Rebleeding of Ruptured Intracranial Aneurysm After Admission: A Multidimensional Nomogram Model to Risk Assessment

Abstract

ObjectiveRebleeding is recognized as the main cause of mortality after intracranial aneurysm rupture. Though timely intervention can prevent poor prognosis, there is no agreement on the surgical priority and choosing medical treatment for a short period after rupture. The aim of this study was to investigate the risk factors related to the rebleeding after admission and establish predicting models for better clinical decision-making.MethodsThe patients with ruptured intracranial aneurysms (RIAs) between January 2018 and September 2020 were reviewed. All patients fell to the primary and the validation cohort by January 2020. The hemodynamic parameters were determined through the computational fluid dynamics simulation. Cox regression analysis was conducted to identify the risk factors of rebleeding. Based on the independent risk factors, nomogram models were built, and their predicting accuracy was assessed by using the area under the curves (AUCs).ResultA total of 577 patients with RIAs were enrolled in this present study, 86 patients of them were identified as undergoing rebleeding after admission. Thirteen parameters were identified as significantly different between stable and rebleeding aneurysms in the primary cohort. Cox regression analysis demonstrated that six parameters, including hypertension [hazard ratio (HR), 2.54; P = 0.044], bifurcation site (HR, 1.95; P = 0.013), irregular shape (HR, 4.22; P = 0.002), aspect ratio (HR, 12.91; P < 0.001), normalized wall shear stress average (HR, 0.16; P = 0.002), and oscillatory stress index (HR, 1.14; P < 0.001) were independent risk factors related to the rebleeding after admission. Two nomograms were established, the nomogram including clinical, morphological, and hemodynamic features (CMH nomogram) had the highest predicting accuracy (AUC, 0.92), followed by the nomogram including clinical and morphological features (CM nomogram; AUC, 0.83), ELAPSS score (AUC, 0.61), and PHASES score (AUC, 0.54). The calibration curve for the probability of rebleeding showed good agreement between prediction by nomograms and actual observation. In the validation cohort, the discrimination of the CMH nomogram was superior to the other models (AUC, 0.93 vs. 0.86, 0.71 and 0.48).ConclusionWe presented two nomogram models, named CMH nomogram and CM nomogram, which could assist in identifying the RIAs with high risk of rebleeding.

Validation of the predictive accuracy of “clinical + morphology nomogram” for the rebleeding risk of ruptured intracranial aneurysms after admission

“…Aspect ratio (AR), size ratio (SR), undulation index (UI), and nonsphericity index (NSI) were calculated [ 19 ]. An irregular shape was identified according to our previous study [ 15 ].…”

“…The nomogram points were calculated based on hypertension, AR and bifurcation site, which were then transferred into risk probability or rebleeding according to our previous study [ 15 ]. The risk probability of rebleeding was used for further analyses.…”

“…We compared the differences between continuous variables of the two groups based on Student’s t tests or Wilcoxon rank sum tests as well as the differences in categorical variables based on chi-square tests or Fisher’s exact tests. The clinical + morphological nomogram was given in our previous study [ 15 ]; the risk of rebleeding after admission was calculated, meanwhile PHASES score and ELAPSS score were calculated according to previous protocols [ 20 , 21 ]. The parameters with significance in univariable analysis were input into Cox regression model to identify the independent risk factors, whose result was presented as hazard ratio (HR) and a confidence interval of 95% (CI).…”

“…There are two main aspects related to the stability of intracranial aneurysms, known as the pathological characteristics of aneurysm wall [ 10 ] and the hemodynamic characteristics of aneurysms [ 11 – 13 ]. Considering the strong correlation between pathological characteristics of aneurysm wall and morphological features [ 14 ], we established a nomogram model based on clinical and morphological factors (hypertension, bifurcation, irregular shape, and aspect ratio) to identify the RIAs with a high risk of rebleeding after admission [ 15 ]. However, the predictive accuracy was not validated by other independent cohorts.…”

Serum IL-1, Pyroptosis and Intracranial Aneurysm Wall Enhancement: Analysis Integrating Radiology, Serum Cytokines and Histology

“…The mentioned characteristics were measured twice by the respective investigator, and the average of the respective investigator was then averaged for the in-depth analysis. Subsequently, the aspect ratio (AR) and the size ratio (SR) were determined following the previous study by the authors (16). AR denotes the ratio of aneurysm size and aneurysm neck diameter, and SR represents the ratio of aneurysm height and diameter of the parent artery.…”