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 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 and Objectives: This study aims to investigate the effect of Type 2 diabetes mellitus (DM) on nutritional status in acute coronary syndrome (ACS) patients and its relationship with various metabolic and hematologic parameters. Materials and Methods: A retrospective and cross-sectional design was used to analyze 485 acute coronary syndrome (ACS) patients who underwent angiography at Fethi Sekin City Hospital between 1 January 2020 and 1 January 2025. Clinical data, biochemical parameters (hemogram, glucose, creatinine, uric acid, lactate dehydrogenase (LDH), albumin, and cholesterol levels) were retrospectively analyzed. The Prognostic Nutrition Index (PNI) and CONUT score were calculated manually. Results: A total of 485 patients were included in this study. Patients were divided into two groups: patients with DM (n = 167) and patients without DM (n = 318). Glucose levels (p < 0.001) and triglyceride levels (p = 0.014) were significantly higher in patients with diabetes, while LDL cholesterol and total cholesterol levels were lower (p < 0.01). In addition, hemoglobin (p < 0.001), albumin (p = 0.010), and PNI scores (p = 0.014) were lower in patients with diabetes. Although CONUT scores were higher in patients with diabetes, this difference was not statistically significant (p = 0.267). Significant differences were observed in lipid profile and inflammation parameters in STEMI and NSTEMI subgroups, especially in patients with diabetes. In particular, triglyceride and neutrophil levels were found to be higher in NSTEMI patients among patients with diabetes. Conclusions: The PNI score may be a useful prognostic tool for predicting cardiovascular complications and determining treatment strategies in acute coronary syndrome patients with diabetes mellitus in whom nutritional status, inflammation, and lipid metabolism are significantly correlated.

Early identification of anatomically significant coronary artery disease (CAD) remains a major clinical challenge despite advances in cardiovascular diagnostics. Novel circulating biomarkers may improve risk stratification and diagnostic discrimination beyond conventional parameters. We investigated the diagnostic utility of four emerging biomarkers—Phoenixin-14, Syntenin-1, Alamandine, and Cerebellin-1—for the assessment of CAD severity. In this prospective observational study, 90 participants undergoing coronary angiography were categorized into three groups: severe CAD (≥70% stenosis; n = 30), non-obstructive/non-critical CAD (<70% stenosis; n = 30), and angiographically normal controls (n = 30). Patients with acute coronary syndrome, diabetes mellitus, prior coronary revascularization, cardiomyopathy, or significant systemic disease were excluded. Circulating biomarker concentrations were quantified using the enzyme-linked immunosorbent assay. Comparative analyses, correlation testing, and receiver operating characteristic (ROC) analyses were performed to evaluate discriminatory performance. Circulating Phoenixin-14 concentrations progressively declined across the control, non-critical CAD, and severe CAD groups [40.1 (29.0–49.7) vs. 24.4 (18.5–30.1) vs. 16.7 (13.4–19.0) pg/mL, respectively; p < 0.001]. Phoenixin-14 demonstrated outstanding discrimination for severe CAD, achieving an area under the ROC curve (AUC) of 0.969 (95% CI, 0.888–0.997), with 86.7% sensitivity and 96.7% specificity at a threshold of ≤20.2 pg/mL. Diagnostic performance was substantially lower for Syntenin-1 (AUC, 0.795), Alamandine (AUC, 0.661), and Cerebellin-1 (AUC, 0.597). Phoenixin-14 also showed robust discrimination for non-critical CAD (AUC, 0.832). Biomarker concentrations exhibited correlations with metabolic indices while remaining largely independent of traditional cardiovascular risk factors. Among the evaluated novel circulating biomarkers, Phoenixin-14 demonstrated superior diagnostic performance for both obstructive and non-obstructive CAD, markedly outperforming Syntenin-1, Alamandine, and Cerebellin-1. These findings identify Phoenixin-14 as a promising candidate biomarker for CAD severity assessment and clinical risk stratification. Larger multicenter studies are warranted to validate these exploratory findings and determine their incremental value in contemporary cardiovascular practice.