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Background: Routine coronary artery disease (CAD) secondary prevention strategies target standard modifiable cardiovascular risk factors (SMuRFs), which include: diabetes mellitus, dyslipidemia, hypertension, and smoking. However, a significant proportion of patients with acute coronary syndrome (ACS) present without any SMuRFs. The angiographic severity of disease in this population has not yet been investigated., Methods: After propensity score matching of patients without SMuRFs and patients with ≥1 SMuRFs (ratio 1:3), we used zero-inflated negative binomial regression modeling to investigate the relationship of SMuRF-less status with the angiographic severity of CAD, as measured by the SYNTAX score. Survival analysis was performed to investigate differences in all-cause mortality at 30 days and at the end of follow-up period., Results: We analyzed 534 patients presenting with ACS who underwent coronary angiography. Of them, 56 (10.5%) presented without any SMuRF. After propensity score matching, the median SYNTAX score was 13.8 (IQR 0-22.1) in 56 SMuRF-less patients and 14 (IQR 5-25) in 166 patients with ≥1 SMuRFs. SMuRF-less status was associated with increased odds of zero SYNTAX score [zero-part model: odds ratio = 2.11, 95% confidence interval (CI): 1.03-4.33], but not with decreased SYNTAX score among patients with non-zero SYNTAX score (count-part model: incidence rate ratio = 0.99, 95% CI: 0.79-1.24); the overall distribution of the SYNTAX score was similar between the two groups ( p = 0.26). The 30-day risk for all-cause mortality was higher for SMuRF-less patients compared to patients with ≥1 SMuRFs [hazard ratio (HR) = 3.58, 95% CI: 1.30-9.88]; however, the all-cause mortality risk was not different between the two groups over a median 1.7-year follow-up (HR = 1.72, 95% CI: 0.83-3.57)., Conclusion: Among patients with ACS, the absence of SMuRFs is associated with increased odds for non-obstructive CAD and with increased short-term mortality rates., Competing Interests: 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., (Copyright © 2022 Papazoglou, Farmakis, Zafeiropoulos, Moysidis, Karagiannidis, Stalikas, Kartas, Stamos, Sofidis, Doundoulakis, Giannopoulos, Giannakoulas and Sianos.)

Our study aims to develop a data-driven framework utilizing heterogenous electronic medical and clinical records and advanced Machine Learning (ML) approaches for: ( i ) the identification of critical risk factors affecting the complexity of Coronary Artery Disease (CAD), as assessed via the SYNTAX score; and ( ii ) the development of ML prediction models for accurate estimation of the expected SYNTAX score. We propose a two-part modeling technique separating the process into two distinct phases: (a) a binary classification task for predicting, whether a patient is more likely to present with a non-zero SYNTAX score; and (b) a regression task to predict the expected SYNTAX score accountable to individual patients with a non-zero SYNTAX score. The framework is based on data collected from the GESS trial (NCT03150680) comprising electronic medical and clinical records for 303 adult patients with suspected CAD, having undergone invasive coronary angiography in AHEPA University Hospital of Thessaloniki, Greece. The deployment of the proposed approach demonstrated that atherogenic index of plasma levels, diabetes mellitus and hypertension can be considered as important risk factors for discriminating patients into zero- and non-zero SYNTAX score groups, whereas diastolic and systolic arterial blood pressure, peripheral vascular disease and body mass index can be considered as significant risk factors for providing an accurate estimation of the expected SYNTAX score, given that a patient belongs to the non-zero SYNTAX score group. The experimental findings utilizing the identified set of important risk factors indicate a sufficient prediction performance for the Support Vector Machine model (classification task) with an F -measure score of ~0.71 and the Support Vector Regression model (regression task) with a median absolute error value of ~6.5. The proposed data-driven framework described herein present evidence of the prediction capacity and the potential clinical usefulness of the developed risk-stratification models. However, further experimentation in a larger clinical setting is needed to ensure the practical utility of the presented models in a way to contribute to a more personalized management and counseling of CAD patients., Competing Interests: FC is employed by Labnet Laboratories. The remaining 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., (Copyright © 2022 Mittas, Chatzopoulou, Kyritsis, Papagiannopoulos, Theodoroula, Papazoglou, Karagiannidis, Sofidis, Moysidis, Stalikas, Papa, Chatzidimitriou, Sianos, Angelis and Vizirianakis.)

Background: Angiographic detection of thrombus in STEMI is associated with adverse outcomes. However, routine thrombus aspiration failed to demonstrate the anticipated benefit. Hence, management of high coronary thrombus burden remains challenging. We sought to assess for the first time extracted thrombotic material characteristics utilizing micro-computed tomography (micro-CT). Methods: One hundred thirteen STEMI patients undergoing thrombus aspiration were enrolled. Micro-CT was undertaken to quantify retrieved thrombus volume, surface, and density. Correlation of these indices with angiographic and electrocardiographic outcomes was performed. Results: Mean aspirated thrombus volume, surface, and density (±standard deviation) were 15.71 ± 20.10 mm 3 , 302.89 ± 692.54 mm 2 , and 3139.04 ± 901.88 Hounsfield units, respectively. Aspirated volume and surface were significantly higher ( p < 0.001) in patients with higher angiographic thrombus burden. After multivariable analysis, independent predictors for thrombus volume were reference vessel diameter (RVD) ( p = 0.011), right coronary artery (RCA) ( p = 0.039), and smoking ( p = 0.027), whereas RVD ( p = 0.018) and RCA ( p = 0.019) were predictive for thrombus surface. Thrombus volume and surface were independently associated with distal embolization ( p = 0.007 and p = 0.028, respectively), no-reflow phenomenon ( p = 0.002 and p = 0.006, respectively), and angiographically evident residual thrombus ( p = 0.007 and p = 0.002, respectively). Higher thrombus density was correlated with worse pre-procedural TIMI flow ( p < 0.001). Patients with higher aspirated volume and surface developed less ST resolution ( p = 0.042 and p = 0.023, respectively). Conclusions: Angiographic outcomes linked with worse prognosis were more frequent among patients with larger extracted thrombus. Despite retrieving larger thrombus load in these patients, current thrombectomy devices fail to deal with thrombotic material adequately. Further studies of novel thrombus aspiration technologies are warranted to improve patient outcomes. Clinical Trial Registration: QUEST-STEMI trial ClinicalTrials.gov number: NCT03429608 Date of registration: February 12, 2018. The study was prospectively registered., Competing Interests: 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., (Copyright © 2021 Karagiannidis, Papazoglou, Sofidis, Chatzinikolaou, Keklikoglou, Panteris, Kartas, Stalikas, Zegkos, Girtovitis, Moysidis, Stefanopoulos, Koupidis, Hadjimiltiades, Giannakoulas, Arvanitidis, Michaelson, Karvounis and Sianos.)