期刊
NATURE COMMUNICATIONS
卷 9, 期 -, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41467-018-03078-2
关键词
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资金
- NIGMS Glue Grant Legacy Award [R24GM102656]
- Instituto de Salud Carlos III [EMER07/050, PI13/02110, PI16/01156]
- National Center for Advancing Translational Sciences of the National Institutes of Health [UL1TR001417]
- NIH [U01AI066569, P20RR016480, HHSN266200400064C]
- Wellcome Trust [074318, 090532/Z/09/Z]
- European Research Council under the European Union's Seventh Framework Programme/ERC [281824]
- Medical Research Council [98082]
- UK Intensive Care Society
- NIHR Oxford Biomedical Research Centre
- National Institute for Health Research through the Comprehensive Clinical Research Network
- Duke University
- Novartis Vaccines and Diagnostics, Inc.
- NIGMS [P50 GM111152]
- Defense Advanced Research Projects Agency
- Army Research Office [W911NF-15-1-0107]
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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