Daily Sepsis Research Analysis
Analyzed 46 papers and selected 3 impactful papers.
Summary
Three studies advance sepsis science and practice: a prospective multicenter cohort distinguishes bacterial from viral sepsis using inflammatory profiles and organ dysfunction patterns; a 5-year hospital-wide quality improvement initiative markedly improved blood culture procurement and reduced contamination; and an explainable AI–enhanced GWAS identifies genetic susceptibility loci for post-operative sepsis, outlining mechanistic pathways.
Research Themes
- Diagnostic stewardship and blood culture quality in sepsis
- Phenotyping bacterial versus viral sepsis
- Genomic susceptibility and explainable AI in sepsis
Selected Articles
1. Differences in the Phenotype of Bacterial and Viral Sepsis-A Prospective, Multicenter, Observational Study.
In a four-ICU prospective cohort (n=90), bacterial sepsis showed higher admission and 48 h peak IL-6 and PCT, with bacterial etiology independently predicting higher cytokine peaks. Viral sepsis more commonly fulfilled SEPSIS-3 via respiratory and cardiovascular SOFA components with fewer other organ dysfunctions. These phenotypic differences can support etiologic differentiation and stewardship.
Impact: Prospective multicenter data delineate clinically actionable differences between bacterial and viral sepsis, informing early diagnostics and antimicrobial stewardship.
Clinical Implications: Use IL-6 and PCT dynamics plus organ dysfunction patterns to prioritize bacterial versus viral etiologies, guiding antibiotic initiation and escalation and supporting de-escalation in likely viral sepsis.
Key Findings
- Prospective cohort across four ICUs enrolled 90 adults: 57 bacterial, 33 viral sepsis.
- Admission and 48 h peak IL-6 and PCT were significantly higher in bacterial sepsis; bacterial etiology independently predicted higher cytokine peaks.
- Viral sepsis met SEPSIS-3 primarily via respiratory and cardiovascular SOFA components, with fewer other organ dysfunctions.
Methodological Strengths
- Prospective multicenter cohort design with SEPSIS-3 criteria and exclusion of recent immunocompromise.
- Adjusted linear regression to identify independent predictors of cytokine peaks.
Limitations
- Moderate sample size (n=90) may limit precision and subgroup analyses.
- Observational design cannot establish causality; external generalizability beyond Austrian ICUs is uncertain.
Future Directions: Validate biomarker thresholds and decision algorithms in larger, international cohorts and test stewardship interventions leveraging bacterial–viral phenotyping.
Sepsis is defined as a dysregulated host response to an infection, leading to life-threatening organ dysfunction. While sepsis is most commonly the result of a bacterial infection, it may also be caused by viral pathogens. The aim of this study was to describe differences in organ dysfunction patterns and inflammatory markers between bacterial and viral sepsis. In this prospective multicenter cohort study, adults meeting SEPSIS-3 criteria were recruited from four Austrian ICUs between 1 August 2021 and 1 April 2024, excluding those who were immunocompromised within the preceding 12 months. Ninety patients were enrolled, of whom 57 had bacterial and 33 viral sepsis. Inflammatory markers, including IL-6 and PCT, were higher at ICU admission in bacterial sepsis.
2. Improving blood culture procurement: a prospective 5-year hospital-wide study.
A hospital-wide quality improvement program combining real-time departmental feedback and targeted education increased two-set blood culture collection from 27% to 46% and reduced contamination from 2.4% to 1.3% over five years, with particularly strong gains in the ED. Simple, scalable interventions enhanced diagnostic stewardship for bacteremia and sepsis.
Impact: Demonstrates measurable, sustained system-level improvements in two core blood culture quality metrics that directly affect sepsis diagnosis and antimicrobial use.
Clinical Implications: Adopting real-time feedback plus brief education can reduce false positives and improve diagnostic yield, enabling faster etiologic confirmation and better antibiotic stewardship in sepsis pathways.
Key Findings
- Two-set blood culture collection increased from 27% (2020) to 46% (2024) overall (IRR 1.16, 95% CI 1.13–1.18; p<0.001).
- Emergency department two-set collection rose from 19% to 53% (IRR 1.33, 95% CI 1.27–1.39; p<0.001).
- False-positive (contaminant-only) cultures decreased from 2.4% to 1.3% overall (IRR 0.82, 95% CI 0.77–0.88; p<0.001); ED from 3.3% to 1.56% (IRR 0.79, 95% CI 0.75–0.83).
Methodological Strengths
- Prospective hospital-wide monitoring with frequent feedback and standardized metrics over five years.
- Use of incidence rate ratios with confidence intervals and department-level benchmarking.
Limitations
- Single-center, nonrandomized quality improvement design; potential secular trends and co-interventions cannot be excluded.
- Outcomes limited to process measures (two-set rate, contamination); patient-centered outcomes were not reported.
Future Directions: Implement interrupted time series or stepped-wedge designs across multiple hospitals to quantify causal effects and link process improvements to clinical outcomes (time to appropriate therapy, mortality).
BACKGROUND: Appropriate procurement of blood cultures (BC) is essential for diagnosis of bacteremia and susceptibility testing. This includes (1) adequate preparation of the venipuncture site to minimize contamination; (2) obtaining ≥ two sets with a time interval before starting antibiotics. Although these recommendations are standard since the 1960s, adherence is far less than expected - which may adversely impact on the management of bacteremic patients. AIMS OF STUDY: This single-center study conducted in Shaare Zedek Medical Center aimed to decrease the proportion of contaminated BCs and to increase the percentage of obtaining two sets of BC/ blood-culture-taking episode. METHODS: Determination of both markers at baseline, then monthly for one year, then subsequently on a quarterly basis; showing data from all departments in real-time to all department directors; and providing short educative lectures during departmental staff meetings, at baseline and after 1-2 years. These markers were adopted as one of the hospital-wide quality measures. RESULTS: In the 20-year period 2000-2019 more than 1 million BCs were obtained, of which 70% were from patients ≤ 72 h in hospital. During the 5-year study (2020-2024), the percent of blood-culture-taking episodes from which two culture sets were obtained increased annually by ± 16% from a baseline of 27% (9010/33306) in 2020, to 46% (18462/40191) in 2024 (Incidence Rate Ratios, IRR 1.16 [95%CI 1.13-1.18], p < 0.001). This improvement was observed in almost all departments and was especially profound in the emergency department (ED), starting at a baseline of 19% (1979/10326) and increasing to 53% (5304/9915)(IRR 1.33 [95%CI 1.27-1.39], p < 0.001). During the same period, the annual proportion of false-positive BCs, from which only contaminants were isolated, decreased annually by 18% from 2.4% (1592/65230) in 2020 to 1.3% (895/68991) in 2024 (IRR 0.82 [95%CI 0.77-0.88], p < 0.001). This improvement was observed in all departments: in the emergency department, this rate decreased from 3.3% (676/20529) to 1.56% (272/17459) (IRR 0.79 [95%CI 0.75-0.83], p < 0.001). CONCLUSION: A simple educational intervention, combined with meticulous data mining and presentation of each department's results, with comparison of all other departments, led to significant and sustained improvement in measurable markers.
3. Identifying sepsis susceptibility genes in post-surgical patients using an artificial intelligence approach.
Using an explainable AI framework on GWAS data from 750 post-surgical sepsis cases and 3,500 controls, the authors prioritized predictive SNPs (e.g., rs17653532, rs1575081785, rs74707084) and implicated pathways in gene regulation, DNA replication, cyclic nucleotide signaling, proliferation, and cardiac dysfunction. The XAI-GWAS approach improved interpretability and highlighted biologically plausible risk loci.
Impact: Introduces an interpretable AI pipeline that enhances discovery of genetic susceptibility to post-operative sepsis and connects loci to mechanistic pathways.
Clinical Implications: While not yet ready for clinical deployment, prioritized loci and pathways offer targets for risk stratification, biomarker development, and potential preventive strategies in surgical patients.
Key Findings
- GWAS of 750 post-surgical sepsis cases and 3,500 controls analyzed with an explainable AI methodology.
- Prioritized SNPs including rs17653532, rs1575081785, and rs74707084 contributed strongly to sepsis prediction.
- Functional enrichment linked risk loci to gene expression regulation, DNA replication, cyclic nucleotide signaling, cell proliferation, and cardiac dysfunction.
Methodological Strengths
- Large case-control GWAS focused on a clinically homogeneous subgroup (post-surgical sepsis).
- Explainable AI for feature prioritization with downstream functional and enrichment analyses.
Limitations
- Lack of external replication/validation cohorts limits generalizability.
- Potential residual confounding and population stratification inherent to GWAS; effect sizes and clinical risk models were not reported.
Future Directions: Replicate prioritized loci across diverse surgical populations, integrate polygenic scores with clinical predictors, and pursue functional validation of top variants.
BACKGROUND: Early detection of sepsis is essential for its successful management. Although genome-wide association studies (GWAS) have shown potential in identifying sepsis-related genetic variants, they often involve heterogeneous patient groups and use single-locus analysis methods. Here, we aim to identify new sepsis susceptibility loci in post-surgical patients using an explainable artificial intelligence (XAI) approach applied to GWAS data. METHODS: GWAS was performed in 750 post-operative patients with sepsis and 3,500 population controls. We applied a novel XAI-based methodology to GWAS-derived single nucleotide polymorphisms (SNPs) to predict sepsis and prioritize new genetic variants associated with post-operative sepsis susceptibility. We also assessed functional and enrichment effects using empirical data from integrated software tools and datasets, with the top-ranked variants and associated genes. RESULTS: Our XAI-GWAS approach showed a notable performance in predicting post-surgical sepsis and prioritized SNPs (such as rs17653532, rs1575081785, and rs74707084) with higher contribution to post-operative sepsis prediction. It also facilitated the discovery of post-operative sepsis risk loci with important functional implications related to gene expression regulation, DNA replication, cyclic nucleotide signaling, cell proliferation, and cardiac dysfunction. CONCLUSION: The combination of GWAS and XAI prioritized loci associated with post-operative sepsis susceptibility. The determination of key genes, such as