Biomarkers in intensive care unit infections, friend or foe?
Review Article

Biomarkers in intensive care unit infections, friend or foe?

Chunhui Xu1, Shu Li2, Yimin Wang3, Min Zhang4, Mi Zhou5

1Clinical Laboratory Center, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China; 2Clinical Laboratory, Qinyang People’s Hospital, Qinyang 454550, China; 3Department of Respiratory and Critical Care Medicine, National Clinical Center for Respiratory Diseases, China-Japan Friendship Hospital, Beijing 100029, China; 4Department of Pharmacy Services, Boston Medical Center, Boston, MA, USA; 5Department of Pharmacy, Children’s Hospital of Soochow University, Suzhou 215000, China

Contributions: (I) Conception and design: None; (II) Administrative support: None; (III) Provision of study materials or patients: None; (IV) Collection and assembly of data: None; (V) Data analysis and interpretation: None; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Mi Zhou. Department of Pharmacy, Children’s Hospital of Soochow University, Suzhou 215000, China. Email: ymzlm001@gmail.com.

Abstract: Antibiotic misuse is a crucial problem for critically ill patients. Biomarkers have emerged as tools to assist the clinician in antimicrobial therapy decisions among critically ill patients in intensive care units (ICU). They are useful for early identification of infection, timely initiation of antimicrobial therapy, and prompt evaluation of treatment course or duration. However, until now, an ideal biomarker has not yet been identified. The combination of procalcitonin (PCT), C-reactive protein (CPR) and other biomarkers may overcome their insufficiencies, with the high sensitivity of CRP compensating for the low sensitivity of PCT. Biomarkers could not predict antimicrobial resistance, and development of molecular diagnosis brings new challenges. The most important thing for the clinician is to understand the advantages and disadvantages of different methods so that to use them reasonably.

Keywords: Biomarker; sepsis; procalcitonin (PCT); critically ill patients; antibiotic stewardship


Received: 27 May 2019; Accepted: 05 June 2019; Published: 17 June 2019.

doi: 10.21037/jeccm.2019.06.02


Optimal antibiotic use is crucial in critically ill patients, especially in the setting of the rising level of antibiotic resistance. Many aspects were analyzed, such as early identification of pathogens, the choice of empiric treatment, de-escalation, pharmacokinetics/pharmacodynamics, and duration (1). Antimicrobial stewardship has been recommended and implemented in intensive care unit (ICU) for rapid identification and optimal treatment of bacterial infections, avoiding unnecessary broad-spectrum antibiotics, and shortening the duration of therapy (2). Biomarkers serve as useful tools to optimize antibiotic therapy among critically ill patients (2). However, the benefits and limitations of biomarkers for clinical decision-making remain controversial (3).


What is biomarker?

The definition of a biomarker is “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to therapeutic intervention.” (4). Many studies have reported almost 200 different biomarkers related to infectious diseases, and also may be used in sepsis, such as C-reactive protein (CRP), procalcitonin (PCT), IL-6, etc. Professor Vincent and his colleague reviewed 3,370 references covering 178 different biomarkers (2). Many researchers are familiar with some of them, but some others not. Novel or traditional biomarkers such as CRP, PCT, IL-6 have been evaluated for diagnosis and prognostication of sepsis.


Why is there a need for biomarkers?

Infection is a common clinical problem in critically ill patients. Fifty-one percent of ICU patients are considered infected, and the prevalence of multidrug resistance was positively correlated with the length of ICU stay (5). Mortality and morbidity associated with sepsis remain unacceptably high. Sepsis is a severe and frequent complication with a complex pathophysiological process. Traditionally, the approach to sepsis diagnosis was based on clinical signs and symptoms of sepsis, such as fever, tachycardia, and tachypnea, supported by relevant microbiological data. However, these are usually not objective indicators. In order to aid diagnosis, biomarkers of sepsis can potentially be used for prognostication to predict the development of organ dysfunction, to guide antibiotic therapy and to evaluate treatment response (2).

For sepsis, each hour of delay in antimicrobial administration was associated with an average decrease in survival of 7.6% (6). In 2018, the Surviving Sepsis Campaign (SSC) had updated the sepsis “hour-3 bundle” for “hour-1 bundle” (7). Two recommendations of the bundles include obtaining blood cultures and administering broad-spectrum antibiotics (7). However, the traditional microbiological method may take a longer time for the result to come back. The turnaround time for blood culture is about 24–48 hours or longer. Unfortunately, studies indicated that the accuracy of clinician decisions to start antimicrobials were disappointing. The experimental treatment was inaccurate in most cases (54%) (8). Another study indicated that the accuracy of empiric diagnosis varies for different infectious sites. For such as gastrointestinal and respiratory tract sources, clinicians’ diagnostic accuracy is much better than urinary tract sources and skin and soft tissues.

Moreover, for intravascular sources, the accuracy is disappointing, just about 56% (9). Precision treatment remains unclear in the early stages of sepsis. In order to change the situation, rapid serological detection and molecular diagnostic methods have been developed, but there is another crucial thing to consider, availability. Novel molecular diagnosis methods such as next-generation sequencing (NGS) (10,11), matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) (12), Filmarray (13), can deliver far more accurate, and rapid diagnosis and provide the value to monitor the clinical status of sepsis (14). However, in many hospitals, they are unavailable and costly. Biomarkers could be alternative options.


What is an ideal biomarker?

What is an ideal biomarker? First, they can be used to rule out infection; second, biomarkers are also markers of disease severity; third, repeated measurements can be helpful to evaluate a patient’s clinical course (15). There are still no perfect biomarkers. In some infectious diseases such as HBV, HIV, brucellosis, and Helicobacter pylori infection, biomarkers have been handy tools. Many biomarkers can be used in sepsis, but they have limited ability to distinguish sepsis from other inflammatory conditions. Sepsis is an extremely complex pathophysiology process that involves the balance of inflammatory and anti-inflammatory processes, humoral and cellular reactions, and circulatory abnormalities. Various biomarkers indicate different stages of human response (2,16,17). Given the complexity of the sepsis response, Pierrakos and his colleagues concluded that it would be unlikely to identify a single ideal biomarker (2). After 5 years, Jensen and his colleagues showed similar conclusion (18). Each biomarker has limited sensitivity and specificity. So, research is still being done to find a better one.


How to do better under existing conditions in early identification?

As known, finding a better one is not an easy thing. Under existing conditions, there are two possible ways to address this dilemma. One way is to establish a bundle of diagnostic methods, including signs, symptoms, medical images, physical examinations, biomarkers, and even clinical experiences. The other way is to use two or more biomarkers combination in order to increase sensitivity and specificity of early diagnosis.

Multivariate analysis revealed that the combination of CRP, PCT and the sepsis-related organ failure (SOFA) score in the bioscore had an area under the curve (AUC) of 0.790 (95% CI, 0.739–0.834, P<0.001) (19). A bioscore of ≥2.65 was considered to be statistically significant in making a positive diagnosis of sepsis (19). Serum concentrations of PCT, soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) and the high-affinity immunoglobulin-Fc fragment receptor I (FcγRI) CD64 on neutrophils (PMN CD64 index) were higher in patients with sepsis compared with all others (P<0.001 for the three markers) (20). The bioscore performed better than each biomarker (20). Another study revealed a similar result. CD64 showed a better positive probability for the identification of sepsis in ICU than CPR or PCT. Moreover, the combination of CRP, PCT, and CD64 improved diagnostic accuracy for sepsis (21). In a multi-center cohort study, they evaluated the reliability and discriminant ability of 47 leukocyte biomarkers as predictors of sepsis (22). Individually, a single leukocyte biomarker expression was associated with subsequent sepsis, but the combination had no clinically relevant predictive validity (22). The multivariate analysis of the surgical cohort showed that the combination of PCT and HLA-DRA (encoding the non-polymorphic region of the alpha-chain of the HLA-DR molecule) improved the identification of sepsis in surgical patients (23).


Biomarker in sepsis combined with multiple organ damage

Sepsis is a syndrome characterized by a series of clinical manifestations and is frequently complicated by multiple organ damage such as acute kidney injury (AKI), cholestasis, encephalopathy (24). Presence of these complications suggests a severe condition and increased mortality.

A pilot study enrolled 33 patients with abdominal surgery, and 22 patients among them developed sepsis with varying degrees of AKI (25). A panel including serum neutrophil gelatinase-associated lipocalin (NGAL), urinary NGAL, calprotectin, SOFA score could predict in-hospital mortality with an AUROC of 0.911 (25). NGAL was human neutrophil lipocalin or lipocalin2, that was first identified as a 25 kDa protein in the secondary granules of human neutrophils (26). In bacterial bloodstream infection, NGAL is released and can be detected (27). Studies have been proven to be a valuable biomarker for early identification of AKI (28). This study illustrated that biomarkers related to AKI might be helpful to predict the complication of organ damage in critical illness. There are some other studies about biomarkers related AKI, such as cytochrome c oxidase subunit B (COX5b) (29), serum PARK7 (30), IL-8 Levels (30), and Alpha1-microglobulin (31).

The liver can release inflammatory mediators such as acute-phase proteins, cytokines, coagulants as a response to sepsis. These substances facilitate the clearance of pathogenic organisms and toxins (32,33). CD39 expression on macrophages limits P2X7-mediated pro-inflammatory responses, and combinations of a P2X7 antagonist and adenosine A2A receptor agonist are hepatoprotective during the acute phase of abdominal sepsis (34). Retinol-binding protein-4 (RBP4) (35), plasma endothelin-1 (36), and C-terminal proendothelin-1 (37) were proven to have potential value in sepsis-induced liver damage.

Other biomarkers might be used in different settings. For example, D-lactate, intestinal fatty acid-binding protein (FABP) and citrulline could be used for acute intestinal ischemic injury (38), and growth arrest-specific gene 6 (Gas6) was used for acute lung injury (39). Interleukin 27 was identified as a sepsis diagnostic biomarker in critically ill children, but not for lung injury (40).


Biomarker in antibiotic stewardship

The Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America published the guidelines for the Antibiotic Stewardship Program (ASPs) (41). The panel suggested the use of serial PCT measurements as a stewardship tool to decrease exposure and shorten the duration of antibiotic therapy, without worsening clinical outcomes (41).

A prospective, multicenter, randomized, controlled, open-label intervention trial was conducted to evaluate the efficacy and safety of the PCT-guided antibiotic treatment. The study enrolled 1,575 patients in ICUs. In the PCT-guided group, the median duration of treatment was 5 days, which was 2 days shorter than the standard-of-care group. The 1-year mortality rate was 36%, which was much lower than the latter (42). Similarly, systematic reviews and meta-analysis revealed similar results. The 30-day mortality rate was significantly lower in PCT-guided patients than in control patients with acute respiratory infections. Besides, PCT guidance was also associated with a reduction in antibiotic exposure and antibiotic-related side-effects (43). Moreover, another system review gave the same conclusion (44).

PCT has been used for several years. The specificity and sensitivity of PCT for the diagnosis of sepsis are not completely convincing (45,46), but more and more evidence showed that serial PCT measurements might be a choice for de-escalation of empirical therapy, prognosis and cost assessment (47,48).


Biomarkers for predicting resistance

In the traditional view, biomarkers could predict patients with or without infection (15), could predict infectious severity (43), could help to reduce treatment duration and cost (42,49), but biomarkers could not predict resistance. Predicting resistance is a crucial issue for empiric therapy.

A study evaluated secretome profile analysis of multidrug-resistant (MDR), monodrug-resistant, and drug-susceptible Mycobacterium tuberculosis in order to find some proteins as potential biomarkers for drug-susceptible identification (50). They found some proteins such as putative prophagephiRv2 integrase, etc. which might suggest putative roles in controlling the anti-tuberculosis ability, but the results were not validated (50). Another study revealed that MDR tuberculosis (MDR-TB) strains contained specific antigens. Five bands from the MDR-TB fractions were not observed in drug-sensitive-TB fractions. These proteins might be potential diagnostic antigens (51).

The antimicrobial resistant profiles of common pathogens such as Klebsiella pneumoniae and Staphylococcus aureus are directly related to clinical decision. However, until now, professionals still depend on traditional culture and antimicrobial susceptibility testing systems. Researchers tried some molecular diagnostic methods such as PCR-based testing methods. By these methods, it is possible to detect genes related to resistance such as carbapenemase genes of Klebsiella pneumoniae and mecA gene of methicillin-resistant Staphylococcus aureus (MRSA) (52). However, genotypic resistance was sometimes different from phenotypic resistance, and even there would be further verified by phenotypic resistance profiles (52). Biomarkers which could predict phenotypes might be more useful and make fewer mistakes. Unfortunately, there is still a long way to go.

Compared to direct evidence, indirect evidence may be the other direction. A study was conducted to analyze volatile organic compounds (VOCs) of bacteria. It aimed to identify and compare the VOCs of antibiotic-resistant and standard strains of Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae (53). This study demonstrated that resistant strains of bacteria produced VOCs were different from those of the standard strains (53). Another study in vitro showed that different interferon (IFN) subtypes played different roles for MRSA infection. IFN-β reduces host susceptibility to MRSA infection, while IFN-α increases susceptibility (54). This indicated different bacterial resistant species infection after influenza virus infection.


Biomarkers for neonatal sepsis

Neonatal sepsis is a leading cause of global mortality in children younger than 1 year (55). The initial, clinical presentation is often subtle and nonspecific. There are many studies about using biomarkers to predict neonatal sepsis (56). Based on the timing of the infection, neonatal sepsis is classified into early-onset sepsis (EOS) (≤3 days of life) and late-onset sepsis (LOS) (4–30 days) (57,58). Pathogens associated with EOS and LOS are similar, but not the same (59). For EOS, the pathogens are mostly transmitted from mothers to infants during the intrapartum period, and LOS may be caused by vertically or horizontally acquired pathogens from the environment after birth (59). This review summarized some biomarkers validated in neonatal sepsis. Similar to their utilization in adult sepsis, there are excellent prospects for CRP, and PCT, for the treatment of neonatal sepsis (60).

A large multicenter, randomized controlled trial assessed PCT-guided decision making for suspected EOS (56). Compared with the standard group, the duration of antibiotic therapy of the PCT group was reduced (55.1 vs. 65.1 h) (56). This study showed the critical role of PCT in antibiotic stewardship. The meta-analysis and systematic review also revealed that the combination of PCT and CRP or presepsin alone improves the accuracy of the diagnosis of neonatal sepsis (61).

However, PCT has some limitations. PCT level is elevated in non-infected newborns requiring neonatal resuscitation and in infants born to mothers with chorioamnionitis (59,62). In healthy neonates, PCT level is affected by maternal Streptococcus agalactiae (GBS) colonization and prolonged rupture of membranes ≥18 h (59,63). Therefore, it is possible to try harder in the setting of a more accurate cutoff valve in neonatal sepsis.


Conclusions

Clinical practice needs to balance the benefits of an earlier infectious identification, appropriate empirical and targeted therapy, and right duration with harms. Clinicians and investigators have been exploring ideal biomarkers for the balance. Perfection is approachable, but it cannot be reached. PCT and CRP have been most widely used, but none has sufficient specificity or sensitivity for rapid diagnosis and treatment of infection or sepsis. Previous studies suggested that biomarker combination would be helpful to improve diagnostic performance. The combination may be more accurate and sensitive, would be more useful in clinical practice for adult and children patients. There are some limitations of PCT, CRP, or combined with other factors. Biomarkers could not predict resistant. With the development of molecular diagnosis, biomarkers would not be the only choice for rapid diagnosis. In conclusion, biomarkers are both friend and foe. The most important thing for clinical practice is to understand the advantages and disadvantages of different methods so that to use them reasonably.


Acknowledgments

Funding: This work supported by the Science and Technology Program of Suzhou (Grant SYSD2018240).


Footnote

Conflicts of Interest: The authors have no conflicts of interest to declare.


References

  1. Vincent JL, Bassetti M, Francois B, et al. Advances in antibiotic therapy in the critically ill. Crit Care 2016;20:133. [Crossref] [PubMed]
  2. Pierrakos C, Vincent JL. Sepsis biomarkers: a review. Crit Care 2010;14:R15. [Crossref] [PubMed]
  3. Albrich WC, Harbarth S. Pros and cons of using biomarkers versus clinical decisions in start and stop decisions for antibiotics in the critical care setting. Intensive Care Med 2015;41:1739-51. [Crossref] [PubMed]
  4. Biomarkers Definitions Working G. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 2001;69:89-95. [Crossref] [PubMed]
  5. Vincent JL, Rello J, Marshall J, et al. International study of the prevalence and outcomes of infection in intensive care units. JAMA 2009;302:2323-9. [Crossref] [PubMed]
  6. Kumar A, Roberts D, Wood KE, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med 2006;34:1589-96. [Crossref] [PubMed]
  7. Levy MM, Evans LE, Rhodes A. The Surviving Sepsis Campaign Bundle: 2018 Update. Crit Care Med 2018;46:997-1000. [Crossref] [PubMed]
  8. Levin PD, Idrees S, Sprung CL, et al. Antimicrobial use in the ICU: indications and accuracy--an observational trial. J Hosp Med 2012;7:672-8. [Crossref] [PubMed]
  9. Ruiz-Giardin JM, Jimenez BC, Martin RM, et al. Clinical diagnostic accuracy of suspected sources of bacteremia and its effect on mortality. Eur J Intern Med 2013;24:541-5. [Crossref] [PubMed]
  10. Long Y, Zhang Y, Gong Y, et al. Diagnosis of Sepsis with Cell-free DNA by Next-Generation Sequencing Technology in ICU Patients. Arch Med Res 2016;47:365-71. [Crossref] [PubMed]
  11. Grumaz S, Stevens P, Grumaz C, et al. Next-generation sequencing diagnostics of bacteremia in septic patients. Genome Med 2016;8:73. [Crossref] [PubMed]
  12. Beganovic M, Costello M, Wieczorkiewicz SM. Effect of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Alone versus MALDI-TOF MS Combined with Real-Time Antimicrobial Stewardship Interventions on Time to Optimal Antimicrobial Therapy in Patients with Positive Blood Cultures. J Clin Microbiol 2017;55:1437-45. [Crossref] [PubMed]
  13. Leber AL, Everhart K, Balada-Llasat JM, et al. Multicenter Evaluation of BioFire FilmArray Meningitis/Encephalitis Panel for Detection of Bacteria, Viruses, and Yeast in Cerebrospinal Fluid Specimens. J Clin Microbiol 2016;54:2251-61. [Crossref] [PubMed]
  14. Daumas A, Alingrin J, Ouedraogo R, et al. MALDI-TOF MS monitoring of PBMC activation status in sepsis. BMC Infect Dis 2018;18:355. [Crossref] [PubMed]
  15. Vincent JL, Teixeira L. Sepsis biomarkers. Value and limitations. Am J Respir Crit Care Med 2014;190:1081-2. [Crossref] [PubMed]
  16. Gullo A, Bianco N, Berlot G. Management of severe sepsis and septic shock: challenges and recommendations. Crit Care Clin 2006;22:489-501. ix. [Crossref] [PubMed]
  17. Hotchkiss RS, Karl IE. The pathophysiology and treatment of sepsis. N Engl J Med 2003;348:138-50. [Crossref] [PubMed]
  18. Jensen JU, Bouadma L. Why biomarkers failed in sepsis. Intensive Care Med 2016;42:2049-51. [Crossref] [PubMed]
  19. Yang Y, Xie J, Guo F, et al. Combination of C-reactive protein, procalcitonin and sepsis-related organ failure score for the diagnosis of sepsis in critical patients. Ann Intensive Care 2016;6:51. [Crossref] [PubMed]
  20. Gibot S, Bene MC, Noel R, et al. Combination biomarkers to diagnose sepsis in the critically ill patient. Am J Respir Crit Care Med 2012;186:65-71. [Crossref] [PubMed]
  21. Jamsa J, Ala-Kokko T, Huotari V, et al. Neutrophil CD64, C-reactive protein, and procalcitonin in the identification of sepsis in the ICU - Post-test probabilities. J Crit Care 2018;43:139-42. [Crossref] [PubMed]
  22. Shankar-Hari M, Datta D, Wilson J, et al. Early PREdiction of sepsis using leukocyte surface biomarkers: the ExPRES-sepsis cohort study. Intensive Care Med 2018;44:1836-48. [Crossref] [PubMed]
  23. Almansa R, Martin S, Martin-Fernandez M, et al. Combined quantification of procalcitonin and HLA-DR improves sepsis detection in surgical patients. Sci Rep 2018;8:11999. [Crossref] [PubMed]
  24. Gotts JE, Matthay MA. Sepsis: pathophysiology and clinical management. BMJ 2016;353:i1585. [Crossref] [PubMed]
  25. Lee CW, Kou HW, Chou HS, et al. A combination of SOFA score and biomarkers gives a better prediction of septic AKI and in-hospital mortality in critically ill surgical patients: a pilot study. World J Emerg Surg 2018;13:41. [Crossref] [PubMed]
  26. Kjeldsen L, Johnsen AH, Sengelov H, et al. Isolation and primary structure of NGAL, a novel protein associated with human neutrophil gelatinase. J Biol Chem 1993;268:10425-32. [PubMed]
  27. Xu SY, Pauksen K, Venge P. Serum measurements of human neutrophil lipocalin (HNL) discriminate between acute bacterial and viral infections. Scand J Clin Lab Invest 1995;55:125-31. [Crossref] [PubMed]
  28. Martensson J, Martling CR, Bell M. Novel biomarkers of acute kidney injury and failure: clinical applicability. Br J Anaesth 2012;109:843-50. [Crossref] [PubMed]
  29. Hinkelbein J, Bohm L, Braunecker S, et al. Decreased Tissue COX5B Expression and Mitochondrial Dysfunction during Sepsis-Induced Kidney Injury in Rats. Oxid Med Cell Longev 2017;2017:8498510. [Crossref] [PubMed]
  30. Liu XW, Ma T, Cai Q, et al. Elevation of Serum PARK7 and IL-8 Levels Is Associated With Acute Lung Injury in Patients With Severe Sepsis/Septic Shock. J Intensive Care Med 2017.885066617709689. [PubMed]
  31. Terzi I, Papaioannou V, Papanas N, et al. Alpha1-microglobulin as an early biomarker of sepsis-associated acute kidney injury: a prospective cohort study. Hippokratia 2014;18:262-8. [PubMed]
  32. Nesseler N, Launey Y, Aninat C, et al. Clinical review: The liver in sepsis. Crit Care 2012;16:235. [Crossref] [PubMed]
  33. Jenniskens M, Langouche L, Vanwijngaerden YM, et al. Cholestatic liver (dys)function during sepsis and other critical illnesses. Intensive Care Med 2016;42:16-27. [Crossref] [PubMed]
  34. Savio LEB, de Andrade Mello P, Figliuolo VR, et al. CD39 limits P2X7 receptor inflammatory signaling and attenuates sepsis-induced liver injury. J Hepatol 2017;67:716-26. [Crossref] [PubMed]
  35. Chen WT, Lee MS, Chang CL, et al. Retinol-binding protein-4 expression marks the short-term mortality of critically ill patients with underlying liver disease: Lipid, but not glucose, matters. Sci Rep 2017;7:2881. [Crossref] [PubMed]
  36. Kaffarnik MF, Ahmadi N, Lock JF, et al. Correlation between plasma endothelin-1 levels and severity of septic liver failure quantified by maximal liver function capacity (LiMAx test). A prospective study. PLoS One 2017;12:e0178237. [Crossref] [PubMed]
  37. Buendgens L, Yagmur E, Bruensing J, et al. C-terminal proendothelin-1 (CT-proET-1) is associated with organ failure and predicts mortality in critically ill patients. J Intensive Care 2017;5:25. [Crossref] [PubMed]
  38. Peoc'h K, Nuzzo A, Guedj K, et al. Diagnosis biomarkers in acute intestinal ischemic injury: so close, yet so far. Clin Chem Lab Med 2018;56:373-85. [Crossref] [PubMed]
  39. Yeh LC, Huang PW, Hsieh KH, et al. Elevated Plasma Levels of Gas6 Are Associated with Acute Lung Injury in Patients with Severe Sepsis. Tohoku J Exp Med 2017;243:187-93. [Crossref] [PubMed]
  40. Wong HR, Lindsell CJ, Lahni P, et al. Interleukin 27 as a sepsis diagnostic biomarker in critically ill adults. Shock 2013;40:382-6. [Crossref] [PubMed]
  41. Barlam TF, Cosgrove SE, Abbo LM, et al. Executive Summary: Implementing an Antibiotic Stewardship Program: Guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. Clin Infect Dis 2016;62:1197-202. [Crossref] [PubMed]
  42. 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;16:819-27. [Crossref] [PubMed]
  43. Schuetz P, Wirz Y, Sager R, et al. Effect of procalcitonin-guided antibiotic treatment on mortality in acute respiratory infections: a patient level meta-analysis. Lancet Infect Dis 2018;18:95-107. [Crossref] [PubMed]
  44. Schuetz P, Wirz Y, Sager R, et al. Procalcitonin to initiate or discontinue antibiotics in acute respiratory tract infections. Cochrane Database Syst Rev 2017;10:CD007498. [PubMed]
  45. Ugarte H, Silva E, Mercan D, et al. Procalcitonin used as a marker of infection in the intensive care unit. Crit Care Med 1999;27:498-504. [Crossref] [PubMed]
  46. Suprin E, Camus C, Gacouin A, et al. Procalcitonin: a valuable indicator of infection in a medical ICU? Intensive Care Med 2000;26:1232-8. [Crossref] [PubMed]
  47. Bartoletti M, Antonelli M, Bruno Blasi FA, et al. Procalcitonin-guided antibiotic therapy: an expert consensus. Clin Chem Lab Med 2018;56:1223-9. [Crossref] [PubMed]
  48. Zilahi G, McMahon MA, Povoa P, et al. Duration of antibiotic therapy in the intensive care unit. J Thorac Dis 2016;8:3774-80. [Crossref] [PubMed]
  49. Kaziani K, Sotiriou A, Dimopoulos G. Duration of pneumonia therapy and the role of biomarkers. Curr Opin Infect Dis 2017;30:221-5. [Crossref] [PubMed]
  50. Putim C, Phaonakrop N, Jaresitthikunchai J, et al. Secretome profile analysis of multidrug-resistant, monodrug-resistant and drug-susceptible Mycobacterium tuberculosis. Arch Microbiol 2018;200:299-309. [Crossref] [PubMed]
  51. Yari S, Hadizadeh Tasbiti A, Ghanei M, et al. Proteome-scale MDR-TB-antibody responses for identification of putative biomarkers for the diagnosis of drug-resistant Mycobacterium tuberculosis. Int J Mycobacteriol 2016;5 Suppl 1:S134-S135. [Crossref] [PubMed]
  52. Hornischer K, Haussler S. Diagnostics and Resistance Profiling of Bacterial Pathogens. Curr Top Microbiol Immunol 2016;398:89-102. [Crossref] [PubMed]
  53. Karami N, Rezadoost H, Mirzajani F, et al. Resistant/susceptible classification of respiratory tract pathogenic bacteria based on volatile organic compounds profiling. Cell Mol Biol (Noisy-le-grand) 2018;64:6-15. [Crossref] [PubMed]
  54. Shepardson KM, Larson K, Morton RV, et al. Differential Type I Interferon Signaling Is a Master Regulator of Susceptibility to Postinfluenza Bacterial Superinfection. MBio 2016.7. [PubMed]
  55. Collaborators GBDCM. Global, regional, national, and selected subnational levels of stillbirths, neonatal, infant, and under-5 mortality, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 2016;388:1725-74. [Crossref] [PubMed]
  56. Stocker M, van Herk W, El Helou S, et al. Procalcitonin-guided decision making for duration of antibiotic therapy in neonates with suspected early-onset sepsis: a multicentre, randomised controlled trial (NeoPIns). Lancet 2017;390:871-81. [Crossref] [PubMed]
  57. Chauhan N, Tiwari S, Jain U. Potential biomarkers for effective screening of neonatal sepsis infections: An overview. Microb Pathog 2017;107:234-42. [Crossref] [PubMed]
  58. Bizzarro MJ, Raskind C, Baltimore RS, et al. Seventy-five years of neonatal sepsis at Yale: 1928-2003. Pediatrics 2005;116:595-602. [Crossref] [PubMed]
  59. Shah BA, Padbury JF. Neonatal sepsis: an old problem with new insights. Virulence 2014;5:170-8. [Crossref] [PubMed]
  60. Sharma D, Farahbakhsh N, Shastri S, et al. Biomarkers for diagnosis of neonatal sepsis: a literature review. J Matern Fetal Neonatal Med 2018;31:1646-59. [Crossref] [PubMed]
  61. Ruan L, Chen GY, Liu Z, et al. The combination of procalcitonin and C-reactive protein or presepsin alone improves the accuracy of diagnosis of neonatal sepsis: a meta-analysis and systematic review. Crit Care 2018;22:316. [Crossref] [PubMed]
  62. Chiesa C, Pellegrini G, Panero A, et al. C-reactive protein, interleukin-6, and procalcitonin in the immediate postnatal period: influence of illness severity, risk status, antenatal and perinatal complications, and infection. Clin Chem 2003;49:60-8. [Crossref] [PubMed]
  63. Assumma M, Signore F, Pacifico L, et al. Serum procalcitonin concentrations in term delivering mothers and their healthy offspring: a longitudinal study. Clin Chem 2000;46:1583-7. [PubMed]
doi: 10.21037/jeccm.2019.06.02
Cite this article as: Xu C, Li S, Wang Y, Zhang M, Zhou M. Biomarkers in intensive care unit infections, friend or foe? J Emerg Crit Care Med 2019;3:27.