Daily Sepsis Research Analysis
Three studies advance sepsis care across mechanisms, prognostics, and antimicrobial stewardship. A European multicenter analysis links persistent candidemia and poor guideline adherence to higher mortality, an externally validated nomogram improves ICU mortality prediction in sepsis-associated encephalopathy, and multi-omics work reveals a dual microbiome–steroid biosynthesis mechanism by which Shenmai Injection mitigates sepsis-associated acute lung injury.
Summary
Three studies advance sepsis care across mechanisms, prognostics, and antimicrobial stewardship. A European multicenter analysis links persistent candidemia and poor guideline adherence to higher mortality, an externally validated nomogram improves ICU mortality prediction in sepsis-associated encephalopathy, and multi-omics work reveals a dual microbiome–steroid biosynthesis mechanism by which Shenmai Injection mitigates sepsis-associated acute lung injury.
Research Themes
- Quality of antifungal care and persistent candidemia
- Mechanistic microbiome–metabolism crosstalk in sepsis lung injury
- Externally validated prognostic modeling for sepsis-associated encephalopathy
Selected Articles
1. Risk factors for persistent candidemia and prognostic implications: Results from the ECMM Candida III study.
In a 60-center European cohort sub-analysis (n=258 with FUBCs), 20.2% had persistent candidemia. Lower EQUAL Candida Scores—reflecting poorer adherence to guideline-recommended management, including initial echinocandin use—predicted persistence, and persistent candidemia ≥5 days independently doubled mortality risk alongside ICU admission.
Impact: Directly links persistent candidemia and guideline adherence with mortality, offering actionable targets—early echinocandin therapy and systematic FUBCs—to improve sepsis outcomes.
Clinical Implications: Ensure prompt echinocandin initiation, adherence to EQUAL Candida recommendations (FUBCs, source control, ophthalmologic exam), and heightened attention to cases with candidemia persisting ≥5 days to mitigate mortality risk.
Key Findings
- 20.2% (52/258) had persistent candidemia; median candidemia duration was 6 days.
- Initial echinocandin use was less frequent in persistent cases (61.5% vs. 78.2%; p=0.014).
- Lower EQUAL Candida Scores independently predicted persistence (OR 0.003; 95% CI 0.0002-0.07; p<0.001).
- Persistent candidemia ≥5 days (HR 2.06; 95% CI 1.26-3.37; p=0.004) and ICU admission (HR 1.59; 95% CI 1.02-2.50; p=0.039) independently predicted mortality.
Methodological Strengths
- Multicenter European cohort with standardized data capture
- Multivariable logistic and Cox models with attention to immortal time bias
- Use of EQUAL Candida Score to quantify guideline adherence
Limitations
- Sub-analysis limited to 40.8% with available FUBCs; potential selection bias
- Observational design precludes causal inference and residual confounding may persist
- Timing and frequency of FUBCs were not standardized across centers
Future Directions: Prospective interventions to improve EQUAL compliance (early echinocandin, source control, FUBCs), and trials testing standardized FUBC protocols to reduce persistence and mortality.
2. Shenmai injection attenuates sepsis-associated acute lung injury by remodeling gut microbiota and restoring steroid hormone biosynthesis.
Using a murine SA-ALI model with integrated network pharmacology, metabolomics, metagenomics, and validation, Shenmai Injection reduced inflammation, restored barrier integrity, and suppressed NF-κB signaling. Active constituents (ophiopogonin A/B, luteolin) targeted steroid biosynthesis enzymes, while gut microbiota remodeling (↓Chlamydiaceae, ↑Lactobacillaceae) correlated with androgen metabolites.
Impact: Elucidates a dual mechanism—microbiota remodeling and steroid hormone biosynthesis modulation—linking host–microbe metabolism to sepsis lung injury recovery, offering a multi-target therapeutic concept.
Clinical Implications: Although preclinical, findings support evaluating SMI or its active components as adjunctive therapy for SA-ALI, with potential biomarkers (steroid metabolites, microbiome signatures) to guide response.
Key Findings
- SMI reduced pulmonary inflammation, restored blood–gas barrier, and suppressed NF-κB activation in SA-ALI mice.
- Network pharmacology and metabolomics implicated steroid biosynthesis modulation via AKR1C3, HSD17B1/2, and SULT1E1 targeted by ophiopogonin A/B and luteolin.
- Metagenomics showed decreased Chlamydiaceae (notably Chlamydia abortus) and increased Lactobacillaceae after SMI.
- Intestinal androstenedione/androsterone levels negatively correlated with Chlamydia abortus abundance during recovery.
Methodological Strengths
- Integrated multi-omics (network pharmacology, metabolomics, metagenomics) with in vivo validation
- Use of dual-hit SA-ALI model (LPS + Poly(I:C)) to capture bacterial/viral mimicry
- Identification of discrete active constituents and enzymatic targets
Limitations
- Mouse model limits generalizability to human sepsis
- Complex herbal formulation poses standardization and dosing challenges
- LPS/Poly(I:C) model may not recapitulate full heterogeneity of human SA-ALI
Future Directions: Isolate and standardize active components, perform dose–response and safety studies, test microbiome-targeted strategies, and conduct early-phase clinical trials with metabolic/microbiome biomarkers.
3. A nomogram for predicting ICU mortality of sepsis associated encephalopathy: a retrospective cohort study based on MIMIC-IV and eICU-CRD.
From 5,242 training and 3,103 external validation cases, an eight-variable nomogram for SAE ICU mortality achieved AUROC 0.832 (train) and 0.825 (validation), outperforming SAPS II, SOFA, and GCS. Calibration and decision-curve analyses supported reliability and clinical net benefit.
Impact: Provides an externally validated, higher-performing prognostic tool for SAE, enabling earlier risk stratification than standard ICU scores.
Clinical Implications: Integrate the nomogram into ICU workflows to triage SAE patients for early neuroprotective and organ support strategies, while planning prospective impact evaluations before routine adoption.
Key Findings
- Training and validation cohorts included 5,242 and 3,103 patients, respectively.
- Eight predictors were selected via LASSO; the nomogram achieved AUROC 0.832 (train) and 0.825 (validation).
- Outperformed SAPS II, SOFA, and GCS; showed good calibration (Hosmer–Lemeshow p=0.129 train, 0.583 validation) and superior decision-curve net benefit.
Methodological Strengths
- Large, multi-database design with external validation
- Transparent variable selection (LASSO) and comprehensive performance assessment (ROC, calibration, DCA)
Limitations
- Retrospective design with potential misclassification of SAE and unmeasured confounding
- Generalizability beyond US ICU databases and the need for prospective impact assessment
- Model inputs limited to variables available in MIMIC/eICU datasets
Future Directions: Prospective validation and impact trials, EHR integration with real-time updating, and calibration across diverse health systems and sepsis phenotypes.