Daily Sepsis Research Analysis

BACKGROUND: How to identify suspected infection for sepsis surveillance purposes remains a well-recognised challenge. This study aimed to operationalise suspected infection for sepsis surveillance by developing an interpretable machine learning (ML) model for retrospective identification of patients with sepsis. METHODS: This multicentre cohort and machine learning study was conducted in two Dutch tertiary care hospitals. Adult patients with a quick Sequential Organ Failure assessment (qSOFA) ≥2 were included. Exclusion criteria included admission to the intensive care unit, transfer to or from another hospital, or patient refusal to reuse data. Cohort one consisted of patients admitted to the Emergency Department (ED) of hospital A between 01/01/2019 and 12/31/2019, to investigate community-onset sepsis. An external validation cohort of ED patients was obtained from hospital B between 01/01/2021 and 06/03/2022. Cohort two included hospitalised patients from hospital A between 01/01/2021 and 06/01/2022, to investigate hospital-onset sepsis. Objective data were extracted from electronic health records. Seven ML methods, including gradient boosting, random forest, logistic regression, decision trees, support vector machines, K nearest neighbours and stochastic gradient descent, were trained to identify sepsis with manual chart review as reference standard. The F1 score (harmonic mean of precision and recall), sensitivity and specificity were used as evaluation metrics. The best performing ML method was compared with other commonly used suspected infection proxies, including the Sepsis-3 definition, an adapted Adult Sepsis Event (ASE) definition and International Classification of Diseases (ICD) codes. FINDINGS: In the ED cohort, 655 patients were included (male: 355 (54.2%), female: 300 (45.8%)) and 240 (36.6%) had sepsis. For community-onset sepsis, gradient boosting performed best with an F1 score of 85.9%, a sensitivity of 91.1% (95%-CI 83.4-95.4%) and a specificity of 89.0% (95%-CI 83.4-92.8%). Most model features reflected either the inflammatory response (CRP, body temperature) or actions taken when an infection is suspected (antibiotic administration, microbial culture). In the external validation cohort, 185 patients were included (male: 94 (50.8%), female: 91 (49.2%)) and 54 (29.2%) had sepsis. External validation yielded an F1 score of 85.7%, a sensitivity of 87.5% (95%-CI 75.3-94.1%) and a specificity of 92.5% (95%-CI 85.9-96.2%). The gradient boosting model outperformed other commonly used proxies for suspected infection in terms of sensitivity, achieving 91.1% (95% CI: 83.4-95.4%), compared to Sepsis-3 with 78.9% (95% CI: 69.4-86.0%), the adapted ASE with 85.6% (95% CI: 76.8-91.4%), and ICD codes with 33.3% (95% CI: 24.5-43.6%). In the hospitalised cohort, 493 patients were included (male: 265 (53.8%), female: 228 (46.2%)) and 129 (26.2%) had sepsis. For hospital-onset sepsis, logistic regression had the highest F1 score (52.2%). Sensitivity was 58.1% (95%-CI 40.6-75.5%) and specificity was 82.9% (95%-CI 76.0-89.8%). INTERPRETATION: ED patients meeting ≥2 qSOFA criteria can be accurately classified as having suspected infection or not by a gradient boosting algorithm, outperforming common suspected infection definitions for sepsis surveillance. Including the inflammatory response in the suspected infection surveillance definition may enhance the accuracy and objectivity of sepsis surveillance. Future research is needed to validate the algorithm using other organ dysfunction criteria and in international settings. FUNDING: None.

BACKGROUND: Histones released in response to cellular injury are important mediators of organ failure and death in sepsis. Preclinical studies demonstrate that neutralization of histones in sepsis is associated with improved outcome. M6229 is a low-anticoagulant heparin able to neutralize histones. We aimed to evaluate the safety, tolerability, pharmacokinetics and pharmacodynamics of M6229 in critically ill patients with sepsis. METHODS: This was a first-in-human, phase I, monocenter trial in patients with sepsis admitted to the intensive care unit (ICU). Patients received a single 6 h intravenous infusion of M6229. A modified continual reassessment method (mCRM) with escalation overdose control was used for dose-escalation. The model was based on the probability of activated partial thromboplastin time (aPTT) being above 90 s (i.e., dose limiting pharmacologic event, DLPE). Three cohorts were studied (1: 0.15 mg/kg/h; 2: 0.45 mg/kg/h; 3: 0.90 mg/kg/h). RESULTS: Ten patients were included. The aPTT increased proportionally with increasing dosages of M6229 and decreased rapidly after infusion cessation. One DLPE occurred (aPTT of 100 s). Based on the mCRM model and data safety monitoring board recommendations, the maximum tolerated dose was defined as 0.9 mg/kg/h for a 6 h infusion of M6229. No serious adverse events were related to study drug infusion. An increase in QTc was probably related to infusion in one patient. M6229 showed close to dose-proportional pharmacokinetics. Total histone H3 and H2b plasma levels increased during and/or in the hours after M6229 infusion in all patients. In four out of five patients with plasma samples positive for histone H3, proteolytic cleavage was observed after infusion start. A decrease in sequential organ failure assessment score was observed in the days after infusion in 70% of patients. CONCLUSIONS: M6229 was deemed safe to use in critically ill sepsis patients. Our results suggest intravascular neutralization of histones by M6229. Future clinical studies need to confirm our findings and the efficacy of M6229.

BACKGROUND: Sepsis is an acute, life-threatening multiple organ dysfunction triggered by an infection. METHODS: This guideline is an update of the S3 guideline "Sepsis-prevention, diagnosis, therapy, and follow-up care" (Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaft [AMWF] Registry No. 079-001) of the German Sepsis Society (DSG) dated 31 December 2018. The update of the "Surviving sepsis campaign (SSC): international guidelines for management of sepsis and septic shock 2021" dated 4 October 2021, was used as the reference guideline. The DSG Guideline Commission compared each recommendation on the underlying PICO questions of the DSG Guideline 2018 (literature search until December 2018) with those of the SSC Guideline 2021 (literature search until July 2019) and evaluated the newly available published data (literature search until December 2024) by means of systematic update searches and literature reviews in compliance with the rules of the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system and the AWMF. RESULTS: A total of 88 PICO questions were addressed, including those related to the diagnosis and treatment of infection and organ failure. Of these, two were agreed upon as statements, 29 as expert consensus, and 57 as evidence-based recommendations (26 with a strong and 31 with a weak recommendation grade). Compared to the previous 2018 guideline, 43 recommendations were reviewed but retained, 16 recommendations were modified, and 29 recommendations were newly issued. CONCLUSION: Given the lack of evidence for numerous measures for the inpatient care of patients with sepsis or septic shock, old and new knowledge gaps were revealed. Among the evidence-based recommendations, the underlying GRADE quality of evidence was high for only 5 recommendations, moderate for 18 recommendations, low for 17 recommendations, and very low for 16. These evidence gaps can only be closed through future multicenter, noncommercial clinical trials. The update to the S3 guideline on sepsis includes some updates to the recommendations of the previous guideline. These updates will need to be incorporated into some of the case- and facility-specific quality assurance indicators of quality assurance (QA) procedure 2025. Impairments in health-related quality of life for survivors must be given greater focus in outpatient care.