Predictors of Outcomes Six Months after Endovascular Coil Embolization of Poor-Grade Aneurysmal Subarachnoid Hemorrhage

Objective

To identify factors associated with the outcome and prognosis of coil embolization for poor-grade aneurysmal subarachnoid hemorrhage (aSAH).

Methods

We retrospectively reviewed 118 patients with World Federation of Neurosurgical Societies (WFNS) grade IV or V subarachnoid hemorrhage at our institute between January 2010 and December 2020. Outcomes were assessed using modified Rankin Scale (mRS) scores at discharge and at six months after aSAH onset. In addition, patient background, aneurysm characteristics, and treatment outcome were compared between patients showing favorable (mRS scores: 0-2) and unfavorable (mRS scores: 3-6) outcomes at six months. Factors for change of mRS during follow-up were explored, and cut off values were calculated for age using the receiver operating characteristic analysis.

Results

Endovascular treatment was performed in 51 of the 118 enrolled patients. Data were analyzed for 43 of these patients who underwent coil embolization of ruptured aneurysms and had complete datasets. The mean age was 61.7 years and 24 (55.8%) patients had WFNS grade V aSAH. Coil embolization-related complications were observed in three patients. There were no treatment-related deaths; however, eight patients (18.6%) died at three months. Multivariate analysis showed that the maximum diameter of the aneurysm (p=0.041) and the postoperative dual antiplatelet therapy (DAPT) (p=0.040) were associated with unfavorable and favorable outcomes, respectively. Older age (p=0.033) was independently associated with mRS score deterioration following discharge. Age 72 years and older was the cut off value for mRS deterioration.

Conclusion

Aneurysm size and postoperative DAPT might be associated with outcomes at 6 months. Moreover, we identified older age as an independent factor that influences mRS deterioration following discharge; thus, especially in cases of elderly patients over 72 years of age, it is highly likely that long-term care to prevent disuse and regular follow-up on imaging will be necessary.

Sports Enterprise Marketing and Financial Risk Management Based on Decision Tree and Data Mining

With the development of modern economy, traditional sports industry enterprises have also been further developed in the financial business. How to ensure information security and financial risk management is the problem faced by sports companies. Risk assessment is the use of mathematical models to calculate the risk factors established in the previous step to predict possible risks. In response to the above problems, we developed a sports enterprise marketing and financial risk management model based on decision trees and data mining. First, we have established a relevant evaluation index system and data samples through in-depth understanding of the actual marketing and financial problems of sports companies. Second, we use the decision tree algorithm to mine and explore related data samples and conduct risk assessment through related indicators. By using the model to calculate the probability of occurrence of the risk, analyze the degree of damage. Finally, the algorithm of this paper is analyzed and discussed through simulation experiments.