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Published in: Critical Care 1/2017

Open Access 01-12-2017 | Review

A path to precision in the ICU

Authors: David M. Maslove, Francois Lamontagne, John C. Marshall, Daren K. Heyland

Published in: Critical Care | Issue 1/2017

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Abstract

Precision medicine is increasingly touted as a groundbreaking new paradigm in biomedicine. In the ICU, the complexity and ambiguity of critical illness syndromes have been identified as fundamental justifications for the adoption of a precision approach to research and practice. Inherently protean diseases states such as sepsis and acute respiratory distress syndrome have manifestations that are physiologically and anatomically diffuse, and that fluctuate over short periods of time. This leads to considerable heterogeneity among patients, and conditions in which a “one size fits all” approach to therapy can lead to widely divergent results. Current ICU therapy can thus be seen as imprecise, with the potential to realize substantial gains from the adoption of precision medicine approaches. A number of challenges still face the development and adoption of precision critical care, a transition that may occur incrementally rather than wholesale. This article describes a few concrete approaches to addressing these challenges.
First, novel clinical trial designs, including registry randomized controlled trials and platform trials, suggest ways in which conventional trials can be adapted to better accommodate the physiologic heterogeneity of critical illness. Second, beyond the “omics” technologies already synonymous with precision medicine, the data-rich environment of the ICU can generate complex physiologic signatures that could fuel precision-minded research and practice. Third, the role of computing infrastructure and modern informatics methods will be central to the pursuit of precision medicine in the ICU, necessitating close collaboration with data scientists. As work toward precision critical care continues, small proof-of-concept studies may prove useful in highlighting the potential of this approach.
Literature
2.
go back to reference Moasser MM, Krop IE. The evolving landscape of HER2 targeting in breast cancer. JAMA Oncol. 2015;1:1154–61.CrossRefPubMed Moasser MM, Krop IE. The evolving landscape of HER2 targeting in breast cancer. JAMA Oncol. 2015;1:1154–61.CrossRefPubMed
3.
go back to reference Maemondo M, Inoue A, Kobayashi K, Sugawara S, Oizumi S, Isobe H, et al. Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR. N Engl J Med. 2010;362:2380–8.CrossRefPubMed Maemondo M, Inoue A, Kobayashi K, Sugawara S, Oizumi S, Isobe H, et al. Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR. N Engl J Med. 2010;362:2380–8.CrossRefPubMed
4.
go back to reference Kaufman DJ, Baker R, Milner LC, Devaney S, Hudson KL. A survey of U.S adults’ opinions about conduct of a Nationwide Precision Medicine Initiative® cohort study of genes and environment. Hernandez Montoya AR, editor. PLoS One. 2016;11:e0160461–14.CrossRefPubMedPubMedCentral Kaufman DJ, Baker R, Milner LC, Devaney S, Hudson KL. A survey of U.S adults’ opinions about conduct of a Nationwide Precision Medicine Initiative® cohort study of genes and environment. Hernandez Montoya AR, editor. PLoS One. 2016;11:e0160461–14.CrossRefPubMedPubMedCentral
5.
go back to reference Antman EM, Loscalzo J. Precision medicine in cardiology. Nat Rev Cardiol. 2016;13:591-602. Antman EM, Loscalzo J. Precision medicine in cardiology. Nat Rev Cardiol. 2016;13:591-602.
6.
go back to reference Rogers GB, Wesselingh S. Precision respiratory medicine and the microbiome. Lancet Respir Med. 2016;4:73–82.CrossRefPubMed Rogers GB, Wesselingh S. Precision respiratory medicine and the microbiome. Lancet Respir Med. 2016;4:73–82.CrossRefPubMed
7.
go back to reference Galli SJ. Toward precision medicine and health: opportunities and challenges in allergic diseases. J Allergy Clin Immunol. 2016;137:1289–300.CrossRefPubMed Galli SJ. Toward precision medicine and health: opportunities and challenges in allergic diseases. J Allergy Clin Immunol. 2016;137:1289–300.CrossRefPubMed
8.
go back to reference Nassan M, Nicholson WT, Elliott MA, Rohrer Vitek CR, Black JL, Frye MA. Pharmacokinetic pharmacogenetic prescribing guidelines for antidepressants: a template for psychiatric precision medicine. Mayo Clin Proc. 2016;91:897–907.CrossRefPubMed Nassan M, Nicholson WT, Elliott MA, Rohrer Vitek CR, Black JL, Frye MA. Pharmacokinetic pharmacogenetic prescribing guidelines for antidepressants: a template for psychiatric precision medicine. Mayo Clin Proc. 2016;91:897–907.CrossRefPubMed
9.
go back to reference Khoury MJ, Galea S. Will precision medicine improve population health? JAMA. 2016;316(13):1357–1358.CrossRefPubMed Khoury MJ, Galea S. Will precision medicine improve population health? JAMA. 2016;316(13):1357–1358.CrossRefPubMed
10.
go back to reference Buchman TG, Billiar TR, Elster E, Kirk AD, Rimawi RH, Vodovotz Y, et al. Precision medicine for critical illness and injury. Crit Care Med. 2016;44:1635–8.CrossRefPubMed Buchman TG, Billiar TR, Elster E, Kirk AD, Rimawi RH, Vodovotz Y, et al. Precision medicine for critical illness and injury. Crit Care Med. 2016;44:1635–8.CrossRefPubMed
11.
go back to reference Prescott HC, Calfee CS, Thompson BT, Angus DC, Liu VX. Toward smarter lumping and smarter splitting: rethinking strategies for sepsis and acute respiratory distress syndrome clinical trial design. Am J Respir Crit Care Med. 2016;194:147–55.CrossRefPubMed Prescott HC, Calfee CS, Thompson BT, Angus DC, Liu VX. Toward smarter lumping and smarter splitting: rethinking strategies for sepsis and acute respiratory distress syndrome clinical trial design. Am J Respir Crit Care Med. 2016;194:147–55.CrossRefPubMed
13.
go back to reference Sims CR, Nguyen TC, Mayeux PR. Could biomarkers direct therapy for the septic patient? J Pharmacol Exp Ther. 2016;357:228–39.CrossRefPubMed Sims CR, Nguyen TC, Mayeux PR. Could biomarkers direct therapy for the septic patient? J Pharmacol Exp Ther. 2016;357:228–39.CrossRefPubMed
14.
go back to reference Christaki E, Giamarellos-Bourboulis EJ. The beginning of personalized medicine in sepsis: small steps to a bright future. Clin Genet. 2014;86:56–61.CrossRefPubMed Christaki E, Giamarellos-Bourboulis EJ. The beginning of personalized medicine in sepsis: small steps to a bright future. Clin Genet. 2014;86:56–61.CrossRefPubMed
16.
go back to reference Beitler JR, Goligher EC, Schmidt M, Spieth PM, Zanella A, Martin-Loeches I, et al. Personalized medicine for ARDS: the 2035 research agenda. Intensive Care Med. 2016;42:756–67.CrossRefPubMed Beitler JR, Goligher EC, Schmidt M, Spieth PM, Zanella A, Martin-Loeches I, et al. Personalized medicine for ARDS: the 2035 research agenda. Intensive Care Med. 2016;42:756–67.CrossRefPubMed
17.
go back to reference Wong HR. Personalized medicine, endotypes, and intensive care medicine. Intensive Care Med. 2015;41:1138–40.CrossRefPubMed Wong HR. Personalized medicine, endotypes, and intensive care medicine. Intensive Care Med. 2015;41:1138–40.CrossRefPubMed
18.
go back to reference Vincent J-L. Individual gene expression and personalised medicine in sepsis. Lancet Respir Med. 2016;4:242–3.CrossRefPubMed Vincent J-L. Individual gene expression and personalised medicine in sepsis. Lancet Respir Med. 2016;4:242–3.CrossRefPubMed
19.
21.
go back to reference McAuley DF, OʼKane C, Griffiths MJD. A stepwise approach to justify phase III randomized clinical trials and enhance the likelihood of a positive result. Crit Care Med. 2010;38:S523–7.CrossRefPubMed McAuley DF, OʼKane C, Griffiths MJD. A stepwise approach to justify phase III randomized clinical trials and enhance the likelihood of a positive result. Crit Care Med. 2010;38:S523–7.CrossRefPubMed
22.
go back to reference Iwashyna TJ, Burke JF, Sussman JB, Prescott HC, Hayward RA, Angus DC. Implications of heterogeneity of treatment effect for reporting and analysis of randomized trials in critical care. Am J Respir Crit Care Med. 2015;192:1045–51.CrossRefPubMedPubMedCentral Iwashyna TJ, Burke JF, Sussman JB, Prescott HC, Hayward RA, Angus DC. Implications of heterogeneity of treatment effect for reporting and analysis of randomized trials in critical care. Am J Respir Crit Care Med. 2015;192:1045–51.CrossRefPubMedPubMedCentral
23.
go back to reference Sweeney TE, Shidham A, Wong HR, Khatri P. A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set. Sci Transl Med. 2015;7(287):287ra71. Sweeney TE, Shidham A, Wong HR, Khatri P. A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set. Sci Transl Med. 2015;7(287):287ra71.
24.
go back to reference Wong HR, Cvijanovich N, Lin R, Allen GL, Thomas NJ, Willson DF, et al. Identification of pediatric septic shock subclasses based on genome-wide expression profiling. BMC Med. 2009;7:34.CrossRefPubMedPubMedCentral Wong HR, Cvijanovich N, Lin R, Allen GL, Thomas NJ, Willson DF, et al. Identification of pediatric septic shock subclasses based on genome-wide expression profiling. BMC Med. 2009;7:34.CrossRefPubMedPubMedCentral
25.
26.
go back to reference Davenport EE, Burnham KL, Radhakrishnan J, Humburg P, Hutton P, Mills TC, et al. Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study. Lancet Respir Med. 2016;4:259–71.CrossRefPubMedPubMedCentral Davenport EE, Burnham KL, Radhakrishnan J, Humburg P, Hutton P, Mills TC, et al. Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study. Lancet Respir Med. 2016;4:259–71.CrossRefPubMedPubMedCentral
27.
go back to reference Wong HR, Atkinson SJ, Cvijanovich NZ, Anas N, Allen GL, Thomas NJ, et al. Combining prognostic and predictive enrichment strategies to identify children with septic shock responsive to corticosteroids. Crit Care Med. 2016;44:e1000–3.CrossRefPubMed Wong HR, Atkinson SJ, Cvijanovich NZ, Anas N, Allen GL, Thomas NJ, et al. Combining prognostic and predictive enrichment strategies to identify children with septic shock responsive to corticosteroids. Crit Care Med. 2016;44:e1000–3.CrossRefPubMed
28.
go back to reference Walley KR, Thain KR, Russell JA, Reilly MP, Meyer NJ, Ferguson JF, et al. PCSK9 is a critical regulator of the innate immune response and septic shock outcome. Sci Transl Med. 2015;6(258):258ra143. Walley KR, Thain KR, Russell JA, Reilly MP, Meyer NJ, Ferguson JF, et al. PCSK9 is a critical regulator of the innate immune response and septic shock outcome. Sci Transl Med. 2015;6(258):258ra143.
29.
go back to reference Sapru A, Liu KD, Wiemels J, Hansen H, Pawlikowska L, Poon A, et al. Association of common genetic variation in the protein C pathway genes with clinical outcomes in acute respiratory distress syndrome. Crit Care. 2016;20(1):151. doi:10.1186/s13054-016-1330-5. Sapru A, Liu KD, Wiemels J, Hansen H, Pawlikowska L, Poon A, et al. Association of common genetic variation in the protein C pathway genes with clinical outcomes in acute respiratory distress syndrome. Crit Care. 2016;20(1):151. doi:10.​1186/​s13054-016-1330-5.
30.
go back to reference Man M, Close SL, Shaw AD, Bernard GR, Douglas IS, Kaner RJ, et al. Beyond single-marker analyses: mining whole genome scans for insights into treatment responses in severe sepsis. Pharmacogenomics J. 2013;13:218–26.CrossRefPubMed Man M, Close SL, Shaw AD, Bernard GR, Douglas IS, Kaner RJ, et al. Beyond single-marker analyses: mining whole genome scans for insights into treatment responses in severe sepsis. Pharmacogenomics J. 2013;13:218–26.CrossRefPubMed
31.
go back to reference Christie JD, Wurfel MM, Feng R, O’Keefe GE, Bradfield J, Ware LB, et al. Genome wide association identifies PPFIA1 as a candidate gene for acute lung injury risk following major trauma. Checkley W, editor. PLoS One. 2012;7:e28268–10.CrossRefPubMedPubMedCentral Christie JD, Wurfel MM, Feng R, O’Keefe GE, Bradfield J, Ware LB, et al. Genome wide association identifies PPFIA1 as a candidate gene for acute lung injury risk following major trauma. Checkley W, editor. PLoS One. 2012;7:e28268–10.CrossRefPubMedPubMedCentral
32.
go back to reference Russell JA. Genomics and pharmacogenomics of sepsis: so close and yet so far. Crit Care. 2016:1–4. Russell JA. Genomics and pharmacogenomics of sepsis: so close and yet so far. Crit Care. 2016:1–4.
33.
go back to reference Knox DB, Lanspa MJ, Kuttler KG, Brewer SC, Brown SM. Phenotypic clusters within sepsis-associated multiple organ dysfunction syndrome. Intensive Care Med. 2015;41:814–22.CrossRefPubMedPubMedCentral Knox DB, Lanspa MJ, Kuttler KG, Brewer SC, Brown SM. Phenotypic clusters within sepsis-associated multiple organ dysfunction syndrome. Intensive Care Med. 2015;41:814–22.CrossRefPubMedPubMedCentral
34.
go back to reference Ware LB, Koyama T, Zhao Z, Janz DR, Wickersham N, Bernard GR, et al. Biomarkers of lung epithelial injury and inflammation distinguish severe sepsis patients with acute respiratory distress syndrome. Crit Care. 2013;17:R253.CrossRefPubMedPubMedCentral Ware LB, Koyama T, Zhao Z, Janz DR, Wickersham N, Bernard GR, et al. Biomarkers of lung epithelial injury and inflammation distinguish severe sepsis patients with acute respiratory distress syndrome. Crit Care. 2013;17:R253.CrossRefPubMedPubMedCentral
35.
go back to reference Calfee CS, Janz DR, Bernard GR, May AK, Kangelaris KN, Matthay MA, et al. Distinct molecular phenotypes of direct vs indirect ARDS in single-center and multicenter studies. Chest. 2015;147:1539–10.CrossRefPubMed Calfee CS, Janz DR, Bernard GR, May AK, Kangelaris KN, Matthay MA, et al. Distinct molecular phenotypes of direct vs indirect ARDS in single-center and multicenter studies. Chest. 2015;147:1539–10.CrossRefPubMed
36.
go back to reference Calfee CS, Delucchi K, Parsons PE, Thompson BT, Ware LB, Matthay MA, et al. Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials. Lancet Respir Med. 2014;2:611–20.CrossRefPubMedPubMedCentral Calfee CS, Delucchi K, Parsons PE, Thompson BT, Ware LB, Matthay MA, et al. Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials. Lancet Respir Med. 2014;2:611–20.CrossRefPubMedPubMedCentral
37.
go back to reference Famous KR, Delucchi K, Ware LB, Kangelaris KN, Liu KD, Thompson BT, et al. ARDS subphenotypes respond differently to randomized fluid management strategy. Am J Respir Crit Care Med. 2017;195(3):331–338.PubMed Famous KR, Delucchi K, Ware LB, Kangelaris KN, Liu KD, Thompson BT, et al. ARDS subphenotypes respond differently to randomized fluid management strategy. Am J Respir Crit Care Med. 2017;195(3):331–338.PubMed
38.
go back to reference Sørensen TI, Nielsen GG, Andersen PK, Teasdale TW. Genetic and environmental influences on premature death in adult adoptees. N Engl J Med. 1988;318:727–32.CrossRefPubMed Sørensen TI, Nielsen GG, Andersen PK, Teasdale TW. Genetic and environmental influences on premature death in adult adoptees. N Engl J Med. 1988;318:727–32.CrossRefPubMed
39.
go back to reference Petersen L, Andersen PK, Sørensen TIA. Genetic influences on incidence and case-fatality of infectious disease. Brandstaetter A, editor. PLoS One. 2010;5:e10603–7.CrossRefPubMedPubMedCentral Petersen L, Andersen PK, Sørensen TIA. Genetic influences on incidence and case-fatality of infectious disease. Brandstaetter A, editor. PLoS One. 2010;5:e10603–7.CrossRefPubMedPubMedCentral
40.
go back to reference Celi LA, Mark RG, Stone DJ, Montgomery RA. “Big data” in the intensive care unit. Closing the data loop. Am J Respir Crit Care Med. 2013;187:1157–60.CrossRefPubMed Celi LA, Mark RG, Stone DJ, Montgomery RA. “Big data” in the intensive care unit. Closing the data loop. Am J Respir Crit Care Med. 2013;187:1157–60.CrossRefPubMed
41.
go back to reference Maslove DM, Dubin JA, Shrivats A, Lee J. Errors, omissions, and outliers in hourly vital signs measurements in intensive care. Crit Care Med. 2016;44(11):e1021–e1030.CrossRefPubMed Maslove DM, Dubin JA, Shrivats A, Lee J. Errors, omissions, and outliers in hourly vital signs measurements in intensive care. Crit Care Med. 2016;44(11):e1021–e1030.CrossRefPubMed
42.
go back to reference Landoni G, Comis M, Conte M, Finco G, Mucchetti M, Paternoster G, et al. Mortality in multicenter critical care trials. Crit Care Med. 2015;43:1559–68.CrossRefPubMed Landoni G, Comis M, Conte M, Finco G, Mucchetti M, Paternoster G, et al. Mortality in multicenter critical care trials. Crit Care Med. 2015;43:1559–68.CrossRefPubMed
43.
go back to reference Cohen J, Vincent J-L, Adhikari NKJ, Machado FR, Angus DC, Calandra T, et al. Sepsis: a roadmap for future research. Lancet Infect Dis. 2015;15:581–614.CrossRefPubMed Cohen J, Vincent J-L, Adhikari NKJ, Machado FR, Angus DC, Calandra T, et al. Sepsis: a roadmap for future research. Lancet Infect Dis. 2015;15:581–614.CrossRefPubMed
44.
go back to reference Angus DC. Fusing randomized trials with big data: the key to self-learning health care systems? JAMA. 2015;314:767–8.CrossRefPubMed Angus DC. Fusing randomized trials with big data: the key to self-learning health care systems? JAMA. 2015;314:767–8.CrossRefPubMed
45.
46.
go back to reference Vincent J-L. We should abandon randomized controlled trials in the intensive care unit. Crit Care Med. 2010;38:S534–8.CrossRefPubMed Vincent J-L. We should abandon randomized controlled trials in the intensive care unit. Crit Care Med. 2010;38:S534–8.CrossRefPubMed
47.
go back to reference Panacek EA, Marshall JC, Albertson TE, Johnson DH, Johnson S, MacArthur RD, et al. Efficacy and safety of the monoclonal anti-tumor necrosis factor antibody F(ab′)2 fragment afelimomab in patients with severe sepsis and elevated interleukin-6 levels. Crit Care Med. 2004;32:2173–82.CrossRefPubMed Panacek EA, Marshall JC, Albertson TE, Johnson DH, Johnson S, MacArthur RD, et al. Efficacy and safety of the monoclonal anti-tumor necrosis factor antibody F(ab′)2 fragment afelimomab in patients with severe sepsis and elevated interleukin-6 levels. Crit Care Med. 2004;32:2173–82.CrossRefPubMed
48.
go back to reference Lauer MS, D’Agostino RB. The randomized registry trial—the next disruptive technology in clinical research? N Engl J Med. 2013;369:1579–81.CrossRefPubMed Lauer MS, D’Agostino RB. The randomized registry trial—the next disruptive technology in clinical research? N Engl J Med. 2013;369:1579–81.CrossRefPubMed
49.
go back to reference Fröbert O, Lagerqvist B, Olivecrona GK, Omerovic E, Gudnason T, Maeng M, et al. Thrombus aspiration during ST-segment elevation myocardial infarction. N Engl J Med. 2013;369:1587–97.CrossRefPubMed Fröbert O, Lagerqvist B, Olivecrona GK, Omerovic E, Gudnason T, Maeng M, et al. Thrombus aspiration during ST-segment elevation myocardial infarction. N Engl J Med. 2013;369:1587–97.CrossRefPubMed
50.
go back to reference Herasevich V, Pickering BW, Dong Y, Peters SG, Gajic O. Informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness. Mayo Clin Proc. 2010;85:247–54.CrossRefPubMedPubMedCentral Herasevich V, Pickering BW, Dong Y, Peters SG, Gajic O. Informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness. Mayo Clin Proc. 2010;85:247–54.CrossRefPubMedPubMedCentral
51.
go back to reference Kashani K, Herasevich V. Sniffing out acute kidney injury in the ICU. Curr Opin Crit Care. 2013;19:531–6.CrossRefPubMed Kashani K, Herasevich V. Sniffing out acute kidney injury in the ICU. Curr Opin Crit Care. 2013;19:531–6.CrossRefPubMed
52.
go back to reference Herasevich V, Pieper MS, Pulido J, Gajic O. Enrollment into a time sensitive clinical study in the critical care setting: results from computerized septic shock sniffer implementation. J Am Med Inform Assoc. 2011;18:639–44.CrossRefPubMedPubMedCentral Herasevich V, Pieper MS, Pulido J, Gajic O. Enrollment into a time sensitive clinical study in the critical care setting: results from computerized septic shock sniffer implementation. J Am Med Inform Assoc. 2011;18:639–44.CrossRefPubMedPubMedCentral
53.
go back to reference Van de Klundert N, Holman R, Dongelmans DA, De Keizer NF. Data resource profile: the Dutch National Intensive Care Evaluation (NICE) Registry of Admissions to Adult Intensive Care Units. Int J Epidemiol. 2015;44:1850-h.CrossRef Van de Klundert N, Holman R, Dongelmans DA, De Keizer NF. Data resource profile: the Dutch National Intensive Care Evaluation (NICE) Registry of Admissions to Adult Intensive Care Units. Int J Epidemiol. 2015;44:1850-h.CrossRef
54.
go back to reference Stow PJ, Hart GK, Higlett T, George C, Herkes R, McWilliam D, et al. Development and implementation of a high-quality clinical database: the Australian and New Zealand Intensive Care Society Adult Patient Database. J Crit Care. 2006;21:133–41.CrossRefPubMed Stow PJ, Hart GK, Higlett T, George C, Herkes R, McWilliam D, et al. Development and implementation of a high-quality clinical database: the Australian and New Zealand Intensive Care Society Adult Patient Database. J Crit Care. 2006;21:133–41.CrossRefPubMed
55.
go back to reference InFACT Global H1N1 Collaboration. InFACT: a global critical care research response to H1N1. Lancet. 2010;375(9708):11–3. InFACT Global H1N1 Collaboration. InFACT: a global critical care research response to H1N1. Lancet. 2010;375(9708):11–3.
56.
go back to reference Berry SM, Connor JT, Lewis RJ. The platform trial: an efficient strategy for evaluating multiple treatments. JAMA. 2015:1–2. Berry SM, Connor JT, Lewis RJ. The platform trial: an efficient strategy for evaluating multiple treatments. JAMA. 2015:1–2.
57.
go back to reference Rogers AJ, McGeachie M, Baron RM, Gazourian L, Haspel JA, et al. Metabolomic derangements are associated with mortality in critically ill adult patients. PLoS ONE. 2014;9(1):e87538. doi:10.1371/journal.pone.0087538. Rogers AJ, McGeachie M, Baron RM, Gazourian L, Haspel JA, et al. Metabolomic derangements are associated with mortality in critically ill adult patients. PLoS ONE. 2014;9(1):e87538. doi:10.​1371/​journal.​pone.​0087538.
59.
go back to reference Herberg JA, Kaforou M, Wright VJ, Shailes H, Eleftherohorinou H, Hoggart CJ, et al. Diagnostic test accuracy of a 2-transcript host RNA signature for discriminating bacterial vs viral infection in febrile children. JAMA. 2016;316:835–11.CrossRefPubMed Herberg JA, Kaforou M, Wright VJ, Shailes H, Eleftherohorinou H, Hoggart CJ, et al. Diagnostic test accuracy of a 2-transcript host RNA signature for discriminating bacterial vs viral infection in febrile children. JAMA. 2016;316:835–11.CrossRefPubMed
60.
go back to reference Basu RK, Standage SW, Cvijanovich NZ, Allen GL, Thomas NJ, Freishtat RJ, et al. Identification of candidate serum biomarkers for severe septic shock-associated kidney injury via microarray. Crit Care. 2011;15:R273.CrossRefPubMedPubMedCentral Basu RK, Standage SW, Cvijanovich NZ, Allen GL, Thomas NJ, Freishtat RJ, et al. Identification of candidate serum biomarkers for severe septic shock-associated kidney injury via microarray. Crit Care. 2011;15:R273.CrossRefPubMedPubMedCentral
61.
go back to reference Cuenca AG, Gentile LF, Lopez MC, Ungaro R, Liu H, Xiao W, et al. Development of a genomic metric that can be rapidly used to predict clinical outcome in severely injured trauma patients. Crit Care Med. 2013;41:1175–85.CrossRefPubMed Cuenca AG, Gentile LF, Lopez MC, Ungaro R, Liu H, Xiao W, et al. Development of a genomic metric that can be rapidly used to predict clinical outcome in severely injured trauma patients. Crit Care Med. 2013;41:1175–85.CrossRefPubMed
62.
go back to reference Heyland DK, Stelfox HT, Garland A, Cook D, Dodek P, Kutsogiannis J, et al. Predicting performance status 1 year after critical illness in patients 80 years or older. Crit Care Med. 2016;44:1718–26.CrossRefPubMed Heyland DK, Stelfox HT, Garland A, Cook D, Dodek P, Kutsogiannis J, et al. Predicting performance status 1 year after critical illness in patients 80 years or older. Crit Care Med. 2016;44:1718–26.CrossRefPubMed
63.
go back to reference Wood M, Song A, Maslove D, Ferri C, Howes D, Muscedere J, et al. Brain tissue oxygenation in patients with septic shock: a feasibility study. Can J Neurol Sci. 2016;43:65–73.CrossRefPubMed Wood M, Song A, Maslove D, Ferri C, Howes D, Muscedere J, et al. Brain tissue oxygenation in patients with septic shock: a feasibility study. Can J Neurol Sci. 2016;43:65–73.CrossRefPubMed
64.
go back to reference Buchman TG, Stein PK, Goldstein B. Heart rate variability in critical illness and critical care. Curr Opin Crit Care. 2002;8:311–5.CrossRefPubMed Buchman TG, Stein PK, Goldstein B. Heart rate variability in critical illness and critical care. Curr Opin Crit Care. 2002;8:311–5.CrossRefPubMed
65.
go back to reference Gale SC, Shanker B-A, Coyle SM, Macor MA, Choi CW, Calvano SE, et al. Continuous enteral and parenteral feeding each reduces heart rate variability but differentially influences monocyte gene expression in humans. Shock (Augusta, Ga). 2012;38:255–61. CrossRef Gale SC, Shanker B-A, Coyle SM, Macor MA, Choi CW, Calvano SE, et al. Continuous enteral and parenteral feeding each reduces heart rate variability but differentially influences monocyte gene expression in humans. Shock (Augusta, Ga). 2012;38:255–61. CrossRef
66.
go back to reference Norris P R, Canter JA, Jenkins JM, Moore JH, Williams AE, Morris JA. Personalized medicine: genetic variation and loss of physiologic complexity are associated with mortality in 644 trauma patients. Ann Surg. 2009;250:524–530.PubMed Norris P R, Canter JA, Jenkins JM, Moore JH, Williams AE, Morris JA. Personalized medicine: genetic variation and loss of physiologic complexity are associated with mortality in 644 trauma patients. Ann Surg. 2009;250:524–530.PubMed
67.
go back to reference Johnson AEW, Pollard TJ, Shen L, Lehman L-WH, Feng M, Ghassemi M, et al. MIMIC-III, a freely accessible critical care database. Sci Data. 2016;3:160035.CrossRefPubMedPubMedCentral Johnson AEW, Pollard TJ, Shen L, Lehman L-WH, Feng M, Ghassemi M, et al. MIMIC-III, a freely accessible critical care database. Sci Data. 2016;3:160035.CrossRefPubMedPubMedCentral
68.
go back to reference Shankar-Hari M, Phillips GS, Levy ML, Seymour CW, Liu VX, Deutschman CS, et al. Developing a new definition and assessing new clinical criteria for septic shock. JAMA. 2016;315:775–13.CrossRefPubMedPubMedCentral Shankar-Hari M, Phillips GS, Levy ML, Seymour CW, Liu VX, Deutschman CS, et al. Developing a new definition and assessing new clinical criteria for septic shock. JAMA. 2016;315:775–13.CrossRefPubMedPubMedCentral
69.
go back to reference Bhuvaneshwar K, Belouali A, Singh V, Johnson RM, Song L, Alaoui A, et al. G-DOC Plus—an integrative bioinformatics platform for precision medicine. BMC Bioinformatics. 2016:1–13. Bhuvaneshwar K, Belouali A, Singh V, Johnson RM, Song L, Alaoui A, et al. G-DOC Plus—an integrative bioinformatics platform for precision medicine. BMC Bioinformatics. 2016:1–13.
71.
go back to reference Noy NF, Shah NH, Whetzel PL, Dai B, Dorf M, Griffith N, et al. BioPortal: ontologies and integrated data resources at the click of a mouse. Nucleic Acids Res. 2009;37:W170–3.CrossRefPubMedPubMedCentral Noy NF, Shah NH, Whetzel PL, Dai B, Dorf M, Griffith N, et al. BioPortal: ontologies and integrated data resources at the click of a mouse. Nucleic Acids Res. 2009;37:W170–3.CrossRefPubMedPubMedCentral
72.
go back to reference Luciano JS, Andersson B, Batchelor C, Bodenreider O, Clark T, Denney CK, et al. The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside. J Biomed Semantics. 2011;2 Suppl 2:S1.CrossRefPubMedPubMedCentral Luciano JS, Andersson B, Batchelor C, Bodenreider O, Clark T, Denney CK, et al. The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside. J Biomed Semantics. 2011;2 Suppl 2:S1.CrossRefPubMedPubMedCentral
73.
go back to reference Shen B, Hwang J. The clinical utility of precision medicine: properly assessing the value of emerging diagnostic tests. Clin Pharmacol Ther. 2010;88:754–6.CrossRefPubMed Shen B, Hwang J. The clinical utility of precision medicine: properly assessing the value of emerging diagnostic tests. Clin Pharmacol Ther. 2010;88:754–6.CrossRefPubMed
74.
75.
go back to reference Heyland DK. Failure to engage hospitalized elderly patients and their families in advance care planning. JAMA Intern Med. 2013;173:778–10.CrossRefPubMed Heyland DK. Failure to engage hospitalized elderly patients and their families in advance care planning. JAMA Intern Med. 2013;173:778–10.CrossRefPubMed
Metadata
Title
A path to precision in the ICU
Authors
David M. Maslove
Francois Lamontagne
John C. Marshall
Daren K. Heyland
Publication date
01-12-2017
Publisher
BioMed Central
Published in
Critical Care / Issue 1/2017
Electronic ISSN: 1364-8535
DOI
https://doi.org/10.1186/s13054-017-1653-x

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