Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis

JAMA - Journal of the American Medical Association - Tập 321 Số 20 - Trang 2003 - 2019
Christopher Seymour1,2,3, Jason Kennedy1,2, Shu Wang4, Chung‐Chou H. Chang1,4,5, Corrine F. Elliott6, Zhongying Xu4, Scott Berry6, Gilles Clermont1,2, Gregory F. Cooper7, Hernando Gómez1,2,3, David T. Huang1,2,3, John A. Kellum1,2, Qi Mi8, Steven M. Opal9, Victor B. Talisa4, Tom van der Poll10, Shyam Visweswaran7, Yoram Vodovotz11, Jeremy C. Weiss12, Donald M. Yealy3, Sachin Yende1,2,13, Derek C. Angus1,2,5
1Clinical Research, Investigation, and Systems Modeling of Acute Illness Center, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
2Department of Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
3Department of Emergency Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
4Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania
5Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
6Berry Consultants, Austin, Texas
7Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
8Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania
9Department of Medicine, Infectious Disease Division, Rhode Island Hospital, Providence
10Center of Experimental and Molecular Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
11Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania
12Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania
13Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania

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Tài liệu tham khảo

Rhee, 2017, Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009-2014., JAMA, 318, 1241, 10.1001/jama.2017.13836

Seymour, 2016, Assessment of clinical criteria for sepsis: for the third international consensus definitions for sepsis and septic shock (Sepsis-3)., JAMA, 315, 762, 10.1001/jama.2016.0288

Scicluna, 2017, Classification of patients with sepsis according to blood genomic endotype., Lancet Respir Med, 5, 816, 10.1016/S2213-2600(17)30294-1

Sweeney, 2018, Unsupervised analysis of transcriptomics in bacterial sepsis across multiple datasets reveals three robust clusters., Crit Care Med, 46, 915, 10.1097/CCM.0000000000003084

Davenport, 2016, Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study., Lancet Respir Med, 4, 259, 10.1016/S2213-2600(16)00046-1

Opal, 2013, Effect of eritoran, an antagonist of MD2-TLR4, on mortality in patients with severe sepsis., JAMA, 309, 1154, 10.1001/jama.2013.2194

Yealy, 2014, A randomized trial of protocol-based care for early septic shock., N Engl J Med, 370, 1683, 10.1056/NEJMoa1401602

Bernard, 2001, Efficacy and safety of recombinant human activated protein C for severe sepsis., N Engl J Med, 344, 699, 10.1056/NEJM200103083441001

Kellum, 2007, Understanding the inflammatory cytokine response in pneumonia and sepsis., Arch Intern Med, 167, 1655, 10.1001/archinte.167.15.1655

Levy, 2003, 2001 SCCM/ESICM/ACCP/ATS/SIS international sepsis definitions conference., Crit Care Med, 31, 1250, 10.1097/01.CCM.0000050454.01978.3B

Vincent, 1996, The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure., Intensive Care Med, 22, 707, 10.1007/BF01709751

Medzhitov, 2012, Disease tolerance as a defense strategy., Science, 335, 936, 10.1126/science.1214935

Angus, 2001, Epidemiology of severe sepsis in the United States., Crit Care Med, 29, 1303, 10.1097/00003246-200107000-00002

Angus, 2013, Severe sepsis and septic shock., N Engl J Med, 369, 2063

Newgard, 2007, Advanced statistics: missing data in clinical research—part 2: multiple imputation., Acad Emerg Med, 14, 669

Ankerst, 1999, OPTICS: ordering points to identify the clustering structure., SIGMOD Rec, 28, 49, 10.1145/304181

Wilkerson, 2010, ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking., Bioinformatics, 26, 1572, 10.1093/bioinformatics/btq170

Calfee, 2014, Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials., Lancet Respir Med, 2, 611, 10.1016/S2213-2600(14)70097-9

Rindskopf, 1986, The value of latent class analysis in medical diagnosis., Stat Med, 5, 21, 10.1002/(ISSN)1097-0258

Knaus, 1991, The APACHE III prognostic system: risk prediction of hospital mortality for critically ill hospitalized adults., Chest, 100, 1619, 10.1378/chest.100.6.1619

Deng, 2013, Lipopolysaccharide clearance, bacterial clearance, and systemic inflammatory responses are regulated by cell type-specific functions of TLR4 during sepsis., J Immunol, 190, 5152, 10.4049/jimmunol.1300496

Abraham, 2005, Drotrecogin alfa (activated) for adults with severe sepsis and a low risk of death., N Engl J Med, 353, 1332, 10.1056/NEJMoa050935

Ranieri, 2012, Drotrecogin alfa (activated) in adults with septic shock., N Engl J Med, 366, 2055, 10.1056/NEJMoa1202290

Maitland, 2011, Mortality after fluid bolus in African children with severe infection., N Engl J Med, 364, 2483, 10.1056/NEJMoa1101549

Andrews, 2014, Simplified severe sepsis protocol: a randomized controlled trial of modified early goal-directed therapy in Zambia., Crit Care Med, 42, 2315, 10.1097/CCM.0000000000000541

Rivers, 2001, Early goal-directed therapy in the treatment of severe sepsis and septic shock., N Engl J Med, 345, 1368, 10.1056/NEJMoa010307

Kent, 2007, Limitations of applying summary results of clinical trials to individual patients: the need for risk stratification., JAMA, 298, 1209, 10.1001/jama.298.10.1209

Berry, 2015, The platform trial: an efficient strategy for evaluating multiple treatments., JAMA, 313, 1619, 10.1001/jama.2015.2316