Download PDF
Semin Respir Crit Care Med
DOI: 10.1055/s-0044-1787270
Review Article

Early Diagnosis of Sepsis: The Role of Biomarkers and Rapid Microbiological Tests

Erika P. Plata-Menchaca
1   Intensive Care Department, Shock, Organ Dysfunction, and Resuscitation (SODIR) Research Group, Vall d'Hebron Research Institute, Vall d'Hebron Hospital Universitari, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
,
Juan Carlos Ruiz-Rodríguez
1   Intensive Care Department, Shock, Organ Dysfunction, and Resuscitation (SODIR) Research Group, Vall d'Hebron Research Institute, Vall d'Hebron Hospital Universitari, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
,
Ricard Ferrer
1   Intensive Care Department, Shock, Organ Dysfunction, and Resuscitation (SODIR) Research Group, Vall d'Hebron Research Institute, Vall d'Hebron Hospital Universitari, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
› Author Affiliations Funding None.
› Further Information
    Permissions and Reprints

Abstract

Sepsis is a medical emergency resulting from a dysregulated response to an infection, causing preventable deaths and a high burden of morbidity. Protocolized and accurate interventions in sepsis are time-critical. Therefore, earlier recognition of cases allows for preventive interventions, early treatment, and improved outcomes. Clinical diagnosis of sepsis by clinical scores cannot be considered an early diagnosis, given that underlying molecular pathophysiological mechanisms have been activated in the preceding hour or days. There is a lack of a widely available tool enhancing preclinical diagnosis of sepsis. Sophisticated technologies for sepsis prediction have several limitations, including high costs. Novel technologies for fast molecular and microbiological diagnosis are focusing on bedside point-of-care combined testing to reach most settings where sepsis represents a challenge.

Keywords

sepsis - septic shock - severe sepsis - diagnosis - biomarkers - screening - early diagnosis - molecular diagnostic techniques - molecular testing


Publication History

Article published online:
01 July 2024

© 2024. Thieme. All rights reserved.

Thieme Medical Publishers, Inc.
333 Seventh Avenue, 18th Floor, New York, NY 10001, USA

 

  • References

  • 1 Rudd KE, Johnson SC, Agesa KM. et al. Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study. Lancet 2020; 395 (10219): 200-211
    CrossrefPubMedGoogle Scholar
  • 2 Rüddel H, Thomas-Rüddel DO, Reinhart K. et al; MEDUSA study group. Adverse effects of delayed antimicrobial treatment and surgical source control in adults with sepsis: results of a planned secondary analysis of a cluster-randomized controlled trial. Crit Care 2022; 26 (01) 51
    CrossrefPubMedGoogle Scholar
  • 3 Mensa J, Barberán J, Ferrer R. et al. Recommendations for antibiotic selection for severe nosocomial infections. Rev Esp Quimioter 2021; 34 (05) 511-524
    CrossrefPubMedGoogle Scholar
  • 4 Prescott HC, Angus DC. Enhancing recovery from sepsis: a review. JAMA 2018; 319 (01) 62-75
    CrossrefPubMedGoogle Scholar
  • 5 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) 2235-2244
    CrossrefPubMedGoogle Scholar
  • 6 Evans L, Rhodes A, Alhazzani W. et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med 2021; 47 (11) 1181-1247
    CrossrefPubMedGoogle Scholar
  • 7 Carlbom DJ, Rubenfeld GD. Barriers to implementing protocol-based sepsis resuscitation in the emergency department–results of a national survey. Crit Care Med 2007; 35 (11) 2525-2532
    CrossrefPubMedGoogle Scholar
  • 8 Simmonds M, Hutchinson A, Chikhani M. et al. Surviving sepsis beyond intensive care: a retrospective cohort study of compliance with the international guidelines. J Intensive Care Soc 2008; 9: 124-127
    CrossrefPubMedGoogle Scholar
  • 9 Ferrer R, González Del Castillo J, Martínez-Martínez M, Plata-Menchaca EP, Larrosa MN. Time to decision in sepsis. Rev Esp Quimioter 2023; 36 (01) 82-87
    CrossrefPubMedGoogle Scholar
  • 10 Singer M, Deutschman CS, Seymour CW. et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016; 315 (08) 801-810
    CrossrefPubMedGoogle Scholar
  • 11 Prescott HC, Cope TM, Gesten FC. et al. Reporting of sepsis cases for performance measurement versus for reimbursement in New York State. Crit Care Med 2018; 46 (05) 666-673
    CrossrefPubMedGoogle Scholar
  • 12 Kim SJ, Hwang SO, Kim YW, Lee JH, Cha KC. Procalcitonin as a diagnostic marker for sepsis/septic shock in the emergency department; a study based on Sepsis-3 definition. Am J Emerg Med 2019; 37 (02) 272-276
    CrossrefPubMedGoogle Scholar
  • 13 Suffoletto B, Frisch A, Prabhu A, Kristan J, Guyette FX, Callaway CW. Prediction of serious infection during prehospital emergency care. Prehosp Emerg Care 2011; 15 (03) 325-330
    CrossrefPubMedGoogle Scholar
  • 14 Kwizera A, Adhikari NKJ, Angus DC. et al. Recognition of sepsis in resource-limited settings. 2019 Feb 9. In: Dondorp AM, Dünser MW, Schultz MJ. eds. Sepsis Management in Resource-limited Settings [Internet]. Cham: Springer; 2019. . Chapter 4
    Google Scholar
  • 15 Kaukonen KM, Bailey M, Pilcher D, Cooper DJ, Bellomo R. Systemic inflammatory response syndrome criteria in defining severe sepsis. N Engl J Med 2015; 372 (17) 1629-1638
    CrossrefPubMedGoogle Scholar
  • 16 Machado FR, Cavalcanti AB, Monteiro MB. et al; Instituto Latino-Americano de Sepsis network investigators. Predictive accuracy of the quick sepsis-related organ failure assessment score in Brazil. a prospective multicenter study. Am J Respir Crit Care Med 2020; 201 (07) 789-798
    CrossrefPubMedGoogle Scholar
  • 17 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 (08) 762-774
    CrossrefPubMedGoogle Scholar
  • 18 Briassoulis G, Briassoulis P, Miliaraki M. et al; Combined Approach for The eArly diagnosis of INfection in sepsis (CAPTAIN) study group. Biomarker cruises in sepsis: who is the CAPTAIN? Discussion on “Circulating biomarkers may be unable to detect infection at the early phase of sepsis in ICU patients: the CAPTAIN prospective multicenter cohort study”. Intensive Care Med 2019; 45 (01) 132-133
    CrossrefPubMedGoogle Scholar
  • 19 Klimpel J, Weidhase L, Bernhard M, Gries A, Petros S. The impact of the Sepsis-3 definition on ICU admission of patients with infection. Scand J Trauma Resusc Emerg Med 2019; 27 (01) 98
    CrossrefPubMedGoogle Scholar
  • 20 Peake SL, Delaney A, Bailey M. et al; ARISE Investigators, ANZICS Clinical Trials Group. Goal-directed resuscitation for patients with early septic shock. N Engl J Med 2014; 371 (16) 1496-1506
    CrossrefPubMedGoogle Scholar
  • 21 Herwanto V, Shetty A, Nalos M. et al. Accuracy of quick sequential organ failure assessment score to predict sepsis mortality in 121 studies including 1,716,017 individuals: a systematic review and meta-analysis. Crit Care Explor 2019; 1 (09) e0043
    CrossrefPubMedGoogle Scholar
  • 22 Serafim R, Gomes JA, Salluh J, Póvoa P. A comparison of the Quick-SOFA and systemic inflammatory response syndrome criteria for the diagnosis of sepsis and prediction of mortality: a systematic review and meta-analysis. Chest 2018; 153 (03) 646-655
    CrossrefPubMedGoogle Scholar
  • 23 Fernando SM, Tran A, Taljaard M. et al. Prognostic accuracy of the quick sequential organ failure assessment for mortality in patients with suspected infection: a systematic review and meta-analysis. Ann Intern Med 2018; 168 (04) 266-275
    CrossrefPubMedGoogle Scholar
  • 24 Liu VX, Lu Y, Carey KA. et al. Comparison of early warning scoring systems for hospitalized patients with and without infection at risk for in-hospital mortality and transfer to the intensive care unit. JAMA Netw Open 2020; 3 (05) e205191
    CrossrefPubMedGoogle Scholar
  • 25 Inada-Kim M. NEWS2 and improving outcomes from sepsis. Clin Med (Lond) 2022; 22 (06) 514-517
    PubMedGoogle Scholar
  • 26 Alberto L, Marshall AP, Walker R, Aitken LM. Screening for sepsis in general hospitalized patients: a systematic review. J Hosp Infect 2017; 96 (04) 305-315
    CrossrefPubMedGoogle Scholar
  • 27 Bhattacharjee P, Edelson DP, Churpek MM. Identifying patients with sepsis on the hospital wards. Chest 2017; 151 (04) 898-907
    CrossrefPubMedGoogle Scholar
  • 28 Makam AN, Nguyen OK, Auerbach AD. Diagnostic accuracy and effectiveness of automated electronic sepsis alert systems: a systematic review. J Hosp Med 2015; 10 (06) 396-402
    CrossrefPubMedGoogle Scholar
  • 29 Downing NL, Rolnick J, Poole SF. et al. Electronic health record-based clinical decision support alert for severe sepsis: a randomised evaluation. BMJ Qual Saf 2019; 28 (09) 762-768
    CrossrefPubMedGoogle Scholar
  • 30 Hooper MH, Weavind L, Wheeler AP. et al. Randomized trial of automated, electronic monitoring to facilitate early detection of sepsis in the intensive care unit*. Crit Care Med 2012; 40 (07) 2096-2101
    CrossrefPubMedGoogle Scholar
  • 31 Shimabukuro DW, Barton CW, Feldman MD, Mataraso SJ, Das R. Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial. BMJ Open Respir Res 2017; 4 (01) e000234
    CrossrefPubMedGoogle Scholar
  • 32 Esteban E, Belda S, García-Soler P. et al. A multifaceted educational intervention shortened time to antibiotic administration in children with severe sepsis and septic shock: ABISS Edusepsis pediatric study. Intensive Care Med 2017; 43 (12) 1916-1918
    CrossrefPubMedGoogle Scholar
  • 33 Ferrer R, Artigas A, Levy MM. et al; Edusepsis Study Group. Improvement in process of care and outcome after a multicenter severe sepsis educational program in Spain. JAMA 2008; 299 (19) 2294-2303
    CrossrefPubMedGoogle Scholar
  • 34 Yébenes JC, Lorencio C, Esteban E. et al; Comisión Asesora para la Atención al Paciente con Sepsis y Grup de Treball de Sèpsia i Xoc Sèptic (GTSiXS) SOCMIC-SOCMUE. Interhospital Sepsis Code in Catalonia (Spain): territorial model for initial care of patients with sepsis. Med Intensiva (Engl Ed) 2020; 44 (01) 36-45
    PubMedGoogle Scholar
  • 35 Damiani E, Donati A, Serafini G. et al. Effect of performance improvement programs on compliance with sepsis bundles and mortality: a systematic review and meta-analysis of observational studies. PLoS One 2015; 10 (05) e0125827
    CrossrefPubMedGoogle Scholar
  • 36 Ferrer R, Ruiz-Rodriguez JC, Larrosa N, Llaneras J, Molas E, González-López JJ. Sepsis code implementation at Vall d'Hebron University Hospital: rapid diagnostics key to success. ICU Management & Practice 2017; 17 (04) 214-215
    PubMedGoogle Scholar
  • 37 Weiss SL, Peters MJ, Alhazzani W. et al. Surviving sepsis campaign international guidelines for the management of septic shock and sepsis-associated organ dysfunction in children. Intensive Care Med 2020; 46 (Suppl. 01) 10-67
    CrossrefPubMedGoogle Scholar
  • 38 Chiscano-Camón L, Plata-Menchaca E, Ruiz-Rodríguez JC, Ferrer R. Fisiopatología del shock séptico. Med Intensiva (Engl Ed) 2022; 46 (Suppl. 01) 1-13
    PubMedGoogle Scholar
  • 39 Wang C, Xu R, Zeng Y, Zhao Y, Hu X. A comparison of qSOFA, SIRS and NEWS in predicting the accuracy of mortality in patients with suspected sepsis: a meta-analysis. PLoS One 2022; 17 (04) e0266755
    CrossrefPubMedGoogle Scholar
  • 40 Ventura F, Pugin J, Tissieres P. ICU Management & Practice, 2021; 23. Accessed July 2, 2023 at: https://healthmanagement.org/c/icu/issuearticle/sepsis-diagnosis-clinical-signs-scores-and-biomarkers
    PubMedGoogle Scholar
  • 41 Simon L, Gauvin F, Amre DK, Saint-Louis P, Lacroix J. Serum procalcitonin and C-reactive protein levels as markers of bacterial infection: a systematic review and meta-analysis. Clin Infect Dis 2004; 39 (02) 206-217
    CrossrefPubMedGoogle Scholar
  • 42 Kondo Y, Umemura Y, Hayashida K, Hara Y, Aihara M, Yamakawa K. Diagnostic value of procalcitonin and presepsin for sepsis in critically ill adult patients: a systematic review and meta-analysis. J Intensive Care 2019; 7: 22
    CrossrefPubMedGoogle Scholar
  • 43 Wacker C, Prkno A, Brunkhorst FM, Schlattmann P. Procalcitonin as a diagnostic marker for sepsis: a systematic review and meta-analysis. Lancet Infect Dis 2013; 13 (05) 426-435
    CrossrefPubMedGoogle Scholar
  • 44 Plata-Menchaca EP, Ferrer R. Procalcitonin is useful for antibiotic deescalation in sepsis. Crit Care Med 2021; 49 (04) 693-696
    CrossrefPubMedGoogle Scholar
  • 45 Layios N, Lambermont B, Canivet JL. et al. Procalcitonin usefulness for the initiation of antibiotic treatment in intensive care unit patients. Crit Care Med 2012; 40 (08) 2304-2309
    CrossrefPubMedGoogle Scholar
  • 46 Schuetz P, Beishuizen A, Broyles M. et al. Procalcitonin (PCT)-guided antibiotic stewardship: an international experts consensus on optimized clinical use. Clin Chem Lab Med 2019; 57 (09) 1308-1318
    CrossrefPubMedGoogle Scholar
  • 47 Yu H, Nie L, Liu A. et al. Combining procalcitonin with the qSOFA and sepsis mortality prediction. Medicine (Baltimore) 2019; 98 (23) e15981
    CrossrefPubMedGoogle Scholar
  • 48 Kalil AC, Metersky ML, Klompas M. et al. Management of adults with hospital-acquired and ventilator-associated pneumonia: 2016 clinical practice guidelines by the Infectious Diseases Society of America and the American Thoracic Society. Clin Infect Dis 2016; 63 (05) e61-e111
    CrossrefPubMedGoogle Scholar
  • 49 Torres A, Niederman MS, Chastre J. et al. International ERS/ESICM/ESCMID/ALAT guidelines for the management of hospital-acquired pneumonia and ventilator-associated pneumonia: guidelines for the management of hospital-acquired pneumonia (HAP)/ventilator-associated pneumonia (VAP) of the European Respiratory Society (ERS), European Society of Intensive Care Medicine (ESICM), European Society of Clinical Microbiology and Infectious Diseases (ESCMID) and Asociación Latinoamericana del Tórax (ALAT). Eur Respir J 2017; 50 (03) 50
    CrossrefPubMedGoogle Scholar
  • 50 Póvoa P, Coelho L, Dal-Pizzol F. et al. How to use biomarkers of infection or sepsis at the bedside: guide to clinicians. Intensive Care Med 2023; 49 (02) 142-153
    CrossrefPubMedGoogle Scholar
  • 51 Christ-Crain M, Opal SM. Clinical review: the role of biomarkers in the diagnosis and management of community-acquired pneumonia. Crit Care 2010; 14 (01) 203
    CrossrefPubMedGoogle Scholar
  • 52 Kamat IS, Ramachandran V, Eswaran H, Guffey D, Musher DM. Procalcitonin to distinguish viral from bacterial pneumonia: a systematic review and meta-analysis. Clin Infect Dis 2020; 70 (03) 538-542
    CrossrefPubMedGoogle Scholar
  • 53 Meier MA, Branche A, Neeser OL. et al. Procalcitonin-guided antibiotic treatment in patients with positive blood cultures: a patient-level meta-analysis of randomized trials. Clin Infect Dis 2019; 69 (03) 388-396
    CrossrefPubMedGoogle Scholar
  • 54 Kennis B, Ali A, Lasoff D, Sweeney DA, Wardi G. The diagnostic utility of procalcitonin is limited in the setting of methamphetamine toxicity. Am J Emerg Med 2022; 54: 36-40
    CrossrefPubMedGoogle Scholar
  • 55 Wirz Y, Meier MA, Bouadma L. et al. Effect of procalcitonin-guided antibiotic treatment on clinical outcomes in intensive care unit patients with infection and sepsis patients: a patient-level meta-analysis of randomized trials. Crit Care 2018; 22 (01) 191
    CrossrefPubMedGoogle Scholar
  • 56 Kyriazopoulou E, Liaskou-Antoniou L, Adamis G. et al. Procalcitonin to reduce long-term infection-associated adverse events in sepsis: a randomized trial. Am J Respir Crit Care Med 2021; 203 (02) 202-210
    CrossrefPubMedGoogle Scholar
  • 57 de Jong E, van Oers JA, Beishuizen A. et al. Efficacy and safety of procalcitonin guidance in reducing the duration of antibiotic treatment in critically ill patients: a randomised, controlled, open-label trial. Lancet Infect Dis 2016; 16 (07) 819-827
    CrossrefPubMedGoogle Scholar
  • 58 Huang Q, Xiong H, Yan P. et al. The diagnostic and prognostic value of suPAR in patients with sepsis: a systematic review and meta-analysis. Shock 2020; 53 (04) 416-425
    CrossrefPubMedGoogle Scholar
  • 59 Bleharski JR, Kiessler V, Buonsanti C. et al. A role for triggering receptor expressed on myeloid cells-1 in host defense during the early-induced and adaptive phases of the immune response. J Immunol 2003; 170 (07) 3812-3818
    CrossrefPubMedGoogle Scholar
  • 60 Gómez-Piña V, Soares-Schanoski A, Rodríguez-Rojas A. et al. Metalloproteinases shed TREM-1 ectodomain from lipopolysaccharide-stimulated human monocytes. J Immunol 2007; 179 (06) 4065-4073
    CrossrefPubMedGoogle Scholar
  • 61 Aksaray S, Alagoz P, Inan A, Cevan S, Ozgultekin A. Diagnostic value of sTREM-1 and procalcitonin levels in the early diagnosis of sepsis. North Clin Istanb 2017; 3 (03) 175-182
    PubMedGoogle Scholar
  • 62 Julián-Jiménez A, Yañez MC, González-Del Castillo J. et al; en representación del grupo INFURG-SEMES. Prognostic power of biomarkers for short-term mortality in the elderly patients seen in Emergency Departments due to infections. Enferm Infecc Microbiol Clin (Engl Ed) 2019; 37 (01) 11-18
    PubMedGoogle Scholar
  • 63 Baldirà J, Ruiz-Rodríguez JC, Wilson DC. et al. Biomarkers and clinical scores to aid the identification of disease severity and intensive care requirement following activation of an in-hospital sepsis code. Ann Intensive Care 2020; 10 (01) 7
    CrossrefPubMedGoogle Scholar
  • 64 Baldirà J, Ruiz-Rodríguez JC, Ruiz-Sanmartin A. et al. Use of biomarkers to improve 28-day mortality stratification in patients with sepsis and SOFA ≤ 6. Biomedicines 2023; 11 (08) 11
    CrossrefPubMedGoogle Scholar
  • 65 Hotchkiss RS, Moldawer LL, Opal SM, Reinhart K, Turnbull IR, Vincent JL. Sepsis and septic shock. Nat Rev Dis Primers 2016; 2: 16045
    CrossrefPubMedGoogle Scholar
  • 66 Munoz C, Carlet J, Fitting C, Misset B, Blériot JP, Cavaillon JM. Dysregulation of in vitro cytokine production by monocytes during sepsis. J Clin Invest 1991; 88 (05) 1747-1754
    CrossrefPubMedGoogle Scholar
  • 67 Shapiro NI, Trzeciak S, Hollander JE. et al. A prospective, multicenter derivation of a biomarker panel to assess risk of organ dysfunction, shock, and death in emergency department patients with suspected sepsis. Crit Care Med 2009; 37 (01) 96-104
    CrossrefPubMedGoogle Scholar
  • 68 Dolin HH, Papadimos TJ, Stepkowski S, Chen X, Pan ZK. A novel combination of biomarkers to herald the onset of sepsis prior to the manifestation of symptoms. Shock 2018; 49 (04) 364-370
    CrossrefPubMedGoogle Scholar
  • 69 Parlato M, Philippart F, Rouquette A. et al; Captain Study Group. Circulating biomarkers may be unable to detect infection at the early phase of sepsis in ICU patients: the CAPTAIN prospective multicenter cohort study. Intensive Care Med 2018; 44 (07) 1061-1070
    CrossrefPubMedGoogle Scholar
  • 70 Teggert A, Datta H, Ali Z. Biomarkers for point-of-care diagnosis of sepsis. Micromachines (Basel) 2020; 11 (03) 11
    PubMedGoogle Scholar
  • 71 Kim M, Song KH, Kim CJ. et al. Electronic alerts with automated consultations promote appropriate antimicrobial prescriptions. PLoS One 2016; 11 (08) e0160551
    CrossrefPubMedGoogle Scholar
  • 72 Adams R, Henry KE, Sridharan A. et al. Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis. Nat Med 2022; 28 (07) 1455-1460
    CrossrefPubMedGoogle Scholar
  • 73 Pugin J, Daix T, Pagani JL. et al. Serial measurement of pancreatic stone protein for the early detection of sepsis in intensive care unit patients: a prospective multicentric study. Crit Care 2021; 25 (01) 151
    CrossrefPubMedGoogle Scholar
  • 74 David VL, Ercisli MF, Rogobete AF. et al. Early prediction of sepsis incidence in critically ill patients using specific genetic polymorphisms. Biochem Genet 2017; 55 (03) 193-203
    CrossrefPubMedGoogle Scholar
  • 75 D'Onofrio V, Heylen D, Pusparum M. et al. A prospective observational cohort study to identify inflammatory biomarkers for the diagnosis and prognosis of patients with sepsis. J Intensive Care 2022; 10 (01) 13
    CrossrefPubMedGoogle Scholar
  • 76 Liu W, Geng F, Yu L. Long non-coding RNA MALAT1/microRNA 125a axis presents excellent value in discriminating sepsis patients and exhibits positive association with general disease severity, organ injury, inflammation level, and mortality in sepsis patients. J Clin Lab Anal 2020; 34 (06) e23222
    CrossrefPubMedGoogle Scholar
  • 77 Assicot M, Gendrel D, Carsin H, Raymond J, Guilbaud J, Bohuon C. High serum procalcitonin concentrations in patients with sepsis and infection. Lancet 1993; 341 (8844) 515-518
    CrossrefPubMedGoogle Scholar
  • 78 Yin WP, Li JB, Zheng XF, An L, Shao H, Li CS. Effect of neutrophil CD64 for diagnosing sepsis in emergency department. World J Emerg Med 2020; 11 (02) 79-86
    CrossrefPubMedGoogle Scholar
  • 79 Brenner T, Uhle F, Fleming T. et al. Soluble TREM-1 as a diagnostic and prognostic biomarker in patients with septic shock: an observational clinical study. Biomarkers 2017; 22 (01) 63-69
    CrossrefPubMedGoogle Scholar
  • 80 Su L, Liu D, Chai W, Liu D, Long Y. Role of sTREM-1 in predicting mortality of infection: a systematic review and meta-analysis. BMJ Open 2016; 6 (05) e010314
    CrossrefPubMedGoogle Scholar
  • 81 Liu M, Zhang X, Chen H. et al. Serum sPD-L1, upregulated in sepsis, may reflect disease severity and clinical outcomes in septic patients. Scand J Immunol 2017; 85 (01) 66-72
    CrossrefPubMedGoogle Scholar
  • 82 Yende S, Kellum JA, Talisa VB. et al. Long-term host immune response trajectories among hospitalized patients with sepsis. JAMA Netw Open 2019; 2 (08) e198686
    CrossrefPubMedGoogle Scholar
  • 83 Hoppensteadt D, Tsuruta K, Hirman J, Kaul I, Osawa Y, Fareed J. Dysregulation of inflammatory and hemostatic markers in sepsis and suspected disseminated intravascular coagulation. Clin Appl Thromb Hemost 2015; 21 (02) 120-127
    CrossrefPubMedGoogle Scholar
  • 84 Matsumoto H, Ogura H, Shimizu K. et al. The clinical importance of a cytokine network in the acute phase of sepsis. Sci Rep 2018; 8 (01) 13995
    CrossrefPubMedGoogle Scholar
  • 85 Barre M, Behnes M, Hamed S. et al. Revisiting the prognostic value of monocyte chemotactic protein 1 and interleukin-6 in the sepsis-3 era. J Crit Care 2018; 43: 21-28
    CrossrefPubMedGoogle Scholar
  • 86 Uusitalo-Seppälä R, Huttunen R, Aittoniemi J. et al. Pentraxin 3 (PTX3) is associated with severe sepsis and fatal disease in emergency room patients with suspected infection: a prospective cohort study. PLoS One 2013; 8 (01) e53661
    CrossrefPubMedGoogle Scholar
  • 87 Hamed S, Behnes M, Pauly D. et al. Pentraxin-3 predicts short- and mid-term mortality in patients with sepsis and septic shock during intensive care treatment. Clin Lab 2018; 64 (06) 999-1011
    PubMedGoogle Scholar
  • 88 Larsson A, Tydén J, Johansson J. et al. Calprotectin is superior to procalcitonin as a sepsis marker and predictor of 30-day mortality in intensive care patients. Scand J Clin Lab Invest 2020; 80 (02) 156-161
    CrossrefPubMedGoogle Scholar
  • 89 Lundberg OHM, Lengquist M, Spångfors M. et al. Circulating bioactive adrenomedullin as a marker of sepsis, septic shock and critical illness. Crit Care 2020; 24 (01) 636
    CrossrefPubMedGoogle Scholar
  • 90 Karampela I, Christodoulatos GS, Kandri E. et al. Circulating eNampt and resistin as a proinflammatory duet predicting independently mortality in critically ill patients with sepsis: a prospective observational study. Cytokine 2019; 119: 62-70
    CrossrefPubMedGoogle Scholar
  • 91 Saboktakin L, Bilan N, Ghalehgolab Behbahan A, Poorebrahim S. Relationship between resistin levels and sepsis among children under 12 years of age: a case control study. Front Pediatr 2019; 7: 355
    CrossrefPubMedGoogle Scholar
  • 92 Eugen-Olsen J, Giamarellos-Bourboulis EJ. suPAR: the unspecific marker for disease presence, severity and prognosis. Int J Antimicrob Agents 2015; 46 (Suppl. 01) S33-S34
    CrossrefPubMedGoogle Scholar
  • 93 Feng Q, Wei WQ, Chaugai S. et al. Association between low-density lipoprotein cholesterol levels and risk for sepsis among patients admitted to the hospital with infection. JAMA Netw Open 2019; 2 (01) e187223
    CrossrefPubMedGoogle Scholar
  • 94 Urbonas V, Eidukaitė A, Tamulienė I. The predictive value of soluble biomarkers (CD14 subtype, interleukin-2 receptor, human leucocyte antigen-G) and procalcitonin in the detection of bacteremia and sepsis in pediatric oncology patients with chemotherapy-induced febrile neutropenia. Cytokine 2013; 62 (01) 34-37
    CrossrefPubMedGoogle Scholar
  • 95 Arai Y, Mizugishi K, Nonomura K, Naitoh K, Takaori-Kondo A, Yamashita K. Phagocytosis by human monocytes is required for the secretion of presepsin. J Infect Chemother 2015; 21 (08) 564-569
    CrossrefPubMedGoogle Scholar
  • 96 Lu B, Zhang Y, Li C. et al. The utility of presepsin in diagnosis and risk stratification for the emergency patients with sepsis. Am J Emerg Med 2018; 36 (08) 1341-1345
    CrossrefPubMedGoogle Scholar
  • 97 Memar MY, Baghi HB. Presepsin: a promising biomarker for the detection of bacterial infections. Biomed Pharmacother 2019; 111: 649-656
    CrossrefPubMedGoogle Scholar
  • 98 Westhoff D, Engelen-Lee JY, Hoogland ICM. et al. Systemic infection and microglia activation: a prospective postmortem study in sepsis patients. Immun Ageing 2019; 16: 18
    CrossrefPubMedGoogle Scholar
  • 99 Lerman YV, Lim K, Hyun Y-M. et al. Sepsis lethality via exacerbated tissue infiltration and TLR-induced cytokine production by neutrophils is integrin α3β1-dependent. Blood 2014; 124 (24) 3515-3523
    CrossrefPubMedGoogle Scholar
  • 100 Sarangi PP, Hyun YM, Lerman YV, Pietropaoli AP, Kim M. Role of β1 integrin in tissue homing of neutrophils during sepsis. Shock 2012; 38 (03) 281-287
    CrossrefPubMedGoogle Scholar
  • 101 Mikacenic C, Hahn WO, Price BL. et al. Biomarkers of endothelial activation are associated with poor outcome in critical illness. PLoS One 2015; 10 (10) e0141251
    CrossrefPubMedGoogle Scholar
  • 102 Gui F, Peng H, Liu Y. Elevated circulating lnc-ANRIL/miR-125a axis level predicts higher risk, more severe disease condition, and worse prognosis of sepsis. J Clin Lab Anal 2019; 33 (06) e22917
    CrossrefPubMedGoogle Scholar
  • 103 Zhao D, Li S, Cui J, Wang L, Ma X, Li Y. Plasma miR-125a and miR-125b in sepsis: Correlation with disease risk, inflammation, severity, and prognosis. J Clin Lab Anal 2020; 34 (02) e23036
    CrossrefPubMedGoogle Scholar
  • 104 Na L, Ding H, Xing E. et al. Lnc-MEG3 acts as a potential biomarker for predicting increased disease risk, systemic inflammation, disease severity, and poor prognosis of sepsis via interacting with miR-21. J Clin Lab Anal 2020; 34 (04) e23123
    CrossrefPubMedGoogle Scholar
  • 105 Tuerxun K, Eklund D, Wallgren U. et al. Predicting sepsis using a combination of clinical information and molecular immune markers sampled in the ambulance. Sci Rep 2023; 13 (01) 14917
    CrossrefPubMedGoogle Scholar
  • 106 Leligdowicz A, Matthay MA. Heterogeneity in sepsis: new biological evidence with clinical applications. Crit Care 2019; 23 (01) 80
    CrossrefPubMedGoogle Scholar
  • 107 Klein Klouwenberg PM, Cremer OL, van Vught LA. et al. Likelihood of infection in patients with presumed sepsis at the time of intensive care unit admission: a cohort study. Crit Care 2015; 19 (01) 319
    CrossrefPubMedGoogle Scholar
  • 108 Luethy PM, Johnson JK. The use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for the identification of pathogens causing sepsis. J Appl Lab Med 2019; 3 (04) 675-685
    CrossrefPubMedGoogle Scholar
  • 109 Timbrook TT, Morton JB, McConeghy KW, Caffrey AR, Mylonakis E, LaPlante KL. The effect of molecular rapid diagnostic testing on clinical outcomes in bloodstream infections: a systematic review and meta-analysis. Clin Infect Dis 2017; 64 (01) 15-23
    CrossrefPubMedGoogle Scholar
  • 110 Vlek AL, Bonten MJ, Boel CH. Direct matrix-assisted laser desorption ionization time-of-flight mass spectrometry improves appropriateness of antibiotic treatment of bacteremia. PLoS One 2012; 7 (03) e32589
    CrossrefPubMedGoogle Scholar
  • 111 Clec'h C, Ferriere F, Karoubi P. et al. Diagnostic and prognostic value of procalcitonin in patients with septic shock. Crit Care Med 2004; 32 (05) 1166-1169
    CrossrefPubMedGoogle Scholar
  • 112 Huang AM, Newton D, Kunapuli A. et al. Impact of rapid organism identification via matrix-assisted laser desorption/ionization time-of-flight combined with antimicrobial stewardship team intervention in adult patients with bacteremia and candidemia. Clin Infect Dis 2013; 57 (09) 1237-1245
    CrossrefPubMedGoogle Scholar
  • 113 Bookstaver PB, Nimmich EB, Smith III TJ. et al. Cumulative effect of an antimicrobial stewardship and rapid diagnostic testing bundle on early streamlining of antimicrobial therapy in gram-negative bloodstream infections. Antimicrob Agents Chemother 2017; 61 (09) 61
    CrossrefPubMedGoogle Scholar
  • 114 Perez KK, Olsen RJ, Musick WL. et al. Integrating rapid pathogen identification and antimicrobial stewardship significantly decreases hospital costs. Arch Pathol Lab Med 2013; 137 (09) 1247-1254
    CrossrefPubMedGoogle Scholar
  • 115 Perez KK, Olsen RJ, Musick WL. et al. Integrating rapid diagnostics and antimicrobial stewardship improves outcomes in patients with antibiotic-resistant Gram-negative bacteremia. J Infect 2014; 69 (03) 216-225
    CrossrefPubMedGoogle Scholar
  • 116 Jung JS, Hamacher C, Gross B. et al. Evaluation of a semiquantitative matrix-assisted laser desorption ionization-time of flight mass spectrometry method for rapid antimicrobial susceptibility testing of positive blood cultures. J Clin Microbiol 2016; 54 (11) 2820-2824
    CrossrefPubMedGoogle Scholar
  • 117 Verroken A, Defourny L, le Polain de Waroux O. et al. Clinical Impact of MALDI-TOF MS Identification and Rapid Susceptibility Testing on Adequate Antimicrobial Treatment in Sepsis with Positive Blood Cultures. PLoS One 2016; 11: e0156299
    CrossrefPubMedGoogle Scholar
  • 118 Banerjee R, Teng CB, Cunningham SA. et al. Randomized trial of rapid multiplex polymerase chain reaction-based blood culture identification and susceptibility testing. Clin Infect Dis 2015; 61 (07) 1071-1080
    CrossrefPubMedGoogle Scholar
  • 119 Hill JT, Tran KD, Barton KL, Labreche MJ, Sharp SE. Evaluation of the nanosphere Verigene BC-GN assay for direct identification of gram-negative bacilli and antibiotic resistance markers from positive blood cultures and potential impact for more-rapid antibiotic interventions. J Clin Microbiol 2014; 52 (10) 3805-3807
    CrossrefPubMedGoogle Scholar
  • 120 Altun O, Almuhayawi M, Ullberg M, Ozenci V. Clinical evaluation of the FilmArray blood culture identification panel in identification of bacteria and yeasts from positive blood culture bottles. J Clin Microbiol 2013; 51 (12) 4130-4136
    CrossrefPubMedGoogle Scholar
  • 121 Dodémont M, De Mendonça R, Nonhoff C, Roisin S, Denis O. Performance of the Verigene Gram-negative blood culture assay for rapid detection of bacteria and resistance determinants. J Clin Microbiol 2014; 52 (08) 3085-3087
    CrossrefPubMedGoogle Scholar
  • 122 Nguyen MH, Clancy CJ, Pasculle AW. et al. Performance of the T2Bacteria panel for diagnosing bloodstream infections: a diagnostic accuracy study. Ann Intern Med 2019; 170 (12) 845-852
    CrossrefPubMedGoogle Scholar
  • 123 Vincent JL, Brealey D, Libert N. et al; Rapid Diagnosis of Infections in the Critically Ill Team. Rapid diagnosis of infection in the critically ill, a multicenter study of molecular detection in bloodstream infections, pneumonia, and sterile site infections. Crit Care Med 2015; 43 (11) 2283-2291
    CrossrefPubMedGoogle Scholar
  • 124 Marschal M, Bachmaier J, Autenrieth I, Oberhettinger P, Willmann M, Peter S. Evaluation of the accelerate pheno system for fast identification and antimicrobial susceptibility testing from positive blood cultures in bloodstream infections caused by gram-negative pathogens. J Clin Microbiol 2017; 55 (07) 2116-2126
    CrossrefPubMedGoogle Scholar
  • 125 Meltzer AC, Newton S, Lange J. et al. A randomized control trial of a multiplex gastrointestinal PCR panel versus usual testing to assess antibiotics use for patients with infectious diarrhea in the emergency department. J Am Coll Emerg Physicians Open 2022; 3 (01) e12616
    CrossrefPubMedGoogle Scholar
  • 126 D'Onofrio V, Salimans L, Bedenić B, Cartuyvels R, Barišić I, Gyssens IC. The clinical impact of rapid molecular microbiological diagnostics for pathogen and resistance gene identification in patients with sepsis: a systematic review. Open Forum Infect Dis 2020; 7 (10) ofaa352
    CrossrefPubMedGoogle Scholar
  • 127 Oeschger T, McCloskey D, Kopparthy V, Singh A, Erickson D. Point of care technologies for sepsis diagnosis and treatment. Lab Chip 2019; 19 (05) 728-737
    CrossrefPubMedGoogle Scholar
  • 128 Ruiz-Rodriguez JC, Plata-Menchaca EP, Chiscano-Camón L. et al. Precision medicine in sepsis and septic shock: from omics to clinical tools. World J Crit Care Med 2022; 11 (01) 1-21
    CrossrefPubMedGoogle Scholar
  • 129 Bermejo-Martin JF, Andaluz-Ojeda D, Almansa R. et al. Defining immunological dysfunction in sepsis: a requisite tool for precision medicine. J Infect 2016; 72 (05) 525-536
    CrossrefPubMedGoogle Scholar
  • 130 Dey P, Fabri-Faja N, Calvo-Lozano O. et al. Label-free bacteria quantification in blood plasma by a bioprinted microarray based interferometric point-of-care device. ACS Sens 2019; 4 (01) 52-60
    CrossrefPubMedGoogle Scholar