Vinodh Vayara Perumall, Ghani Abdul Rahman Izaini, Kandasamy Regunath, Sellamuthu Pulivendhan, Zenian Mohd Sofan, Keowmani Thamron
Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kelantan, Malaysia.
Department of Neurosurgery, Queen Elizabeth 2 Hospital, Sabah, Malaysia.
Malays J Med Sci. 2022 Apr;29(2):43-54. doi: 10.21315/mjms2022.29.2.5. Epub 2022 Apr 21.
Morbidity and mortality is high among aneurysm rupture patients. Despite surviving the initial rupture, morbidity is high as they suffer from vasospasm and cerebral infarction (CI). Most prediction tools for CI after aneurysmal subarachnoid haemorrhage (SAH) are complex and are not routinely available in all neurosurgical centres. Current therapies for prevention of CI are still debatable and selective usage among high-risk patients is advised. These factors necessitate a simple prediction model for identifying patients in the high risk group to initiate early preventive treatment of CI.
Patients with anterior circulation aneurysm rupture who underwent surgical clipping were included. Demographic data and factors related to CI were collected to determine significance and were used to develop VINODH score (VS).
Two hundred patients were included with a median age of 51 years old. Multivariate analysis proved only four predictors were significant ( < 0.01) for developing CI. These predictors were used for the development of VS which was named after the main author and the model's sensitivity was 79.0% and specificity was 83.0%. This highly predictive score (receiver operating characteristic [ROC]: 0.902) was internally validated.
VS is a reliable tool for early identification of patients at risk of CI after aneurysmal SAH.
动脉瘤破裂患者的发病率和死亡率很高。尽管在初次破裂后存活下来，但由于他们会出现血管痉挛和脑梗死（CI），所以发病率仍然很高。大多数用于预测动脉瘤性蛛网膜下腔出血（SAH）后发生CI的工具都很复杂，并非所有神经外科中心都能常规使用。目前预防CI的治疗方法仍存在争议，建议在高危患者中选择性使用。这些因素需要一个简单的预测模型来识别高危组患者，以便尽早开始CI的预防性治疗。
纳入接受手术夹闭的前循环动脉瘤破裂患者。收集人口统计学数据和与CI相关的因素以确定其显著性，并用于开发维诺德评分（VS）。
纳入200例患者，中位年龄为51岁。多变量分析证明只有四个预测因素对发生CI具有显著性（<0.01）。这些预测因素被用于开发VS，该评分以主要作者命名，模型的敏感性为79.0%，特异性为83.0%。这个具有高度预测性的评分（受试者工作特征曲线[ROC]：0.902）经过了内部验证。
VS是早期识别动脉瘤性SAH后有CI风险患者的可靠工具。
