Sepsis, October 4 edition

Using patient single-cell RNA-sequencing data, septic mice, and macrophage models, the study identified Peli1 as a driver of sepsis-associated inflammation and coagulopathy. Peli1 promoted site-specific polyubiquitination of Lipg at the KR2 residue, stabilizing Lipg and sustaining inflammatory activation; myeloid Peli1 deficiency improved platelet abnormalities and survival in septic mice.

Impact: This study provides a mechanistic bridge between macrophage inflammatory activation and immunothrombosis by identifying a specific Peli1-Lipg post-translational regulatory axis. It offers a defined molecular target for therapeutic development beyond nonspecific anti-inflammatory strategies.

Clinical Implications: The Peli1-Lipg axis could eventually support targeted therapies for sepsis-associated inflammation and coagulopathy. Translation will require validation in human tissue, assessment of infection-control risks, and development of agents that selectively modulate this pathway without impairing host defense.

Future Directions: Future studies should determine whether Peli1 or Lipg is therapeutically tractable in human sepsis, define cell- and stage-specific effects, and test selective pathway modulation in clinically relevant infection models.

In 1,572 adults with suspected community-onset sepsis, interpretable models using 13 admission-stage variables achieved AUROCs of 0.753-0.767 in an internal holdout test set, exceeding conventional biomarkers and SIRS. Explainable Boosting Machine had the highest sensitivity at 0.845, while age, procalcitonin, oxygen saturation, respiratory rate, and neutrophil-to-lymphocyte ratio were the leading predictors.

Impact: The study demonstrates a practical approach to combining early, routinely available variables with transparent machine learning for Sepsis-3 recognition. Its clinically useful sensitivity and explainability address important barriers to adoption of artificial intelligence in emergency care.

Clinical Implications: These models could support emergency department triage and early sepsis evaluation, particularly where rapid laboratory and clinical data are available. They should not replace clinical assessment until external validation, calibration testing, prospective impact studies, and evaluation across different health systems are completed.

Future Directions: Prospective multicenter external validation should assess calibration, fairness across demographic groups, clinician interaction, alert-related harms, and net clinical benefit before implementation.

In a propensity score-matched cohort of 23,938 adults with type 2 diabetes who developed sepsis, prior GLP-1 receptor agonist use was associated with lower 90-day mortality than prior SGLT2 inhibitor use (HR 0.81, 95% CI 0.75-0.88). Associations with lower cardiovascular events and intensive care admission were observed, but many secondary outcomes lost statistical significance after multiplicity correction and residual confounding remains possible.

Impact: This is one of the largest comparative observational analyses addressing whether pre-existing diabetes therapy may modify outcomes after sepsis. The mortality signal is clinically important and hypothesis-generating, but it should not be interpreted as evidence that GLP-1 receptor agonists prevent sepsis mortality without randomized or prospective confirmation.

Clinical Implications: The findings may inform medication-history assessment and the design of future trials in patients with type 2 diabetes who develop sepsis. They do not justify changing glucose-lowering therapy solely to reduce post-sepsis mortality, because treatment allocation was nonrandomized and individual-agent effects were not evaluated.

Future Directions: Prospective emulated-trial studies and randomized trials should compare individual GLP-1 receptor agonists and SGLT2 inhibitors, account for treatment duration and adherence, and investigate biological mechanisms underlying any differential sepsis outcomes.