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Revista de Investigacion Clinica

Distinguishing Intracerebral Hemorrhage from Acute Cerebral Infarction through Metabolomics.

Watumiaji waliosajiliwa tu ndio wanaweza kutafsiri nakala
Ingia / Ingia
Kiungo kimehifadhiwa kwenye clipboard
Xuxin Zhang
Yanzhao Li
Yan Liang
Pitong Sun
Xue Wu
Jinhui Song
Xiaoyu Sun
Mo Hong
Peng Gao
Dongfeng Deng

Maneno muhimu

Kikemikali

UNASSIGNED

Acute 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.

UNASSIGNED

To screen for biomarkers to differentiate ICH from ACI, we enrolled 129 ACI and 128 ICH patients and 65 healthy individuals as controls.

UNASSIGNED

Patients 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.

UNASSIGNED

Through 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).

UNASSIGNED

This study confirmed that metabolomic analysis is a promising tool for rapid and timely stroke differentiation and prediction based on differential metabolites.

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