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.

There is currently limited information on the prognostic value of the dNLR-PNI (the combination of the derived neutrophil-to-lymphocyte ratio [dNLR] and prognostic nutritional index [PNI]) score for patients with acute coronary syndrome (ACS). We aimed to explore the predictive value of a dNLR-PNI score on the long-term prognosis of patients with ACS undergoing percutaneous coronary intervention (PCI). A total of 1773 patients with ACS who underwent PCI were consecutively enrolled from January 2016 to December 2018. The cutoff values of dNLR and PNI to predict major adverse cardiovascular events (MACE) were calculated using receiver operating characteristic curves. The patients were divided into three groups based on the dNLR-PNI score, and Kaplan–Meier curves and Cox regression models were used for survival analysis. The endpoints were MACE, including all-cause mortality and rehospitalisation for severe heart failure during follow-up. A total of 1542 patients with ACS who underwent PCI were included. Kaplan–Meier curves showed that a higher level of dNLR, PNI, or dNLR-PNI score was associated with a higher risk of MACE (all p < .001). In multivariate Cox regression models, the dNLR-PNI two score (hazard ratio 3.049, 95% confidence interval 1.503–6.184, p = .002) was found to be an independent predictor of all-cause mortality and rehospitalization for severe heart failure. A high dNLR-PNI score was independently associated with a higher risk of developing MACE in patients with ACS undergoing PCI. The dNLR-PNI score may be a useful prognostic parameter for identifying high-risk ACS patients after PCI.

Abstract Background: No cardiac load index (CLI) has been established for patients with coronary artery disease (CAD). We propose a simple method for calculating CLI and explore the association of CLI with CAD.Methods: We enrolled 4145 consecutive inpatients with suspected stable CAD from December 2011 to June 2017 at the Chengde Medical University Affiliated Hospital. All patients were divided into the CAD (n=2914) and the NCAD groups (n=1231) according to coronary computed tomography angiography. We retrospectively collected data and calculated the CLI values of all patients. The receiver operating characteristic diagnostic test analysis was performed with CLI≥77, CLI≥125, CLI≥171, CLI≥217, and CLI≥264, respectively. Multivariate logistic regression models were established to determine the risk factors of CAD. Results: The CLI was significantly higher in the CAD group than in the NCAD group and higher in the male than in the female subgroup (both P<0.001). CLI≥171 was the diagnostic cut-off value. The predictive power of CLI≥171 for CAD improved after considering other risk factors. CLI≥171 is a new independent risk factor for CAD, and is an independent risk factor for CAD in males and females (all P<0.001).Conclusions: Increased CLI is an independent risk factor for CAD, it may be used as a predictor for the prevalence for CAD to improve diagnosis and prevention.