Daily Sepsis Research Analysis
Three impactful sepsis studies span mechanistic immunology, antibiotic stewardship, and AI-enabled diagnostics. A preclinical study identifies neutrophil-mediated trogocytosis of B-1a cells as a therapeutic target to attenuate sepsis-induced acute lung injury, while a large real-world cohort supports narrow-spectrum β-lactam plus gentamicin as safe empiric therapy. Separately, a machine-learning model using triage data accurately predicts bacteremia in febrile ED patients.
Summary
Three impactful sepsis studies span mechanistic immunology, antibiotic stewardship, and AI-enabled diagnostics. A preclinical study identifies neutrophil-mediated trogocytosis of B-1a cells as a therapeutic target to attenuate sepsis-induced acute lung injury, while a large real-world cohort supports narrow-spectrum β-lactam plus gentamicin as safe empiric therapy. Separately, a machine-learning model using triage data accurately predicts bacteremia in febrile ED patients.
Research Themes
- Immunomodulation and pathophysiology of sepsis-induced organ injury
- Antibiotic stewardship in empiric therapy for suspected sepsis
- AI/ML for early infection detection and risk stratification
Selected Articles
1. A novel molecule targeting neutrophil-mediated B-1a cell trogocytosis attenuates sepsis-induced acute lung injury.
Using a murine cecal ligation and puncture (CLP) model, the authors implicate neutrophil-mediated trogocytosis in the depletion of B-1a cells during sepsis and show that a novel molecule targeting this process preserves B-1a cells and attenuates acute lung injury. The work links Siglec-G–regulated B-1a biology to neutrophil interactions and identifies a potentially druggable pathway.
Impact: This provides a mechanistic framework connecting B-1a cell loss to lung injury in sepsis and proposes a novel therapeutic target by interrupting neutrophil-mediated trogocytosis.
Clinical Implications: Although preclinical, targeting trogocytosis to preserve protective B-1a cells could inspire immunomodulatory strategies to mitigate sepsis-induced acute lung injury and guide biomarker development.
Key Findings
- In a CLP mouse model of sepsis, neutrophils accumulated in lungs/serosa while B-1a cells declined, implicating neutrophil-mediated trogocytosis in B-1a depletion.
- A novel molecule that targets neutrophil-mediated trogocytosis preserved B-1a cells in vivo.
- Therapeutic targeting of trogocytosis attenuated sepsis-induced acute lung injury in treated mice.
Methodological Strengths
- Use of a well-established CLP model to recapitulate polymicrobial sepsis and lung injury
- Mechanism-driven intervention targeting a defined cellular process (trogocytosis)
Limitations
- Preclinical mouse study without human validation
- Incomplete mechanistic detail and safety/PK data for the novel molecule are not provided in the abstract
Future Directions: Validate the pathway in independent models and human samples; develop biomarkers of B-1a cell depletion/trogocytosis; and evaluate safety/efficacy in early-phase clinical studies.
2. Empiric Antibiotic Therapy in Suspected Sepsis: Impact of Gentamicin-Based Regimens on Incident Renal Failure and Mortality.
In a 1,917-patient retrospective cohort of suspected sepsis, narrow-spectrum β-lactam plus gentamicin was not associated with higher AKI or mortality compared with broad-spectrum β-lactams. Broad-spectrum therapy was linked to worse ordinal outcomes (AKI stage/death; adjusted OR 1.61), and gentamicin cumulative dose did not correlate with peak creatinine.
Impact: Provides real-world evidence supporting stewardship-friendly empiric regimens without increased renal harm or mortality, potentially reducing broad-spectrum β-lactam use.
Clinical Implications: When local resistance patterns allow, consider narrow-spectrum β-lactam plus gentamicin for empiric coverage in suspected sepsis to limit broad-spectrum exposure while maintaining safety.
Key Findings
- Among 1,917 suspected sepsis patients, 33.1% received narrow-spectrum β-lactam/gentamicin and 66.9% received broad-spectrum β-lactams.
- Broad-spectrum β-lactams were associated with a higher posttreatment AKI stage or death (adjusted OR 1.61; 95% CI 1.27–2.04).
- No significant association was observed between cumulative gentamicin dose and peak creatinine; AKI cases on gentamicin normalized creatinine within 30 days.
Methodological Strengths
- Large real-world cohort with adjustment using an ordinal composite outcome from no AKI to death
- Direct comparison of stewardship-relevant regimens with clinically meaningful endpoints over 30 days
Limitations
- Retrospective, nonrandomized design with baseline imbalances and potential residual confounding
- Single health system; microbiological eradication and resistance emergence were not detailed
Future Directions: Prospective randomized trials to confirm safety/effectiveness; assess microbiologic outcomes and resistance; and evaluate subgroup effects (e.g., renal impairment).
3. Developing Machine-Learning Models to Predict Bacteremia in Febrile Adults Presenting to the Emergency Department: A Retrospective Cohort Study from a Large Center.
Using 80,201 febrile adult ED encounters with blood cultures, ML models trained on triage-available variables achieved strong performance for bacteremia prediction, with CatBoost AUC 0.844. The approach demonstrates feasibility for real-time risk stratification with minimal data burden.
Impact: The scale and performance suggest immediate translational potential for ED triage workflows, potentially improving timely diagnostics and antibiotic decisions.
Clinical Implications: Integration into ED triage could prioritize blood cultures, early antibiotics, and observation for high-risk patients, while reducing unnecessary workup in low-risk patients.
Key Findings
- Dataset included 80,201 febrile adult ED visits (2009–2018), with bacteremia prevalence ~12%.
- CatBoost achieved the highest AUC of 0.844 (95% CI 0.837–0.850); other gradient boosting models performed similarly.
- Models relied solely on triage-available features (demographics, symptoms, triage vitals/history), enabling potential real-time deployment.
Methodological Strengths
- Very large single-center cohort with predefined train/test split and K-fold validation
- Comparison of multiple supervised ML algorithms with confidence intervals for AUC
Limitations
- Single-center retrospective design without external prospective validation
- Outcome defined by blood culture positivity (may not capture all clinically significant sepsis); potential label noise
Future Directions: External validation and prospective impact studies; integration into EHR with clinician-in-the-loop; fairness and drift monitoring; calibration for different prevalence settings.