An explainable prognostic prediction panel for sepsis based on serum amino acid profiles - Takeaways - MDSpire

An explainable prognostic prediction panel for sepsis based on serum amino acid profiles

  • By

  • Yue Liu

  • Long Zhao

  • Mingyue Sun

  • Jingyao Zhang

  • Chong Gu

  • Nanbin Hu

  • Shuangshuang Gu

  • Yan Shi

  • June 1, 2026

  • 0 min

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  • 1

    A study utilized serum amino acid profiles to differentiate patients with sepsis from healthy controls using liquid chromatography mass spectrometry.

  • 2

    Significant differences in amino acid abundance were observed among healthy controls, septic shock, and non-septic shock groups.

  • 3

    Five machine learning models were employed, with the deephit model demonstrating the best predictive performance for sepsis survival probability.

  • 4

    The optimized deephit model identified five key amino acids: glutamine, glycine, lysine, pyroglutamic acid, and proline for prognostic prediction.

  • 5

    Alterations in serum amino acid profiles are strongly associated with clinical outcomes in sepsis, supporting their potential as prognostic biomarkers.

Original Source(s)

An explainable prognostic prediction panel for sepsis based on serum amino acid profiles

  • by Yue Liu, Long Zhao, Mingyue Sun, Jingyao Zhang, Chong Gu, Nanbin Hu, Shuangshuang Gu, Yan Shi

  • June 1, 2026

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