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An Integrated Clinico-Metabolomic Model Improves Prediction of Death in Sepsis

2013; American Association for the Advancement of Science; Volume: 5; Issue: 195 Linguagem: Inglês

10.1126/scitranslmed.3005893

1946-6242

Raymond J. Langley, Ephraim L. Tsalik, Jennifer C. van Velkinburgh, Seth W. Glickman, Brandon Rice, Chunping Wang, Bo Chen, Lawrence Carin, Arturo Suarez, Robert P. Mohney, Debra H. Freeman, Mu Wang, Jinsam You, Jacob Wulff, J. Will Thompson, M. Arthur Moseley, Stephanie J. Reisinger, Brian T. Edmonds, Brian W. Grinnell, David R. Nelson, Darrell L. Dinwiddie, Neil Miller, Carol Saunders, Sarah S. Soden, Angela J. Rogers, Lee Gazourian, Laura E. Fredenburgh, Anthony F. Massaro, Rebecca M. Baron, Augustine M.K. Choi, G. Ralph Corey, Geoffrey S. Ginsburg, Charles B. Cairns, Ronny Otero, Vance G. Fowler, Emanuel P. Rivers, Christopher W. Woods, Stephen F. Kingsmore,

Gut microbiota and health

A molecular signature, derived from integrated analysis of clinical data, the metabolome, and the proteome in prospective human studies, improved the prediction of death in patients with sepsis, potentially identifying a subset of patients who merit intensive treatment.