Influencing factors of outcome after first-pass complete recanalization in patients with acute ischemic stroke and establishment of a nomogram model
Objectives To investigate the risk factors for poor outcome in patients with acute ischemic stroke(AIS)who obtained first-pass complete recanalization(FPCR),to construct a nomogram model with early prediction value.Methods Clinical data of patients with acute ischemic stroke with large vessel occlusion(AIS-LVO)who underwent mechanical thrombectomy and obtained FPCR from January 2020 to January 2023 in the Stroke Centre of the Affiliated Hospital of Nantong University(38 patients)and the Department of Interventional Radiology of the First Affiliated Hospital of Soochow University(60 patients)were retrospectively analyzed.According to 90-day modified Rankin scale(mRS)score,98 patients were divided into favorable outcome group(mRS of 0-2)and unfavorable outcome group(mRS of 3-6).The general information,laboratory examination indexes,imaging examination indexes and operation information of patients in the two groups were compared.The items with statistically significant differences(P＜0.05)were included in multivariate logistic regression analysis to identify the independent factors related to unfavorable outcome and construct a nomogram model.The performance of the nomogram was verified by the receiver operating characteristic(ROC)and calibration chart respectively.Results There were 44 cases in favorable outcome group and 54 cases in unfavorable outcome group.The results of univariate analysis demonstrated that the observed differences between the two groups in terms of age,National Institute of Health stroke scale(NIHSS)score,Alberta stroke program early computed tomography score(ASPECTS),proportion of patients with clot burden score(CBS)＞6,high regional leptomeningeal collateral(rLMC)grading,neutrophil count,neutrophil-to-lymphocyte ratio(NLR),platelet count,proportion of patients with local anesthesia,and proportion of hemorrhage transformation were statistically significant(all P＜0.05).Multivariate logistic regression analysis showed that older age(OR:0.94,95％CI:0.89-0.99,P=0.037),high NIHSS scores at admission(OR:0.86,95％CI:0.77-0.97,P=0.010),high NLR(OR:0.88,95％CI:0.77-0.99,P=0.045)and poor collateral status(OR:0.03,95％CI:0.00-0.24,P=0.001)were independent risk factors for unfavorable outcome.Based on these results,a nomogram model was developed and the area under the ROC curve was 0.90(95％CI:0.84-0.96).Conclusion This nomogram,including age,NIHSS score on admission,NLR and collateral status may be used to predict individual probability of poor outcomes in AIS patients despite obtaining FPCR.
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