Introduction
Staphylococcus aureus is a leading cause of bacteremia with mortality rates of up to 30% [
1]. Risk factors for mortality in patients with
S. aureus bacteremia (SAB) include older age, endovascular source of infection, and presence of sepsis [
1]. In addition, in a large cohort study of nearly 900 patients with SAB, our group found that persistent bacteremia defined by positive blood cultures for 3 days or longer significantly predicted mortality and that each day of continued bacteremia increased risk of mortality by 16% [
2]. Despite receipt of antimicrobial therapy with apparent in vitro susceptibility for at least 72 h, one third of the patients with SAB continued to have growth of
S. aureus in the blood [
3].
We, and others, have shown that serum levels of immune biomarkers, including interferon-gamma (IFNγ), interleukin (IL-1β, IL-6, IL-8, IL-10, IL-17) and tissue necrosis factor (TNF), differentiate between patients with SAB who developed persistent bacteremia or died compared to those with prompt bacterial clearance and survived [
4‐
9]. Importantly, we have shown that a dysregulated host immune response, characterized by the predominance of anti-inflammatory over pro-inflammatory cytokine release during the early course of SAB significantly predicts persistence and 30-day mortality [
5,
8]. Thus, these immune biomarkers, in conjunction with clinical variables, could serve as a prognostic tool for clinicians to identify SAB patients who are more likely to have worse outcomes and to guide management, that may include empiric combination antibiotic therapy or adjunctive immunotherapy.
The threshold concentration for a specific cytokine that correlates with poor outcome of SAB is currently unknown. Further complicating the interpretation of cytokine measurements, our group has observed high interpatient variability in cytokine concentrations during SAB. For a given cytokine, measurements could vary > 1000 fold between patients. Given the heterogeneity between individuals, we calculated quartile values for a panel of cytokines measured on Day 1 and Day 4 of SAB and tested the predictability of clinical factors, with or without inclusion of each cytokine value in quartile, for bacterial persistence and 30-day mortality, respectively. We hypothesize that there is a set range of cytokine measurement that represents host immune response unique to a physiological insult (e.g. S. aureus bacteremia) and that the magnitude of response within that range represents a distinct immunophenotype predictive of outcome. Our aims in this study are to: 1) describe the predictive value of cytokine quartiles for duration of bacteremia and mortality in patients with SAB in conjunction with clinical variables and 2) define a concentration range for cytokine levels that could guide clinical decisions.
Methods
Study design/setting/patients
We conducted a prospective, observational study from July 2012 to July 2018 at three affiliated medical centers in Los Angeles County, CA. Hospitalized patients were included if they met the following criteria: age ≥ 18 years, had monomicrobial S. aureus growth from at least one blood culture, received at least 48 h of effective antibiotic therapy, and had blood cytokine measurements on either Day 1 and/or Day 4 of SAB. Day 1 was defined as the day of the first positive blood culture with S. aureus, and Day 4 was 72 h thereafter. Patients were excluded if blood cultures were polymicrobial, serum samples not available for cytokine analysis, medical records were incomplete or unavailable, or anti-staphylococcal therapy was either delayed (> 48 h) or less than 48 h of therapy was administered.
Clinical endpoints
Primary clinical endpoints were bacterial persistence and 30-day all-cause mortality. Bacterial persistence was defined as four or more consecutive days of positive blood cultures after initiation of anti-staphylococcal therapy [
5]. Mortality was assessed for up to 30-days after the first positive
S. aureus blood culture. Demographic data, including age, sex, and comorbid conditions, as well as antibiotic treatment details and receipt of chemotherapy or other immunosuppressive drugs were recorded. Microbiologic and laboratory results included culture and sensitivities, vital signs, complete blood cell count, comprehensive metabolic panel, and presence of sepsis or septic shock. Complicated bacteremia as defined by any one the following variables were documented: endocarditis, implanted prostheses, temperature of > 38.3 °C after 72 h of initiating effective therapy, and evidence of metastatic sites of infection. Time to procedure performed for source control was recorded. Pitt bacteremia score was calculated using the worst score within 48 h before or on the day of the first positive blood culture. qSOFA score was calculated based on three clinical variables worth 1 point each: systolic blood pressure ≤ 100 mmHg, respiratory rate ≥ 22 breaths/min, and Glasgow coma score < 15 or altered mental status noted by the treating physician [
10]. Source of bacteremia was divided relative to risk of mortality as previously defined [
11]: high (> 20%), intermediate (10–20%), and low (< 10%). Study data were collected and managed using REDCap electronic data capture tools hosted at University of Southern California [
12,
13].
Cytokine measurements
Convenience blood samples were obtained on Day 1 and/or Day 4 of SAB where available for cytokine analysis. Samples were centrifuged and stored at − 80 °C until further analyses. Cytokine concentrations (IFNγ, IL-1β, IL-6, IL-8, IL-10, IL-17, TNF) were measured in duplicates using Luminex multiplex assay (Millipore, Billerica, MA) per manufacturer’s instructions.
Data analyses
To explore the predictive value of cytokine levels, cytokines were categorized by quartile values. Descriptive analyses were performed by either Student t test or Mann-Whitney U test for continuous variables and Fisher’s exact or chi-square test for categorical variables. Based on their measured cytokine response, patients were grouped into their respective quartile group for each cytokine and Bonferroni correction was applied for Chi-square test on the comparisons between any two quartiles among the study groups.
Univariate logistic regression was performed to assess the association of clinical variables and cytokine quartiles with bacterial persistence and 30-day mortality. To develop the predictive models for persistence and mortality, variables from the univariate analysis with a p-value < 0.20 were included in subsequent multivariable model selection. Calculated cytokine quartiles were then added individually into the multivariable model with clinical variables only. For the bacterial persistence model, Day 1 cytokine quartiles were considered as potential early biomarkers predictive of prolonged duration of bacteremia. Day 4 cytokine quartiles were explored in the 30-day mortality model, where therapeutic management could be re-evaluated in patients failing to respond after 72 h of antimicrobial therapy. Subgroup analysis on patients with MRSA and MSSA bacteremia was performed and multivariable models were developed separately. Receiver operating characteristics (ROC) and area under the ROC curve (AUC) analyses were generated to compare the predictive performance of the clinical base models versus cytokine-added models. Statistical analyses were performed using GraphPad Prism version 8.4.2 (San Diego, CA, USA) and SAS software, version 9.4 (SAS Institute Inc., Cary, NC, USA.) was used for univariate and multivariate logistic regression modeling.
Discussion
Elevated cytokine measurements (e.g. IL-10) during
S. aureus bacteremia (SAB) have been shown to significantly predict poor clinical outcomes, including persistent infection [
4‐
6], all-cause mortality [
4‐
7,
9], and complicated SAB [
14], but the concentration range that defines an “elevated” measurement remains unclear. Here, we grouped the cytokine levels measured from a large cohort of patients with confirmed SAB into quartiles, then determined the predictive value of cytokine quartile groups, when combined with clinical variables, for bacterial persistence and mortality as the outcome endpoints using univariate and multivariable regression analysis. Our study found that the addition of either IL-10 or TNF quartile groups to clinical variables improved model prediction for both bacterial persistence and 30-day mortality.
Studies describing the association between cytokines and persistence in patients with SAB have used varying definitions to define bacterial persistence, ranging from 3 to 7 consecutive days of positive blood cultures [
4,
6]. Additionally, differences in blood sample collection times were noted across studies. We used the persistence definition of ≥4 days of consecutive
S. aureus blood cultures and found the ratio of IL-10/TNF levels measured on day 1 of SAB to be the most predictive [
5], whereas others who defined persistence as > 4 days reported IL-10 [
4] and IL-17A [
6] as a significant predictors. For the studies using a persistence definition of > 4 days, sample collection times differed between the studies and were collected at either Day 1 of SAB or within 2 days of empiric antibiotic initiation, respectively. Using a definition of ≥4 days, our current study identified IL-10 and TNF quartiles, but not IL-17A, measured on Day 1 to be the most predictive for persistent bacteremia. Interestingly, the source of SAB infection may also affect cytokine production. In a study that reported IL-17A as the most predictive marker for persistent bacteremia, baseline levels were also noted to be highest in patients with an endovascular source [
6]. In contrast, among those with a baseline cytokine measurement in our study population, only 18% had an endovascular source of infection while most had skin and skin structure infections which may explain why IL-17 was not found to be a significantly predictor in our cohort of SAB patients. Differences in sample collection time may have also contributed to variations in significant cytokines observed since different cytokines have varying peak times during the course of infection.
With respect to 30-day mortality, Day 1 IL-10 levels [
4] and Day 4 IL-10/TNF ratio [
5] were previously reported to be significant predictors, whereas IL-8 and CCL2 levels measured on Day 1–3 of empiric antibiotic therapy were associated with 90-day all-cause mortality [
6]. In this study, the strongest predictive model for 30-day mortality was one that included clinical variables with either IL-10 or TNF quartiles collected on Day 4 of SAB. Others have reported that complicated SAB is associated with significantly higher baseline IL-6 levels compared to uncomplicated bacteremia. Our study found the most predictive model for 30-day mortality is one that incorporates either IL-10 or TNF quartiles collected on Day 4 of SAB with clinical variables. It is also possible that IL-8 can be used to predict late deaths in patients with SAB, rather than deaths occurring within 30 days of bacteremia onset. Others also found that Day 1 IL-6 levels were significantly higher in patients with a complicated infection when compared to uncomplicated SAB [
14]. Here, we observed an association between IL-6 quartiles and mortality. While significant, IL-6 did not add to the predictive value of the model based on clinical variables alone. Taken together, it appears that outcome definitions (i.e. duration of bacteremia used to define persistence), the source of bacteremia, and the timing of sample collection may impact which cytokines are predictive of outcome.
While the association between cytokines and bacterial persistence or mortality have been previously described, the actual cutoff value used to discriminate between patients with SAB at risk for poor outcomes is unclear. It is worth noting that a “normal” level defined by reference laboratories is typically based on data obtained from healthy volunteers. In a study that collected serial samples from patients meeting sepsis-3 criteria until discharge [
15], differences in cytokine measurements on Day 1 of sepsis were seen, where IL-1β, IL-10, IL-6, and IL-8 levels were among six cytokines found to be significantly elevated compared to controls. Beyond Day 1 of sepsis, both IL-6 and IL-8 remained significantly higher than controls. Other cytokine biomarkers, including IFNγ, IL-17A, TNF, were also evaluated but no differences were noted between study groups. Thus, an elevated cytokine measurement above the normal range is consistent with an active infectious disease process but does not differentiate between those who are at risk for poor outcome in patients with sepsis due to all causes.
Bacterial infections caused by gram negative compared to gram positive bacteria appear to elicit different cytokine responses [
16]. Accordingly, infection-specific cytokine breakpoints will be important for identifying patients at high risk for poor outcomes. In this study focusing on patients with
S. aureus bacteremia, we found IL-10 and TNF quartile groups to be the most predictive for persistence and 30-day mortality in patients with SAB. High interpatient variability in cytokine response was observed among patients with levels ranging from 1.36 to 2335.45 pg/ml for TNF and 0.07 to 2836.60 pg/ml for IL-10 on Day 1 of SAB. We therefore grouped cytokine measurements on Day 1 and Day 4 into Quartiles for comparison between those with persistent bacteremia vs prompt clearance and between those who died vs survived. Specifically, cytokine levels that fell within the ranges for Quartile 1 and Quartile 4 respectively on Day 1 of SAB were: IL-10 (< 11.11 pg/ml; > 118.22 pg/ml), TNF (< 9.54 pg/ml; > 36.85 pg/ml). The findings from our study highlights the need to identify the cytokine concentration range specific to the patient population with the disease of interest when used as a prognostic marker to predict outcomes. Importantly, we have shown the enhanced predictive value of cytokine measurements grouped in quartiles (e.g. IL-10 and/or TNF) when considered together with clinical variables in identifying patients with SAB at risk for persistence and mortality. Our subgroup analysis comparing MSSA vs MRSA bacteremia confirmed the enhanced predictive value observed above for the overall study population upon addition of either IL10 or TNF to the models, though the predictive value for the MRSA subgroup for persistence did not change with addition of Day 1 cytokine levels likely due to the limited sample size.
Notably, we observed a correlation with empiric vancomycin and beta-lactam combination therapy against development of persistent bacteremia. Others have shown that the combination of vancomycin and a beta-lactam agent to possess synergistic activity against
S. aureus in vitro [
17‐
19] and to reduce time to bacterial clearance in MRSA bacteremia [
20,
21]. However, in a subset of patients, combination therapy has been associated with an increased risk of acute kidney injury and has no clear association with reduction in mortality [
22]. Our findings could have practical applications in the management of patients with SAB. Measurement of either IL-10 or TNF at onset along with clinical risk factors may potentially help identify patients at risk for developing persistence and thus aid clinicians in deciding whether or not to initiate combination vancomycin and beta-lactam therapy empirically. Additionally, a measured level of either IL-10 or TNF in Quartile 4 identifies those at risk for death which provides a quantitative marker that together with clinical indicators could help prompt clinicians to re-evaluate management of SAB and source control measures as appropriate. Importantly, persistent growth of
S. aureus in the blood may reflect a state of immunoparalysis that hinders bacterial clearance [
23]. A quantitative biomarker measurement that is predictive of mortality can aid in the design of future biomarker-informed clinical trials to test the therapeutic benefit of adjunctive immune activating therapy that could potentially correct the underlying dysregulated host immune response.
This study has several limitations. First, we analyzed a limited cytokine panel. Other groups have identified additional cytokines and proteins, such as IL-1RN and CCL2, and found a significant association with persistent SAB and mortality. Our current study has expanded the panel of cytokines to include IFNγ and IL-1β. While it is possible that other biomarkers not included in this current study could also serve as prognostic markers, IL-10 and TNF have consistently been found to be significant predictors of outcome in patients with SAB. Second, despite over 600 patients had at least one cytokine measurement, only a subset of patients (n = 241) with persistent bacteremia had Day 1 cytokine measurements. Additionally, while the overall mortality is low in our study population, we have shown strong predictive value in this study for persistence and mortality when cytokine measurements are considered along with clinical variables. Future studies involving patients with different source of S. aureus bacteremia associated with high risk of death should be performed to confirm our findings. Finally, given that the majority of infections were caused by methicillin-susceptible S. aureus and that worse outcome is associated with bacteremia due to MRSA compared to MSSA, future studies exploring how methicillin resistance might affect cytokine response leading to different outcomes is of interest.
In conclusion, our observational study of a large cohort of over 600 patients with S. aureus bacteremia who had cytokine measurements enable us to identify the specific cytokines and define the respective concentration ranges measured at onset and Day 4 of bacteremia that are strongly predictive of bacterial persistence and 30-day mortality.
The re-defined “abnormal” range for IL-10 and TNF serum concentrations during S. aureus bacteremia differs greatly from that published by laboratory references which were derived from concentrations measured in healthy volunteers. Pending confirmation from future biomarker-informed studies, these quantitative immune biomarker measurements early during the course of infection could potentially help clinicians to better identify patients who would benefit from empiric combination antibiotic therapy or aggressive management that may include adjunctive immunomodulatory therapy.
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