Neurosurgery Unit, Department of Surgery, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
PLoS One. 2022 Mar 15;17(3):e0264844. doi: 10.1371/journal.pone.0264844. eCollection 2022.
A scoring system for aneurysmal subarachnoid hemorrhage (aSAH) is useful for guiding treatment decisions, especially in urgent-care limited settings. This study developed a simple algorithm of clinical conditions and grading to predict outcomes in patients treated by clipping or coiling.
Data on patients with aSAH hospitalized in a university's neurovascular center in Thailand from 2013 to 2018 were obtained for chart review. Factors associated with poor outcomes evaluated at one year were identified using a stepwise logistic regression model. For each patient, the rounded regression coefficients of independent risk factors were linearly combined into a total score, which was assessed for its performance in predicting outcomes using receiver operating characteristic analysis. An appropriate cutoff point of the scores for poor outcomes was based on Youden's criteria, which maximized the summation between sensitivity or true positive rate and the specificity or true negative rate.
Patients (n, 121) with poor outcomes (modified Rankin Scale, mRS score, 4-6) had a significantly higher proportion of old age, underlying hypertension, diabetes and chronic kidney disease, high clinical severity grading, preoperative rebleeding, and hydrocephalus than those (n, 336) with good outcomes (mRS score, 0-3). Six variables, including age >70 years, diabetes mellitus, World Federation of Neurosurgical Societies (WFNS) scaling of IV-V, modified Fisher grading of 3-4, rebleeding, and hydrocephalus, were identified as independent risk factors and were assigned a score weight of 2, 1, 2, 1, 3 and 1, respectively. Among the total possible scores ranging from 0-10, the cut point at score 3 yielded the maximum Youden's index (0.527), which resulted in a sensitivity of 77.7% and specificity of 75.0%.
A simple 0-10 scoring system on six risk factors for poor outcomes was validated for aSAH and should be advocated for use in limited resource settings.
对于指导治疗决策，特别是在急救资源有限的情况下，动脉瘤性蛛网膜下腔出血（aSAH）的评分系统很有用。本研究开发了一种简单的临床情况和分级算法，以预测接受夹闭或栓塞治疗的患者的结局。
通过病历回顾，获取了 2013 年至 2018 年在泰国一所大学神经血管中心住院的 aSAH 患者的数据。使用逐步逻辑回归模型确定了在一年时与不良结局相关的因素。对于每位患者，将独立危险因素的回归系数四舍五入并线性组合成一个总分，然后使用接受者操作特征分析评估该总分在预测结局方面的表现。根据 Youden 标准确定不良结局评分的适当切点，该标准最大程度地提高了灵敏度或真阳性率与特异性或真阴性率之间的总和。
预后不良（改良 Rankin 量表评分 4-6）的患者比例显著高于预后良好（改良 Rankin 量表评分 0-3）的患者，前者的比例更高，分别为老年患者、合并有高血压、糖尿病和慢性肾脏病患者、临床严重程度分级高的患者、术前再出血的患者和脑积水患者。年龄＞70 岁、糖尿病、世界神经外科学联合会（WFNS）分级 4-5 级、改良 Fisher 分级 3-4 级、再出血和脑积水 6 个变量被确定为独立危险因素，并分别给予 2、1、2、1、3 和 1 的评分权重。在总分 0-10 分的范围内，评分 3 分的切点产生了最大的 Youden 指数（0.527），其灵敏度为 77.7%，特异性为 75.0%。
针对预后不良的 6 个危险因素的简单 0-10 分评分系统已在 aSAH 中得到验证，应在资源有限的情况下推广使用。
