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《Nature，5月14日，An interpretable mortality prediction model for COVID-19 patients》

  • 来源专题：COVID-19科研动态监测
  • 编译者： zhangmin
  • 发布时间：2020-05-15

  • An interpretable mortality prediction model for COVID-19 patients

    Li Yan, Hai-Tao Zhang, […]Ye Yuan

    Nature Machine Intelligence (2020)

    Abstract

    The sudden increase in COVID-19 cases is putting high pressure on healthcare services worldwide. At this stage, fast, accurate and early clinical assessment of the disease severity is vital. To support decision making and logistical planning in healthcare systems, this study leverages a database of blood samples from 485 infected patients in the region of Wuhan, China, to identify crucial predictive biomarkers of disease mortality. For this purpose, machine learning tools selected three biomarkers that predict the mortality of individual patients more than 10 days in advance with more than 90% accuracy: lactic dehydrogenase (LDH), lymphocyte and high-sensitivity C-reactive protein (hs-CRP). In particular, relatively high levels of LDH alone seem to play a crucial role in distinguishing the vast majority of cases that require immediate medical attention.

  • 原文来源：https://www.nature.com/articles/s42256-020-0180-7
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