Biomarkers of sepsis: lost in translation?

Use of biomarkers in pediatric sepsis: literature review

Despite advances in recent years, sepsis is still a leading cause of hospitalization and mortality in infants and children. The presence of biomarkers during the response to an infectious insult makes it possible to use such biomarkers in screening, diagnosis, prognosis (risk stratification), monitoring of therapeutic response, and rational use of antibiotics (for example, the determination of adequate treatment length). Studies of biomarkers in sepsis in children are still relatively scarce. This review addresses the use of biomarkers in sepsis in pediatric patients with emphasis on C-reactive protein, procalcitonin, interleukins 6, 8, and 18, human neutrophil gelatinase, and proadrenomedullin. Assessment of these biomarkers may be useful in the management of pediatric sepsis.

Prognostic utility and characterization of cell-free DNA in patients with severe sepsis

Introduction

Although sepsis is the leading cause of death in noncoronary critically ill patients, identification of patients at high risk of death remains a challenge. In this study, we examined the incremental usefulness of adding multiple biomarkers to clinical scoring systems for predicting intensive care unit (ICU) mortality in patients with severe sepsis.

Methods

This retrospective observational study used stored plasma samples obtained from 80 severe sepsis patients recruited at three tertiary hospital ICUs in Hamilton, Ontario, Canada. Clinical data and plasma samples were obtained at study inclusion for all 80 patients, and then daily for 1 week, and weekly thereafter for a subset of 50 patients. Plasma levels of cell-free DNA (cfDNA), interleukin 6 (IL-6), thrombin, and protein C were measured and compared with clinical characteristics, including the primary outcome of ICU mortality and morbidity measured with the Multiple Organ Dysfunction (MODS) score and Acute Physiology and Chronic Health Evaluation (APACHE) II scores.

Results

The level of cfDNA in plasma at study inclusion had better prognostic utility than did MODS or APACHE II scores, or the biomarkers measured. The area under the receiver operating characteristic (ROC) curves for cfDNA to predict ICU mortality is 0.97 (95% CI, 0.93 to 1.00) and to predict hospital mortality is 0.84 (95% CI, 0.75 to 0.94). We found that a cfDNA cutoff value of 2.35 ng/μl had a sensitivity of 87.9% and specificity of 93.5% for predicting ICU mortality. Sequential measurements of cfDNA suggested that ICU mortality may be predicted within 24 hours of study inclusion, and that the predictive power of cfDNA may be enhanced by combining it with protein C levels or MODS scores. DNA-sequence analyses and studies with Toll-like receptor 9 (TLR9) reporter cells suggests that the cfDNA from sepsis patients is host derived.

Conclusions

These studies suggest that cfDNA provides high prognostic accuracy in patients with severe sepsis. The serial data suggest that the combination of cfDNA with protein C and MODS scores may yield even stronger predictive power. Incorporation of cfDNA in sepsis risk-stratification systems may be valuable for clinical decision making or for inclusion into sepsis trials.

Computational approaches for translational clinical research in disease progression

Today, there is an ever-increasing amount of biological and clinical data available that could be used to enhance a systems-based understanding of disease progression through innovative computational analysis. In this article, we review a selection of published research regarding computational methods, primarily from systems biology, which support translational research from the molecular level to the bedside, with a focus on applications in trauma and critical care. Trauma is the leading cause of mortality in Americans younger than 45 years, and its rapid progression offers both opportunities and challenges for computational analysis of trends in molecular patterns associated with outcomes and therapeutic interventions.This review presents methods and domain-specific examples that may inspire the development of new algorithms and computational methods that use both molecular and clinical data for diagnosis, prognosis, and therapy in disease progression.

Microalbuminuria: A novel biomarker of sepsis

CONTEXT

Diffused endothelial dysfunction in sepsis leads to an increase in systemic capillary permeability, the renal component manifesting as microalbuminuria. The degree of microalbuminuria correlates with the severity of the acute insult, the quantification of which may serve to predict sepsis and mortality in critically ill patients.

AIMS

To evaluate whether the degree of microalbuminuria could differentiate patients with sepsis from those without and predict mortality in critically ill patients.

SETTINGS AND DESIGN

Prospective, non-interventional study in a 20-bed Intensive Care Unit (ICU) of a tertiary care hospital.

METHODS AND MATERIALS

After exclusions, between Jan-May 2007, 94 consecutive adult patients were found eligible. Albumin-creatinine ratio (ACR, mg/g) was measured in urine samples collected on ICU admission (ACR1) and at 24 hours (ACR2).

RESULTS

PATIENTS WERE CLASSIFIED INTO TWO GROUPS: those with sepsis, severe sepsis and septic shock (n = 30) and those without sepsis [patients without systemic inflammatory response syndrome (SIRS) and with SIRS due to noninfectious causes] (n = 64). In the sepsis group, median ACR1 [206.5 (IQR129.7-506.1)] was significantly higher compared to the non sepsis group [76.4 (IQR29-167.1)] (P = 0.0016, Mann Whitney). The receiver operating characteristics (ROC) curve analysis showed that at a cut off value 124 mg/g, ACR1 may be able to discriminate between patients with and without sepsis with a sensitivity of 80%, specificity of 64.1%, positive predictive value (PPV) of 51.1% and negative predictive value (NPV) of 87.3%. The median ACR2 [154 (IQR114.4-395.3)] was significantly higher (P = 0.004) in nonsurvivors (n = 13) as compared to survivors [50.8 (IQR 21.6-144.7)]. The ROC curve analysis revealed that ACR2 at a cut-off of 99.6 mg/g could predict ICU mortality with sensitivity of 85%, specificity of 68% with a NPV of 97% and PPV of 30%.

CONCLUSION

Absence of significant microalbuminuria on ICU admission is unlikely to be associated with sepsis. At 24 hours, absence of elevated levels of microalbuminuria is strongly predictive of ICU survival, equivalent to the time-tested APACHE II scores.

Established and novel biomarkers of sepsis

The increased incidence of sepsis, a systemic response to infection that occurs in some patients, has stimulated interest in identifying infected patients who are at risk and intervening early. When this condition progresses to severe sepsis (characterized by organ dysfunction), mortality is high. Hospitals that have implemented recommendations of the Surviving Sepsis Campaign have seen a reduction in mortality rate for hospital-acquired severe sepsis. They may reduce this further by focusing on new approaches to diagnosing sepsis, especially at an early stage. Sepsis is a complicated syndrome with many physiological derangements and many emerging laboratory markers of sepsis have been proposed as adjuncts to clinical evaluation. The list includes cytokines, acute phase proteins, neutrophil activation markers, markers of abnormal coagulation and, recently, markers of suppression of both the innate and adaptive immune response. The perfect biomarker would accurately identify patients at risk of developing severe sepsis and then guide targeted therapy.

Systems engineering medicine: engineering the inflammation response to infectious and traumatic challenges

The complexity of the systemic inflammatory response and the lack of a treatment breakthrough in the treatment of pathogenic infection demand that advanced tools be brought to bear in the treatment of severe sepsis and trauma. Systems medicine, the translational science counterpart to basic science's systems biology, is the interface at which these tools may be constructed. Rapid initial strides in improving sepsis treatment are possible through the use of phenomenological modelling and optimization tools for process understanding and device design. Higher impact, and more generalizable, treatment designs are based on mechanistic understanding developed through the use of physiologically based models, characterization of population variability, and the use of control-theoretic systems engineering concepts. In this review we introduce acute inflammation and sepsis as an example of just one area that is currently underserved by the systems medicine community, and, therefore, an area in which contributions of all types can be made.

Serum lipopolysaccharide binding protein levels predict severity of lung injury and mortality in patients with severe sepsis

Background

There is a need for biomarkers insuring identification of septic patients at high-risk for death. We performed a prospective, multicenter, observational study to investigate the time-course of lipopolysaccharide binding protein (LBP) serum levels in patients with severe sepsis and examined whether serial serum levels of LBP could be used as a marker of outcome.

Methodology/Principal Findings

LBP serum levels at study entry, at 48 hours and at day-7 were measured in 180 patients with severe sepsis. Data regarding the nature of infections, disease severity, development of acute lung injury (ALI) and acute respiratory distress syndrome (ARDS), and intensive care unit (ICU) outcome were recorded. LBP serum levels were similar in survivors and non-survivors at study entry (117.4±75.7 µg/mL vs. 129.8±71.3 µg/mL, P = 0.249) but there were significant differences at 48 hours (77.2±57.0 vs. 121.2±73.4 µg/mL, P<0.0001) and at day-7 (64.7±45.8 vs. 89.7±61.1 µg/ml, p = 0.017). At 48 hours, LBP levels were significantly higher in ARDS patients than in ALI patients (112.5±71.8 µg/ml vs. 76.6±55.9 µg/ml, P = 0.0001). An increase of LBP levels at 48 hours was associated with higher mortality (odds ratio 3.97; 95%CI: 1.84–8.56; P<0.001).

Conclusions/Significance

Serial LBP serum measurements may offer a clinically useful biomarker for identification of patients with severe sepsis having the worst outcomes and the highest probability of developing sepsis-induced ARDS.