This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
Vea A, Llorente-Cortes V, de Gonzalo-Calvo D. Circular RNAs: a novel tool in cardiovascular biomarker development? Non-coding RNA Investig. 2018; 2:39.VeaALlorente-CortesVdeGonzalo-Calvo DCircular RNAs: a novel tool in cardiovascular biomarker development?201823910.21037/ncri.2018.06.06Search in Google Scholar
Kertai MD, Li YJ, Li YW et al. Genome-wide association study of perioperative myocardial infarction after coronary artery bypass surgery. BMJ Open. 2015; 6;5(5):e006920 10.1136/bmjopen-2014-006920KertaiMDLiYJLiYWet alGenome-wide association study of perioperative myocardial infarction after coronary artery bypass surgery2015655e00692010.1136/bmjopen-2014-006920443116925948407Open DOISearch in Google Scholar
Valpione S, Martinoli C, Fava P, Mocellin S, Campana LG, Quaglino P. Personalized medicine: Development and external validation of a prognostic model for metastatic melanoma patients treated with ipilimumab. EJC. 2015; (14): 2086–94.ValpioneSMartinoliCFavaPMocellinSCampanaLGQuaglinoPPersonalized medicine: Development and external validation of a prognostic model for metastatic melanoma patients treated with ipilimumab2015142086–9410.1016/j.ejca.2015.06.13026227432Search in Google Scholar
Molinaro, S, Pieroni S, Mariani F, Liebman M. Personalized medicine: Moving from correlation to causality in breast cancer. European Journal of Molecular & Clinical Medicine. 2015; 2(2): 59.MolinaroSPieroniSMarianiFLiebmanMPersonalized medicine: Moving from correlation to causality in breast cancer2015225910.1016/j.nhtm.2014.11.017Search in Google Scholar
Stafford-Smith M, Li YJ, Mathew JP et al. Genome-wide association study of acute kidney injury after coronary bypass graft surgery identifies susceptibility loci. Kidney Int. 2015; 88(4):823-32.Stafford-SmithMLiYJMathewJPet alGenome-wide association study of acute kidney injury after coronary bypass graft surgery identifies susceptibility loci2015884823–3210.1038/ki.2015.161458943926083657Search in Google Scholar
Kunin A, PolivkaJr P, Moiseeva N, Golubnitschaja O. Dry mouth and “Flammer” syndromes—neglected risks in adolescents and new concepts by predictive, preventive and personalised approach. EPMA Journal.2018; 9:307-12.KuninAPolivkaJrPMoiseevaNGolubnitschajaODry mouth and “Flammer” syndromes—neglected risks in adolescents and new concepts by predictive, preventive and personalised approach9307–1210.1007/s13167-018-0145-7610745530174766Search in Google Scholar
Li X, Seebacher NA, Hornicek FJ, Xiao T, Duan Z. Application of liquid biopsy in bone and soft tissue sarcomas: Present and future. Cancer Let. 2018; 439:66-77.LiXSeebacherNAHornicekFJXiaoTDuanZApplication of liquid biopsy in bone and soft tissue sarcomas: Present and future201843966–7710.1016/j.canlet.2018.09.01230223067Search in Google Scholar
Maslove MD, Lamontagn L, Marshall JC, Heyland KD. A path to precision in the ICU. Critical Care.2017; 21:79-85.MasloveMDLamontagnLMarshallJCHeylandKDA path to precision in the ICU20172179–8510.1186/s13054-017-1653-x537668928366166Search in Google Scholar
Food and Drug Administration. Science and Research Drugs,Table of Pharmacogenomicbiomarkers. Available at: https://www.fda.gov/downloads/Drugs/ScienceResearch/UCM578588.pdfAvailable athttps://www.fda.gov/downloads/Drugs/ScienceResearch/UCM578588.pdfSearch in Google Scholar
National Research Council. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease. Available at https://www.nap.edu/catalog/13284/toward-precision-medicine-building-a-knowledge-network-for-biomedical-researchAvailable athttps://www.nap.edu/catalog/13284/toward-precision-medicine-building-a-knowledge-network-for-biomedical-researchSearch in Google Scholar
Topol EJ. Individualized medicine from prewomb to tomb. Cell. 2014; 157(1):241-53.TopolEJIndividualized medicine from prewomb to tomb20141571241–5310.1016/j.cell.2014.02.012399512724679539Search in Google Scholar
Sweeney TE, Shidham A, Wong HR, Khatri P. A comprehensive time-course-based multi cohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set. Sci Transl Med. 2015;7(287):287ra71. 10.1126/scitranslmed.aaa5993SweeneyTEShidhamAWongHRKhatriPA comprehensive time-course-based multi cohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set20157287287ra7110.1126/scitranslmed.aaa5993473436225972003Open DOISearch in Google Scholar
Wong HR, Atkinson SJ, Cvijanovich NZ, et al. Combining Prognostic and Predictive Enrichment Strategies to Identify Children With Septic Shock Responsive to Corticosteroids. Crit Care Med. 2016;44(10):e1000–e1003. 10.1097/CCM.0000000000001833WongHRAtkinsonSJCvijanovichNZet alCombining Prognostic and Predictive Enrichment Strategies to Identify Children With Septic Shock Responsive to Corticosteroids20164410e1000–e100310.1097/CCM.0000000000001833502654027270179Open DOISearch in Google Scholar
Walley KR, Thain KR, Russell JA, et al. PCSK9 is a critical regulator of the innate immune response and septic shock outcome. Sci Transl Med. 2014;6(258):258ra143. 10.1126/scitranslmed.3008782WalleyKRThainKRRussellJAet alPCSK9 is a critical regulator of the innate immune response and septic shock outcome20146258258ra14310.1126/scitranslmed.3008782434214725320235Open DOISearch in Google Scholar
Sapru A, Liu KD, Wiemels J et al. Association of common genetic variation in the protein C pathway geneswith clinical outcomes in acute respiratory distress syndrome. Crit Care.2016; 20(1):151.SapruALiuKDWiemelsJet alAssociation of common genetic variation in the protein C pathway geneswith clinical outcomes in acute respiratory distress syndrome201620115110.1186/s13054-016-1330-5487655927215212Search in Google Scholar
Russell JA. Genomics and pharmacogenomics of sepsis: so close and yet so far. Crit Care. 2016;1–4.RussellJAGenomics and pharmacogenomics of sepsis: so close and yet so far20161–410.1186/s13054-016-1374-6493625127384443Search in Google Scholar
Calfee CS, Janz DR, Bernard GR et al. Distinct molecular phenotypes of direct vs indirect ARDS in single-center and multicenter studies. Chest. 2015; 147:1539–48.CalfeeCSJanzDRBernardGRet alDistinct molecular phenotypes of direct vs indirect ARDS in single-center and multicenter studies20151471539–4810.1378/chest.14-2454445170826033126Search in Google Scholar
Weinstein JN, C Collisson EA, Mills GB, Shaw KR, Ozenberger BA, Ellrot K. The cancer Genome Atlas Pan-Cancer analysis project. Nat Genet.2013; 45(10): 1113–20.WeinsteinJNCCollisson EAMillsGBShawKROzenbergerBAEllrotKThe cancer Genome Atlas Pan-Cancer analysis project201345101113–2010.1038/ng.2764391996924071849Search in Google Scholar
Barretina, Caponigro G, Stransky N et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anti-cancer drug sensitivity. Nature. 2012; 483(7391): 603–7.BarretinaCaponigro GStranskyNet alThe Cancer Cell Line Encyclopedia enables predictive modelling of anti-cancer drug sensitivity20124837391603–710.1038/nature11003332002722460905Search in Google Scholar
Garnet MJ, Sys Edelman EJ, Heidorn SJ et al. Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature. 2012; 483(7391): 570–5.GarnetMJSysEdelman EJHeidornSJet alSystematic identification of genomic markers of drug sensitivity in cancer cells20124837391570–510.1038/nature11005334923322460902Search in Google Scholar
Johnson AEW, Pollard TJ, Shen L, et al. MIMIC-III, a freely accessible critical care database. Sci Data.2016; 3:160035. 10.1038/sdata.2016.35JohnsonAEWPollardTJShenLet alMIMIC-III, a freely accessible critical care database2016316003510.1038/sdata.2016.35487827827219127Open DOISearch in Google Scholar
Shankar-Hari M, Phillips GS, Levy ML et al. Developing a new definition and assessing new clinical criteria for septic shock. JAMA. 2016; 315(8):775–87.Shankar-HariMPhillipsGSLevyMLet alDeveloping a new definition and assessing new clinical criteria for septic shock20163158775–8710.1001/jama.2016.0289491039226903336Search in Google Scholar
Mayr FB, Yende S, Angus DC. Epidemiology of severe sepsis. Virulence 2014; 5:4–11.MayrFBYendeSAngusDCEpidemiology of severe sepsis201454–1110.4161/viru.27372Search in Google Scholar
Alberti C, Brun-Buisson C, Chevret S et al. Systemic inflammatory response and progress into severe sepsis in critically ill infected patients. Am J Resp Crit Care Med. 2005; 171:461–8.AlbertiCBrun-BuissonCChevretSet alSystemic inflammatory response and progress into severe sepsis in critically ill infected patients2005171461–810.1164/rccm.200403-324OCSearch in Google Scholar
King EG, Bauzá GJ, Mella JR, Remick DG. Pathophysiologic mechanisms in septic shock. Lab Invest 2014; 94:4–12.KingEGBauzáGJMellaJRRemickDGPathophysiologic mechanisms in septic shock2014944–1210.1038/labinvest.2013.110Search in Google Scholar
Katsenos CS, Antonopoulou AN, Apostolidou EN et al. Early administration of hydrocortisone replacement after the advent of septic shock: impact on survival and immune response. Crit Care Med.2014; 42(7):1651–7.KatsenosCSAntonopoulouANApostolidouENet alEarly administration of hydrocortisone replacement after the advent of septic shock: impact on survival and immune response20144271651–710.1097/CCM.0000000000000318Search in Google Scholar
Lv S, Han M, Yi R, Kwon S, Dai C, Wang R. Anti‐TNF‐α therapy for patients with sepsis: a systematic meta‐analysis. Int J ClinPract. 2014; 68(4):520–8.LvSHanMYiRKwonSDaiCWangRAnti‐TNF‐α therapy for patients with sepsis: a systematic meta‐analysis2014684520–810.1111/ijcp.12382Search in Google Scholar
Shindo Y, Unsinger J, Burnham C-A, Green JM, Hotchkiss RS. Interleukin-7 and anti-programmed cell death 1 antibody have differing effects to reverse sepsis-induced immunosuppression. Shock. 2015; 43(4):334–43.ShindoYUnsingerJBurnhamC-AGreenJMHotchkissRSInterleukin-7 and anti-programmed cell death 1 antibody have differing effects to reverse sepsis-induced immunosuppression2015434334–4310.1097/SHK.0000000000000317Search in Google Scholar
Kowalska MA, Zhao G, Zhai L et al. Modulation of protein C activation by histones, platelet factor 4, and heparinoids new insights into activated protein C formation. Arterioscler Thromb Vasc Biol.2014; 34:120–6.KowalskaMAZhaoGZhaiLet alModulation of protein C activation by histones, platelet factor 4, and heparinoids new insights into activated protein C formation201434120–610.1161/ATVBAHA.113.302236Search in Google Scholar
Schomburg L. Selenium in sepsis-substitution, supplementation or pro-oxidative bolus? Crit Care. 2014; 18:444. 10.1186/cc13963SchomburgLSelenium in sepsis-substitution, supplementation or pro-oxidative bolus?20141844410.1186/cc13963Open DOISearch in Google Scholar
Wilson JX. Antioxidants in sepsis. In: Systems biology of free radicals and antioxidants. Springer. 2014: 3267–72.WilsonJXAntioxidants in sepsisInSpringer20143267–7210.1007/978-3-642-30018-9_62Search in Google Scholar
Lupu F, Keshari RS, Lambris JD, Coggeshall KM. Crosstalk between the coagulation and complement systems in sepsis. Thromb Res. 2014; 133(1):S28–S31.LupuFKeshariRSLambrisJDCoggeshallKMCrosstalk between the coagulation and complement systems in sepsis20141331S28–S3110.1016/j.thromres.2014.03.014Search in Google Scholar
Hutchins NA, Unsinger J, Hotchkiss RS, Ayala A. The new normal: immunomodulatory agents against sepsis immune suppression. Trends Mol Med. 2014; 20(4):224–33.HutchinsNAUnsingerJHotchkissRSAyalaAThe new normal: immunomodulatory agents against sepsis immune suppression2014204224–3310.1016/j.molmed.2014.01.002397678524485901Search in Google Scholar
Seymour CW, Liu VX, Iwashyna TJ et al. Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016; 315(8):762-74.SeymourCWLiuVXIwashynaTJet alAssessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)20163158762–7410.1001/jama.2016.0288543343526903335Search in Google Scholar
Wong HR, Wheeler DS, Tegtmeyer K, et al. Toward a clinically feasible gene expression-based subclassification strategy for septic shock: proof of concept. Crit Care Med. 2010;38(10):1955–61.WongHRWheelerDSTegtmeyerKet alToward a clinically feasible gene expression-based subclassification strategy for septic shock: proof of concept201038101955–6110.1097/CCM.0b013e3181eb924f294355320639748Search in Google Scholar
Joehanes R, Zhang X, Huan T, et al. Integrated genome-wide analysis of expression quantitative trait loci aids interpretation of genomic association studies. Genome Biol. 2017;18(1):16.JoehanesRZhangXHuanTet alIntegrated genome-wide analysis of expression quantitative trait loci aids interpretation of genomic association studies20171811610.1186/s13059-016-1142-6526446628122634Search in Google Scholar
Seymour CW, Gesten F, Prescott HC, et al. Time to Treatment and Mortality during Mandated Emergency Care for Sepsis. N Engl J Med. 2017;376(23):2235–44.SeymourCWGestenFPrescottHCet alTime to Treatment and Mortality during Mandated Emergency Care for Sepsis2017376232235–4410.1056/NEJMoa1703058553825828528569Search in Google Scholar
László I, Trásy D, Molnár Z, Fazakas J. Sepsis: From Pathophysiology to Individualized Patient Care. J Immunol Res. 2015;2015:510436.LászlóITrásyDMolnárZFazakasJSepsis: From Pathophysiology to Individualized Patient Care2015201551043610.1155/2015/510436451817426258150Search in Google Scholar