A prospective observational cohort study to identify inflammatory biomarkers for the diagnosis and prognosis of patients with sepsis.

BACKGROUND: Sepsis is a life-threatening organ dysfunction. A fast diagnosis is crucial for patient management. Proteins that are synthesized during the inflammatory response can be used as biomarkers, helping in a rapid clinical assessment or an early diagnosis of infection. The aim of this study was to identify biomarkers of inflammation for the diagnosis and prognosis of infection in patients with suspected sepsis. METHODS: In total 406 episodes were included in a prospective cohort study. Plasma was collected from all patients with suspected sepsis, for whom blood cultures were drawn, in the emergency department (ED), the department of infectious diseases, or the haemodialysis unit on the first day of a new episode. Samples were analysed using a 92-plex proteomic panel based on a proximity extension assay with oligonucleotide-labelled antibody probe pairs (OLink, Uppsala, Sweden). Supervised and unsupervised differential expression analyses and pathway enrichment analyses were performed to search for inflammatory proteins that were different between patients with viral or bacterial sepsis and between patients with worse or less severe outcome. RESULTS: Supervised differential expression analysis revealed 21 proteins that were significantly lower in circulation of patients with viral infections compared to patients with bacterial infections. More strongly, higher expression levels were observed for 38 proteins in patients with high SOFA scores (> 4), and for 21 proteins in patients with worse outcome. These proteins are mostly involved in pathways known to be activated early in the inflammatory response. Unsupervised, hierarchical clustering confirmed that inflammatory response was more strongly related to disease severity than to aetiology. CONCLUSION: Several differentially expressed inflammatory proteins were identified that could be used as biomarkers for sepsis. These proteins are mostly related to disease severity. Within the setting of an emergency department, they could be used for outcome prediction, patient monitoring, and directing diagnostics. TRAIL REGISTRATION NUMBER: clinicaltrial.gov identifier NCT03841162.

Audit of empirical antibiotic therapy for sepsis and the impact of early multidisciplinary consultation on patient outcomes.

OBJECTIVES: To perform an audit of empirical antibiotic therapy (EAT) of sepsis at the emergency department and to analyse the impact of an antimicrobial stewardship (AMS) programme on process and patient outcomes. PATIENTS AND METHODS: A prospective, single-centre cohort study including patients with sequential organ failure assessment (SOFA) score ≥2 from whom blood cultures were taken was conducted between February 2019 and April 2020. EAT was assessed using eight applicable inpatient quality indicators (IQIs) for responsible antibiotic use. Patient outcomes were hospital length-of-stay (LOS), ICU admission, ICU LOS, and in-hospital mortality. RESULTS: The audit included 900 sepsis episodes in 803 patients. Full guideline adherence regarding choice and dosing was 45.9%; adherence regarding choice alone was 68.1%. EAT was active against all likely pathogens in 665/787 (84.5%) episodes. In the guideline non-adherent group, choice of EAT was inappropriate in 122/251 (48.6%) episodes. Changes within 3 days occurred in 335/900 (37.2%) episodes. Treating physicians changed administration route more often, whereas microbiological/infectious disease (ID)/AMS consultant advice resulted in de-escalation and discontinuation (P = 0.000). Guideline-adherent choice was associated with significantly shorter LOS (6 (4-11) vs. 8 (5-15) days). Full adherence was associated with significantly lower mortality (23 (6.4%) vs. 48 (11.3%)) and shorter LOS (6 (4-10) vs. 8 (5-14) days). CONCLUSION: Five global quality indicators of EAT were measurable in routine clinical practice. Full adherence to guidelines was only moderate. Adherence to guidelines was associated with better patient outcomes.

Risk Factors for Mortality, Intensive Care Unit Admission, and Bacteremia in Patients Suspected of Sepsis at the Emergency Department: A Prospective Cohort Study.

BACKGROUND: There is a clear need for a better assessment of independent risk factors for in-hospital mortality, intensive care unit admission, and bacteremia in patients presenting with suspected sepsis at the emergency department. METHODS: A prospective observational cohort study including 1690 patients was performed. Two multivariable logistic regression models were used to identify independent risk factors. RESULTS: Sequential organ failure assessment (SOFA) score of ≥2 and serum lactate of ≥2mmol/L were associated with all outcomes. Other independent risk factors were individual SOFA variables and systemic inflammatory response syndrome variables but varied per outcome. Mean arterial pressure <70 mmHg negatively impacted all outcomes. CONCLUSIONS: These readily available measurements can help with early risk stratification and prediction of prognosis.

Differentiating influenza from COVID-19 in patients presenting with suspected sepsis.

There is a need for a quick assessment of severely ill patients presenting to the hospital. The objectives of this study were to identify clinical, laboratory and imaging parameters that could differentiate between influenza and COVID-19 and to assess the frequency and impact of early bacterial co-infection. A prospective observational cohort study was performed between February 2019 and April 2020. A retrospective cohort was studied early in the COVID-19 pandemic. Patients suspected of sepsis with PCR-confirmed influenza or SARS-CoV-2 were included. A multivariable logistic regression model was built to differentiate COVID-19 from influenza. In total, 103 patients tested positive for influenza and 110 patients for SARS-CoV-2, respectively. Hypertension (OR 6.550), both unilateral (OR 4.764) and bilateral (OR 7.916), chest X-ray abnormalities, lower temperature (OR 0.535), lower absolute leukocyte count (OR 0.857), lower AST levels (OR 0.946), higher LDH (OR 1.008), higher ALT (OR 1.044) and higher ferritin (OR 1.001) were predictive of COVID-19. Early bacterial co-infection was more frequent in patients with influenza (10.7% vs. 2.7%). Empiric antibiotic usage was high (76.7% vs. 84.5%). Several factors determined at presentation to the hospital can differentiate between influenza and COVID-19. In the future, this could help in triage, diagnosis and early management. Clinicaltrial.gov Identifier: NCT03841162.