Faculty Collaboration Database

An integrated clinico-metabolomic model improves prediction of death in sepsis. Sci Transl Med 2013 Jul 24;5(195):195ra95

Date

07/26/2013

Pubmed ID

23884467

Pubmed Central ID

PMC3924586

DOI

10.1126/scitranslmed.3005893

Scopus ID

2-s2.0-84882977493 (requires institutional sign-in at Scopus site)   352 Citations

Abstract

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.

Author List

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 AM, Corey GR, Ginsburg GS, Cairns CB, Otero RM, Fowler VG Jr, Rivers EP, Woods CW, Kingsmore SF

Author

Ronny M. Otero MD Vice Chair, Professor in the Emergency Medicine department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

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