Yamada Shuhei, Nishida Takeo, Takenaka Tomofumi, Yamazaki Hiroki, Nakagawa Ryota, Takagaki Masatoshi, Yano Yoshihiro, Nakamura Hajime, Toyota Shingo, Fujinaka Toshiyuki, Taki Takuyu, Fujita Toshiaki, Kishima Haruhiko
Department of Neurosurgery, the University of Osaka Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Department of Neurosurgery, Kansai Rosai Hospital, Amagasaki, Hyogo, Japan.
Acta Neurochir (Wien). 2025 Jul 24;167(1):200. doi: 10.1007/s00701-025-06611-7.
Aneurysmal subarachnoid hemorrhage (aSAH) with World Federation of Neurological Societies (WFNS) grade V has a high mortality rate and poor prognosis. Some patients with WFNS grade V aSAH have had good outcomes after aggressive treatment; however, outcome predictions based on routine examinations and findings obtained at admission are yet to be reported. This study aimed to develop a decision tree model for predicting outcomes of patients with WFNS grade V aSAH to aid decision-making for treatment strategy.
A multicenter study with retrospective and prospective data collected from 201 (derivation cohort) and 26 (validation cohort) patients with WFNS grade V aSAH, respectively, was conducted. Clinical outcomes were divided into good (Modified Rankin Scale [mRS] score at the time of discharge: 0-2) and poor (mRS score: 3-6) outcomes. A decision tree model was developed for the derivation cohort using the classification and regression tree method with clinical data including laboratory findings; it was named OPAS-V (Outcome Prediction in Aneurysmal Subarachnoid hemorrhage with WFNS grade V). The performance of the model was evaluated by area under the curve (AUC) and overall accuracy in both cohorts.
OPAS-V comprised 3 metrics; the percentage of lymphocytes (< 49.9% or not), age (> 50 yrs or not), and glucose to potassium ratio (≥ 3.2 or not). The model achieved an AUC of 0.828 (95% confidence interval: 0.712-0.944) and overall accuracy of 0.930. Moreover, the model performed well in the validation cohort with an AUC of 0.727 (95% confidence interval: 0.441-1) and overall accuracy of 0.885.
This study developed the first decision tree model for predicting outcomes of patients with WFNS grade V aSAH, based on simple findings obtained at admission. This may aid clinicians in determining treatment strategies for severe conditions such as WFNS grade V aSAH.
世界神经外科联盟(WFNS)分级为V级的动脉瘤性蛛网膜下腔出血(aSAH)死亡率高且预后差。一些WFNS V级aSAH患者在积极治疗后取得了良好的预后;然而,基于常规检查和入院时获得的检查结果进行预后预测的研究尚未见报道。本研究旨在建立一个决策树模型,用于预测WFNS V级aSAH患者的预后,以辅助治疗策略的决策制定。
开展一项多中心研究,分别从201例(推导队列)和26例(验证队列)WFNS V级aSAH患者中收集回顾性和前瞻性数据。临床结局分为良好(出院时改良Rankin量表[mRS]评分:0 - 2)和不良(mRS评分:3 - 6)结局。使用分类与回归树方法,结合包括实验室检查结果在内的临床数据,为推导队列建立决策树模型;将其命名为OPAS - V(WFNS V级动脉瘤性蛛网膜下腔出血的结局预测模型)。通过曲线下面积(AUC)和两个队列的总体准确率评估该模型的性能。
OPAS - V包含3个指标:淋巴细胞百分比(<49.9%或否)、年龄(>50岁或否)以及血糖与血钾比值(≥3.2或否)。该模型的AUC为0.828(95%置信区间:0.712 - 0.944),总体准确率为0.930。此外,该模型在验证队列中表现良好,AUC为0.727(95%置信区间:0.441 - 1),总体准确率为0.885。
本研究基于入院时获得的简单检查结果,建立了首个用于预测WFNS V级aSAH患者预后的决策树模型。这可能有助于临床医生确定针对WFNS V级aSAH等严重病情的治疗策略。