In-hospital Death Analysis Of Patients With Large Hemispheric Infarction And A Web Based Prediction Model For Malignant Cerebral Edema

Part 1.A Nomogram for Predicting the In-hospital Mortality after Large Hemispheric InfarctionObjectives: 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 who didn’t receive decompressive hemicraniectomy.Methods: We performed a retrospective study of 187 consecutive patients with LHI between January 1,2016 to May 31,2019.Logistic regression analysis was performed to explore the factors were associated with in-hospital death.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.Results: 158 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 [a OR]=1.066;95% confidence interval [CI],1.025–1.108;P=0.001),midline shift(MLS,a OR=1.330,95% CI,1.177–1.503;P<0.001),and neutrophil-to-lymphocyte ratio(NLR,a OR=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,the AUC-ROC of nomogram was 0.858(95% CI,0.794-0.908).Conclusions: 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.Part 2.A Web Based Dynamic Nomogram for Predicting the Malignant Cerebral EdemaObjectives: For large hemispheric infarction(LHI),malignant cerebral edema(MCE)is a life-threatening complication with mortality approaching 80%.Establishing a convenient prediction model of MCE after LHI is vital for rapid identification of high-risk patients and understanding of the potential mechanism of MCE.Methods: 142 consecutive patients with LHI within 24 h of onset from January 1,2016 to August 31,2019 were retrospectively collected.MCE was defined as patient death or received DHC with obvious mass effect(≥ 5mm midline shift).Binary logistic regression was performed to evaluated the independent predictors of MCE.Independent prognostic factors were incorporated to build dynamic MANA nomogram to predict MCE.Results: After adjustment for confounders,four independent factors were identified,including previously known atrial fibrillation(KAF),midline shift(MLS),National Institutes of Health Stroke Scale(NIHSS)and anterior cerebral artery(ACA)territory involvement.Furthermore,to facilitate the use of the nomogram for clinicians,we use “Dynnom” package to build dynamic MANA(acronym for MLS,ACA territory involvement,NIHSS and KAF)nomogram on web page(http://www.MANA-nom.com)to calculate the exact probability of developing MCE.The c-statistic of MANA nomogram was up to 0.887 ± 0.041 and AUC-ROC value in this cohort was 0.887(95%CI,0.828~0.934).Conclusions: Independent predictors of MCE included KAF,MLS,NIHSS,and ACA territory involvement.The dynamic MANA nomogram is a convenient,practical and effective clinical decision-making tool for predicting MCE after LHI in Chinese patients.