医学
生物标志物
动脉瘤
内科学
放射科
神经血管束
置信区间
病理
生物
生物化学
作者
Jiabin Su,Jing Cao,Heng Yang,Wei Xu,Wanshan Liu,Ruimin Wang,Yida Huang,Jiao Wu,Xinjie Gao,Ruiyuan Weng,Jun Pu,Ning Liu,Yuxiang Gu,Kun Qian,Wei Ni
出处
期刊:Small methods
[Wiley]
日期:2023-01-12
卷期号:7 (3): e2201486-e2201486
被引量:10
标识
DOI:10.1002/smtd.202201486
摘要
Unruptured intracranial aneurysm (UIA) is a high-risk cerebrovascular saccular dilatation, the effective medical management of which depends on high-performance diagnosis. However, most UIAs are diagnosed incidentally during neurovascular imaging modalities, which are time-consuming and harmful (e.g., radiation). Serum metabolic fingerprints is a promising alternative for early diagnosis of UIA. Here, nanoparticle enhanced laser desorption/ionization mass spectrometry is applied to obtain high-performance UIA-specific serum metabolic fingerprints. Diagnostic performance with an area-under-the-curve (AUC) of 0.842 (95% confidence interval (CI): 0.783-0.891) is achieved by the constructed machine learning (ML) model, including ML algorithm selection and feature selection. Lactate, glutamine, homoarginine, and 3-methylglutaconic acid are identified as the metabolic biomarker panel, which showed satisfactory diagnosis (AUC of 0.812, 95% CI: 0.727-0.897) and effective growth risk assessment (p<0.05, two-tailed t-test) of UIAs. This work aims to promote the diagnostics of UIAs and metabolic biomarker screening for medical management.
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