Patient Characteristics, Management, and Predictors of Outcome from Severe Community-Onset Staphylococcal Sepsis in Northeast Thailand: A Prospective Multicenter Study

A Prognostic Model of Persistent Bacteremia and Mortality in Complicated Staphylococcus aureus Bloodstream Infection

BACKGROUND

Staphylococcus aureus is a leading cause of bacteremia, yet there remains a significant knowledge gap in the identification of relevant biomarkers that predict clinical outcomes. Heterogeneity in the host response to invasive S. aureus infection suggests that specific biomarker signatures could be utilized to differentiate patients prone to severe disease, thereby facilitating earlier implementation of more aggressive therapies.

METHODS

To further elucidate the inflammatory correlates of poor clinical outcomes in patients with S. aureus bacteremia, we evaluated the association between a panel of blood proteins at initial presentation of bacteremia and disease severity outcomes using 2 cohorts of patients with S. aureus bacteremia (n = 32 and n = 124).

RESULTS

We identified 13 candidate proteins that were correlated with mortality and persistent bacteremia. Prognostic modeling identified interleukin (IL)-8 and CCL2 as the strongest individual predictors of mortality, with the combination of these biomarkers classifying fatal outcome with 89% sensitivity and 77% specificity (P < .0001). Baseline IL-17A levels were elevated in patients with persistent bacteremia (P < .0001), endovascular (P = .026) and metastatic tissue infections (P = .012).

CONCLUSIONS

These results demonstrate the potential utility of selected biomarkers to distinguish patients with the highest risk for treatment failure and bacteremia-related complications, providing a valuable tool for clinicians in the management of S. aureus bacteremia. Additionally, these biomarkers could identify patients with the greatest potential to benefit from novel therapies in clinical trials.

Risk stratification biomarkers for Staphylococcus aureus bacteraemia

Objectives

To identify risk stratification biomarkers to enrich for the subset of Staphylococcus aureus bacteraemia patients who develop deep‐seated tissue infections with high morbidity and mortality to guide clinical trial enrolment and clinical management.

Methods

We evaluated the prognostic value of eight biomarkers for persistent bacteraemia, mortality and endovascular infection foci in a validation cohort of 160 patients with S. aureus bacteraemia enrolled consecutively over 3 years.

Results

High levels of IL‐17A, IL‐10 or soluble E‐selectin at bacteraemia diagnosis correlated with the duration of positive blood cultures. When thresholds defined in an independent cohort were applied, these biomarkers were robust predictors of persistent bacteraemia or endovascular infection. High serum levels of IL‐17A and IL‐10 often preceded the radiographic diagnosis of infective endocarditis, suggesting potential utility for prioritising diagnostic radiographic imaging. High IL‐8 was prognostic for all‐cause mortality, while IL‐17A and IL‐10 were superior to clinical metrics in discriminating between attributable mortality and non‐attributable mortality. High IL‐17A and IL‐10 identified more patients who developed microbiological failure or mortality than were identified by infective endocarditis diagnosis.

Conclusion

These biomarkers offer potential utility to identify patients at risk of persistent bacteraemia to guide diagnostic imaging and clinical management. Low biomarker levels could be used to rule out the need for more invasive TEE imaging in patients at lower risk of infective endocarditis. These biomarkers could enable clinical trials by enriching for patients with the greatest need for novel therapies.

Host-Based Prognostic Biomarkers to Improve Risk Stratification and Outcome of Febrile Children in Low- and Middle-Income Countries

Fever is one of the leading causes for pediatric medical consultation and the most common symptom at clinical presentation in low- and middle-income countries (LMICs). Most febrile episodes are due to self-limited infections, but a small proportion of children will develop life-threatening infections. The early recognition of children who have or are progressing to a critical illness among all febrile cases is challenging, and there are currently no objective and quantitative tools to do so. This results in increased morbidity and mortality among children with impending life-threatening infections, whilst contributing to the unnecessary prescription of antibiotics, overwhelming health care facilities, and harm to patients receiving avoidable antimicrobial treatment. Specific fever origin is difficult to ascertain and co-infections in LMICs are common. However, many severe infections share common pathways of host injury irrespective of etiology, including immune and endothelial activation that contribute to the pathobiology of sepsis (i.e., pathogen "agnostic" mechanisms of disease). Importantly, mediators of these pathways are independent markers of disease severity and outcome. We propose that measuring circulating levels of these factors can provide quantitative and objective evidence to: enable early recognition of severe infection; guide patient triage and management; enhance post-discharge risk stratification and follow up; and mitigate potential gender bias in clinical decisions. Here, we review the clinical and biological evidence supporting the clinical utility of host immune and endothelial activation biomarkers as components of novel rapid triage tests, and discuss the challenges and needs for developing and implementing such tools.

A nomogram for predicting the risk of sepsis in patients with acute cholangitis

OBJECTIVE

Sepsis is a serious complication of acute cholangitis. We aimed to establish a nomogram for predicting the probability of sepsis in patients with acute cholangitis.

METHODS

Subjects were patients with acute cholangitis in the Medical Information Mart for Intensive Care database. Extraneous variables were excluded based on stepwise regression. The nomogram was established using logistic regression.

RESULTS

The predictive model comprised five variables: age (odds ratio [OR]: 1.03, 95% confidence interval [CI]: 1.01–1.04), ventilator-support time (OR: 1.004, 95% CI: 1.001–1.008), diabetes (OR: 10.74, 95% CI: 2.80–70.57), coagulopathy (OR: 2.92, 95% CI: 1.83–4.73) and systolic blood pressure (OR: 0.62, 95% CI: 0.41–0.93). The areas under the receiver operating characteristic curve of the nomogram for the training and validation sets were 0.700 and 0.647, respectively. The Hosmer–Lemeshow goodness-of-fit test revealed high concordance between the predicted and observed probabilities for both the training and validation sets. The calibration plot also demonstrated good agreement between the predicted and observed outcomes for both the training and validation sets.

CONCLUSIONS

We developed and validated a risk-prediction model for sepsis in patients with acute cholangitis. Our results will be helpful for preventing sepsis in patients with acute cholangitis.

Predictive Validity of the qSOFA Score for Sepsis in Adults with Community-Onset Staphylococcal Infection in Thailand

The quick sequential organ failure assessment (qSOFA) score has had limited validation in lower resource settings and was developed using data from high-income countries. We sought to evaluate the predictive validity of the qSOFA score for sepsis within a low- and middle-income country (LMIC) population with culture-proven staphylococcal infection. This was a secondary analysis of a prospective multicenter cohort in Thailand with culture-positive infection due to Staphylococcus aureus or S. argenteus within 24 h of admission and positive (≥2/4) systemic inflammatory response syndrome (SIRS) criteria. Primary exposure was maximum qSOFA score within 48 h of culture collection and primary outcome was mortality at 28 days. Baseline risk of mortality was determined using a multivariable logistic regression model with age, gender, and co-morbidities significantly associated with the outcome. Predictive validity was assessed by discrimination of mortality using area under the receiver operating characteristic (AUROC) curve compared to a model using baseline risk factors alone. Of 253 patients (mean age 54 years (SD 16)) included in the analysis, 23 (9.1%) died by 28 days after enrollment. Of those who died, 0 (0%) had a qSOFA score of 0, 8 (35%) had a score of 1, and 15 (65%) had a score ≥2. The AUROC of qSOFA plus baseline risk was significantly greater than for the baseline risk model alone (AUROC_qSOFA = 0.80 (95% CI, 0.70–0.89), AUROC_baseline = 0.62 (95% CI, 0.49–0.75); p < 0.001). Among adults admitted to four Thai hospitals with community-onset coagulase-positive staphylococcal infection and SIRS, the qSOFA score had good predictive validity for sepsis.

Identification of Potential Transcriptional Biomarkers Differently Expressed in Both S. aureus- and E. coli-Induced Sepsis via Integrated Analysis

Sepsis is a critical, complex medical condition, and the major causative pathogens of sepsis are both Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). Genome-wide studies identify differentially expressed genes for sepsis. However, the results for the identification of DEGs are inconsistent or discrepant among different studies because of heterogeneity of specimen sources, various data processing methods, or different backgrounds of the samples. To identify potential transcriptional biomarkers that are differently expressed in S. aureus- and E. coli-induced sepsis, we have analyzed four microarray datasets from GEO database and integrated results with bioinformatics tools. 42 and 54 DEGs were identified in both S. aureus and E. coli samples from any three different arrays, respectively. Hierarchical clustering revealed dramatic differences between control and sepsis samples. GO functional annotations suggested that DEGs in the S. aureus group were mainly involved in the responses of both defense and immune regulation, but DEGs in the E. coli group were mainly related to the regulation of endopeptidase activity involved in the apoptotic signaling pathway. Although KEGG showed inflammatory bowel disease in the E. coli group, the KEGG pathway analysis showed that these DEGs were mainly involved in the tumor necrosis factor signaling pathway, fructose metabolism, and mannose metabolism in both S. aureus- and E. coli-induced sepsis. Eight common genes were identified between sepsis patients with either S. aureus or E. coli infection and controls in this study. All the candidate genes were further validated to be differentially expressed by an ex-vivo human blood model, and the relative expression of these genes was performed by qPCR. The qPCR results suggest that GK and PFKFB3 might contribute to the progression of S. aureus-induced sepsis, and CEACAM1, TNFAIP6, PSTPIP2, SOCS3, and IL18RAP might be closely linked with E. coli-induced sepsis. These results provide new viewpoints for the pathogenesis of both sepsis and pathogen identification.