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

Urinary microRNAs in sepsis function as a novel prognostic marker

Renal dysfunction is a common complication of sepsis. Early diagnosis and prompt treatment of sepsis with renal insufficiency are crucial for improving patient outcomes. Diagnostic markers can help identify patients at risk for sepsis and AKI, allowing for early intervention and potentially preventing the development of severe complications. The aim of the present study was to investigate the expression difference of urinary microRNAs (miRNAs/miRs) in elderly patients with sepsis and secondary renal insufficiency, and to evaluate their diagnostic value in these patients. In the present study, RNA was extracted from urine samples of elderly sepsis-related acute renal damage patients and the expression profiles of several miRNAs were analyzed. In order to evaluate the expression profile of several miRNAs, urine samples from elderly patients with acute renal damage brought on by sepsis were obtained. RNA extraction and sequencing were then performed on the samples. Furthermore, multiple bioinformatics methods were used to analyze miRNA profiles, including differential expression analysis, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of different miRNA target genes, to further explore miRNAs that are suitable for utilization as biomarkers. A total of four miRNAs, including hsa-miR-31-5p, hsa-miR-151a-3p, hsa-miR-142-5p and hsa-miR-16-5p, were identified as potential biological markers and were further confirmed in sepsis using reverse transcription-quantitative PCR. The results of the present study demonstrated that the four urinary miRNAs were differentially expressed and may serve as specific markers for prediction of secondary acute kidney injury in elderly patients with sepsis.

Revisiting factors associated with blood culture positivity: Critical factors after the introduction of automated continuous monitoring blood culture systems

Blood culture is the main tool used to identify causative pathogens. Adequate volume and number of culture sets are considered key to blood culture positivity rate. It is not known whether these factors remain critical to the positivity rate after the introduction of automated continuous blood culture system monitoring. We measured blood volume per bottle and described the distribution of blood volume and number of culture sets. Multivariate logistic regression was performed to determine the independent association of blood volume, number of culture sets, diagnosis of sepsis in a patient, and other covariates with blood culture results. Only 6.9% of the blood culture bottle volumes complied with the guidance (8-10 mL), with the highest culture positivity rate (18%). Of the culture events, only one set of blood was cultured in 60.9% of events. In the multivariate analysis, blood culture volume per event (odds ratio [OR], 1.09 [95% confidence interval [CI], 1.06-1.11]), patients with a diagnosis of sepsis (OR, 2.86 [95% CI, 2.06-3.98]), and samples from the emergency department (OR, 2.29 [95% CI, 1.72-3.04]), but not the number of culture sets (OR, 0.74 [95% CI, 0.50-1.12]), were observed to be statistically significant with respect to blood culture positivity rate. Our results revealed that the total blood culture volume and the diagnosis of sepsis were critical factors affecting blood culture positivity rate. However, the proportion of blood culture bottles with the optimal blood volume was very low, and optimizing blood volume would be key to increasing blood culture positivity rate.

Prognostic Accuracy of qSOFA and SIRS for Mortality in the Emergency Department: A Meta-Analysis and Systematic Review of Prospective Studies

Objective

This meta-analysis aimed to determine the prognostic performance of quick sequential organ failure assessment (qSOFA) score in comparison to systemic inflammatory response syndrome (SIRS) in predicting in-hospital mortality in the emergency department (ED) patients.

Methods

Eligible studies comparing the performance of qSOFA and SIRS in predicting in-hospital death of ED patients were identified from searching PubMed, Embase, and Cochrane. Raw data were collected, and the pooled sensitivity and specificity were calculated for qSOFA and SIRS. The summary receiver operating curve was also plotted to calculate the area under the curve.

Results

A total of 16 prospective studies with 35,756 patients and 2,285 deaths were included. The pooled sensitivity was 0.43 (95% CI: 0.32–0.54) and 0.8 (95% CI: 0.73–0.86) for qSOFA and SIRS, respectively. The pooled specificity was 0.89 (95% CI: 0.84–0.93) and 0.39 (95% CI: 0.3–0.5) for qSOFA and SIRS, respectively. The area under the summary receiver operating curve was 0.76 (95% CI: 0.72–0.8) and 0.67 (95% CI: 0.62–0.72) for qSOFA and SIRS, respectively. A significant heterogeneity was observed for both qSOFA and SIRS studies.

Conclusion

The present meta-analysis suggested that qSOFA had a higher specificity but a lower sensitivity as compared with SIRS in predicting in-hospital mortality in the ED patients. qSOFA appeared to be a more concise and simple way to recognize patients at high risk for death. However, the use of SIRS in the ED cannot be completely replaced since the sensitivity of qSOFA was relatively lower.

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.

Prediction of 90-Day Mortality among Sepsis Patients Based on a Nomogram Integrating Diverse Clinical Indices

Background

Sepsis is prevalent among intensive care units and is a frequent cause of death. Several studies have identified individual risk factors or potential predictors of sepsis-associated mortality, without defining an integrated predictive model. The present work was aimed at defining a nomogram for reliably predicting mortality.

Methods

We carried out a retrospective, single-center study based on 231 patients with sepsis who were admitted to our intensive care unit between May 2018 and October 2020. Patients were randomly split into training and validation cohorts. In the training cohort, multivariate logistic regression and a stepwise algorithm were performed to identify risk factors, which were then integrated into a predictive nomogram. Nomogram performance was assessed against the training and validation cohorts based on the area under receiver operating characteristic curves (AUC), calibration plots, and decision curve analysis.

Results

Among the 161 patients in the training cohort and 70 patients in the validation cohort, 90-day mortality was 31.6%. Older age and higher values for the international normalized ratio, lactate level, and thrombomodulin level were associated with greater risk of 90-day mortality. The nomogram showed an AUC of 0.810 (95% CI 0.739 to 0.881) in the training cohort and 0.813 (95% CI 0.708 to 0.917) in the validation cohort. The nomogram also performed well based on the calibration curve and decision curve analysis.

Conclusion

This nomogram may help identify sepsis patients at elevated risk of 90-day mortality, which may help clinicians allocate resources appropriately to improve patient outcomes.

A personalised approach to antibiotic pharmacokinetics and pharmacodynamics in critically ill patients

Critically ill patients admitted to intensive care unit (ICU) with severe infections, or those who develop nosocomial infections, have poor outcomes with substantial morbidity and mortality. Such patients commonly have suboptimal antibiotic exposures at routinely used antibiotic doses related to an increased volume of distribution and altered clearance due to their underlying altered physiology. Furthermore, the use of extracorporeal devices such as renal replacement therapy and extracorporeal membrane oxygenation in these group of patients also has the potential to alter in vivo drug concentrations. Moreover, ICU patients are likely to be infected with less-susceptible pathogens. Therefore, one potential contributing cause to the poor outcomes observed in critically ill patients may be related to subtherapeutic antibiotic exposures. Newer concepts include the clinician considering optimised dosing based on a blood antibiotic exposure defined by pharmacokinetic modelling and therapeutic drug monitoring, combined with a knowledge of the antibiotic penetration into the site of infection, thereby achieving optimal bacterial killing. Such optimised dosing is likely to improve patient outcomes. The aim of this review is to highlight key aspects of antibiotic pharmacokinetics and pharmacodynamics (PK/PD) in critically ill patients and provide a PK/PD approach to tailor antibiotic dosing to the individual patient.

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.