Daily Sepsis Research Analysis
Analyzed 32 papers and selected 3 impactful papers.
Summary
Mechanistic and clinical sepsis research advanced on three fronts: a FASEB Journal study uncovered a GATA3–BMP9–Smad1/5–YAP axis that suppresses ferroptosis in sepsis-associated ARDS; a prospectively registered meta-analysis found modest real-world performance of Epic’s EHR predictive tools, including the Epic Sepsis Model; and a nationwide JACC cohort characterized culture-negative endocarditis, showing less sepsis/fever but more embolism and a notable PET-CT diagnostic yield.
Research Themes
- Mechanistic pathways and ferroptosis modulation in sepsis-associated ARDS
- Real-world validation of EHR-based sepsis prediction and deterioration models
- Phenotyping and imaging strategies in culture-negative infective endocarditis
Selected Articles
1. Transcription Factor GATA3 Ameliorates Sepsis-Associated Acute Respiratory Distress Syndrome by Activating Smad1/5-YAP Pathway via BMP9.
In LPS-induced sepsis-ARDS models, BMP9 overexpression reduced inflammation and ferroptosis by activating the Smad1/5–YAP pathway. GATA3 was identified as an upstream transcription factor that drives BMP9 expression; inhibiting Smad1/5 or YAP, or knocking down GATA3, abrogated protection. These data define a GATA3–BMP9–Smad1/5–YAP axis as a therapeutic mechanism in sepsis-related lung injury.
Impact: This work uncovers a previously unrecognized transcriptional control of BMP9 by GATA3 that mitigates ferroptosis via Smad1/5–YAP, offering a mechanistic blueprint for targeted therapies in sepsis-associated ARDS.
Clinical Implications: Although preclinical, the GATA3–BMP9–Smad1/5–YAP axis suggests druggable nodes (e.g., BMP9 agonism, Smad1/5–YAP modulation) and biomarker candidates for stratifying sepsis-ARDS patients susceptible to ferroptosis-driven injury.
Key Findings
- LPS reduced BMP9, p-Smad1/5, and YAP, while BMP9 overexpression alleviated lung injury and ferroptosis.
- Blocking Smad1/5 (LDN193189) or knocking down Smad1/5 or YAP weakened BMP9’s protective effects.
- GATA3 bound the BMP9 promoter, upregulated BMP9 transcription, and its knockdown aggravated ARDS phenotypes.
Methodological Strengths
- Multi-system validation (in vivo mouse ARDS and in vitro MLE-12 cells) with loss- and gain-of-function approaches
- Mechanistic depth using ChIP-qPCR, luciferase reporter assays, and pathway inhibition (LDN193189)
Limitations
- Preclinical models (LPS-induced ARDS, MLE-12 cells) may not fully capture human sepsis-ARDS heterogeneity
- Reliance on overexpression/knockdown systems may overestimate effect sizes; no human tissue validation
Future Directions: Validate the axis in human sepsis-ARDS tissues, test pharmacologic BMP9/GATA3 modulators, and develop ferroptosis-informed patient stratification for early-phase trials.
BMP9 protects against sepsis-induced lung injury. This research aimed to explore how BMP9 affects sepsis-associated acute respiratory distress syndrome (ARDS). Mice and MLE12 cells overexpressing BMP9 were treated with LPS to induce ARDS. Changes in ARDS-related pathological features, ferroptosis, BMP9 expression, and the Smad1/5-YAP pathway were analyzed. Regulation of BMP9 in the Smad1/5 pathway was investigated using the Smad pathway inhibitor LDN193189 and loss-of-function assays. The potential transcription factor of BMP9 was identified using the GEO and ChEA databases and validated through ChIP-qPCR, luciferase reporter assay, and functional experiments. LPS-induced mice exhibited severe lung injury, accompanied by increased inflammation, oxidative stress, and ferroptosis. Furthermore, LPS induction notably decreased BMP9, p-Smad1/5, and YAP levels in mice. BMP9 overexpression alleviated ARDS symptoms and ferroptosis while activating the Smad1/5-YAP pathway. LPS induction reduced cell viability and promoted inflammation, oxidative stress, and ferroptosis in MLE-12 cells, but BMP9 overexpression reversed these changes. Importantly, the protective effects of BMP9 overexpression were weakened by LDN193189 or by Smad1/5 or YAP knockdown. GATA3 was identified as the upstream transcription factor of BMP9, binding upstream of the BMP9 promoter region and activating its transcription. GATA3 knockdown significantly downregulated BMP9 expression in MLE-12 cells. GATA3 expression was notably decreased in ARDS models. In MLE-12 cells overexpressing BMP9, GATA3 knockdown markedly downregulated BMP9, p-Smad1/5, and YAP levels, thereby aggravating ARDS, whereas overexpression of GATA3 exerted protective effects in LPS-treated MLE-12 cells with BMP9 knockdown. In conclusion, GATA3 activates BMP9 transcription, thereby reducing inflammation and ferroptosis in sepsis-associated ARDS via the Smad1/5-YAP pathway.
2. A Systematic Review and Meta-analysis of Externally Validated Epic Clinical Decision Support Tools.
Across >2.3 million patients, Epic’s externally validated models had modest discrimination: EDI AUROC 0.79, Epic Sepsis Model 0.65, with high between-site heterogeneity. Several models underperformed vendor-reported ranges, underscoring the necessity of local validation, calibration, and governance before clinical deployment.
Impact: Provides the first prospectively registered synthesis of Epic tools’ real-world performance, including the Epic Sepsis Model, informing hospital policy on prediction model deployment.
Clinical Implications: Hospitals should not rely on vendor-reported metrics; instead, perform local validation, assess calibration and equity, and implement human-in-the-loop oversight, especially for sepsis alerts with modest AUROC.
Key Findings
- Pooled AUROC: EDI 0.79, Epic Sepsis Model 0.65, EURM 0.70, EEOL-CI 0.76, ERPNS 0.62 across >2.3 million patients.
- High heterogeneity across sites; several models underperformed vendor-reported performance ranges.
- Prospective registration and multi-site validations support generalizability of the performance estimates.
Methodological Strengths
- PROSPERO-registered systematic review with random-effects meta-analysis
- Large cumulative sample size (>2.3 million) and multi-site external validations
Limitations
- High heterogeneity and potential publication bias; calibration and subgroup equity often underreported
- Proprietary model opacity limits assessment of drift and transportability
Future Directions: Mandate site-level validation and calibration, share model documentation and shift to transparent models; evaluate impact on workflow, bias, and patient-centered outcomes, especially for sepsis alerts.
BACKGROUND: Clinical Decision Support (CDS) tools integrated with Electronic Health Records increasingly guide clinical practice. Epic Systems, storing more than 325 million patient records, offers various proprietary predictive models to healthcare systems. Despite widespread adoption, no systematic review has examined these tools' real-world performance compared to vendor-reported metrics. METHODS: This study was prospectively registered on PROSPERO (CRD420251148571). We systematically searched PubMed, Scopus, and Embase (January 2018 to August 2025) for external validations of Epic's CDS tools. We pooled Area Under the Receiver Operating Characteristic Curve (AUROC) values using random-effects models and assessed heterogeneity using Higgins' I RESULTS: We included 22 studies in our systematic review, validating Epic CDS tools on a total of over 2.3 million patients and 34 sites. The Epic Deterioration Index (EDI, 7 studies, 542,983 patients) achieved pooled AUROC 0.79 [95% CI 0.76-0.80]; Epic Sepsis Model (ESM, 3 studies, 922,754 patients) 0.65 [0.61-0.70]; Epic Unplanned Readmission Model (EURM, 5 studies, 145,595 patients) 0.70 [0.68-0.73]; Epic End-of-Life Care Index (EEOL-CI, 3 studies, 217,885 patients) 0.76 [0.67-0.83]; and Epic Risk of Patient No-Show (ERPNS, 2 studies, 93,863 patients) 0.62 [0.54-0.68]. All models showed high heterogeneity (I CONCLUSION: Epic's CDS tools demonstrated modest real-world performance, with none exceeding AUROC 0.79. Three models (ESM, EURM, EEOL-CI) underperformed Epic's reported ranges. High heterogeneity across sites emphasizes the need for local validation before clinical deployment.
3. Culture-Negative IE in the Modern Diagnostic Era: Patient Characteristics and Heterogeneity in a Nationwide Cohort.
In a nationwide unselected cohort (n=2,875), culture-negative IE accounted for 7.4% and presented with less sepsis and fever but more embolism and valvular insufficiency than culture-positive IE. PET-CT contributed diagnostic information in 13.1% overall and nearly 50% among prosthetic valve CNIE, highlighting subgroup-specific diagnostic strategies.
Impact: Defines modern-era CNIE phenotypes at national scale and quantifies PET-CT’s diagnostic yield, informing diagnostic pathways where classic sepsis/fever signs are absent.
Clinical Implications: Absence of sepsis/fever should not deter IE workup; early embolic surveillance and PET-CT—especially in prosthetic valves—can improve diagnostic confidence and tailor therapy.
Key Findings
- CNIE prevalence was 7.4% (212/2,875) with smaller vegetations (8 mm vs 10 mm) than CPIE.
- CNIE had less sepsis (7.1% vs 24.6%) and fever (44.3% vs 61.7%) but more embolism (25.9% vs 10.8%).
- PET-CT was diagnostic in 13.1% of CNIE overall and nearly 50% in prosthetic valve CNIE.
Methodological Strengths
- Nationwide, unselected registry minimizing referral bias and enhancing generalizability
- Integrated modern diagnostics (blood/tissue culture, PCR, and PET-CT) for phenotype characterization
Limitations
- Observational design with potential residual confounding and misclassification
- Limited outcome granularity beyond diagnostic yield (e.g., long-term mortality not detailed)
Future Directions: Prospective studies to evaluate outcome impact of PET-CT–guided pathways and to refine CNIE subgroups using molecular diagnostics.
BACKGROUND: Culture-negative infective endocarditis (CNIE) remains a diagnostic and therapeutic challenge. Current evidence on this disease is limited by small sample sizes, lack of granularity, and highly selected data. OBJECTIVES: This study sought to provide a granular characterization of CNIE in the modern diagnostic era from the first nationwide cohort of patients with infective endocarditis (IE). METHODS: This study used data from the nationwide Danish NIDUS (NatIonal Danish endocarditis stUdieS) registry, including all patients hospitalized with first-time left-sided IE (2016-2021). Patients were categorized as having CNIE or culture-positive infective endocarditis (CPIE) on the basis of blood cultures, valve tissue cultures, and polymerase chain reaction analyses. The study described patients' medical history, IE-specific disease features, clinical practice patterns, and treatment regimens. RESULTS: Of 2,875 IE patients, 212 (7.4%) had CNIE. Compared with CPIE, CNIE patients were more likely to have congenital heart disease (9.9% vs 2.9%) and less likely to have previous cancer (9.3% vs 14.7%). At admission, CNIE patients presented less frequently with sepsis (7.1% vs 24.6%) and fever (44.3% vs 61.7%), but they presented more often with embolism (25.9% vs 10.8%) and valvular insufficiency (11.3% vs 7.4%). The median size of vegetations was smaller (8 mm vs 10 mm) for patients with CNIE, whereas rates of prosthetic valve infection (22.2% vs 23.1%) and valve surgery (20.3% vs 21.8%) were similar. Positron emission tomography with computed tomography (PET-CT) was commonly used in both groups (67%-68%), and it was diagnostic in 13.1% of CNIE cases and 10.7% of CPIE cases. Among patients with prosthetic valve CNIE, the diagnostic yield of PET-CT was almost 50%. CONCLUSIONS: Using the first nationwide, unselected IE cohort, this study demonstrated a lower proportion of culture-negative cases than reported in previous studies. Patients with CNIE differed from CPIE in clinical presentation and disease characteristics, notably with less frequent fever and sepsis but higher embolic complication rates. However, culture-negative IE is highly heterogeneous and is better defined by distinct subgroups rather than by a single phenotype.