Department of Neurosurgery, Wessex Neurological Centre, Southampton General Hospital, Southampton, SO16 6YD, UK.
Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK.
Neurosurg Rev. 2024 Oct 8;47(1):752. doi: 10.1007/s10143-024-03001-y.
This study aimed to describe the relationship between blood and CSF volumes in different compartments on baseline CT after aSAH, assess if they independently predict long-term outcome, and explore their interaction with age. CT scans from patients participating in a prospective multicenter randomized controlled trial of patients with aSAH were segmented for blood and CSF volumes. The primary outcomes were the mRS, and the Subarachnoid Hemorrhage Outcome Tool (SAHOT) at day 28 and 180. Univariate regressions were conducted to identify significant predictors of poor outcomes, followed by principal component analysis to explore correlations between imaging variables and WFNS. A multivariate predictive model was then developed and optimized using stepwise regression. CT scans from 97 patients with a median delay from symptom onset of 271 min (131-547) were analyzed. Univariate analysis showed only WFNS, and total blood volume (TBV) were significant predictors of both short and long-term outcome with WFNS more predictive of mRS and TBV more predictive of SAHOT. Principal component analysis showed strong dependencies between the imaging predictors. Multivariate ordinal regression showed models with WFNS alone were most predictive of day 180 mRS and models with TBV alone were most predictive of SAHOT. TBV was the most significant measured imaging predictor of poor long-term outcome after aSAH. All these imaging predictors are correlated, however, and may have multiple complex interactions necessitating larger datasets to detect if they provide any additional predictive value for long-term outcome.
本研究旨在描述 aSAH 后基线 CT 上不同部位的血液和 CSF 体积之间的关系,评估它们是否独立预测长期预后,并探讨它们与年龄的相互作用。对参与前瞻性多中心随机对照试验的 aSAH 患者的 CT 扫描进行分割,以测量血液和 CSF 体积。主要结局指标为 mRS 和第 28 天及 180 天的蛛网膜下腔出血结局工具(SAHOT)评分。进行单变量回归以确定不良预后的显著预测因素,然后进行主成分分析以探讨影像学变量与 WFNS 之间的相关性。然后使用逐步回归法建立并优化多变量预测模型。分析了 97 例患者的 CT 扫描,其从症状发作到 CT 扫描的中位数时间延迟为 271 分钟(131-547 分钟)。单变量分析显示仅 WFNS 和总血容量(TBV)是短期和长期预后的显著预测因素,WFNS 对 mRS 的预测作用更强,TBV 对 SAHOT 的预测作用更强。主成分分析显示影像学预测因素之间存在很强的依赖性。多变量有序回归显示,仅 WFNS 的模型对第 180 天 mRS 的预测作用最强,仅 TBV 的模型对 SAHOT 的预测作用最强。TBV 是 aSAH 后不良长期预后的最显著的影像学预测因素。然而,所有这些影像学预测因素都是相关的,可能存在多种复杂的相互作用,需要更大的数据集来检测它们是否对长期预后提供任何额外的预测价值。