Abstract
Objectives: Risk stratification in coronary artery bypass grafting (CABG) remains challenging despite existing models. The Endothelial Activation and Stress Index (EASIX), originally developed for hematological conditions, has shown promise in various medical fields as a predictor of adverse outcomes. EASIX, calculated from lactate dehydrogenase, creatinine, and platelet count, reflects endothelial dysfunction and systemic inflammation. This study investigates EASIX’s potential in predicting mortality and morbidity in patients undergoing CABG. Methods: A total of 475 patients undergoing isolated CABG between January 2017 and June 2020 were retrospectively analyzed. EASIX scores were calculated from pre-operative blood samples. Patients were stratified based on an EASIX cut-off value of 1.16. Results: Patients with EASIX ≥ 1.16 were older and had more comorbidities. They experienced higher 30-day mortality (5.0% vs. 0.8%, p = 0.004), increased wound infections (6.7% vs. 2.5%, p = 0.035), and more frequent prolonged ventilation (9.2% vs. 4.2%, p = 0.040). The long-term survival analysis showed significant differences at 3 years (p = 0.030) and 5 years (p < 0.001). EASIX demonstrated moderate discriminatory power for long-term survival (AUROC 0.669, 95% CI: 0.598–0.740, p < 0.001). Importantly, the multivariable analysis revealed EASIX as an independent risk factor for long-term mortality, even after adjusting for traditional risk factors and comorbidities (HR: 2.65, 95% CI: 1.59–4.42, p < 0.001). Conclusions: EASIX ≥ 1.16 was associated with postoperative morbidity and poorer long-term survival in patients undergoing CABG. This easily calculable score could enhance risk stratification and guide personalized postoperative management.
1. Introduction
The Endothelial Activation and Stress Index (EASIX) has emerged as a promising prognostic tool across various medical disciplines. This composite index, derived from serum lactate dehydrogenase (LDH), platelet count, and creatinine levels, serves as a surrogate marker for systemic inflammation and renal stress.
Originally developed as a prognostic marker in hematological malignancies, EASIX was first utilized in patients undergoing allogeneic hematopoietic stem-cell transplantation (alloSCT), where an EASIX score ≥ 3 was associated with a more than twofold increase in transplant-related mortality [1]. Beyond alloSCT, EASIX has demonstrated prognostic value in diffuse large B-cell lymphoma [2] and multiple myeloma [3].
Beyond hematology, EASIX has gained relevance in infectious diseases, particularly during the COVID-19 pandemic, where it was proposed as a simple and universal prognostic index for survival in infected patients [4,5]. More recently, its applicability has extended to traumatic brain injury, where it has been identified as an effective predictor of mortality [6].
Preoperative risk assessment plays an important role in optimizing outcomes for patients undergoing coronary artery bypass grafting (CABG). Given the complexity and inherent risks associated with cardiac surgery, a comprehensive evaluation that integrates clinical scoring systems, biomarkers, and frailty assessments is essential.
Traditional risk models, such as the Society of Thoracic Surgeons (STS) Score and EuroSCORE II, have long been established as the cornerstone of preoperative evaluation in cardiac surgery [7,8].
In addition to traditional risk scores, circulating biomarkers may offer valuable complementary insights. Biomarkers such as high-sensitivity troponin, natriuretic peptides, and C-reactive protein have been associated with myocardial injury, hemodynamic stress, and systemic inflammation, respectively [9], and have shown predictive value for prognosis in cardiovascular disease [10,11,12]. Preoperative frailty assessment, with systemic inflammation regarded as a key pathogenetic mechanism, has become increasingly important in risk stratification prior to CABG [13,14].
A study published in 2024 highlighted its potential as a predictor of mortality in coronary artery disease (CAD) patients. Elevated EASIX predicted independently mortality in CAD [15].
The analyzed cohort did not include patients undergoing CABG, a group typically characterized by more extensive macroangiopathy. The prognostic value of EASIX demonstrated in this study pertains specifically to patients with less advanced disease managed medically or with percutaneous coronary intervention (PCI) and may not be generalizable to surgically treated populations.
The EASIX-Score is derived from routine laboratory parameters; it offers a cost-effective, objective, and easily measurable approach to evaluate inflammation, endothelial stress, and renal function, and therefore, it might be an interesting tool in preoperative risk stratification.
2. Material and Methods
From January 2017 to June 2020, 475 consecutive patients scheduled for elective or urgent isolated CABG at the Department of Cardiac, Vascular, and Endovascular Surgery at Paracelsus Medical University in Salzburg, Austria, were enrolled in the study. Patients with acute coronary syndrome with ST elevation myocardial infarction (STEMI), unstable angina as defined in the (ESC) Guidelines for the management of acute coronary syndromes [16], and patients requiring concomitant procedures were excluded in advance to ensure a homogenous cohort. Patient demographics are summarized in Table 1.
Table 1.
Baseline characteristics between the low and high EASIX score group.
The local ethics committee of the state of Salzburg granted approval for the study under protocol number 1168/2020 on 25 November 2020. Data management adhered to the ethical principles set forth in the Declaration of Helsinki and the (ICH-GCP) guidelines (International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use—Good Clinical Practice). The requirement for informed consent was waived.
Patient information was obtained from the ORBIS electronic medical records system (Version 08043301.04110DACHL, Dedalus Healthcare GmbH, Bonn, Germany). Long-term mortality was assessed with follow-up calls.
2.1. Patient Sample Collection and EASIX Score
Blood samples from patients were collected 1–3 days before CABG surgery. All samples were obtained following standard venipuncture procedures and processed immediately to ensure the stability of key biomarkers. Laboratory parameters relevant to the EASIX score were measured using standardized clinical chemistry assays in an accredited laboratory.
The Endothelial Activation and Stress Index (EASIX) was calculated using routine laboratory parameters, specifically lactate dehydrogenase (LDH), creatinine, and platelet count (EASIX = LDH (U/L) × Creatinine (mg/dL)/Platelet Count (109/L)).
2.2. Surgical Procedure
The indication for CABG was ischemic heart disease, determined by a specialized multidisciplinary heart team consisting of a cardiac surgeon, cardiologist, and cardiac anesthesiologist in accordance with current guidelines [17]. The procedures were performed either by senior surgeons or by residents under supervision. Most patients underwent median sternotomy under general anesthesia. Graft selection and perioperative medication management followed established guideline recommendations [18].
3. Statistics
All statistical analyses and data visualizations were performed using the SPSS software (Version 25.0, SPSS Inc., Armonk, NY, USA). The Kolmogorov–Smirnov–Lilliefors test was utilized to assess the distribution of variables. Continuous variables exhibiting a normal distribution are presented as mean ± standard deviation (SD) and were compared using an unpaired Student’s t-test. For variables that do not follow a normal distribution, data are expressed as the median with an interquartile range (IQR) and were analyzed via the Mann–Whitney U test. Categorical variables are reported as frequencies or percentages and were evaluated using the chi-squared test. Patients were divided into quartiles based on their EASIX values, with individuals in the highest quartile identified as particularly vulnerable to increased overall mortality and cardiovascular events.
To assess the predictive value of EASIX for long-term outcomes in CABG surgery, an area under the receiver operating characteristic (AUROC) curve was generated. The area under the curve (AUC), sensitivity, specificity, and Youden Index (YI) was determined. Univariate Cox regression analysis was employed to investigate whether various clinical characteristics (e.g., sex, age, diabetes) were associated with an elevated risk of mortality in relation to AS severity.
A Kaplan–Meier survival analysis was conducted to examine differences in short- and long-term mortality after CABG based on varying EASIX cut-off values, with log-rank tests and corresponding risk numbers included. Additionally, a univariate Cox regression analysis was performed to identify clinical factors associated with long-term mortality across the patient cohort. To enhance comparability, metric data underwent z-transformation. Variables with a p-value ≤ 0.100 in univariate analysis were incorporated into a subsequent multivariable Cox regression model to determine independent mortality predictors, utilizing backward elimination for model refinement.
A p-value of < 0.050 was regarded as statistically significant in all analyses.
A comprehensive post hoc power analysis using G*Power 3.1 [19] confirmed that the study achieved a statistical power exceeding 95%, considering an allocation ratio of 3:1. This high-power level underscores the study’s ability to detect meaningful differences or significant effects between groups, thereby minimizing the risk of a Type II error (failing to identify an existing effect). The analysis was conducted with a conventional alpha (α) level of 0.05, the standard threshold for statistical significance, assuming a medium effect size (d = 0.5).
4. Results
4.1. Determination of Cut-Off Value EASIX ≥ 1.16
Due to lack of evidence for a reliable cut-off value in our study population, we explored a potential cut-off value with two methods: Patients were stratified into quartiles based on their EASIX scores. The higher quartile were patients with an EASIX score of 1.16 and above.
Furthermore, an AUROC curve analysis for EASIX as a predictor of long-term survival following CABG was conducted (Figure 1). The AUC was 0.669 (95% CI: 0.598–0.740, p < 0.001), indicating a moderate discriminative ability. The optimal cut-off value for the EASIX score was determined to be 1.16—identical to the value of the calculated higher quartile of the study cohort—with a sensitivity of 0.50 and a specificity of 0.80. The Youden Index (YI) was calculated at 0.30, indicating a moderate ability of the EASIX score to discriminate between patients regarding to survival outcomes.
Figure 1.
The AUROC curve for EASIX as a predictor of long-term survival following CABG.
4.2. Baseline Characteristics
Male patients represented the majority of the cohort (79.8%), with no significant difference in sex distribution between the groups (p = 0.167). Patients with an EASIX ≥ 1.16 were older (74 vs. 68 years p < 0.001), were more likely to have peripheral artery disease (PAOD), 20.8% vs. 9.6%, p = 0.001), atrial fibrillation (AF, 15.0% vs. 6.5%, p = 0.004), and prior myocardial infarction (MI, 42.5% vs. 31.3%, p = 0.025).
As expected, renal function and related parameters included in the EASIX score were significantly different.
The EuroSCORE II was significantly higher in the higher EASIX group (2.6 ± 3.1 vs. 1.5 ± 1.4, p < 0.001).
Further baseline characteristics are shown in Table 1.
4.3. Intraoperative Data
There was no significant difference regarding the use of the heart–lung machine (p = 0.063) between the groups. Aortic cross-clamp time was shorter (45.0 ± 27.5 min vs. 50.0 ± 28.0 min, p = 0.028), arterial bypass grafts were fewer (median: 1.0 vs. 2.0, p = 0.001), and venous bypass grafts were more frequent (median: 2.0 vs. 1.0, p = 0.030) in the EASIX ≥ 1.16 group. Table 2 shows the intraoperative data.
Table 2.
The intraoperative data of the low EASIX group vs. high EASIX group.
4.4. Postoperative Outcomes
Patients with EASIX levels ≥ 1.16 demonstrated a significantly higher 30-day mortality compared to those with EASIX < 1.16 (5.0% vs. 0.8%; p = 0.004). The incidence of wound infections was significantly higher in the EASIX ≥ 1.16 group (6.7% vs. 2.5% p = 0.035) as well as prolonged ventilation (9.2% vs. 4.2% p = 0.040) and ICU stay (standard criteria for discharging were applied and followed by the staff, p= 0.002). There was no difference regarding the incidence of myocardial infarction defined as type 5 myocardial infarction (myocardial infarction associated with coronary artery bypass grafting according to the 4th universal definition of myocardial infarction, 1.1% vs. 3.3% p = 0.104) and major neurological events (modified Rankin score ≥ 2 at 90 days postoperatively 1.7% vs. 1.7% p = 0.986). Other postoperative outcome parameters are shown in Table 3.
Table 3.
The in-hospital outcome parameters between the low vs. high EASIX group.
4.5. Mid- and Long-Term Outcomes
Figure 2 shows a Kaplan–Meier survival curve demonstrating a significant difference in overall survival between patients with EASIX scores below and above the cut-off value of 1.16. While 1-year survival rates were not significantly different (p = 0.165), survival differences became evident at 3 years (p = 0.030) and were highly significant at 5 years (p < 0.001). Overall survival across the entire follow-up period was significantly worse for patients with an EASIX score ≥ 1.16 (log-rank p < 0.001).
Figure 2.
A Kaplan–Meier survival curve demonstrating a significant lower overall survival in patients with EASIX ≥ 1.16.
Figure 3 presents a Cox proportional hazards regression analysis, evaluating HR for overall mortality across several subgroups in patients with EASIX ≥ 1.16. Independent of the selected patient characteristics, a consistently significant increase in HR values was observed for an EASIX score ≥ 1.16. Notably, even patients younger than 70 years had a 2.5-fold higher risk of long-term mortality after CABG when their EASIX score exceeded 1.16 (p = 0.025).
Figure 3.
A Cox proportional hazards regression analysis, evaluating HR for overall mortality across several subgroups in patients with EASIX ≥ 1.16.
4.6. EASIX as Independent Risk Factor for Long-Term Mortality in CABG
Another Cox proportional hazard regression analysis, presented in Table 4, identified several factors associated with general long-term mortality in patients after CABG. EASIX emerged as a significant independent risk factor for long-term mortality, with a HR of 3.063 (95% CI: 1.904–4.928, p < 0.001) in the univariate analysis, which remained robust in the multivariable model (HR: 2.652, 95% CI: 1.593–4.415, p < 0.001). Age was significant in the univariate analysis (HR: 1.420, 95% CI: 1.086–1.856, p = 0.010), but this association did not persist after adjusting for other variables (HR: 1.109, 95% CI: 0.795–1.549, p = 0.542), suggesting it is confounded by other clinical factors. Other significant predictors in the multivariable model included BMI (HR: 1.336, 95% CI: 1.027–1.738, p = 0.031), hemoglobin (HR: 0.725, 95% CI: 0.586–0.897, p = 0.003), and LVEF (HR: 1.379, 95% CI: 1.077–1.767, p = 0.001), while variables such as EuroSCORE II, arterial hypertension, and prior comorbidities lost significance after adjustment.
Table 4.
A univariate and multivariable Cox proportional hazard regression analysis.
5. Discussion
This study demonstrates that EASIX might be a valuable prognostic tool for predicting long-term mortality. In our cohort, an EASIX score ≥ 1.16 was associated with significantly higher 30-day mortality, increased incidence of wound infections, prolonged ventilation and ICU stay, as well as worse long-term survival outcomes increasingly apparent at 3 and 5 years post-CABG.
Initially designed for hematological disorders [1,2,3], the EASIX score has demonstrated exceptional adaptability across multiple medical fields. Our study extends its applicability to coronary artery disease undergoing CABG procedure, where it demonstrates a predictive value for both short-term complications and long-term mortality. The AUROC of 0.669 for long-term survival prediction indicates moderate discriminatory power, suggesting that EASIX could be a useful addition to existing risk stratification tools in CABG patients.
Patients with EASIX ≥ 1.16 were typically older and had a higher prevalence of comorbidities such as peripheral artery disease, atrial fibrillation, and prior myocardial infarction. This aligns with the understanding that endothelial dysfunction and systemic inflammation, which EASIX aims to quantify, are more prevalent in older individuals and those with multiple cardiovascular risk factors [20,21]. The higher EuroSCORE II values in this group further confirm their increased surgical risk profile [8,22].
Intraoperatively, patients with elevated EASIX scores received fewer bilateral internal mammary artery (BIMA) grafts, which may reflect surgeons’ preference for less extensive procedures in higher-risk patients. The shorter cross-clamping times and fewer arterial bypasses in this group could also be attributed to a more conservative surgical approach in patients perceived to be at higher risk.
The predictive capability of EASIX for short-term survival was recently demonstrated by Sang et al. [23] in a cohort of coronary heart disease patients with over 1000 myocardial infarction patients. Notably, the calculated cut-off values were considerably higher than those in the present study, likely due to the fundamentally different patient populations analyzed (ST elevation myocardial infarction and patients with ongoing ischemia were excluded in our study).
The consistent elevation in hazard ratios across various subgroups for patients with EASIX ≥ 1.16 suggests that the prognostic value of EASIX is independent of these traditional risk factors. These findings align with the study by Finke et al. [15]. Elevated EASIX score was an independent prognostic marker for overall survival before and after coronary catheterization. Importantly, these effects remained significant after adjusting for similar confounding factors such as age, diabetes, and left ventricular function, emphasizing EASIX’s ability to reflect systemic endothelial stress beyond conventional risk factors, as it was shown in our study.
Due to its simplicity in calculation, relying on routinely collected laboratory parameters, the EASIX score might be an attractive option for clinical implementation. Future research should focus on validating these findings in larger, multi-center prospective studies and exploring how EASIX can be integrated with existing risk stratification tools to enhance perioperative decision-making and long-term patient management in cardiac surgery.
6. Limitations of the Study
This study has several limitations that should be acknowledged. First, its retrospective, single-center design introduces inherent risks of selection bias and limits the generalizability of the findings to other institutions or patient populations. Second, emergency procedures and patients undergoing concomitant cardiac surgeries were excluded, which restricts the applicability of the results to elective, isolated CABG cases. Third, while the EASIX score demonstrated moderate predictive value for short- and long-term outcomes, the study did not assess its integration with established risk models, such as EuroSCORE II or the STS risk score. Fourth, an internal validation was not conducted, which limits our ability to assess the robustness and potential overfitting of the model within our dataset. Moreover, external validation in independent, multi-center cohorts was not performed, which is necessary to confirm the robustness and transferability of these findings. Prospective studies are warranted to address these limitations and to evaluate the potential role of EASIX in enhancing existing risk stratification tools in cardiac surgery.
Author Contributions
P.K.-R.: Conceptualization; Data curation; Formal analysis; Investigation; Writing—original draft; Methodology. A.V.: Conceptualization; Writing—review and editing. K.L.: Writing—review and editing. R.S.: Writing—review and editing. R.G.: Writing—review and editing. M.L.: Conceptualization. M.H.: Writing—review and editing. E.B.: Statistics; Writing—original draft; Methodology; Formal analysis; Investigation; A.W.: Data curation; Writing—review and editing. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki and approved by the local ethics committee of the state of Salzburg, Austria (protocol code 1168/2020 and date of approval: 25 November 2020).
Informed Consent Statement
Due to the retrospective nature of the study, informed consent was waived by the ethics committee.
Data Availability Statement
The data underlying this article will be shared upon reasonable request to the corresponding author.
Conflicts of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Abbreviations
| AF | Atrial Fibrillation |
| alloSCT | Allogeneic Hematopoietic Stem-Cell Transplantation |
| AUC | Area Under the Curve |
| CABG | Coronary Artery Bypass Grafting |
| CAD | Coronary Artery Disease |
| COPD | Chronic Obstructive Pulmonary Disease |
| CV | Cardiovascular |
| EASIX | Endothelial Activation and Stress Index |
| eGFR | Estimated Glomerular Filtration Rate |
| ESC | European Society of Cardiology |
| HR | Hazard Ratio |
| ICH-GCP | International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use—Good Clinical Practice |
| LDH | Lactate Dehydrogenase |
| LVEF | Left Ventricular Ejection Fraction |
| MI | Myocardial Infarction |
| NYHA | New York Heart Association |
| PAOD | Peripheral Arterial Obstructive Disease |
| PCI | Percutaneous Coronary Intervention |
| SD | Standard Deviation |
| STEMI | ST elevation myocardial infarction |
| YI | Youden Index |
References
- Penack, O.; Luft, T.; Peczynski, C.; Benner, A.; Sica, S.; Arat, M.; Itäla-Remes, M.; Corral, L.L.; Schaap, N.P.M.; Karas, M.; et al. Endothelial Activation and Stress Index (EASIX) to predict mortality after allogeneic stem cell transplantation: A prospective study. J. Immunother. Cancer 2024, 12, e007635. [Google Scholar] [CrossRef] [PubMed]
- Park, S.; Go, S.-I.; Lee, G.-W. The Endothelial Activation and Stress Index (EASIX) score is an independent prognostic factor in patients with diffuse large B-cell lymphoma. BMC Cancer 2022, 22, 816. [Google Scholar] [CrossRef]
- Song, G.-Y.; Jung, S.-H.; Kim, K.; Kim, S.J.; Yoon, S.E.; Lee, H.S.; Kim, M.; Ahn, S.-Y.; Ahn, J.-S.; Yang, D.-H.; et al. Endothelial activation and stress index (EASIX) is a reliable predictor for overall survival in patients with multiple myeloma. BMC Cancer 2020, 20, 803. [Google Scholar] [CrossRef] [PubMed]
- Kalicińska, E.; Biernat, M.; Rybka, J.; Zińczuk, A.; Janocha-Litwin, J.; Rosiek-Biegus, M.; Morawska, M.; Waszczuk-Gajda, A.; Drozd-Sokołowska, J.; Szukalski, Ł.; et al. Endothelial Activation and Stress Index (EASIX) as an Early Predictor for Mortality and Overall Survival in Hematological and Non-Hematological Patients with COVID-19: Multicenter Cohort Study. J. Clin. Med. 2021, 10, 4373. [Google Scholar] [CrossRef]
- Luft, T.; Wendtner, C.-M.; Kosely, F.; Radujkovic, A.; Benner, A.; Korell, F.; Kihm, L.; Bauer, M.F.; Dreger, P.; Merle, U. EASIX for Prediction of Outcome in Hospitalized SARS-CoV-2 Infected Patients. Front. Immunol. 2021, 12, 634416. [Google Scholar] [CrossRef] [PubMed]
- Wang, R.; Jiang, Y.; He, M.; Xu, J. EASIX is an effective marker in predicting mortality of traumatic brain injury patients. Eur. J. Med. Res. 2024, 29, 300. [Google Scholar] [CrossRef]
- Shahian, D.M.; O’Brien, S.M.; Filardo, G.; Ferraris, V.A.; Haan, C.K.; Rich, J.B.; Normand, S.-L.T.; DeLong, E.R.; Shewan, C.M.; Dokholyan, R.S.; et al. The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 1-Coronary Artery Bypass Grafting Surgery. Ann. Thorac. Surg. 2009, 88 (Suppl. 1), S2–S22. [Google Scholar] [CrossRef]
- Biancari, F.; Vasques, F.; Mikkola, R.; Martin, M.; Lahtinen, J.; Heikkinen, J. Validation of EuroSCORE II in Patients Undergoing Coronary Artery Bypass Surgery. Ann. Thorac. Surg. 2012, 93, 1930–1935. [Google Scholar] [CrossRef]
- Thygesen, K.; Alpert, J.S.; Jaffe, A.S.; Simoons, M.L.; Chaitman, B.R.; White, H.D. Third universal definition of myocardial infarction. J. Am. Coll. Cardiol. 2012, 60, 1581–1598. [Google Scholar] [CrossRef]
- Demir, F.A.; Ersoy, I.; Yılmaz, A.Ş.; Taylan, G.; Kaya, E.E.; Aydın, E.; Karakayalı, M.; Öğütveren, M.M.; Acar, A.T.; Hidayet, Ş. Serum glucose–potassium ratio predicts inhospital mortality in patients admitted to coronary care unit. Rev. Assoc. Med. Bras. 2024, 70, e20240508. [Google Scholar] [CrossRef]
- Tanriverdi, Z.; Gungoren, F.; Tascanov, M.B.; Besli, F.; Altiparmak, I.H. Comparing the Diagnostic Value of the C-Reactive Protein to Albumin Ratio with Other Inflammatory Markers in Patients with Stable Angina Pectoris. Angiology 2020, 71, 360–365. [Google Scholar] [CrossRef]
- Karakayali, M.; Altunova, M.; Yakisan, T.; Aslan, S.; Omar, T.; Artac, I.; Ilis, D.; Arslan, A.; Cagin, Z.; Karabag, Y.; et al. A Relação entre o Índice de Imuno-Inflamação Sistêmica e Isquemia com Artérias Coronárias Não Obstrutivas em Pacientes Submetidos à Angiografia Coronária. Arq. Bras. Cardiol. 2024, 121, e20230540. [Google Scholar] [CrossRef]
- Sündermann, S.H.; Bäck, C.; Bischoff-Ferrari, H.A.; Dehbi, H.-M.; Szekely, A.; Völler, H.; Niebauer, J. Preinterventional frailty assessment in patients scheduled for cardiac surgery or transcatheter aortic valve implantation: A consensus statement of the European Association for Cardio-Thoracic Surgery (EACTS) and the European Association of Preventive Cardiology (EAPC) of the European Society of Cardiology (ESC). Eur. J. Cardio-Thorac. Surg. 2023, 64, 146–181. [Google Scholar] [CrossRef]
- Krombholz-Reindl, P.; Winkler, A.; Vötsch, A.; Hitzl, W.; Schernthaner, C.; Hecht, S.; Seitelberger, R.; Gottardi, R. Thoracic sarcopenia measured by Hounsfield unit average calculation predicts morbidity and mortality in coronary artery bypass grafting. Eur. J. Cardio-Thorac. Surg. 2024, 66, ezae303. [Google Scholar] [CrossRef] [PubMed]
- Finke, D.; Hund, H.; Frey, N.; Luft, T.; Lehmann, L.H. EASIX (endothelial activation and stress index) predicts mortality in patients with coronary artery disease. In Clinical Research in Cardiology; Springer: Berlin/Heidelberg, Germany, 2024. [Google Scholar] [CrossRef]
- Byrne, R.A.; Rossello, X.; Coughlan, J.J.; Barbato, E.; Berry, C.; Chieffo, A.; Claeys, M.J.; Dan, G.-A.; Dweck, M.R.; Galbraith, M.; et al. 2023 ESC Guidelines for the management of acute coronary syndromes. Eur. Heart J. 2023, 44, 3720–3826. [Google Scholar] [CrossRef] [PubMed]
- Luckraz, H.; Norell, M.; Buch, M.; James, R.; Cooper, G. Structure and functioning of a multidisciplinary ‘Heart Team’ for patients with coronary artery disease: Rationale and recommendations from a joint BCS/BCIS/SCTS working group. Eur. J. Cardio-Thorac. Surg. 2015, 48, 524–529. [Google Scholar] [CrossRef]
- Sousa-Uva, M.; Neumann, F.-J.; Ahlsson, A.; Alfonso, F.; Banning, A.P.; Benedetto, U.; Byrne, R.A.; Collet, J.-P.; Falk, V.; Head, S.J.; et al. 2018 ESC/EACTS Guidelines on myocardial revascularization. Eur. J. Cardio-Thorac. Surg. 2019, 55, 4–90. [Google Scholar] [CrossRef]
- Erdfelder, E.; Faul, F.; Buchner, A. GPOWER: A general power analysis program. Behav. Res. Methods 2007, 39. [Google Scholar] [CrossRef]
- Widmer, R.J.; Lerman, A. Endothelial dysfunction and cardiovascular disease. Glob. Cardiol. Sci. Pract. 2014, 2014, 43. [Google Scholar] [CrossRef]
- Pacinella, G.; Ciaccio, A.M.; Tuttolomondo, A. Endothelial Dysfunction and Chronic Inflammation: The Cornerstones of Vascular Alterations in Age-Related Diseases. Int. J. Mol. Sci. 2022, 23, 15722. [Google Scholar] [CrossRef]
- O’Boyle, F.; Mediratta, N.; Fabri, B.; Pullan, M.; Chalmers, J.; McShane, J.; Shaw, M.; Poullis, M. Long-term survival after coronary artery bypass surgery stratified by EuroSCORE. Eur. J. Cardio-Thorac. Surg. 2012, 42, 101–107. [Google Scholar] [CrossRef] [PubMed]
- Sang, M.; Ma, X.; Zhu, F.; Zhu, C.; Ying, Z. Association between endothelial activation and stress index and 30-day mortality risk in acute myocardial infarction patients: A study based on the medical information mart for intensive care-IV database. BMC Cardiovasc. Disord. 2024, 24, 699. [Google Scholar] [CrossRef] [PubMed]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).