• Xuxin Zhang, Yanzhao Li, Yan Liang, Pitong Sun, Xue Wu, Jinhui Song, Xiaoyu Sun, Mo Hong, Peng Gao, and Dongfeng Deng.
• Department of Neurosurgery, Affiliated Zhongshan Hospital of Dalian University, Dalian, Liaoning, China.
• Rev Invest Clin. 2017 Nov 1; 69 (6): 319-328.

BackgroundAcute cerebral infarction (ACI) and intracerebral hemorrhage (ICH) are potentially lethal cerebrovascular diseases that seriously impact public health. ACI and ICH share several common clinical manifestations but have totally divergent therapeutic strategies. A poor diagnosis can affect stroke treatment.ObjectiveTo screen for biomarkers to differentiate ICH from ACI, we enrolled 129 ACI and 128 ICH patients and 65 healthy individuals as controls.MethodsPatients with stroke were diagnosed by computed tomography/magnetic resonance imaging, and their blood samples were obtained by fingertip puncture within 2-12 h after stroke initiation. We compared changes in metabolites between ACI and ICH using dried blood spot-based direct infusion mass spectrometry technology for differentiating ICH from ACI.ResultsThrough multivariate statistical approaches, 11 biomarkers including 3-hydroxylbutyrylcarnitine, glutarylcarnitine (C5DC), myristoylcarnitine, 3-hydroxypalmitoylcarnitine, tyrosine/citrulline (Cit), valine/phenylalanine, C5DC/3-hydroxyisovalerylcarnitine, C5DC/palmitoylcarnitine, hydroxystearoylcarnitine, ratio of sum of C0, C2, C3, C16, and C18:1 to Cit, and propionylcarnitine/methionine were screened. An artificial neural network model was constructed based on these parameters. A training set was evaluated by cross-validation method. The accuracy of this model was checked by an external test set showing a sensitivity of 0.8400 (95% confidence interval [CI], 0.7394-0.9406) and specificity of 0.7692 (95% CI, 0.6536-0.8848).ConclusionThis study confirmed that metabolomic analysis is a promising tool for rapid and timely stroke differentiation and prediction based on differential metabolites.Copyright: © 2017 SecretarÍa de Salud

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