Daily Sepsis Research Analysis

Sepsis is a heterogeneous syndrome with high morbidity and mortality. Despite extensive clinical trials, therapeutic progress remains limited, in part due to the absence of actionable sepsis subtypes.This study aimed to evaluate the feasibility of using HL7 Fast Healthcare Interoperability Resources (FHIR) for prerandomization sepsis subtyping to support clinical trial enrichment across multiple health systems.Data from 765 encounters at two academic medical centers were analyzed. FHIR-based resources were extracted from both research data warehouses (RDWs) and electronic health records (EHRs). A Python implementation of the Sepsis Endotyping in Emergency Care (SENECA) sepsis subtyping algorithm was developed to query and assemble FHIR resources for subtype classification.Open-source Python code for the SENECA algorithm is provided on GitHub. Experiments demonstrated: (1) successful sepsis subtyping across both health systems; (2) concordance between the original R implementation and the new Python implementation; and (3) discrepancies when comparing RDW-derived versus EHR-integrated FHIR APIs, primarily due to query and filtering limitations. Missing data were common and influenced by both clinical practice and FHIR API constraints. We provide five recommendations to address these challenges.FHIR can support multi-institutional sepsis subtyping and trial enrichment, though technical and governance challenges remain.

Previous studies on the association between adiposity indices and risk of infection have been inconsistent. To investigate the causality between different adiposity indices (body mass index [BMI], waist circumference [WC], and hip circumference [HC]) and the risk of infection (sepsis susceptibility (SS), sepsis mortality (SM), cholecystitis, intestinal infections, infections of the skin and subcutaneous tissue [SSTI], and acute lower respiratory infections). Mendelian randomization (MR) analysis was conducted to explore the causality between the 3 adiposity indices and the risk of 5 infectious diseases. Twenty-eight MR analyses were conducted to evaluate the final results, comprising 18 forward univariate MR, 5 reverse univariate MR, and 5 multivariable MR (MVMR) analyses. Data on adiposity indices and infections were obtained from the UK Biobanks, FinnGen Biobanks, Medical Research Council Integrative Epidemiology Unit, and within the family genome-wide association study consortium. Preliminary genetic variants associated with BMI (n = 11), WC (n = 374), and HC (n = 420) were selected as instrumental variables. The inverse-variance weighted (IVW) method combined with different types of MR methods was used to enhance the robustness of the final results. The statistical significance threshold was corrected using the Bonferroni method. The MVMR-IVW (random) analysis revealed that only WC had a significant and independent causal association with SS (odds ratio [OR] = 1.95; 95% confidence interval [CI]: 1.41-2.69; P < .001), SM (OR = 3.23; 95% CI: 1.52-6.86; P = .002), cholecystitis (OR = 1.87; 95% CI: 1.36-2.55; P < .001), and SSTI (OR = 1.74; 95% CI: 1.26-2.41; P = .001). These results were confirmed by other MVMR methods (least absolute shrinkage and selection operator regression, and MVMR-robust). Neither pleiotropy nor reverse causality was detected. WC may predict infectious disease risk more efficiently than other indices, and controlling WC may help decrease the risk of infectious diseases. Future long-term prospective studies are needed to explore the associations between dynamic adiposity indices and diverse infectious diseases in different populations.

BACKGROUND: Pneumonia is the leading source of sepsis worldwide and remains associated with high morbidity and mortality. However, prospective long-term studies specifically describing the clinical characteristics, microbiology, and outcomes of patients with respiratory-source sepsis are scarce. METHODS: We conducted a 12-year prospective observational study (January 1, 2012-December 31, 2023) at the Department of Intensive Care Medicine, Donostia University Hospital, the only tertiary care center in Gipuzkoa, Spain. All adult ICU patients with sepsis or septic shock were included; this analysis focused on those with pneumonia as the infection source. Demographic and clinical features, microbiology, management, and prognostic factors for mortality were analyzed. RESULTS: Our sepsis registry included 2116 ICU patients with sepsis or septic shock; pneumonia was identified as the infectious source in 590 cases (27.9 %), of which 434 (73.6 %) were community-acquired (CAP) and 156 (26.4 %) hospital-acquired (HAP), including 19 ventilator-associated pneumonia (VAP). Compared with CAP, HAP patients had higher APACHE II and SOFA scores, more frequent hemodynamic instability and thrombocytopenia, and greater need for vasoactive support, mechanical ventilation (MV), and renal replacement therapy (RRT). No significant differences were observed in sex, age, or admission levels of procalcitonin and lactate. Streptococcus pneumoniae predominated in CAP, whereas Escherichia coli and Pseudomonas aeruginosa were most common in HAP. ICU mortality was 24.7 % and overall hospital mortality 33.7 %, both higher in HAP. Multivariate analysis identified nosocomial origin as the strongest independent predictor of mortality, along with thrombocytopenia, hypoglycemia, need for MV and RRT, higher APACHE II, and lactate at admission. CONCLUSIONS: Within our prospective sepsis registry, pneumonia was the most frequent infectious source. Nosocomial pneumonia, although less common than CAP, was associated with greater severity and emerged as the main independent predictor of mortality.