The systemic immune-inflammatory index (SII) and derived neutrophil-lymphocyte ratio (dNLR) are novel indexes that simultaneously reflect the host inflammatory and immune status and have prognostic value in some cancers. SII was associated with major cardiovascular events in coronary artery disease patients who received percutaneous coronary intervention (PCI). However, dNLR correlations with clinical outcomes in acute coronary syndrome (ACS) patients undergoing PCI remain unclear. This study aimed to elucidate the predictive values of SII and dNLR on the long-term prognosis of patients with ACS undergoing PCI. In total, 1,553 ACS patients undergoing PCI were consecutively enrolled from January 2016 to December 2018. The subjects were divided into high and low SII and dNLR groups for comparison (high vs. low). The SII and dNLR cutoff values for predicting major adverse cardiovascular events (MACE) were calculated using receiver operating characteristic curves, and Kaplan-Meier curves and Cox regression models were used for survival analyses. The endpoint was a MACE, which included all-cause mortality and rehospitalization for severe heart failure during follow-up. The Kaplan-Meier curves showed that a higher SII or dNLR value was associated with a higher risk of MACE (all P < 0.001). Multivariate Cox regression models showed that SII (hazard ratio [HR]: 2.545; 95% confidence interval [CI]: 1.416-4.574; P = 0.002) and dNLR (HR: 2.610, 95% CI: 1.454-4.685, P = 0.001) were independent predictors for MACE. dNLR may be a suitable laboratory marker to identify high-risk ACS patients after PCI.

Objective This study aimed to investigate the predictive value of inflammatory cells in peripheral blood on the prognosis of patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI). Methods Patients (n=1558) were consecutively enrolled and the median follow-up was 1142 days. Patients were divided into the major adverse cardiac events (MACE) 1 group (n=63) (all-cause mortality [n=58] and rehospitalization for severe heart failure [n=5], no MACE1 group (n=1495), MACE2 group (n=38) (cardiac mortality [n=33] and rehospitalization for severe heart failure [n=5]), and no MACE2 group (n=1520). The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) were analyzed. Results The NLR, MLR, and PLR were higher in the MACE groups than in the no MACE groups. Different subsets of inflammatory cells had similar diagnostic values for MACE. Kaplan–Meier curves showed that the survival time gradually decreased with an increase in the degree of risk as determined by the NLR, MLR, and PLR. The risk of MACE was highest in the extremely high-risk group. Conclusion Peripheral blood inflammatory cell subsets can predict MACE in patients with ACS undergoing PCI. These cell subsets could be important laboratory markers for the prognosis and clinical treatment of these patients.

Aim To develop and validate 3 nomograms incorporating the advanced lung cancer inflammation index (ALI) that can aid in predicting the risk of coronary artery disease (CAD) and coronary artery calcification (CAC). Methods The study enrolled 562 consecutive patients with suspected CAD who underwent coronary computed tomographic angiography between September 2015 and June 2017. Independent risk factors for CAD, CAC, and CAD with CAC were identified via univariate and multivariate analysis, and nomograms were established based on the independent predictors identified. The area under the curve (AUC), calibration curve, and decision curve analysis were used to evaluate the nomograms. Correlations between ALI and other clinical indicators were examined via Spearman correlation analysis. Results In total, 549 patients with suspected CAD who underwent coronary computed tomographic angiography were included. Male sex, hypertension, diabetes, dyslipidemia, ischemic stroke, and ALI were independent predictors of both CAD and CAC. Male sex, hypertension, diabetes, dyslipidemia, and ALI were also identified as independent predictors of CAD with CAC. The AUC values for the nomograms developed using these risk factors were 0.739 (95% confidence interval [CI], 0.693-0.785), 0.728 (95% CI, 0.684-0.772), and 0.717 (95% CI 0.673-0.761), respectively. ALI was negatively correlated with neutrophil-to-lymphocyte ratio and CAC score and positively correlated with serum albumin levels and body mass index (all P < .05). Conclusions ALI is an independent predictor of CAD, CAC, and CAD with CAC. Our ALI-based nomograms can provide accurate and individualized risk predictions for patients with suspected CAD.

CHADS2 and CHA2DS2-VASc scores have been used to assess the prognostic risk of thromboembolism in non-valvular atrial fibrillation patients. Recent studies have shown the utility of CHADS2 and CHA2DS2-VASc scores for evaluating the severity of coronary artery disease (CAD). The newly defined CHA2DS2-VASc-HSF score evaluates atherosclerosis and is associated with CAD severity. This study investigated the association between the CHA2DS2-VASc-HSF score and acute coronary syndrome (ACS) severity as assessed by the Gensini score and the number of vessels. Furthermore, this study also compared the diagnostic value of the CHADS2, CHA2 DS2-VASc, and CHA2DS2-VASc-HSF score for ACS. A total of 2367 eligible inpatients (ACS group [ n = 2030]; non-CAD group [ n = 337]) were consecutively enrolled in this study. Receiver operating characteristic curve diagnostic tests and logistic regression models were used to analyze the risk factors for ACS. The CHADS2, CHA2DS2-VASc, and CHA2DS2-VASc-HSF scores were significantly higher in the ACS group than those in the control group. After adjusting for numerous traditional CAD risk factors, an increased CHA2DS2-VASc-HSF score was found to be an independent risk factor for patients with ACS (odds ratio 1.401, 95% confidence interval 1.044, −1.879; P < 0.05). A newly diagnosed CHA2DS2-VASc-HSF score predicts the severity of ACS.

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