Objective: This study aimed to investigate the relationship between the Aggregate Index of Systemic Inflammation (AISI) and NRF/SF development in non-ST-elevation myocardial infarction (NSTEMI) patients undergoing percutaneous coronary intervention (PCI). Methods: This retrospective observational study included 1092 NSTEMI patients who underwent PCI. Complete blood count-derived inflammatory indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to- monocyte ratio (LMR), and AISI, were calculated before PCI. AISI was calculated using the ‘’neutrophil count x monocyte count x platelet/lymphocyte count’’ formula. NRF/ SF was defined as post- procedural TIMI flow <3 in the absence of mechanical obstruction. The study cohort was divided into 2 groups based on a median AISI score of 298. After determining the parameters associated with NRF/SF through univariate analysis, multivariate logistic regression analysis was performed to identify independent predictors. The De-Long test was conducted to assess the discriminatory ability and predictive performance of inflammation-based indices. Results: A total of 94 (8.6%) patients suffered from NRF/SF, and it was more common in patients with high AISI values compared to those with low values (p< 0.001). Considering the inflammatory parameters, higher NLR (OR= 1.347, p<0.001), higher PLR (OR= 1.003, p=0.017), higher AISI (OR= 1.003, p<0.001) and lower LMR (OR= 0.713, p<0.001) independently predicted the NRF/SF development. De-Long test analysis revealed that AISI has better predictive performance compared to other inflammation-based scores (AUC= 0.703, p<0.001). Conclusion: As an independent predictor of the NRF/SF phenomenon, AISI can serve as a practical and cost-effective biomarker for the early diagnosis of high-risk patients.

Background and Objectives: and Objectives: Admission hyperglycemia (AH) is common in acute ST-elevation myocardial infarction (STEMI) and linked to poor prognosis. The stress hyperglycemia ratio (SHR) reflects relative hyperglycemia and may more accurately predict outcomes. This study examined AH, SHR, and in-hospital stent thrombosis (ST) in STEMI patients undergoing primary percutaneous coronary intervention (p-PCI). Material and Methods: Retrospective analysis included 1034 patients. AH was defined as glucose ≥ 11.1 mmol/L at admission. SHR was calculated as admission glucose divided by estimated average glucose derived from hemoglobin A1c (HbA1c). The primary outcome was in-hospital stent thrombosis. Patients were grouped by the occurrence of in-hospital ST. Univariable, multivariable, and LASSO (Least Absolute Shrinkage and Selection Operator) logistic regression identified predictors of ST. Results: In-hospital ST occurred in 1.5% of patients. ST patients had higher Killip class, heart rate, white blood cell, platelet counts, creatinine, AH, and SHR. SHR was an independent predictor of ST (OR 3.15, 95% CI 1.88–5.27, p < 0.001), whereas AH was not (p = 0.182). Neutrophil count, correlated with WBC, was also a significant risk factor. ROC analysis showed SHR ≥ 1.26 as an optimal cutoff predicting ST. Conclusions: SHR is a strong independent predictor of in-hospital ST after STEMI, superior to AH. Monitoring and managing stress-induced hyperglycemia play a crucial role in the setting of STEMI. Further studies are needed.

Background/Objectives: Despite the contemporary management of ST segment elevation myocardial infarction (STEMI) patients, in-hospital mortality rates remain considerable. Therefore, the assessment of in-hospital mortality risk of patients with STEMI has a major role in terms of disease course. R2CHADS2, R2CHA2DS2-VASc, and R2CHA2DS2-VA scores are potential candidate for the prediction of in-hospital mortality in STEMI patients. This study aims to determine the association between R2CHADS2, R2CHA2DS2-VASc, and R2CHA2DS2-VA scores and in-hospital mortality in patients with STEMI who have undergone primary percutaneous coronary intervention (p-PCI). Methods: A total of 857 consecutive patients diagnosed with STEMI who were admitted to our hospital and treated with p-PCI were included in our study. Results: The mean age of the study population was 58 ± 11 years and the population was predominantly male (78.5%). Patients in the in-hospital mortality group tended to be older compared to those who survived (65 ± 12 and 57 ± 11 years, respectively, p < 0.001), while gender showed no significant difference. Multivariable regression models showed that left ventricular ejection fraction, eGFR, R2CHADS2 (OR 2.21, 95% CI 1.38–3.54, p = 0.001), R2CHA2DS2-VASc (OR 1.91, 95% CI 1.30–2.80, p = 0.001), and R2CHA2DS2-VA (OR 1.97, 95% CI 1.345–2.910, p = 0.001) scores were independent predictors of in-hospital mortality. Conclusions: The R2CHADS2, R2CHA2DS2-VASc, and R2CHA2DS2-VA scores demonstrate strong predictive ability for in-hospital mortality in STEMI patients, and their non-negligible advantages support their implementation in clinical practice.

Background and Objectives: Postoperative atrial fibrillation (POAF) is the most common arrhythmia after coronary artery bypass grafting (CABG) and is linked to adverse outcomes. This study evaluated the predictive value of the Left Atrial Coupling Index (LACI) for POAF and compared two calculation methods, LACI₁ and the novel LACI₂. Materials and Methods: This prospective study included 130 patients undergoing isolated CABG between January 2022 and June 2023. Preoperative echocardiography was performed to calculate conventional parameters and LACI values: LACI₁ = LAVI/TDI-septal a′ and LACI₂ = LAVI/min (TDI-septal a′, TDI-lateral a′). Patients were classified into POAF (+) and POAF (−) groups. Clinical, echocardiographic, and outcome data were compared. Logistic regression and receiver operating characteristic (ROC) analyses were performed. Results: POAF occurred in 59 patients (45.4%). Those with POAF were older, had more diabetes mellitus(DM), hypertension(HT), and higher EuroSCORE II values (all p < 0.05). POAF was associated with longer hospitalization and higher in-hospital mortality. Both LACI₁ (4.21 ± 2.62 vs. 2.94 ± 1.02, p < 0.001) and LACI₂ (4.27 ± 2.60 vs. 2.96 ± 1.02, p < 0.001) were significantly higher in the POAF group. In multivariate analysis, LACI₁ (OR 1.45, p = 0.020) and LACI₂ (OR 1.50, p = 0.004) remained independent predictors. ROC analysis showed numerically higher discriminatory performance for LACI₂ (AUC = 0.690, specificity 74.5%) compared with LACI₁ (AUC = 0.677, specificity 67.6%). Conclusions: LACI is an independent predictor of POAF after CABG. The novel LACI₂ demonstrated numerically higher predictive performance compared with LACI₁ and may improve preoperative risk stratification and guide preventive strategies.