Comparison of neutrophil-to-lymphocyte ratio and mean platelet volume in the prediction of adverse events after primary percutaneous coronary intervention in patients with ST-elevation myocardial infarction.
Elevated neutrophil-to-lymphocyte ratio (NLR) and mean platelet volume (MPV) are indirect inflammatory markers. There is some evidence that both are associated with worse outcomes in ST-segment elevation myocardial infarction (STEMI) after primary percutaneous coronary intervention (PCI). The aim of the present study was to compare the capacity of NLR and MPV to predict adverse events after primary PCI.
In a prospective cohort study, 625 consecutive patients with STEMI, who underwent primary PCI, were followed. Receiver operating characteristic (ROC) curve analysis was performed to calculate the area under the curve (AUC) for the occurrence of procedural complications, mortality and major adverse cardiovascular events (MACE).
Mean age was 60.7 (±12.1) years, 67.5% were male. The median of NLR was 6.17 (3.8-9.4) and MPV was 10.7 (10.0-11.3). In multivariate analysis, both NLR and MPV remained independent predictors of no-reflow (relative risk [RR] = 2.26; 95%confidence interval [95%CI] = 1.16-4.32; p = 0.01 and RR = 2.68; 95%CI = 1.40-5.10; p < 0.01, respectively), but only NLR remained an independent predictor of in-hospital MACE (RR = 1.01; 95%CI = 1.00-1.06; p = 0.02). The AUC for in-hospital MACE was 0.57 for NLR (95%CI = 0.53-0.60; p = 0.03) and 0.56 for MPV (95%CI = 0.52-0.60; p = 0.07). However, when AUC were compared with DeLong test, there was no statistically significant difference for these outcomes (p > 0.05). NLR had an excellent negative predictive value (NPV) of 96.7 for no-reflow and 89.0 for in-hospital MACE.
Despite no difference in the ROC curve comparison with MPV, only NLR remained an independent predictor for in-hospital MACE. A low NLR has an excellent NPV for no-reflow and in-hospital MACE, and this could be of clinical relevance in the management of low-risk patients.
Machado GP
，Araujo GN
，Carpes CK
，Lech M
，Mariani S
，Valle FH
，Bergoli LCC
，Gonçalves SC
，Wainstein RV
，Wainstein MV
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Construction and evaluation of nomogram model for individualized prediction of risk of major adverse cardiovascular events during hospitalization after percutaneous coronary intervention in patients with acute ST-segment elevation myocardial infarction.
Emergency percutaneous coronary intervention (PCI) in patients with acute ST-segment elevation myocardial infarction (STEMI) helps to reduce the occurrence of major adverse cardiovascular events (MACEs) such as death, cardiogenic shock, and malignant arrhythmia, but in-hospital MACEs may still occur after emergency PCI, and their mortality is significantly increased once they occur. The aim of this study was to investigate the risk factors associated with MACE during hospitalization after PCI in STEMI patients, construct a nomogram prediction model and evaluate its effectiveness.
A retrospective analysis of 466 STEMI patients admitted to our hospital from January 2018 to June 2022. According to the occurrence of MACE during hospitalization, they were divided into MACE group (n = 127) and non-MACE group (n = 339), and the clinical data of the two groups were compared; least absolute shrinkage and selection operator (LASSO) regression was used to screen out the predictors with non-zero coefficients, and multivariate Logistic regression was used to analyze STEMI Independent risk factors for in-hospital MACE in patients after emergency PCI; a nomogram model for predicting the risk of in-hospital MACE in STEMI patients after PCI was constructed based on predictive factors, and the C-index was used to evaluate the predictive performance of the prediction model; the Bootstrap method was used to repeat sampling 1,000 Internal validation was carried out for the second time, the Hosmer-Lemeshow test was used to evaluate the model fit, and the calibration curve was drawn to evaluate the calibration degree of the model. Receiver operating characteristic (ROC) curves were drawn to evaluate the efficacy of the nomogram model and thrombolysis in myocardial infarction (TIMI) score in predicting in-hospital MACE in STEMI patients after acute PCI.
The results of LASSO regression showed that systolic blood pressure, diastolic blood pressure, Killip grade II-IV, urea nitrogen and left ventricular ejection fraction (LVEF), IABP, NT-ProBNP were important predictors with non-zero coefficients, and multivariate logistic regression analysis was performed to analyze that Killip grade II-IV, urea nitrogen, LVEF, and NT-ProBNP were independent factors for in-hospital MACE after PCI in STEMI patients; a nomogram model for predicting the risk of in-hospital MACE after PCI in STEMI patients was constructed with the above independent predictors, with a C-index of 0.826 (95% CI: 0.785-0.868) having a good predictive power; the results of H-L goodness of fit test showed χ2 = 1.3328, P = 0.25, the model calibration curve was close to the ideal model, and the internal validation C-index was 0.818; clinical decision analysis also showed that the nomogram model had a good clinical efficacy, especially when the threshold probability was 0.1-0.99, the nomogram model could bring clinical net benefits to patients. The nomogram model predicted a greater AUC (0.826) than the TIMI score (0.696) for in-hospital MACE after PCI in STEMI patients.
Urea nitrogen, Killip class II-IV, LVEF, and NT-ProBNP are independent factors for in-hospital MACE after PCI in STEMI patients, and nomogram models constructed based on the above factors have high predictive efficacy and feasibility.
Fang C
，Chen Z
，Zhang J
，Jin X
，Yang M
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《Frontiers in Cardiovascular Medicine》
ResearchGate
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