The challenge of molecular diagnosis of bloodstream infections

Inflammatory mechanisms and intervention strategies for sepsis-induced myocardial dysfunction

Sepsis-induced myocardial dysfunction (SIMD) is the leading cause of death in patients with sepsis in the intensive care units. The main manifestations of SIMD are systolic and diastolic dysfunctions of the myocardium. Despite our initial understanding of the SIMD over the past three decades, the incidence and mortality of SIMD remain high. This may be attributed to the large degree of heterogeneity among the initiating factors, disease processes, and host states involved in SIMD. Previously, organ dysfunction caused by sepsis was thought to be an impairment brought about by an excessive inflammatory response. However, many recent studies have shown that SIMD is a consequence of a combination of factors shaped by the inflammatory responses between the pathogen and the host. In this article, we review the mechanisms of the inflammatory responses and potential novel therapeutic strategies in SIMD.

[Rapid diagnosis of bacteremia by genomic identification]

Our objective was to make a focus on the methods for rapid diagnosis of bacteremia by genomic identification. We also aimed to evaluate the interest of using them in the laboratory practice. The different methods currently available have been presented according to their technologic approach. It is also possible to classify these methods according to the data provided, only bacterial and/or resistance gene identification or also bacterial susceptibility to antibiotics. In case of mono-microbial blood cultures, the performances recorded with these methods are very good as compared to the subcultures on agar media. Nevertheless, they are better for identifications (>90%) than for susceptibility to antibiotics (>80%). Numerous studies demonstrated the positive impact of these methods for decreasing the time necessary to the prescription of an appropriate antimicrobial treatment. However, it is noteworthy that an appropriate organization of the laboratory and a strategy of antimicrobial stewardship in the hospital are necessary. Concurrently, the impact on the patient outcome has not been clearly demonstrated. Lastly, few medico-economic studies have been reported. However, as these methods have a substantial cost, their utilization strategy must be economically viable.

Clinical Application and Influencing Factor Analysis of Metagenomic Next-Generation Sequencing (mNGS) in ICU Patients With Sepsis

Objective

To analyze the clinical application and related influencing factors of metagenomic next-generation sequencing (mNGS) in patients with sepsis in intensive care unit (ICU).

Methods

The study included 124 patients with severe sepsis admitted to the ICU in the First Affiliated Hospital of Zhengzhou University from June 2020 to September 2021. Two experienced clinicians took blood mNGS and routine blood cultures of patients meeting the sepsis diagnostic criteria within 24 hours after sepsis was considered, and collection the general clinical data.

Results

mNGS positive rate was higher than traditional blood culture (67.74% vs. 19.35%). APACHE II score [odds ratio (OR)=1.096], immune-related diseases (OR=6.544), and hypertension (OR=2.819) were considered as positive independent factors for mNGS or culture-positive. The sequence number of microorganisms and pathogen detection (mNGS) type had no effect on prognosis. Age (OR=1.016), female (OR=5.963), myoglobin (OR=1.005), and positive virus result (OR=8.531) were independent risk factors of sepsis mortality. Adjusting antibiotics according to mNGS results, there was no statistical difference in the prognosis of patients with sepsis.

Conclusion

mNGS has the advantages of rapid and high positive rate in the detection of pathogens in patients with severe sepsis. Patients with high APACHE II score, immune-related diseases, and hypertension are more likely to obtain positive mNGS results. The effect of adjusting antibiotics according to mNGS results on the prognosis of sepsis needs to be further evaluated.

[Diagnosis and treatment of catheter-related bloodstream infection in hemodialysis: 10 years later]

Patients in hemodialysis on central venous catheter as vascular access are at risk of infections. Catheter-related bloodstream infection is one of the most serious catheter-complications in hemodialysis patients. Its clinical and microbiological diagnosis is challenging. The implementation of empiric antibiotic therapy is based on old recommendations proposing the combination of a molecule targeting methicillin-resistant Staphylococcus aureus and a betalactamin active on P. aeruginosa, and also adapting this probabilistic treatment by carrying out a microbiological register on a local scale, which is rarely done. In our hemodialysis center at Bordeaux University Hospital, an analysis of the microorganisms causing all catheter-related bloodstream infection over the period 2018-2020 enabled us to propose, in agreement with the infectious disease specialists, an adapted probabilistic antibiotic therapy protocol. This approach allowed us to observe a low incidence of meticillinoresistance of Staphylococcus. For catheters inserted more than 6 months ago, we observed no Staphylococcus, no multi-resistant Pseudomonas, and only 2% of Enterobacteria resistant to cephalosporins. A frequent updating of the microbiological epidemiology of catheter-related bloodstream infection, in partnership with the infectious diseases team in each hemodialysis center, allowing an adaptation of the probabilistic antibiotic therapy, and seems to have a good feasibility. This strategy might favor the preservation of microbial ecology on an individual and collective scale in maintenance hemodialysis patients.

Molecular diagnosis of bacteremia in a pediatric intensive care unit: a step forward

Aim: T2Bacteria^® Panel detects six ESKAPE pathogens in around 3.5 h directly in whole blood. Our aim was to compare T2Bacteria with simultaneous blood culture in critically ill children with suspected bloodstream infection. Materials & methods: Retrospective study of critically ill children admitted to our tertiary-care center (2018-2020). Results: A total of 60 patients were recruited, including 63 episodes and 75 T2Bacteria/blood cultures were performed. Overall agreement between T2Bacteria and blood culture was 78.7% with a discordance of 21.3% (16/75 samples). Conclusion: T2Bacteria Panel may be useful in critically ill children providing an accurate and fast diagnosis of bacteremia directly from blood sample and detecting pathogens not recovered in blood cultures.

Machine learning identification of specific changes in myeloid cell phenotype during bloodstream infections

The early identification of bacteremia is critical for ensuring appropriate treatment of nosocomial infections in intensive care unit (ICU) patients. The aim of this study was to use flow cytometric data of myeloid cells as a biomarker of bloodstream infection (BSI). An eight-color antibody panel was used to identify seven monocyte and two dendritic cell subsets. In the learning cohort, immunophenotyping was applied to (1) control subjects, (2) postoperative heart surgery patients, as a model of noninfectious inflammatory responses, and (3) blood culture-positive patients. Of the complex changes in the myeloid cell phenotype, a decrease in myeloid and plasmacytoid dendritic cell numbers, increase in CD14⁺CD16⁺ inflammatory monocyte numbers, and upregulation of neutrophils CD64 and CD123 expression were prominent in BSI patients. An extreme gradient boosting (XGBoost) algorithm called the “infection detection and ranging score” (iDAR), ranging from 0 to 100, was developed to identify infection-specific changes in 101 phenotypic variables related to neutrophils, monocytes and dendritic cells. The tenfold cross-validation achieved an area under the receiver operating characteristic (AUROC) of 0.988 (95% CI 0.985–1) for the detection of bacteremic patients. In an out-of-sample, in-house validation, iDAR achieved an AUROC of 0.85 (95% CI 0.71–0.98) in differentiating localized from bloodstream infection and 0.95 (95% CI 0.89–1) in discriminating infected from noninfected ICU patients. In conclusion, a machine learning approach was used to translate the changes in myeloid cell phenotype in response to infection into a score that could identify bacteremia with high specificity in ICU patients.

Choosing Wisely For Critical Care: The Next Five

OBJECTIVES

To formulate new "Choosing Wisely" for Critical Care recommendations that identify best practices to avoid waste and promote value while providing critical care.

DATA SOURCES

Semistructured narrative literature review and quantitative survey assessments.

STUDY SELECTION

English language publications that examined critical care practices in relation to reducing cost or waste.

DATA EXTRACTION

Practices assessed to add no value to critical care were grouped by category. Taskforce assessment, modified Delphi consensus building, and quantitative survey analysis identified eight novel recommendations to avoid wasteful critical care practices. These were submitted to the Society of Critical Care Medicine membership for evaluation and ranking.

DATA SYNTHESIS

Results from the quantitative Society of Critical Care Medicine membership survey identified the top scoring five of eight recommendations. These five highest ranked recommendations established Society of Critical Care Medicine's Next Five "Choosing" Wisely for Critical Care practices.

CONCLUSIONS

Five new recommendations to reduce waste and enhance value in the practice of critical care address invasive devices, proactive liberation from mechanical ventilation, antibiotic stewardship, early mobilization, and providing goal-concordant care. These recommendations supplement the initial critical care recommendations from the "Choosing Wisely" campaign.

Antimicrobial and resource utilization with T2 magnetic resonance for rapid diagnosis of bloodstream infections: systematic review with meta-analysis of controlled studies

Objectives: To compare antimicrobial and resource utilization with T2 Magnetic Resonance (T2MR) versus blood culture (BC) in patients with suspected bloodstream infection.Methods: We systematically searched MEDLINE, EMBASE, and CENTRAL for randomized trials or observational controlled studies of patients with suspected bloodstream infection receiving a diagnosis with T2MR or BC. Using an inverse variance meta-analysis model, we reported mortality using the risk ratio (RR) and the remaining outcomes as the mean difference (MD).Results: Fourteen studies were included in the meta-analysis. Time to detection (MD = -81 hours; p < 0.001) and time to species identification (MD = -77 hours; p < 0.001) were faster with T2MR. Patients testing positive on T2MR received targeted antimicrobial therapy faster (-42 hours; p < 0.001) and patients testing negative on T2MR were de-escalated from empirical therapy faster (-7 hours; p = 0.02) vs. BC. Length of intensive care unit stay (MD = -5.0 days; p = 0.03) and hospital stay (MD = -4.8 days; p = 0.03) were shorter with T2MR. Mortality rates were comparable between T2MR and BC (28.9% vs. 29.9%, RR = 1.02, p = 0.86).Conclusion: Utilization of T2MR for identification of bloodstream pathogens provides faster time to detection, faster transition to targeted microbial therapy, faster de-escalation of empirical therapy, shorter ICU and hospital stay, and with comparable mortality rate versus BC.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Antimicrobial Peptides as Probes in Biosensors Detecting Whole Bacteria: A Review

Bacterial resistance is becoming a global issue due to its rapid growth. Potential new drugs as antimicrobial peptides (AMPs) are considered for several decades as promising candidates to circumvent this threat. Nonetheless, AMPs have also been used more recently in other settings such as molecular probes grafted on biosensors able to detect whole bacteria. Rapid, reliable and cost-efficient diagnostic tools for bacterial infection could prevent the spread of the pathogen from the earliest stages. Biosensors based on AMPs would enable easy monitoring of potentially infected samples, thanks to their powerful versatility and integrability in pre-existent settings. AMPs, which show a broad spectrum of interactions with bacterial membranes, can be tailored in order to design ubiquitous biosensors easily adaptable to clinical settings. This review aims to focus on the state of the art of AMPs used as the recognition elements of whole bacteria in label-free biosensors with a particular focus on the characteristics obtained in terms of threshold, volume of sample analysable and medium, in order to assess their workability in real-world applications.

Identification of New Peptide Biomarkers for Bacterial Bloodstream Infection

PURPOSE

Due to a lack of effective early diagnostic measures, new diagnostic methods for bacterial bloodstream infections (BSIs) are urgently needed. A protein-peptide profiling approach can be used to identify novel diagnostic biomarkers of BSIs.

EXPERIMENTAL DESIGN

In this study, MALDI-TOF MS and nano-LC/ESI-MS/MS are used to analyze serum peptides. In addition, GO and network analyses are conducted as a means of analyzing these potential protein markers. Finally, the potential biomarkers are verified in independent clinical samples via ELISA.

RESULTS

m/z 1533.8, 2794.3, 3597.3, 5007.3, and 7816.7 reveal an identical trend; the intensity of m/z 1533.8, 2794.3, and 3597.3 are higher in the infection group relative to controls, whereas the intensity of m/z 5007.3 and 7816.7 are lower in the infection group. Four peaks are successfully identified including ITIH4, KNG1, SAA2, and C3. GO and network analyses find these proteins to form an interaction network, which may be correlated with BSI. ELISA results indicate that ITIH4, KNG1, and SAA2 are effective in differentiating infected from normal control group and the febrile group.

CONCLUSIONS AND CLINICAL RELEVANCE

These biomarkers have the potential to offer new insights into the signaling networks underlying the development and progression of BSI.