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A community approach to mortality prediction in sepsis via gene expression analysis.

Publication ,  Journal Article
Sweeney, TE; Perumal, TM; Henao, R; Nichols, M; Howrylak, JA; Choi, AM; Bermejo-Martin, JF; Almansa, R; Tamayo, E; Davenport, EE; Burnham, KL ...
Published in: Nat Commun
February 15, 2018

Improved risk stratification and prognosis prediction in sepsis is a critical unmet need. Clinical severity scores and available assays such as blood lactate reflect global illness severity with suboptimal performance, and do not specifically reveal the underlying dysregulation of sepsis. Here, we present prognostic models for 30-day mortality generated independently by three scientific groups by using 12 discovery cohorts containing transcriptomic data collected from primarily community-onset sepsis patients. Predictive performance is validated in five cohorts of community-onset sepsis patients in which the models show summary AUROCs ranging from 0.765-0.89. Similar performance is observed in four cohorts of hospital-acquired sepsis. Combining the new gene-expression-based prognostic models with prior clinical severity scores leads to significant improvement in prediction of 30-day mortality as measured via AUROC and net reclassification improvement index These models provide an opportunity to develop molecular bedside tests that may improve risk stratification and mortality prediction in patients with sepsis.

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Published In

Nat Commun

DOI

EISSN

2041-1723

Publication Date

February 15, 2018

Volume

9

Issue

1

Start / End Page

694

Location

England

Related Subject Headings

  • Severity of Illness Index
  • Sepsis
  • Prognosis
  • Models, Theoretical
  • Humans
  • Gene Expression Profiling
  • Cross Infection
  • Community-Acquired Infections
  • Biomarkers
 

Citation

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Sweeney, T. E., Perumal, T. M., Henao, R., Nichols, M., Howrylak, J. A., Choi, A. M., … Langley, R. J. (2018). A community approach to mortality prediction in sepsis via gene expression analysis. Nat Commun, 9(1), 694. https://doi.org/10.1038/s41467-018-03078-2
Sweeney, Timothy E., Thanneer M. Perumal, Ricardo Henao, Marshall Nichols, Judith A. Howrylak, Augustine M. Choi, Jesús F. Bermejo-Martin, et al. “A community approach to mortality prediction in sepsis via gene expression analysis.Nat Commun 9, no. 1 (February 15, 2018): 694. https://doi.org/10.1038/s41467-018-03078-2.
Sweeney TE, Perumal TM, Henao R, Nichols M, Howrylak JA, Choi AM, et al. A community approach to mortality prediction in sepsis via gene expression analysis. Nat Commun. 2018 Feb 15;9(1):694.
Sweeney, Timothy E., et al. “A community approach to mortality prediction in sepsis via gene expression analysis.Nat Commun, vol. 9, no. 1, Feb. 2018, p. 694. Pubmed, doi:10.1038/s41467-018-03078-2.
Sweeney TE, Perumal TM, Henao R, Nichols M, Howrylak JA, Choi AM, Bermejo-Martin JF, Almansa R, Tamayo E, Davenport EE, Burnham KL, Hinds CJ, Knight JC, Woods CW, Kingsmore SF, Ginsburg GS, Wong HR, Parnell GP, Tang B, Moldawer LL, Moore FE, Omberg L, Khatri P, Tsalik EL, Mangravite LM, Langley RJ. A community approach to mortality prediction in sepsis via gene expression analysis. Nat Commun. 2018 Feb 15;9(1):694.

Published In

Nat Commun

DOI

EISSN

2041-1723

Publication Date

February 15, 2018

Volume

9

Issue

1

Start / End Page

694

Location

England

Related Subject Headings

  • Severity of Illness Index
  • Sepsis
  • Prognosis
  • Models, Theoretical
  • Humans
  • Gene Expression Profiling
  • Cross Infection
  • Community-Acquired Infections
  • Biomarkers