Background: Even though medication and interventional therapy have improved the death rate for non-ST elevation myocardial infarction (NSTEMI) patients, these patients still have a substantial residual risk of cardiovascular events. Early identification of high-risk individuals is critical for improving prognosis, especially in this patient group. The focus of recent research has switched to finding new related indicators that can help distinguish high-risk patients. For this purpose, we examined the relationship between the pan-immune-inflammation value (PIV) and the severity of coronary artery disease (CAD) defined by the SYNTAX score (SxS) in NSTEMI patients. Methods: Based on the SxS, CAD patients were split into three groups. To evaluate the risk variables of CAD, multivariate logistic analysis was employed. Results: The PIV (odds ratio: 1.003; 95% CI: 1.001–1.005; p = 0.005) was found to be an independent predictor of a high SxS in the multivariate logistic regression analysis. Additionally, there was a positive association between the PIV and SxS (r: 0.68; p < 0.001). The PIV predicted the severe coronary lesion in the receiver-operating characteristic curve analysis with a sensitivity of 91% and specificity of 81.1%, using an appropriate cutoff value of 568.2. Conclusions: In patients with non-STEMI, the PIV, a cheap and easily measured laboratory variable, was substantially correlated with a high SxS and the severity of CAD.

Background: Accumulating evidence from clinical trials, large registries, and meta-analyses of population studies shows that increased Blood Pressure Variability (BPV) is predictive of Cardiovascular (CV) outcomes, independently of the average Blood Pressure (BP) values. One of the mechanisms explaining the relationship between BPV and target organ damage is the inflammatory response. The Systemic Immune Inflammation Index (SII), which relies on peripheral blood cell counts, including platelets, neutrophils, and lymphocytes, has emerged as a predictor of prognosis and outcomes in various diseases. The aim of this study was to investigate the association of the SII with Ambulatory Blood Pressure Variability (ABPV) in newly diagnosed hypertensive patients. Methods: This study was designed as a cross-sectional observational study. A total of 1606 consecutive newly diagnosed Hypertension (HT) patients were included in the study. The population was evaluated across 3 different categories according to HT grades (5 groups), eligibility for antihypertensive therapy (2 groups) and ABPV levels (2 groups). Results: Significant differences were observed between ABPV groups in terms of Neutrophil to Lymphocyte ratio, Platelet to Lymphocyte ratio, glucose, SII, high-sensitive CRP, HT grade, Inter-Ventricular Septum, Posterior Wall thickness, and Left Ventricular Mass (p < 0.005). There was a significant relationship between SII and ABPV (r: 0.619, p < 0.05). At the cutoff value of 580.49, SII had 77% sensitivity and 71% specificity for ABPV > 14 (AUC: 0.788). Conclusions: SII may assist in developing an early treatment approach to minimize complications in patients with high ABPV who are at a higher risk of CV events.

Background and Objectives: The neutrophil-percentage-to-albumin ratio (NPAR) has been recognized as an independent risk factor for cardiovascular diseases. In our study, we investigated whether the NPAR is associated with the formation of coronary collateral circulation (CCC) in patients with chronic coronary syndrome (CCS). Materials and Methods: A total of 681 patients with CCS were included in this study. Of these patients, 571 had chronic total occlusion in at least one major vessel and developed collateral vessels. In total, 110 patients were in the control group, who had CCS but did not have complete occlusion in a major vessel and did not develop collateral vessels. Patients with collateral vessels on coronary angiography were divided into two groups according to the Rentrop score: poor CCC (Rentrop 0–1) and good CCC (Rentrop 2–3). Blood samples were taken for the NPAR and other biochemical parameters in all patients during hospitalization. The NPAR was calculated as the neutrophil-percentage-to-albumin ratio. Results: The group of patients with poor CCC had a higher white blood count (WBC), neutrophil, C-reactive protein (CRP), neutrophil–lymphocyte ratio (NLR), CRP/albumin ratio (CAR), and NPAR values than patients with good CCC (p < 0.001, for all). Multivariate logistic regression analysis showed that high NPAR levels were an independent predictor of poor CCC (OR: 2.79, 95% CI:1.7–4.6, p < 0.001), accompanied by neutrophil, CRP, CAR, and NLR levels. In the receiver operator characteristic curve (ROC analysis), the cut-off value for the NPAR to indicate poor CCC was 1.78 with a sensitivity of 76.6% and specificity of 81.4% (area under ROC curve = 0.804 95% CI (0.753–0.854), p < 0.001). Conclusions: We demonstrated that the NPAR may be an independent predictor of poor CCC development in clinical practice.

Background/Objectives: Coronary artery ectasia (CAE) is characterized by abnormal dilation of the coronary arteries and is associated with adverse cardiovascular events. Inflammation is believed to play a pivotal role in the development and progression of CAE. The neutrophil-percentage-to-albumin ratio (NPAR) has emerged as a novel marker of systemic inflammation and may serve as a useful tool in the evaluation of CAE. This study aimed to assess the association between the NPAR and CAE and compare its predictive value to established inflammatory biomarkers, including highly sensitive C-reactive protein (hsCRP), the neutrophil-to-lymphocyte ratio (NLR), and the platelet-to-lymphocyte ratio (PLR). Methods: A retrospective analysis was conducted on 5212 patients who underwent elective coronary angiography between March 2019 and March 2023. The cohort included 165 patients with isolated CAE and 180 controls with normal coronary anatomy. Inflammatory markers and their correlation with CAE were analyzed using logistic regression models and receiver operating characteristic (ROC) analysis to determine predictive performance. Results: The NPAR was significantly elevated in the CAE group compared to the controls (p < 0.001). Multivariate analysis identified the NPAR (OR: 2.14, p = 0.003) and CRP (OR: 1.53, p = 0.02) as independent predictors of CAE. ROC analysis demonstrated that the NPAR had superior predictive value over CRP (AUC: 0.725 vs. 0.635). Additionally, the NPAR showed a strong correlation with CAE severity based on the Markis classification, with higher NPAR values associated with more advanced disease. Conclusions: The NPAR is an independent predictor of CAE and outperforms CRP in predicting both the presence and severity of the condition. As a cost-effective and accessible biomarker, the NPAR may enhance the clinical assessment of CAE and provide valuable insights into its inflammatory underpinnings. Further prospective studies are warranted to validate these findings and explore the potential of the NPAR in risk stratification and management of CAE patients.