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Published on: November 19, 2020
Nomogram for predicting delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage in the Chinese population
Haonan Liu1, Qian Xu2, Aimin Li1
1Department of Neurosurgery, Lianyungang Clinical College of Nanjing Medical University (The First People's Hospital of Lianyungang), 182 Tongguan North Road, Lianyungang 222002, China.
Background:
Delayed cerebral ischemia is a serious complication of aneurysmal subarachnoid hemorrhage with debilitating and fatal consequences. Lack of well-established risk factors impedes early identification of high-risk patients with delayed cerebral ischemia. A nomogram provides personalized, evidence-based, and accurate risk estimation. To offset the lack of a predictive tool, we developed a nomogram to predict delayed cerebral ischemia before performing surgical interventions for aneurysmal subarachnoid hemorrhage to aid surgical decision-making.
Methods:
We retrospectively collected data from 887 consecutive eligible Chinese patients who underwent surgical clipping or endovascular coiling for aneurysmal subarachnoid hemorrhage. Patients who previously underwent surgery formed the training cohort (n = 621) for nomogram development; those who underwent surgery later formed the validation cohort (n = 266) to confirm the performance of the model. A multivariate logistic regression analysis identified the independent risk factors associated with delayed cerebral ischemia, which were then incorporated into the nomogram.
Results:
Delayed cerebral ischemia was identified in 158/621 patients (25.4%) in the training cohort and in 66/266 patients (24.8%) in the validation cohort. Preoperative factors associated with delayed cerebral ischemia were age > 65 years, modified Fisher grade of 3-4, ruptured aneurysm in the anterior circulation, Hunt-Hess grade of 4-5, high blood pressure on admission, and plasma homocysteine level ≥ 10 μmol/L. Incorporating these six factors in the nomogram achieved efficient concordance indices of 0.73 (95% confidence interval, 0.68-0.77) and 0.65 (95% confidence interval, 0.57-0.72) in predicting delayed cerebral ischemia in the training and validation cohorts, respectively.
Conclusions:
Our model can help determine an individual's risk of developing delayed cerebral ischemia in the Chinese population, and thereby, facilitate reasonable treatment-related decision-making.
