0.01) as independent risk factors for acute heart failure in ACS patients. Detailed results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUnivariate and Multivariate COX Regression Analysis for Acute Heart Failure\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnivariate Analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultivariate Analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoronary Artery Ectasia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.30 (1.88\u0026thinsp;~\u0026thinsp;56.49)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.10 (1.01\u0026thinsp;~\u0026thinsp;1.20)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.24 (0.04\u0026thinsp;~\u0026thinsp;1.29)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.89 (0.34\u0026thinsp;~\u0026thinsp;24.76)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.28 (0.23\u0026thinsp;~\u0026thinsp;7.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking History\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.21 (0.02\u0026thinsp;~\u0026thinsp;1.83)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCholesterol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.28 (0.84\u0026thinsp;~\u0026thinsp;1.97)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglycerides\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.08 (0.76\u0026thinsp;~\u0026thinsp;1.54)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL Cholesterol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.39 (0.72\u0026thinsp;~\u0026thinsp;2.67)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeft Ventricular Ejection Fraction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.90 (0.81\u0026thinsp;~\u0026thinsp;0.98)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of Diseased Vessels\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.01 (0.41\u0026thinsp;~\u0026thinsp;2.50)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of Stents Implanted\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.95 (0.37\u0026thinsp;~\u0026thinsp;2.44)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntiplatelet Therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLipid-Lowering Drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRAS Inhibitors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.90 (0.16\u0026thinsp;~\u0026thinsp;4.92)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBeta-Blockers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.80 (0.15\u0026thinsp;~\u0026thinsp;4.36)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnticoagulation Therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe prognostic implications of coronary artery ectasia (CAE) in patients with acute coronary syndrome (ACS) remain a subject of considerable debate, with heterogeneous findings reported across various studies. Our investigation revealed a statistically significant divergence in clinical outcomes between the CAE-positive (CAE [+]) and CAE-negative (CAE [-]) cohorts (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Specifically, when major adverse cardiovascular events (MACE) were employed as the primary endpoint, the CAE (+) group demonstrated a markedly elevated risk of MACE compared to the CAE (-) group. Kaplan-Meier survival analysis corroborated this finding, with the CAE (+) cohort exhibiting significantly inferior survival rates (Log-rank P\u0026thinsp;=\u0026thinsp;0.02). Subsequent univariate and multivariate Cox regression analyses confirmed CAE as an independent predictor of MACE in ACS patients (HR 3.75, 95% CI 1.63\u0026ndash;8.60, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). These findings align with prior large-scale cohort studies. For instance, a study involving 1,698 acute myocardial infarction (AMI) patients reported that CAE increased the risk of future major cardiac events (including cardiac death and non-fatal myocardial infarction) by 3.25-fold, a relationship that persisted after multivariate and propensity-matched analyses[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Similarly, Wang et al[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]observed consistent results in a cohort of 4,788 AMI patients, identifying CAE as an independent predictor of MACE (HR 1.597, 95% CI 1.238\u0026ndash;2.060, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, conflicting evidence exists, as some studies have failed to establish CAE as an additional risk factor in patients with coronary artery disease (CAD)[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. For example, a retrospective cohort study comparing 203 CAE patients with 173 obstructive CAD patients found no significant difference in MACE incidence (12.4% vs. 10.4%) or cardiac mortality risk (3.3% vs. 5.2%)[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo elucidate the pathophysiological mechanisms underlying the heightened MACE risk in CAE patients, we conducted a detailed review of coronary angiography images. These analyses revealed a transition from laminar to turbulent blood flow in ectatic segments, a hemodynamic alteration that promotes erythrocyte aggregation and increases blood viscosity. Furthermore, emerging evidence suggests that CAE patients frequently exhibit platelet activation and coagulation system activation, both of which predispose to thrombus formation. Collectively, these factors render CAE patients more susceptible to local thrombus formation, distal microvascular obstruction, and myocardial perfusion impairment, potentially culminating in acute myocardial infarction[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAdditionally, multiple studies[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]have documented that CAE patients often present with coronary slow flow, reduced TIMI flow grades, and increased thrombus burden. For instance, among STEMI patients undergoing primary percutaneous coronary intervention (PCI), only 64.8% of CAE patients achieved TIMI flow grade 3, significantly lower than the 88.2% observed in non-CAE patients (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001)[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. A comprehensive evaluation of coronary angiography in 667 STEMI patients further demonstrated that CAE patients had fewer instances of TIMI flow grade II or III pre-PCI (7.4% vs. 27.5%, P\u0026thinsp;=\u0026thinsp;0.001) and post-PCI (49.4% vs. 68.4%, P\u0026thinsp;=\u0026thinsp;0.001). Multivariate analysis revealed that CAE increased the risk of post-PCI TIMI flow grade II by 2.239-fold (OR: 2.239; 95% CI: 1.392\u0026ndash;3.599; P\u0026thinsp;=\u0026thinsp;0.001)[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Moreover, a longitudinal study following 64 patients with coronary slow flow for 21 months reported that 84% experienced recurrent angina pectoris, substantiating the association between coronary slow flow and myocardial ischemia, acute coronary syndrome, and acute myocardial infarction[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn summary, we postulate that the elevated MACE risk (encompassing all-cause mortality, non-fatal myocardial infarction, unplanned revascularization, and cerebrovascular events) in CAE (+) patients may be attributable to altered hemodynamics, platelet activation, coagulation system activation, and coronary slow flow. Notably, few survival analyses have incorporated heart failure as an endpoint in CAE patients. Our study identified a statistically significant difference in Kaplan-Meier curves between CAE (+) and CAE (-) groups when acute heart failure was employed as the endpoint (Log-rank P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Subsequent univariate and multivariate Cox regression analyses established CAE as an independent risk factor for acute heart failure in ACS patients (HR 17.17, 95% CI 2.60-113.27, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). We hypothesize that the increased heart failure risk in CAE patients may be secondary to myocardial ischemia. As previously discussed, multiple studies have identified coronary slow flow in CAE patients, with some scholars proposing that slow flow may represent a novel mechanism of ischemic heart disease[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This hypothesis is supported by findings that CAE patients with AMI had fewer instances of TIMI flow grade III post-PCI compared to non-CAE patients. Furthermore, significantly reduced coronary flow reserve has been documented in CAE patients relative to controls. These observations collectively suggest that CAE patients experience suboptimal coronary perfusion compared to non-CAE patients, potentially predisposing to ischemic cardiomyopathy (ICM) in ACS patients with concomitant CAE[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSeveral limitations of this study warrant consideration. First, this single-center retrospective cohort study is constrained by a relatively modest sample size, which may limit its generalizability. The low prevalence of CAE and restricted sample size may compromise statistical power, potentially yielding spurious results. Second, as with many retrospective investigations, residual confounding factors may persist despite statistical adjustments, necessitating prospective studies to validate these observations. Third, the current evidence remains insufficient to definitively establish CAE as a risk factor for acute heart failure in ACS patients, underscoring the need for larger-scale clinical trials to substantiate this hypothesis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, our findings indicate that CAE serves as an independent risk factor for both MACE and acute heart failure in ACS patients, while left ventricular ejection fraction and the number of diseased vessels emerge as independent risk factors for MACE. These results highlight the need for heightened clinical vigilance in managing CAE patients, particularly in the context of ACS, and emphasize the importance of further research to elucidate the underlying mechanisms and optimize therapeutic strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all the participants for their time and effort.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy concept and design: Hongwei Tian and Xin Wang; acquisition of data:\u0026nbsp;Libo Sheng and Qian Yang; analysis and interpretation of data: Qichang Zhu; drafting of the manuscript: Xing Wang; critical revision of the manuscript: Hongwei Tian. All the authors read approved the fnal manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Special Talent Start-up Program of Ningxia Medical University (NO. XZ20200012) and the Key Research and Development Plan - Talent Introduction Special Project Foundation of Ningxia, China (NO. 2024BEH04079).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to the strict management and protection requirements for patient data under hospital policies, but are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll methods were carried out in accordance with the Declaration of Helsinki. This study involves human participants and was approved by the Ethics Committee of the People\u0026rsquo;s Hospital of Ningxia Hui Autonomous Region. Due to the retrospective nature of this study, written informed consent was waived by the Ethics Committee of the People\u0026rsquo;s Hospital of Ningxia Hui Autonomous Region.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Cardiology, People\u0026apos;s Hospital of Ningxia Hui Autonomous\u0026ensp;Region, Ningxia Medical University, Yinchuan, 750002, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKawsara A, et al. Management of Coronary Artery Aneurysms. JACC Cardiovasc Interv 2018, 11(13):1211-1223.\u003c/li\u003e\n\u003cli\u003eDevabhaktuni S, et al. Coronary Artery Ectasia-A Review of Current Literature. Curr Cardiol Rev 2016, 12(4):318-323.\u003c/li\u003e\n\u003cli\u003eWozniak P, et al. Coronary Artery Aneurysm or Ectasia as a Form of Coronary Artery Remodeling: Etiology, Pathogenesis, Diagnostics, Complications, and Treatment. Biomedicines 2024, 12(9).\u003c/li\u003e\n\u003cli\u003eDoi T, et al. Coronary Artery Ectasia Predicts Future Cardiac Events in Patients With Acute Myocardial Infarction. Arteriosclerosis 2017, 37(12).\u003c/li\u003e\n\u003cli\u003eWang X, et al. Prevalence and Long-term Outcomes of Patients with Coronary Artery Ectasia Presenting with Acute Myocardial Infarction. AM J CARDIOL 2021, 156:9-15.\u003c/li\u003e\n\u003cli\u003eDemopoulos VP, et al. The natural history of aneurysmal coronary artery disease. HEART 1997, 78(2):136-141.\u003c/li\u003e\n\u003cli\u003eTimir S, et al. Risk factors and outcomes in patients with coronary artery aneurysms. AM J CARDIOL 2004.\u003c/li\u003e\n\u003cli\u003eWei W, et al. Difference in inflammation, atherosclerosis, and platelet activation between coronary artery aneurysm and coronary artery ectasia. J THORAC DIS 2020, 12(10):5811-5821.\u003c/li\u003e\n\u003cli\u003eEitan A, Roguin A. Coronary artery ectasia: new insights into pathophysiology, diagnosis, and treatment. Coron Artery Dis 2016, 27(5):420-428.\u003c/li\u003e\n\u003cli\u003eLuo Y, et al. Coronary Artery Aneurysm Differs From Coronary Artery Ectasia: Angiographic Characteristics and Cardiovascular Risk Factor Analysis in Patients Referred for Coronary Angiography. ANGIOLOGY 2016.\u003c/li\u003e\n\u003cli\u003eMood EP, et al. Ectasia and slow flow phenomena of coronary artery related to apical hypertrophic cardiomyopathy. Clinical Case Reports 2023, 11(9):6.\u003c/li\u003e\n\u003cli\u003eKaplan M, et al. Slow Flow Phenomenon Impairs the Prognosis of Coronary Artery Ectasia as Well as Coronary Atherosclerosis. BRAZ J CARDIOV SURG 2021(3).\u003c/li\u003e\n\u003cli\u003eSchram H, et al. Coronary artery ectasia, an independent predictor of no-reflow after primary PCI for ST-elevation myocardial infarction. INT J CARDIOL 2018, 265:12-17.\u003c/li\u003e\n\u003cli\u003eGeraiely B, et al. Angiographic Characteristics of ST-Elevation Myocardial Infarction Patients With Infarct-related Coronary Artery Ectasia Undergoing Primary Percutaneous Coronary Intervention. Critical pathways in cardiology 2018, 17(2):95-97.\u003c/li\u003e\n\u003cli\u003eBeltrame J, Ganz P. The Coronary Slow Flow Phenomenon. Springer London 2013.\u003c/li\u003e\n\u003cli\u003eKaplan M, et al. Slow Flow Phenomenon Impairs the Prognosis of Coronary Artery Ectasia as Well as Coronary Atherosclerosis. Braz J Cardiovasc Surg 2021, 36(3):346-353.\u003c/li\u003e\n\u003cli\u003eAky\u0026uuml;rek M, et al. Altered coronary flow properties in diffuse coronary artery ectasia. AM HEART J 2003, 145(1):66-72.\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":"Coronary artery ectasia, Acute coronary syndrome, Prognosis","lastPublishedDoi":"10.21203/rs.3.rs-6999116/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6999116/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo investigate the impact of coronary artery ectasia (CAE) on the prognosis of patients with acute coronary syndrome (ACS).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA retrospective cohort study was conducted, including 266 patients diagnosed with ACS who underwent coronary angiography at the People\u0026rsquo;s Hospital of Ningxia Hui Autonomous Region between January 1, 2019, and January 31, 2020. Clinical data were collected, and the prognostic outcomes were analyzed. Major adverse cardiovascular events (MACE), defined as a composite of all-cause mortality, non-fatal acute myocardial infarction, unplanned revascularization, and cerebrovascular accidents, along with acute heart failure, were utilized as endpoint events. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent risk factors associated with these outcomes.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eMultivariate Cox analysis demonstrated that the presence of CAE (HR 3.75, 95% CI 1.63\u0026ndash;8.60, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), reduced left ventricular ejection fraction (LVEF) (HR 0.90, 95% CI 0.86\u0026ndash;0.94, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and an increased number of diseased vessels (HR 1.75, 95% CI 1.06\u0026ndash;2.87, P\u0026thinsp;=\u0026thinsp;0.03) were independently associated with a significantly elevated risk of MACE in ACS patients. Furthermore, the presence of CAE (HR 17.17, 95% CI 2.60-113.27, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and reduced LVEF (HR 0.84, 95% CI 0.75\u0026ndash;0.95, P\u0026thinsp;=\u0026thinsp;0.01) were identified as robust predictors of an increased risk of acute heart failure in this patient population.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eCAE is an independent risk factor for the occurrence of both MACE and acute heart failure in ACS patients. Additionally, reduced LVEF and an increased number of diseased vessels are independent risk factors for MACE in this population. These findings highlight the critical role of CAE and impaired left ventricular function in predicting adverse cardiovascular outcomes in ACS patients, underscoring the need for targeted therapeutic strategies and close monitoring in this high-risk subgroup.\u003c/p\u003e","manuscriptTitle":"The Impact of Coronary Artery Ectasia on the Prognosis of Patients with Acute Coronary Syndrome","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-14 10:04:04","doi":"10.21203/rs.3.rs-6999116/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":"0d995920-e894-43cb-bc74-0dccec80a456","owner":[],"postedDate":"August 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-03T10:09:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-14 10:04:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6999116","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6999116","identity":"rs-6999116","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}