This study investigated the time course of 15 cytokines, including both pro- and anti-inflammatory cytokines and chemokines, in a cohort of 40 patients who experienced severe trauma with regard to the incidence of septic complications within the initial 14 days after trauma. As expected, the levels of five cytokines, including IL-6, IL-10, sCD40L, GRO, and G-CSF, were significantly interactional between time and the presence of sepsis, which was indicated by a significantly steeper change in plasma levels in patients with sepsis as opposed to those without sepsis. This interaction suggests that, besides a cut-off value, the time-related kinetics of cytokine biomarkers has a crucial role in the preclinical identification of septic patients.
When combining these cytokines, the ROC curve analysis achieved even higher AUCs of up to 0.90 at day 3. On the one hand, the increase in accuracy was favorable; on the other hand, day 3 after trauma demonstrated a remarkable increase (by 5%) when combining these biomarkers. These data suggest that combining multiple cytokines might be advantageous, especially in the early phase after trauma. However, it is to be noted that standard ROC curve analysis represents a theoretical model, which does not account for time dependency of an event. This limitation of considering an event (i.e., sepsis) status for an individual as fixed over time is often encountered in biomarker studies and demands cautious data interpretation. Therefore, the event-related analysis as shown in Fig. 4 compensates for that and better reflects the predictive strength of a biomarker. Against this background, IL-6, IL-10, G-CSF, and FGF-2 have excellent predictive ability for septic progression.
The ultimate goal in sepsis biomarker research, however, is the development of a score that is useful for sepsis prediction, diagnosis, and risk stratification. With the availability of systems biology approaches, such a sepsis score may ideally comprise a combination of several biomarkers, including genomic, transcriptomic, proteomic, and metabolomic candidates, as well as clinical parameters. Examples of preliminary scores in different sepsis cohorts include the combination of clinical and transcriptomic markers, metabolic and protein-mediator profiling, or the combination of biomarkers with established clinical scores [7, 15, 16]. In our opinion, some cytokines are also very promising candidates to be included in a sepsis score in general and in particular for discrimination of septic complications in patients with underlying systemic inflammation as indicated by the results of the present study. Nevertheless, based on the experience of previous studies , the development of a multibiomarker score for predicting and diagnosing sepsis represents an intricate endeavor. The implementation of novel fields, such as bioinformatics, computational biology, and machine learning, into sepsis research might open up new possibilities to adequately reflect the complexity and dynamics of sepsis for development of a valid and reliable diagnostic tool in the future.
As early decision making with the initiation of therapy is key to survival, especially in trauma, inflammatory biomarkers are urgently needed, aiming at the preclinical detection of deterioration . In contrast, this patient population has some major methodological advantages in regard to testing novel biomarkers compared to other critically ill patients, making up for some key limitations of previous studies as follows: (A) Prophylactic administration of antibiotics, which is generally considered a major incommoding confounder in sepsis-related biomarker research, is strongly avoided in patients with blunt trauma injuries due to resistance breeding. (B) The trauma victim is mostly young to middle-aged with no or few comorbidities, thus greatly diminishing confounding effects. (C) The ICU stay of severe trauma victims is usually prolonged. Therefore, detailed monitoring and documentation of clinical and laboratory parameters are valuable prerequisites to retrospectively identify rapid changes in the conditions of patients. (D) Trauma victims are thought to be more susceptible to infectious complications than any other patient population, allowing for statistically balanced juxtaposition of septic versus nonseptic patients. (E) Trauma represents a rather homogenous entity with directly measurable trauma severity (i.e., ISS and AIS), which can simply be adjusted for statistical analyses.
Elucidating the role of cytokines in severe trauma patients with respect to the occurrence of sepsis, the present study represents a crucial step on the way to testing for potentially helpful biomarkers for early sepsis prediction and detection. In this context, the present study needs to be considered as hypothesis generating and awaiting confirmation in future clinical trials, since there are some limitations. Given the relatively small number of patients included and the single center design of our study, there is no external validation of our data, which has to be addressed in further studies. Likewise, measurement of biomarkers and assessment of clinical parameters were performed only once per 48 hours, neglecting potential alterations between these intervals. Moreover, the influence of the type of infection and of repetitive surgical tissue damage on cytokine serum levels need to be clarified in further studies. We believe that these findings will have implications for the management of patients with trauma.