The frequency of imaging markers adjusted for time since symptom onset in intracerebral hemorrhage: A novel predictor for hematoma expansion

医学 置信区间 脑出血 接收机工作特性 优势比 脑室出血 格拉斯哥昏迷指数 曲线下面积 血肿 内科学 试验预测值 多元分析 诊断试验中的似然比 心脏病学 自发性脑出血 磁共振成像 核医学 放射科 外科 胎龄 怀孕 生物 遗传学
作者
Lei Song,Jun Cheng,Cun Zhang,Hang Zhou,Wenmin Guo,Yu Ye,Rujia Wang,Hui Xiong,Ji Zhang,Ke Ren,Dongfang Tang,Yu‐Fei Fu,Zhibing He,Liwei Zou,Longsheng Wang,Lianghong Kuang,Xiaoming Qiu,Tingting Guo,Yongqiang Yu
出处
期刊:International Journal of Stroke [SAGE]
卷期号:19 (2): 226-234 被引量:5
标识
DOI:10.1177/17474930231205221
摘要

Background: Hematoma expansion (HE) is common in patients with intracerebral hemorrhage (ICH) and associated with a worse outcome. Imaging makers and shorter time from symptom onset are both associated with HE, but prognostic scores based on these parameters individually have not been satisfactory. We hypothesized that a score including both imaging markers of expansion, and time of onset, would improve prediction. Methods: Patients with supratentorial ICH within 6 h after onset were consecutively recruited from six centers between January 2018 and August 2022. Three markers were used: hypodensities, the blend sign, and the island sign. We first defined frequency of imaging markers (FIM) as the relationship between the number of imaging markers and onset-to-CT time (OCT). The time-adjusted FIM was defined as the ratio of the number of imaging markers to the onset-to-initial imaging time. Multivariate analysis was performed to determine the relationship between FIM and HE. Receiver operating curve analysis was used to identify potential threshold values of FIM that optimally predict HE. In addition, the sensitivity, specificity, positive and negative predictive values (PPVs and NPVs), and the area under the curve (AUC) of the optimal cut-off in predicting HE were calculated. Results: In total, 1488 patients were eligible for inclusion, of whom 418 had incident HE. Multivariate analysis showed that age, male sex, baseline Glasgow Coma Scale score, presence of intraventricular hemorrhage, and FIM were independent predictors of HE (odds ratio (OR) = 0.98, 95% confidence interval (CI) = 0.97–0.99; OR = 1.73, 95% CI = 1.28–2.35; OR = 0.87, 95% CI = 0.83–0.92; OR = 0.42, 95% CI = 0.28–0.62; OR = 7.82, 95% CI = 5.86–10.42, respectively). The optimal cut-off point for FIM in predicting HE was 0.63, with sensitivity, specificity, PPV, NPV, and AUC values of 0.69, 0.89, 0.71, 0.88, and 0.83, respectively. Conclusion: The FIM adjusted for time since symptom onset is a significant predictor of HE. Its use may allow improved prediction of those patients with ICH who develop HE, and the score may be clinically applicable in the management of patients with ICH.
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