Mijderwijk Hendrik-Jan, de Winkel Jordi, Nieboer Daan, Abdelaal Ahmed, Germans Menno R, Karadag Cihat, Cornelius Jan F, Sorteberg Angelika, Roozenbeek Bob, Lingsma Hester F, Boogaarts Hieronymus D, van Lieshout Jasper H
Department of Neurosurgery, Medical Faculty Düsseldorf, Heinrich Heine University, Düsseldorf , Germany.
Department of Neurology, Erasmus MC University Medical Center Rotterdam, Rotterdam , The Netherlands.
Neurosurgery. 2024 Nov 21;97(1):120-129. doi: 10.1227/neu.0000000000003275.
To externally validate the Aneurysmal RebleedIng after Subarachnoid hEmorrhage (ARISE) prediction models that predict preinterventional aneurysmal rebleeding within 24 and 72 hours after aneurysmal subarachnoid hemorrhage (aSAH).
We pooled data from two international hospital registries from University Hospital Oslo, Norway, and University Hospital Rotterdam, The Netherlands, to validate the ARISE base model (including patient age, sex, hypertension, World Federation of Neurological Surgeons grade, Fisher grade, aneurysm size, and cerebrospinal fluid diversion) and the ARISE extended model (adding aneurysm irregularity to the base model). Model performance was assessed with discrimination (Harrell c-statistic, model-based c-statistic) and calibration (calibration-in-the-large, calibration slope, and calibration plots). After validation, we updated the ARISE models as appropriate.
The combined cohort consisted of 1467 patients, of whom 143 (10%) suffered preinterventional rebleeding. In the University Hospital Oslo, Norway cohort, the externally validated c-statistics were 0.75 (95% CI: 0.71-0.80) for the ARISE base model and 0.71 (0.66-0.76) for the ARISE extended model. In the University Hospital Rotterdam, The Netherlands cohort, the c-statistics were 0.70 (0.64-0.76) for the ARISE base model and 0.64 (0.57-0.72) for the ARISE extended model. Calibration-in-the-large was poor; the average predicted risks were lower than the average observed risk for both models in both centers. After updating the baseline hazard, the base model calibrated excellently over the range of clinically relevant probabilities of rebleeding.
The ARISE base model had good discriminative ability for the prediction of preinterventional rebleeding in patients suffering from aSAH. Updating the baseline hazard for each center was needed to improve calibration. After local validation and adjustment of the baseline hazard if required, the ARISE baseline model may well be used for risk prediction in patients with aSAH in other settings. The ARISE extended model needs further modification before reliable application can take place.
对外验证蛛网膜下腔出血后动脉瘤再出血(ARISE)预测模型,该模型用于预测动脉瘤性蛛网膜下腔出血(aSAH)后24小时和72小时内的介入前动脉瘤再出血情况。
我们汇总了来自挪威奥斯陆大学医院和荷兰鹿特丹大学医院两个国际医院登记处的数据,以验证ARISE基础模型(包括患者年龄、性别、高血压、世界神经外科医生联合会分级、Fisher分级、动脉瘤大小和脑脊液引流情况)和ARISE扩展模型(在基础模型中增加动脉瘤不规则性)。通过区分度(Harrell c统计量、基于模型的c统计量)和校准(整体校准、校准斜率和校准图)来评估模型性能。验证后,我们对ARISE模型进行了适当更新。
合并队列包括1467例患者,其中143例(10%)发生介入前再出血。在挪威奥斯陆大学医院队列中,ARISE基础模型的外部验证c统计量为0.75(95%CI:0.71 - 0.80),ARISE扩展模型为0.71(0.66 - 0.76)。在荷兰鹿特丹大学医院队列中,ARISE基础模型的c统计量为0.70(0.64 - 0.76),ARISE扩展模型为0.64(0.57 - 0.72)。整体校准较差;两个中心的两个模型的平均预测风险均低于平均观察到的风险。更新基线风险后,基础模型在临床相关再出血概率范围内校准良好。
ARISE基础模型对预测aSAH患者介入前再出血具有良好的区分能力。需要更新每个中心的基线风险以改善校准。经过局部验证并在需要时调整基线风险后,ARISE基线模型很可能可用于其他情况下aSAH患者的风险预测。ARISE扩展模型在可靠应用之前需要进一步修改。