Background: Oxidative stress is crucial in the pathogenesis of atherosclerosis and acute myocardial infarction (AMI). Under the generic terms “oxidative stress” (OS), many biomarkers belonging to different pathways have been proposed. Aim: To compare the levels of recently proposed OS-related parameters in acute coronary syndromes (ACS) and stable coronary artery disease (CAD), to evaluate their effectiveness as additive risk or illness indicators of stable and acute ischemic events, and their response over time during the course of AMI. Methods: 76 ACS, 77 CAD patients, and 63 controls were enrolled in the study. Different OS-related biomarkers, including reactive oxygen metabolites (ROM), the total antioxidant capacity (OXY), nitrite/nitrate (final nitric oxide products, NO_x), and Lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1), were evaluated. Moreover, time response during AMI course (admission, and 6, 12, 18, 24, 36, and 48 hours after, T0-T6, respectively) and correlation with traditional cardiovascular (CV) risk factors (age, gender, hypertension, diabetes mellitus, dyslipidemia, smoking habit) were also assessed. Results: Over time, ROM progressively increased while OXY and NO_x decreased. Kinetics of LOX-1 during AMI shows that this biomarker boosts early during the acute event (T1 and T2) and then progressively decreases, being significantly lower from T0 to T6. Different OS-related biomarkers were differentially associated with CV risk factors and CAD or ACS presence. Conclusion: Differences in OS-related biomarkers (between groups, according to the response over time during AMI, and to the presence of CV risk factors) confirmed OS involvement in the transition from healthy status to stable CAD and ACS, although evidencing the heterogeneous nature of redox processes. In future, a multi-marker panel including different biomarkers and pathways of oxidative stress could be evaluated as an additive tool to be used in the CV prevention, diagnosis, patient stratification, and treatment.

Background: New-onset postoperative atrial fibrillation (NOAF) is the most prevalent arrythmia after cardiac surgery with a significant clinical and economic impact. Therefore, simple and practical biomarkers for NOAF prediction remain a clinical priority. Increasing evidence indicates that malnutrition is linked to postoperative complications, including the onset of atrial fibrillation. The Prognostic Nutritional Index (PNI), which reflects the immunonutritional and inflammatory status through serum albumin concentration and lymphocyte count, has emerged as a reliable prognostic indicator in cardiovascular disease. The present study aimed to investigate the association between PNI and the development of NOAF in patients undergoing surgical aortic valve replacement (SAVR). Methods: A total of 241 consecutive patients who underwent AVR for severe aortic stenosis or regurgitation were enrolled in this study. The population was stratified into two groups according to the development of NOAF (NOAF group) or the lack thereof (no NOAF group). Results: In both univariate and multivariate logistic regression analyses adjusted for several established NOAF determinants, age and PNI, both as continuous variables, were independently associated with NOAF in both univariate (OR = 1.03; CI 95% = 1.01–1.06, p = 0.009, and OR = 0.9; CI 95% = 0.8–0.9, p = 0.01, respectively) and multivariate models (OR = 1.02; CI 95% = 1.01–1.06, p = 0.05, and OR = 0.9; CI 95% = 0.8–0.9, p = 0.03, respectively). When PNI was analyzed by tertiles, patients in the lowest tertile (PNI < 41.5) showed a significantly higher risk of developing NOAF at both univariate (OR = 1.9; CI 95% = 1.2–2.8, p = 0.004) and multivariate analysis (OR = 1.6; CI 95% = 1–2.6, p = 0.03), whereas age lost statistical significance (OR = 1.0; 95% CI = 0.9–1.05; p = 0.06). Furthermore, when the study population was divided into two groups based on the median age (70 years), PNI values differed significantly between NOAF and no NOAF patients only in patients under 70 years (p = 0.01). In this younger subgroup, PNI remained an independent predictor of NOAF, both when considered as a continuous variable (OR = 0.86; CI 95% = 0.74–0.98, p = 0.02), and nominal variable (PNI < 41.5, OR = 0.88; CI 95% = 0.80–0.97, p = 0.01). Conclusions: Overall, these findings identify PNI as an independent predictor of NOAF following SAVR, particularly in patients younger than 70 years. This study underlines the potential clinical value of preoperative nutritional assessment for risk stratification. Incorporating nutritional parameters such as PNI into current predictive models may enhance the accuracy of prognostic evaluation and support targeted perioperative management strategies.

Background: Several blood biomarkers have shown a major role in predicting major adverse complications (MACs) in patients who have undergone cardiac surgery. Here, we aimed to investigate the possible role of the blood urea nitrogen (BUN) to serum albumin ratio (BAR) and the inflammatory prognostic index (IPI) in predicting major adverse complication after surgical aorta valve replacement (SAVR). Methods: The clinical, echocardiographic, and clinical-chemistry laboratory data of 195 patients who underwent SAVR were evaluated. The post-surgical MACs (death, surgical re-exploration, myocardial infarction and cerebral ischemia) during the hospitalization were recorded. Univariate and multivariate logistic regression analyses were studied by comparing the basic clinical features, echocardiographic parameters, and patients’ hematological indices between patients with or without MACs. Results: The mean age was 66.1 years, and 62.5% were males. Logistic regression analysis showed that the left atrium volume (LAV), BAR, and IPI as either continuous or categorical variables were independently associated with MACs. Moreover, we found a combined effect of higher LAV with a higher value of BAR or IPI. Combined higher levels of LAV and BAR increased the risk of developing MACs by 9.8 (CI 95% = 2.8–34.3, p = 0.0003), while higher values of LAV and IPI increased the risk of developing MACs by 4.5. Conclusions: Higher levels of BAR and IPI, alone or in combination with higher LAVs, showed an independent predictive value of MACs after SAVR. These findings strongly support the importance of evaluating easily available biomarkers of the pre-operative status of patients in order to predict adverse outcomes.