[Predictive value of whole brain perfusion on admission for shunt-dependent hydrocephalus fllowing aneurysmal subarachnoid hemorrhage].

ABSTRACT

Objective: To explore the value of predicting shunt-dependent hydrocephalus (SDHC) in patients with aneurysmal subarachnoid hemorrhage (aSAH) based on whole brain CT perfusion(CTP) and clinical data within 24 hours at admission. Methods: The clinical and imaging data of aSAH patients who received interventional embolization in our hospital were retrospectively collected from March 2018 to August 2022. All patients underwent one-stop whole brain CT examination within 24 hours after symptom onset, and the qualitative and quantitative CTP parameters were obtained after post-processing. Follow-up was conducted once every 2 months by consulting electronic medical records or by telephone for 6 months. According to whether SDHC occurred or not, the patients were divided into SDHC group and non-SDHC group. The differences between the two groups were compared. Logistic regression model was used to analyze and determine the predictive factors of SDHC, and the SDHC predictive model was established. The effectiveness of the predictive model was evaluated by drawing the receiver operating characteristic (ROC) curve of the subjects. Results: A total of 414 patients were included, including 132 males and 282 females, aged (59±11) years. 17.6%(73/414) patients had SDHC. There were significant differences in the occurrence of acute hydrocephalus, the World Neurosurgical League Scale (WFNS), the Hunt-Hess scale, the modified Fisher score (mFS), and the qualitative and quantitative parameters of CTP between the two groups (both P<0.001). Multivariate logistic regression analysis showed that acute hydrocephalus (OR=8.621, 95%CI 4.237-17.542),old age (OR=1.107, 95%CI 1.068-1.148), high mFS and high Hunt-Hess classification (OR=3.740, 95%CI 1.352-10.342) were the risk factors of SDHC in aSAH patients, and high mean cerebral blood flow (mCBF) (OR=0.931, 95%CI 0.885-0.980) was a protective factor of SDHC.The area under ROC curve (AUC) of the prediction model constructed by these five variables was 0.923(95%CI 0.89-0.95), with 84.5% sensitivity and 87.7% specificity. Conclusion: The mCBF and acute hydrocephalus, age, mFS and Hunt-Hess classification within 24 hours at admission can be used to predict SDHC for aSAH patients.