Mounting researches have illuminated that the neutrophil-related ratios were related to the prognosis of acute ischemic stroke (AIS). However, few have compared their predictive value and accuracy. To make such comparison and identify the best indicator on the 90-day outcome, we investigated biomarkers including neutrophil ratio (Nr), neutrophil count (Nc), lymphocyte (L), neutrophil-to-lymphocyte ratio (NLR), platelet (P or PLT), platelet-to-neutrophil ratio (PNR), NLR-to-platelet ratio (NLR/PLT), eosinophil (E), neutrophil-to-eosinophil ratio (NER), monocyte (M), and monocyte-to-neutrophil ratio (MNR).
This retrospective study recruited 283 AIS and 872 healthy controls (HCs) receiving intravenous thrombolysis (IVT). Blood samples were collected after 24 h of admission before IVT. Propensity Score Matching (PSM) was used to explore whether these ratios differentiated AIS and HCs. We applied univariate and multivariate analyses to evaluate the prediction effect of these ratios separately or added in the model and figured out a clinical prediction model. To estimate the discrimination and calibration of the new models, the receiver operating characteristics (ROC) curve analysis, DeLong method, and likelihood ratio test (LR test) were utilized.
PSM showed that Nr, Nc, NLR, P, PNR, NLR/PLT, NER, and MNR facilitates the differentiation of the HCs and AIS. Among the eight biomarkers, PNR and MNR could differentiate the 90-day outcome, and it was found out that PNR performed better. Univariate regression analysis demonstrated that PNR was the only independent predictor which needs no adjustment. Besides, the multivariate regression analysis, Delong method, and LR test indicated that among the neutrophil-related ratios, NLR, PNR, NLR/PLT, NER, and MNR exerted little influence on the discrimination but could enhance the calibration of the base model, and NER proved to work best.
Low PNR was the best indicator among the neutrophil-related ratios tin predicting a poor 90-day outcome of AIS patients. Moreover, high NER performed best when predicting the 90-day outcome to improve the calibration of the base model.