Daily Sepsis Research Analysis
Three impactful sepsis studies span methods, mechanisms, and targets: a prospective multicenter study shows current ICD-based approaches poorly capture Sepsis-3 cases; a proteome-wide Mendelian randomization across major biobanks prioritizes causal proteins with experimental validation as therapeutic targets; and an FDA-approved antiepileptic, phensuximide, selectively inhibits RIPK1 to protect against LPS- and TNF-induced SIRS in vivo, suggesting drug repurposing potential.
Summary
Three impactful sepsis studies span methods, mechanisms, and targets: a prospective multicenter study shows current ICD-based approaches poorly capture Sepsis-3 cases; a proteome-wide Mendelian randomization across major biobanks prioritizes causal proteins with experimental validation as therapeutic targets; and an FDA-approved antiepileptic, phensuximide, selectively inhibits RIPK1 to protect against LPS- and TNF-induced SIRS in vivo, suggesting drug repurposing potential.
Research Themes
- Validity of administrative coding versus Sepsis-3 clinical diagnosis
- Proteome-wide causal target discovery and validation for sepsis
- Drug repurposing targeting RIPK1 to modulate inflammatory cell death
Selected Articles
1. Accuracy of the modified Global Burden of Disease International Classification of Diseases coding methods for identifying sepsis: a prospective multicentre cohort study.
In a prospective multicenter ED cohort (n=450) adjudicated by Sepsis-3, ICD-based methods derived from the GBD study underperformed, with the implicit-plus approach achieving sensitivity 67.4% and specificity 67.2%. Agreement with clinical sepsis was low (α=0.52–0.56); misclassification often involved unspecified UTI, hypotension, and AKI codes, and many false negatives lacked documented pathogens.
Impact: Accurate sepsis surveillance and benchmarking hinge on reliable case identification; this study shows commonly used ICD strategies diverge substantially from Sepsis-3 diagnoses in real time.
Clinical Implications: Administrative data should be used cautiously for sepsis quality metrics and epidemiology. Coding strategies and clinician documentation need refinement; hybrid approaches (e.g., clinician adjudication, NLP of notes) may improve case capture.
Key Findings
- Among 450 high-risk ED patients, clinical sepsis prevalence was 47.8% (215/450).
- Sensitivity/specificity: explicit 41.4%/91.9%, implicit 58.1%/78.7%, implicit-plus 67.4%/67.2%, Angus 55.8%/79.1%.
- Agreement with clinical Sepsis-3 diagnosis was low across methods (Cronbach α=0.52–0.56).
- False positives often involved unspecified UTI, hypotension, and AKI codes; 44.3%–55.6% of false negatives lacked documented pathogens.
Methodological Strengths
- Prospective multicenter design with Sepsis-3 clinical adjudication
- Head-to-head comparison of multiple ICD-based definitions including Angus and modified GBD methods
- Pre-registered study (ANZCTR ACTRN12621000333819)
Limitations
- Conducted in high-risk ED population from nine hospitals in NSW, Australia, which may limit generalizability
- Sample size (n=450) may constrain precision for subgroup analyses
Future Directions: Refine ICD algorithms (e.g., exclude nonspecific UTI codes), integrate laboratory/microbiology and NLP of clinical notes, and validate across diverse health systems and EHRs.
BACKGROUND: This study assessed the accuracy of three International Classification of Diseases (ICD) codes methods derived from Global Burden of Disease (GBD) sepsis study (modified GBD method) in identifying sepsis, compared to the Angus method. Sources of errors in these methods were also reported. METHODS: Prospective multicentre, observational, study. Emergency Department patients aged ≥ 16 years with high sepsis risk from nine hospitals in NSW, Australia were screened for clinical sepsis using Sepsis 3 criteria and coded as having sepsis or not using the modified GBD and Angus methods. The three modified GBD methods were: Explicit-sepsis-specific ICD code recorded; Implicit-sepsis-specific code or infection as primary ICD code plus organ dysfunction code; Implicit plus-as for Implicit but infection as primary or secondary ICD code. Agreement between clinical sepsis and ICD coding methods was assessed using Cronbach alpha (α). For false positive cases (ICD-coded sepsis but not clinically diagnosed), the ICD codes leading to those errors were documented. For false negatives (clinically diagnosed sepsis but ICD-coded), uncoded sources of infection and organ dysfunction were documented. RESULTS: Of 6869 screened patients, 450 (median age 72.4 years, 48.9% females) met inclusion criteria. Clinical sepsis was diagnosed in 215/450 (47.8%). The explicit, implicit, implicit plus and Angus methods identified sepsis in 108/450 (24.0%), 175/450 (38.9%), 222/450 (49.3%) and 170/450 (37.8%), respectively. Sensitivity was 41.4%, 58.1%, 67.4% and 55.8%, and specificity 91.9%, 78.7%, 67.2% and 79.1%, respectively. Agreement between clinical sepsis and all ICD coding methods was low (α = 0.52-0.56). False positives were 19, 50, and 77, while false negatives were 126, 90, and 70 for the explicit, implicit, and implicit plus methods, respectively. For false positive cases, unspecified urinary tract infection, hypotension and acute kidney failure were commonly assigned infection and organ dysfunction codes. About half (44.3%-55.6%) of the false negative cases didn't have a pathogen documented. CONCLUSION: The modified GBD method demonstrated low accuracy in identifying sepsis; with the implicit plus method being the most accurate. Errors in identifying sepsis using ICD codes arise mostly from coding for unspecified urinary infections and associated organ dysfunction. TRIAL REGISTRATION: The study was registered at the ANZCTR (ACTRN12621000333819) on 24 March 2021.
2. Therapeutic Targets for Sepsis: Multicenter Proteome-Wide Analyses and Experimental Validation.
Using proteome-wide MR across FinnGen, UK Biobank-PPP, and deCODE, the authors identified plasma proteins causally associated with sepsis (FinnGen: 16,074 cases/363,227 controls; UKB: 11,643/474,841) across four exposure–outcome combinations. Proteins meeting FDR<0.05 were prioritized and subsequently validated experimentally, nominating therapeutic targets for sepsis.
Impact: Causal inference at proteome scale, coupled with experimental confirmation, provides a rigorous route to nominate drug targets for a disease with repeated RCT failures.
Clinical Implications: Findings offer a prioritized list of causal protein targets for therapeutic development and potential biomarker discovery; translation will require target validation in diverse populations and interventional studies.
Key Findings
- Proteome-wide MR across FinnGen, UKB-PPP, and deCODE evaluated causal links between plasma proteins and sepsis.
- Large-scale samples: FinnGen (16,074 cases; 363,227 controls) and UK Biobank (11,643 cases; 474,841 controls).
- Proteins were prioritized when achieving FDR<0.05 across four exposure–outcome MR combinations.
- Experimental validation corroborated MR-identified targets, nominating candidates for therapeutics.
Methodological Strengths
- Causal inference via Mendelian randomization across multiple large biobanks
- Independent experimental validation to support target nomination
Limitations
- MR conclusions depend on instrument validity and absence of horizontal pleiotropy
- Generalizability may be constrained by cohort ancestries and proteomic panel coverage
Future Directions: Mechanistic dissection of top targets, validation in non-European ancestries, and progression to early-phase interventional trials guided by human genetics.
Sepsis is a life-threatening condition with high mortality, underscoring the urgent need for effective therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) analysis using plasma protein data from the FinnGen, UKB-PPP, and deCODE cohorts to identify proteins causally associated with sepsis. The analysis included 16,074 cases and 363,227 controls in FinnGen and 11,643 cases and 474,841 controls in the UK Biobank, spanning four exposure-outcome combinations. Proteins were prioritized based on a false discovery rate <0.05 in one combination and
3. FDA-approved phensuximide inhibits RIPK1-dependent immunogenic cell death.
Phensuximide, an FDA-approved antiepileptic, was identified as a selective RIPK1 kinase inhibitor that blocks necroptosis and preserves signaling through NF-κB/MAPK. In vivo, it protected against LPS- and TNF-induced SIRS, nominating a repurposing opportunity for RIPK1-mediated inflammatory diseases, including sepsis models.
Impact: Repurposing an approved drug to modulate RIPK1-dependent cell death offers a rapid translational path in a field with limited effective therapies.
Clinical Implications: Although preclinical, these data support exploring phensuximide or next-generation RIPK1 inhibitors in early-phase trials for hyperinflammatory states and sepsis, with careful dose, safety, and off-target assessment.
Key Findings
- Small-scale screen of Nec-1-like compounds identified phensuximide as a RIPK1 kinase inhibitor.
- Phensuximide prevented necroptosis while sparing NF-κB and MAPK signaling.
- In vivo, phensuximide protected against both LPS- and TNF-induced SIRS, sepsis-relevant models of RIPK1 activation.
Methodological Strengths
- Drug-repurposing screen among FDA-approved and trial-stage compounds
- Mechanistic specificity demonstrated (RIPK1 kinase inhibition without disrupting NF-κB/MAPK) and in vivo validation
Limitations
- Preclinical models (SIRS) may not fully recapitulate human sepsis pathophysiology
- Dosing, pharmacokinetics, and safety in septic patients remain untested
Future Directions: Define pharmacology and therapeutic window in infection-driven sepsis models, assess combination with standard-of-care, and progress to phase I/II studies with biomarkers of RIPK1 activity.
Receptor-interacting serine/threonine kinase 1 (RIPK1) is a pivotal protein controlling cell death and inflammation. RIPK1 is an attractive therapeutic target, given that the inhibition of RIPK1 kinase activity has been shown to be effective in animal models of human diseases such as autoimmune and neurodegenerative diseases. Here, we screened a collection of drugs with structural similarity to necrostatin-1 (Nec-1), an inhibitor of RIPK1, to assess their abilities to regulate RIPK1-mediated immunogenic cell death. Through this small-scale screening of drugs from ongoing clinical trials and FDA-approved drugs, we discovered that the drug phensuximide could prevent necroptosis by targeting RIPK1 kinase activity. Importantly, phensuximide, which has already been approved by the FDA for the treatment of epilepsy, effectively prevents the kinase activity of RIPK1 without affecting the NF-κB and MAPK pathways. The potency of phensuximide is that it protects against both LPS- and TNF-induced systemic inflammatory response syndrome (SIRS), which are sepsis models involving RIPK1 kinase activity. Our findings suggest that phensuximide may serve as a promising strategy for targeting RIPK1-mediated diseases.