• World Neurosurg · Mar 2019

    Meta Analysis

    Predictive Validity of Hypodensities on Noncontrast Computed Tomography for Hematoma Growth in Intracerebral Hemorrhage: a Meta-Analysis.

    • Zhiyuan Yu, Jun Zheng, Lu Ma, Rui Guo, Chao You, and Hao Li.
    • Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China.
    • World Neurosurg. 2019 Mar 1; 123: e639-e645.

    ObjectiveIntracerebral hemorrhage (ICH) is a type of stroke that leads to high mortality. Hematoma growth (HG) happens in about one third of all patients with ICH and is independently related to poor outcome. Previous studies have shown that an indicator on noncontrast computed tomography, called hypodensities, can predict HG in patients with ICH. Thus, this study was done to assess the predictive validity of this marker.MethodsBibliographic databases were searched, without language restriction, for original investigation on hypodensities and HG in ICH. Data were extracted, and study quality was assessed by 2 reviewers independently. Pooled sensitivity, specificity, positive likelihood ratio (LR), negative LR, diagnostic odds ratio, and their 95% confidence intervals (CIs) were obtained. A summary receiver operating characteristic curve was depicted.ResultsFive cohorts with 2157 patients in 4 studies were included in the present meta-analysis. The pooled sensitivity was 0.58 (95% CI 0.46-0.68) and the pooled specificity was 0.71 (95% CI 0.62-0.79). In addition, the pooled positive LR was 2.0 (95% CI 1.6-2.5) and the pooled negative LR was 0.60 (95% CI 0.49-0.73). The pooled diagnostic odds ratio was 3 (95% CI 2-5) and the area under summary receiver operating characteristic curve was 0.69 (95% CI 0.65-0.73).ConclusionsThis study suggests that hypodensities on noncontrast computed tomography can be helpful in HG prediction, although its pooled predictive values are not very satisfying in the current study. The role of hypodensities in predicting HG should be confirmed by further studies.Copyright © 2018 Elsevier Inc. All rights reserved.

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