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An integrated clinico-metabolomic model improves prediction of death in sepsis.

Publication ,  Journal Article
Langley, RJ; Tsalik, EL; van Velkinburgh, JC; Glickman, SW; Rice, BJ; Wang, C; Chen, B; Carin, L; Suarez, A; Mohney, RP; Freeman, DH; Wang, M ...
Published in: Sci Transl Med
July 24, 2013

Sepsis is a common cause of death, but outcomes in individual patients are difficult to predict. Elucidating the molecular processes that differ between sepsis patients who survive and those who die may permit more appropriate treatments to be deployed. We examined the clinical features and the plasma metabolome and proteome of patients with and without community-acquired sepsis, upon their arrival at hospital emergency departments and 24 hours later. The metabolomes and proteomes of patients at hospital admittance who would ultimately die differed markedly from those of patients who would survive. The different profiles of proteins and metabolites clustered into the following groups: fatty acid transport and β-oxidation, gluconeogenesis, and the citric acid cycle. They differed consistently among several sets of patients, and diverged more as death approached. In contrast, the metabolomes and proteomes of surviving patients with mild sepsis did not differ from survivors with severe sepsis or septic shock. An algorithm derived from clinical features together with measurements of five metabolites predicted patient survival. This algorithm may help to guide the treatment of individual patients with sepsis.

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Published In

Sci Transl Med

DOI

EISSN

1946-6242

Publication Date

July 24, 2013

Volume

5

Issue

195

Start / End Page

195ra95

Location

United States

Related Subject Headings

  • Sepsis
  • Proteomics
  • Models, Theoretical
  • Middle Aged
  • Metabolomics
  • Male
  • Humans
  • Female
  • Algorithms
  • Aged
 

Citation

APA
Chicago
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Langley, R. J., Tsalik, E. L., van Velkinburgh, J. C., Glickman, S. W., Rice, B. J., Wang, C., … Kingsmore, S. F. (2013). An integrated clinico-metabolomic model improves prediction of death in sepsis. Sci Transl Med, 5(195), 195ra95. https://doi.org/10.1126/scitranslmed.3005893
Langley, Raymond J., Ephraim L. Tsalik, Jennifer C. van Velkinburgh, Seth W. Glickman, Brandon J. Rice, Chunping Wang, Bo Chen, et al. “An integrated clinico-metabolomic model improves prediction of death in sepsis.Sci Transl Med 5, no. 195 (July 24, 2013): 195ra95. https://doi.org/10.1126/scitranslmed.3005893.
Langley RJ, Tsalik EL, van Velkinburgh JC, Glickman SW, Rice BJ, Wang C, et al. An integrated clinico-metabolomic model improves prediction of death in sepsis. Sci Transl Med. 2013 Jul 24;5(195):195ra95.
Langley, Raymond J., et al. “An integrated clinico-metabolomic model improves prediction of death in sepsis.Sci Transl Med, vol. 5, no. 195, July 2013, p. 195ra95. Pubmed, doi:10.1126/scitranslmed.3005893.
Langley RJ, Tsalik EL, van Velkinburgh JC, Glickman SW, Rice BJ, Wang C, Chen B, Carin L, Suarez A, Mohney RP, Freeman DH, Wang M, You J, Wulff J, Thompson JW, Moseley MA, Reisinger S, Edmonds BT, Grinnell B, Nelson DR, Dinwiddie DL, Miller NA, Saunders CJ, Soden SS, Rogers AJ, Gazourian L, Fredenburgh LE, Massaro AF, Baron RM, Choi AMK, Corey GR, Ginsburg GS, Cairns CB, Otero RM, Fowler VG, Rivers EP, Woods CW, Kingsmore SF. An integrated clinico-metabolomic model improves prediction of death in sepsis. Sci Transl Med. 2013 Jul 24;5(195):195ra95.

Published In

Sci Transl Med

DOI

EISSN

1946-6242

Publication Date

July 24, 2013

Volume

5

Issue

195

Start / End Page

195ra95

Location

United States

Related Subject Headings

  • Sepsis
  • Proteomics
  • Models, Theoretical
  • Middle Aged
  • Metabolomics
  • Male
  • Humans
  • Female
  • Algorithms
  • Aged