A nomogram for predicting the in-hospital mortality after large hemispheric infarction

Abstract

Background: Large hemispheric infarction (LHI) is a severe form of stroke with high mortality and disability rates. The purpose of this study was to explore predictive indicators of the in-hospital mortality of LHI patients treated conservatively without decompressive hemicraniectomy. Method: We performed a retrospective study of 187 consecutive patients with LHI between January 1, 2016 to May 31, 2019. The receiver operating curves were preformed to evaluate predictive performance of demographics factors, biomarkers and radiologic characteristics. Significant prognostic factors were combined to build a nomogram to predict the risk of in-hospital death of individual patients. Result: One hundred fifty-eight patients with LHI were finally enrolled, 58 of which died. Through multivariate logistic regression analysis, we identified that independent prognostic factors for in-hospital death were age (adjusted odds ratio [aOR] = 1.066; 95% confidence interval [CI], 1.025-1.108; P = 0.001), midline shift (MLS, aOR = 1.330, 95% CI, 1.177-1.503; P < 0.001), and neutrophil-to-lymphocyte ratio (NLR, aOR = 3.319, 95% CI, 1.542-7.144; P = 0.002). NLR may serve as a better predictor than white blood count (WBC) and neutrophil counts. Lastly, we used all of the clinical characteristics to establish a nomogram for predicting the prognosis, area under the curve (AUC) of this nomogram was 0.858 (95% CI, 0.794-0.908). Conclusion: This study shows that age, MLS, and admission NLR value are independent predictors of in-hospital mortality in patients with LHI. Moreover, nomogram, serve as a precise and convenient tool for the prognosis of LHI patients.