Noncontrast Computed Tomography Markers of Cerebral Hemorrhage Expansion: Diagnostic Accuracy Meta-Analysis

医学 脑出血 荟萃分析 血肿 计算机断层摄影术 逻辑回归 符号(数学) 放射科 核医学 内科学 蛛网膜下腔出血 数学 数学分析
作者
Francesco Arba,Chiara Rinaldi,Grégoire Boulouis,Enrico Fainardi,Andreas Charidimou,Andrea Morotti
出处
期刊:International Journal of Stroke [SAGE]
卷期号:17 (8): 835-847 被引量:17
标识
DOI:10.1177/17474930211061639
摘要

Background and purpose Assess the diagnostic accuracy of noncontrast computed tomography (NCCT) markers of hematoma expansion in patients with primary intracerebral hemorrhage. Methods We performed a meta-analysis of observational studies and randomized controlled trials with available data for calculation of sensitivity and specificity of NCCT markers for hematoma expansion (absolute growth >6 or 12.5 mL and/or relative growth >33%). The following NCCT markers were analyzed: irregular shape, island sign (shape-related features); hypodensity, heterogeneous density, blend sign, black hole sign, and swirl sign (density-related features). Pooled accuracy values for each marker were derived from hierarchical logistic regression models. Results A total of 10,363 subjects from 23 eligible studies were included. Significant risk of bias of included studies was noted. Hematoma expansion frequency ranged from 7% to 40%, mean intracerebral hemorrhage volume from 9 to 27.8 ml, presence of NCCT markers from 9% (island sign) to 82% (irregular shape). Among shape features, sensitivity ranged from 0.32 (95%CI = 0.20–0.47) for island sign to 0.68 (95%CI = 0.57–0.77) for irregular shape, specificity ranged from 0.47 (95%CI = 0.36–0.59) for irregular shape to 0.92 (95%CI = 0.85–0.96) for island sign; among density features sensitivity ranged from 0.28 (95%CI = 0.21–0.35) for black hole sign to 0.63 (95%CI = 0.44–0.78) for hypodensity, specificity ranged from 0.65 (95%CI = 0.56–0.73) for heterogeneous density to 0.89 (95%CI = 0.85–0.92) for blend sign. Conclusion Diagnostic accuracy of NCCT markers remains suboptimal for implementation in clinical trials although density features performed better than shape-related features. This analysis may help in better tailoring patients’ selection for hematoma expansion targeted trials.
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