Biomarkers in Sepsis

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Klein Klouwenberg, 2015, Likelihood of infection in patients with presumed sepsis at the time of intensive care unit admission: a cohort study, Crit Care, 19, 319, 10.1186/s13054-015-1035-1

Dandona, 1994, Procalcitonin increase after endotoxin injection in normal subjects, J Clin Endocrinol Metab, 79, 1605

Brunkhorst, 1998, Kinetics of procalcitonin in iatrogenic sepsis, Intensive Care Med, 24, 888, 10.1007/s001340050683

Meisner, 2001, The plasma elimination rate and urinary secretion of procalcitonin in patients with normal and impaired renal function, Eur J anaesthesiology, 18, 79, 10.1097/00003643-200102000-00004

Wacker, 2013, Procalcitonin as a diagnostic marker for sepsis: a systematic review and meta-analysis, Lancet Infect Dis, 13, 426, 10.1016/S1473-3099(12)70323-7

Schuetz, 2012, Procalcitonin to guide initiation and duration of antibiotic treatment in acute respiratory infections: an individual patient data meta-analysis, Clin Infect Dis, 55, 651, 10.1093/cid/cis464

Bloos, 2011, Multinational, observational study of procalcitonin in ICU patients with pneumonia requiring mechanical ventilation: a multicenter observational study, Crit Care, 15, R88, 10.1186/cc10087

Schuetz, 2013, Procalcitonin decrease over 72 hours in US critical care units predicts fatal outcome in sepsis patients, Crit Care, 17, R115, 10.1186/cc12787

Schuetz, 2017, Serial procalcitonin predicts mortality in severe sepsis patients: results from the Multicenter Procalcitonin Monitoring Sepsis (MOSES) study, Crit Care Med, 45, 781, 10.1097/CCM.0000000000002321

Reinhart, 2011, Biomarkers in the critically ill patient: procalcitonin, Crit Care Clin, 27, 253, 10.1016/j.ccc.2011.01.002

Schuetz, 2012, Procalcitonin to initiate or discontinue antibiotics in acute respiratory tract infections, Cochrane Database Syst Rev, 10.1002/14651858.CD007498.pub2

Bloos, 2016, Effect of sodium selenite administration and procalcitonin-guided therapy on mortality in patients with severe sepsis or septic shock: a randomized clinical trial, JAMA Intern Med, 176, 1266, 10.1001/jamainternmed.2016.2514

Shehabi, 2014, Procalcitonin algorithm in critically ill adults with undifferentiated infection or suspected sepsis. A randomized controlled trial, Am J Respir Crit Care Med, 190, 1102, 10.1164/rccm.201408-1483OC

Chu, 2017, Practice patterns and outcomes associated with procalcitonin use in critically ill patients with sepsis, Clin Infect Dis, 64, 1509, 10.1093/cid/cix179

Simon, 2004, Serum procalcitonin and C-reactive protein levels as markers of bacterial infection: a systematic review and meta-analysis, Clin Infect Dis, 39, 206, 10.1086/421997

Sakr, 2008, Lipopolysaccharide binding protein in a surgical intensive care unit: a marker of sepsis?, Crit Care Med, 36, 2014, 10.1097/CCM.0b013e31817b86e3

Bouchon, 2001, TREM-1 amplifies inflammation and is a crucial mediator of septic shock, Nature, 410, 1103, 10.1038/35074114

Wu, 2012, Accuracy of plasma sTREM-1 for sepsis diagnosis in systemic inflammatory patients: a systematic review and meta-analysis, Crit Care, 16, R229, 10.1186/cc11884

Backes, 2012, Usefulness of suPAR as a biological marker in patients with systemic inflammation or infection: a systematic review, Intensive Care Med, 38, 1418, 10.1007/s00134-012-2613-1

Skibsted, 2013, Bench-to-bedside review: future novel diagnostics for sepsis - a systems biology approach, Crit Care, 17, 231, 10.1186/cc12693

Goh, 2017, Enhanced understanding of the host-pathogen interaction in sepsis: new opportunities for omic approaches, Lancet Respir Med, 5, 212, 10.1016/S2213-2600(17)30045-0

Reinhart, 2012, New approaches to sepsis: molecular diagnostics and biomarkers, Clin Microbiol Rev, 25, 609, 10.1128/CMR.00016-12

Holcomb, 2017, Host-based peripheral blood gene expression analysis for diagnosis of infectious diseases, J Clin Microbiol, 55, 360, 10.1128/JCM.01057-16

PR newswire. News releases: revolutionary diagnostic septiCyte™ LAB cleared by FDA for suspected sepsis patients. 2017. Available at: http://www.prnewswire.com/news-releases/revolutionary-diagnostic-septicyte-lab-cleared-by-fda-for-suspected-sepsis-patients-300411470.html. Accessed April 19, 2017.

McHugh, 2015, A molecular host response assay to discriminate between sepsis and infection-negative systemic inflammation in critically ill patients: discovery and validation in independent cohorts, PLoS Med, 12, e1001916, 10.1371/journal.pmed.1001916

Sweeney, 2015, A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set, Sci translational Med, 7, 287ra71, 10.1126/scitranslmed.aaa5993

Bauer, 2016, A transcriptomic biomarker to quantify systemic inflammation in sepsis - a prospective multicenter phase II diagnostic study, EBioMedicine, 6, 114, 10.1016/j.ebiom.2016.03.006

Scicluna, 2015, A molecular biomarker to diagnose community-acquired pneumonia on intensive care unit admission, Am J Respir Crit Care Med, 192, 826, 10.1164/rccm.201502-0355OC

Sweeney, 2015, Comprehensive validation of the FAIM3:PLAC8 ratio in time-matched public gene expression data, Am J Respir Crit Care Med, 192, 1260, 10.1164/rccm.201507-1321LE

Sweeney, 2017, Benchmarking sepsis gene expression diagnostics using public data, Crit Care Med, 45, 1, 10.1097/CCM.0000000000002021

Tsalik, 2016, Host gene expression classifiers diagnose acute respiratory illness etiology, Sci translational Med, 8, 322ra11, 10.1126/scitranslmed.aad6873

Suarez, 2015, Superiority of transcriptional profiling over procalcitonin for distinguishing bacterial from viral lower respiratory tract infections in hospitalized adults, J Infect Dis, 212, 213, 10.1093/infdis/jiv047

Parnell, 2012, A distinct influenza infection signature in the blood transcriptome of patients with severe community-acquired pneumonia, Crit Care, 16, R157, 10.1186/cc11477

Sweeney, 2016, Robust classification of bacterial and viral infections via integrated host gene expression diagnostics, Sci translational Med, 8, 346ra91, 10.1126/scitranslmed.aaf7165

Ramilo, 2007, Gene expression patterns in blood leukocytes discriminate patients with acute infections, Blood, 109, 2066, 10.1182/blood-2006-02-002477

Hu, 2013, Gene expression profiles in febrile children with defined viral and bacterial infection, Proc Natl Acad Sci U S A, 110, 12792, 10.1073/pnas.1302968110

Mejias, 2013, Whole blood gene expression profiles to assess pathogenesis and disease severity in infants with respiratory syncytial virus infection, PLoS Med, 10, e1001549, 10.1371/journal.pmed.1001549

Herberg, 2016, Diagnostic test accuracy of a 2-transcript host RNA signature for discriminating bacterial vs viral infection in febrile children, JAMA, 316, 835, 10.1001/jama.2016.11236

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

Wong, 2012, The pediatric sepsis biomarker risk model, Crit Care, 16, R174, 10.1186/cc11652

Wong, 2013, Genome-wide expression profiling in pediatric septic shock, Pediatr Res, 73, 564, 10.1038/pr.2013.11

Wong, 2014, A multibiomarker-based outcome risk stratification model for adult septic shock*, Crit Care Med, 42, 781, 10.1097/CCM.0000000000000106

Wong, 2017, Improved risk stratification in pediatric septic shock using both protein and mRNA Biomarkers: PERSEVERE-XP, Am J Respir Crit Care Med, 196, 494, 10.1164/rccm.201701-0066OC

Scicluna, 2017, Turning a new page in sepsis molecular diagnostics necessitates context-specific biomarkers, Crit Care Med, 45, e457, 10.1097/CCM.0000000000002214

Ludwig, 2017, Mass spectrometry for the discovery of biomarkers of sepsis, Mol Biosystems, 13, 648, 10.1039/C6MB00656F

Oved, 2015, A novel host-proteome signature for distinguishing between acute bacterial and viral infections, PLoS One, 10, e0120012, 10.1371/journal.pone.0120012

DeCoux, 2015, Plasma glycoproteomics reveals sepsis outcomes linked to distinct proteins in common pathways, Crit Care Med, 43, 2049, 10.1097/CCM.0000000000001134

Schmerler, 2012, Targeted metabolomics for discrimination of systemic inflammatory disorders in critically ill patients, J Lipid Res, 53, 1369, 10.1194/jlr.P023309

Rogers, 2014, Metabolomic derangements are associated with mortality in critically ill adult patients, PLoS One, 9, e87538, 10.1371/journal.pone.0087538

Mickiewicz, 2014, Metabolic profiling of serum samples by 1H nuclear magnetic resonance spectroscopy as a potential diagnostic approach for septic shock, Crit Care Med, 42, 1140, 10.1097/CCM.0000000000000142

Langley, 2013, An integrated clinico-metabolomic model improves prediction of death in sepsis, Sci translational Med, 5, 195ra95, 10.1126/scitranslmed.3005893

Neugebauer, 2016, Metabolite profiles in sepsis: developing prognostic tools based on the type of infection, Crit Care Med, 44, 1649, 10.1097/CCM.0000000000001740

Ferrario, 2016, Mortality prediction in patients with severe septic shock: a pilot study using a target metabolomics approach, Scientific Rep, 6, 20391, 10.1038/srep20391

Wang, 2017, Human genetic and metabolite variation reveals that methylthioadenosine is a prognostic biomarker and an inflammatory regulator in sepsis, Sci Adv, 3, e1602096, 10.1126/sciadv.1602096