Sui Jianfei, Wang Nuochuan, Jiang Pengjun, Wu Jun, Wang Qingzhen, Yuan Qiaolin, He Hongwei
Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
Department of Transfusion, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
Chin Neurosurg J. 2022 Mar 1;8(1):5. doi: 10.1186/s41016-022-00274-4.
Rebleeding can cause a catastrophic outcome after aneurysmal subarachnoid hemorrhage. A clinical + morphology nomogram was promoted in our previous study to assist in discriminating the rupture intracranial aneurysms (RIAs) with a high risk of rebleeding. The aim of this study was to validate the predictive accuracy of this nomogram model.
The patients with RIAs in two medical centers from December 2020 to September 2021 were retrospectively reviewed, whose clinical and morphological parameters were collected. The Cox regression model was employed to identify the risk factors related to rebleeding after their admission. The predicting accuracy of clinical + morphological nomogram, ELAPSS score and PHASES score was compared based on the area under the curves (AUCs).
One hundred thirty-eight patients with RIAs were finally included in this study, 20 of whom suffering from rebleeding after admission. Hypertension (hazard ratio (HR), 2.54; a confidence interval of 95% (CI), 1.01-6.40; P = 0.047), bifurcation (HR, 3.88; 95% CI, 1.29-11.66; P = 0.016), and AR (HR, 2.68; 95% CI, 1.63-4.41; P < 0.001) were demonstrated through Cox regression analysis as the independent risk factors for rebleeding after admission. The clinical + morphological nomogram had the highest predicting accuracy (AUC, 0.939, P < 0.01), followed by the bifurcation (AUC, 0.735, P = 0.001), AR (AUC, 0.666, P = 0.018), and ELAPSS score (AUC, 0.682, P = 0.009). Hypertension (AUC, 0.693, P = 0.080) or PHASES score (AUC, 0.577, P = 0.244) could not be used to predict the risk of rebleeding after admission. The calibration curve for the probability of rebleeding showed a good agreement between the prediction through clinical + morphological nomogram and actual observation.
Hypertension, bifurcation site, and AR were independent risk factors related to the rebleeding of RIAs after admission. The clinical + morphological nomogram could help doctors to identify the high-risk RIAs with a high predictive accuracy.
动脉瘤性蛛网膜下腔出血后再出血可导致灾难性后果。在我们之前的研究中提出了一种临床+形态学列线图，以协助鉴别具有再出血高风险的破裂颅内动脉瘤（RIAs）。本研究的目的是验证该列线图模型的预测准确性。
回顾性分析2020年12月至2021年9月在两个医疗中心的RIAs患者，收集其临床和形态学参数。采用Cox回归模型确定入院后与再出血相关的危险因素。基于曲线下面积（AUC）比较临床+形态学列线图、ELAPSS评分和PHASES评分的预测准确性。
本研究最终纳入138例RIAs患者，其中20例入院后发生再出血。通过Cox回归分析显示，高血压（风险比（HR），2.54；95%置信区间（CI），1.01-6.40；P = 0.047）、分叉（HR，3.88；95% CI，1.29-11.66；P = 0.016）和AR（HR，2.68；95% CI，1.63-4.41；P < 0.001）是入院后再出血的独立危险因素。临床+形态学列线图具有最高的预测准确性（AUC，0.939，P < 0.01），其次是分叉（AUC，0.735，P = 0.001）、AR（AUC，0.666，P = 0.018）和ELAPSS评分（AUC，0.682，P = 0.009）。高血压（AUC，0.693，P = 0.080）或PHASES评分（AUC，0.577，P = 0.244）不能用于预测入院后再出血的风险。再出血概率的校准曲线显示，通过临床+形态学列线图的预测与实际观察之间具有良好的一致性。
高血压、分叉部位和AR是入院后RIAs再出血的独立危险因素。临床+形态学列线图可帮助医生识别预测准确性高的高风险RIAs。
