Predictive values of island signs and blend signs on non-contrast CT in early hematoma enlargement of spontaneous intracerebral hemorrhage

W. Jia, Changqing Shi, Yalong Liu, Wenyong Li
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引用次数: 1

Abstract

Objective To explore the predictive values of island signs and blend signs on non-contrast CT in early hematoma enlargement of spontaneous intracerebral hemorrhage (sICH). Methods A total of 84 patients with sICH were admitted to Department of Neurosurgery, Wenjiang District People′s Hospital of Chengdu from January 2015 to December 2017 and consecutively enrolled into this study. The time from onset to the first CT examination was ≤6 h, and the second CT examination time was ≤24 h. According to the results of those 2 examinations, the patients were divided into the early hematoma enlargement group (35 cases) and the hematoma non-enlargement group (49 cases). The effects of CT island signs and blend signs on early hematoma enlargement and their diagnostic efficacy for early hematoma enlargement were analyzed. Results Non-contrast CT scan showed that 60.0% (21/35) in the early hematoma enlargement group had island sign, and 71.4% (25/35) had blend sign. Compared with 14.3% (7/49) and 24.5% (12/49) in non-enlargement group, those differences were statistically significant (both P<0.01). Multivariate logistic regression analysis revealed that both island sign (OR=12.720, 95% CI: 3.501-46.218, P<0.01) and blend sign (OR=10.793, 95% CI: 3.172-36.727, P=0.01) were independent predictors of early hematoma enlargement. The sensitivity, specificity, positive predictive value, negative predictive value and Youden index of island sign for early hematoma enlargement were 60.0%, 85.7%, 75.0%, 75.0% and 45.7% respectively. The sensitivity, specificity, positive predictive value, negative predictive value and Youden index of blend sign for early hematoma enlargement were 71.4%, 75.5%, 67.6%, 78.7% and 46.9% respectively. The sensitivity, specificity, positive predictive value, negative predictive value and Youden index of island sign combined with blend sign for early hematoma enlargement were 91.4%, 63.3%, 64.0%, 91.2% and 54.7% respectively. Conclusions Island sign and blend sign are independent predictors of early enlargement of hematoma. The diagnostic performance with the combination of island sign and blend sign seems higher than the that of either single indicator. Key words: Spontaneous intracerebral hemorrhage; X-ray computed tomography; Hematoma enlargement; Island sign; Blend sign
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非对比CT岛状征和混合征对自发性脑出血早期血肿扩大的预测价值
目的探讨非对比CT岛状征和混合征对自发性脑出血早期血肿扩大的预测价值。方法2015年1月至2017年12月,共有84例sICH患者入住成都市温江区人民医院神经外科,并连续纳入本研究。从发病到第一次CT检查的时间≤6h,第二次CT检查时间≤24h。根据这两次检查的结果,将患者分为早期血肿扩大组(35例)和血肿未扩大组(49例)。分析CT岛状征和混合征对早期血肿扩大的影响及其对早期血肿增大的诊断效果。结果早期血肿扩大组60.0%(21/35)有岛状征,71.4%(25/35)有混合征,与非扩大组14.3%(7/49)和24.5%(12/49)相比,多因素logistic回归分析显示,岛征(OR=12.720,95%CI:3.501-46.218,P<0.01)和混合征(OR=10.793,95%CI:3.172-36.727,P<0.01)是早期血肿扩大的独立预测因素。岛征早期血肿扩大的敏感性、特异性、阳性预测值、阴性预测值和Youden指数分别为60.0%、85.7%、75.0%、75.0%和45.7%。混合征对早期血肿扩大的敏感性、特异性、阳性预测值、阴性预测值和Youden指数分别为71.4%、75.5%、67.6%、78.7%和46.9%。岛征合并混合征早期血肿扩大的敏感性、特异性、阳性预测值、阴性预测值和Youden指数分别为91.4%、63.3%、64.0%、91.2%和54.7%。结论岛征和混合征是早期血肿扩大的独立预测因素。岛征和混合征相结合的诊断性能似乎高于单一指标。关键词:自发性脑出血;X射线计算机断层扫描;血肿增大;海岛标志;混合符号
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来源期刊
中华神经外科杂志
中华神经外科杂志 Medicine-Surgery
CiteScore
0.10
自引率
0.00%
发文量
10706
期刊介绍: Chinese Journal of Neurosurgery is one of the series of journals organized by the Chinese Medical Association under the supervision of the China Association for Science and Technology. The journal is aimed at neurosurgeons and related researchers, and reports on the leading scientific research results and clinical experience in the field of neurosurgery, as well as the basic theoretical research closely related to neurosurgery.Chinese Journal of Neurosurgery has been included in many famous domestic search organizations, such as China Knowledge Resources Database, China Biomedical Journal Citation Database, Chinese Biomedical Journal Literature Database, China Science Citation Database, China Biomedical Literature Database, China Science and Technology Paper Citation Statistical Analysis Database, and China Science and Technology Journal Full Text Database, Wanfang Data Database of Medical Journals, etc.
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