Graduate School, Qinghai University, Xining, China.
Department of Neurosurgery, Qinghai Provincial People's Hospital, Xining, China,
Cerebrovasc Dis. 2020;49(5):556-562. doi: 10.1159/000510805. Epub 2020 Oct 2.
Intracerebral hemorrhage (ICH) is the most fatal type of stroke worldwide. Herein, we aim to develop a predictive model based on computed tomography (CT) markers in an ICH cohort and validate it in another cohort.
This retrospective observational cohort study was conducted in 3 medical centers in China. The values of CT markers, including hypodensities, hematoma density, blend sign, black hole sign, island sign, midline shift, baseline hematoma volume, and satellite sign, in predicting poor outcome were analyzed by logistic regression analysis. A nomogram was developed based on the results of multivariate logistic regression analysis in development cohort. Area under curve (AUC) and calibration plot were used to assess the accuracy of nomogram in this development cohort and validate in another cohort.
A total of 1,498 patients were included in this study. Multivariate logistic regression analysis indicated that hypodensities, black hole sign, island sign, midline shift, and baseline hematoma volume were independently associated with poor outcome in development cohort. The AUC was 0.75 (95% confidence interval [CI]: 0.73-0.76) in the internal validation with development cohort and 0.74 (95% CI: 0.72-0.75) in the external validation with validation cohort. The calibration plot in development and validation cohort indicated that the nomogram was well calibrated.
CT markers of hypodensities, black hole sign, and island sign might predict poor outcome of ICH patients within 90 days.
脑出血（ICH）是全球最致命的中风类型。在此，我们旨在建立一个基于 ICH 队列 CT 标志物的预测模型，并在另一个队列中进行验证。
这是一项在中国 3 家医疗中心进行的回顾性观察队列研究。通过逻辑回归分析，对 CT 标志物（包括低信号区、血肿密度、混合征、黑洞征、孤岛征、中线移位、基线血肿体积和卫星征）在预测不良预后中的价值进行分析。基于多变量逻辑回归分析的结果，在开发队列中制定了一个列线图。使用曲线下面积（AUC）和校准图评估列线图在开发队列中的准确性，并在另一个队列中进行验证。
本研究共纳入 1498 例患者。多变量逻辑回归分析表明，低信号区、黑洞征、孤岛征、中线移位和基线血肿体积与开发队列的不良预后独立相关。内部验证的 AUC 为 0.75（95%置信区间[CI]：0.73-0.76），外部验证的 AUC 为 0.74（95% CI：0.72-0.75）。开发和验证队列的校准图表明，该列线图具有良好的校准度。
低信号区、黑洞征和孤岛征等 CT 标志物可能预测 90 天内 ICH 患者的不良预后。
