Establishment and validation of a predictive model for delayed cerebral vasospasm after aneurysmal subarachnoid hemorrhage
LIU Yun-shi
YAN Tian-ling
WANG Dong-hua
CAO You-lin
ZHOU Xiao-li
HU Ping
CHEN Qian-xue
Abstract：Objective To investigate the risk factors of delayed cerebral vasospasm(DCV)in patients with aneurysmal subarachnoid hemorrhage(aSAH),and to further establish and validate a predictive model.Methods The clinical data of 105 patients with aSAH admitted from August 2016 to September 2021 were retrospectively analyzed.DCV was diagnosed based on clinical manifestations and imaging examinations 3 to 14 days after the onset.LASSO regression was employed to screen the predictive variables,and a nomogram model was constructed using R software version 4.2.0 and validated.Results Of the 105 patients with aSAH,16 patients developed DCV after surgery,with an incidence rate of 15.2%.The variables selected by LASSO regression included gender,Hunt-Hess grade,modified Fisher score,intraventricular hemorrhage,location and number of aneurysms,and rebleeding.Based on these variables,a Nomogram model was established using R software version 4.2.0.ROC curve analysis revealed that the area under the curve of this model for predicting DCV was 0.905(95%CI 0.841～0.955),demonstrating good calibration.Conclusion The Nomogram model established in this study can effectively predict the risk of DCV in patients with aSAH and can better guide clinical treatment.
Keywords：Aneurysmal subarachnoid hemorrhageDelayed cerebral vasospasmPrediction model
Publication Date：2025-01-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 10-14 )