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J Neurol ; 265(8): 1883-1890, 2018 Aug.
Article in English | MEDLINE | ID: mdl-29948249

ABSTRACT

BACKGROUND AND PURPOSE: The hematoma expansion (HE) is an important risk factor for early neurological deterioration and poor prognosis. In this study, we aimed to compare the black hole sign with other computed tomography (CT) features to predict the HE and the outcome in patients with intracerebral hemorrhage (ICH). METHODS: Patients were enrolled within 12 h after stroke attack in the emergency department of Henan Provincial People's Hospital between January 2012 and June 2016. The clinical characters and CT features including the initial CT and the follow-up CT within 48 h were recorded. The outcome was assessed by using the modified Rankin Scale on discharge. Logistic regression analyses were used to investigate whether the factors were the independent predictor of HE and the outcome in patients with ICH. The sensitivity, specificity, positive predictive value, and negative predictive of CT features in predicting HE were calculated. RESULTS: A total of 185 ICH patients were enrolled, including 70 (37.8%) patients in HE group and 115 (62.2%) patients in non-HE group. There were significant difference in the initial hematoma volume, irregular shape, and CT black hole sign (P = 0.013, 0.006 and P < 0.001) between the two groups. While irregular shape and CT black hole sign were independent predictors for HE, the sensitivity and specificity were 71.45 and 54.78, 51.4 and 81.7%, respectively. Multivariable analysis identified CT black hole sign (P = 0.108) and initial intraventricular hemorrhage expansion (P = 0.214) were not the independent predictors of poor outcome. CONCLUSION: CT black hole sign presented the best predictive accuracy of predicting HE in patients with ICH compared to other CT features. However, it was not an independent predictor of poor outcome.


Subject(s)
Brain/diagnostic imaging , Cerebral Hemorrhage/diagnostic imaging , Hematoma/diagnostic imaging , Tomography, X-Ray Computed , Adult , Aged , Aged, 80 and over , Disease Progression , Female , Follow-Up Studies , Humans , Logistic Models , Male , Middle Aged , Prognosis , Retrospective Studies , Stroke/diagnostic imaging
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