Direct Detection of Pathogens in Bloodstream During Sepsis: Are We There Yet?

Early Diagnosis of Bloodstream Infections Using Serum Metabolomic Analysis

BACKGROUND

Bloodstream infections (BSIs) pose a great challenge to treating patients, especially those with underlying diseases, such as immunodeficiency diseases. Early diagnosis helps to direct precise empirical antibiotic administration and proper clinical management. This study carried out a serum metabolomic analysis using blood specimens sampled from patients with a suspected infection whose routine culture results were later demonstrated to be positive.

METHODS

A liquid chromatograph-mass spectrometry-based metabolomic analysis was carried out to profile the BSI serum samples. The serum metabolomics data could be used to successfully differentiate BSIs from non-BSIs.

RESULTS

The major classes of the isolated pathogens (e.g., Gram-positive and Gram-negative bacteria) could be differentiated using our optimized statistical algorithms. In addition, by using different machine-learning algorithms, the isolated pathogens could also be classified at the species levels (e.g., Escherichia coli and Klebsiella pneumoniae) or according to their specific antibiotic-resistant phenotypes (e.g., extended-spectrum β-lactamase-producing and non-producing phenotypes) if needed.

CONCLUSIONS

This study provides an early diagnosis method that could be an alternative to the traditional time-consuming culture process to identify BSIs. Moreover, this metabolomics strategy was less affected by several risk factors (e.g., antibiotics administration) that could produce false culture results.

A host immune-related LncRNA and mRNA signature as a discriminant classifier for bacterial from non-bacterial sepsis in children

Background

The variations in non-coding RNA alterations and the host immune response between patients with bacterial and non-bacterial sepsis, along with their clinical characteristics, are largely unknown.

Methods

The landscape of long non-coding RNA (lncRNA) and mRNA in whole blood cells from pediatric patients with bacterial sepsis or non-bacterial sepsis were characterized using an Arraystar human LncRNA microarray. Weighted correlation network analysis (WGCNA) were conducted to identify immune-related LncRNA-mRNA signatures. Least absolute shrinkage and selection operator (Lasso) regression and Ridge regression analysis were employed to develop a specific LncRNA-mRNA signature, serving as a discriminant classifier for bacterial and non-bacterial sepsis in children.

Results

A total of 33 differentially expressed lncRNAs and 52 mRNAs were identified in pediatric patients with either bacterial sepsis or non-bacterial sepsis. Among these, 69 lncRNAs and mRNAs were pinpointed using WGCNA and found to be significantly correlated with clinical parameters. Further intersection analysis identified 12 lncRNAs and 16 mRNAs as immune-related signature for discerning bacterial infections in children with sepsis. Additionaly, the lncRNA-mRNA co-expression network highlighted the key lncRNAs (AC090159.1 and AC080129.2) and mRNAs (S100A8 and TCF7L2) as an infection score model. Lasso regression analysis revealed that this infection score model achieved an area under the received operating curve (AUROC) of 0.96 in the training set and 0.86 in the validation set. Ultimately, the expression levels of these 4 key lncRNAs and mRNAs showed significant correlation with CRP or PCT levels.

Conclusion

The machine learning model, developed utilizing key lncRNAs (AC090159.1 and AC080129.2) and mRNAs (S100A8 and TCF7L2), demonstrates robust discrimination and calibration capabilities for distinguishing between bacterial and non-bacterial sepsis in children.

Development of a One-Step Multiplex qPCR Assay for Detection of Methicillin and Vancomycin Drug Resistance Genes in Antibiotic-Resistant Bacteria

The most common antibiotic-resistant bacteria in Korea are methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE). Pathogen identification in clinical laboratories can be divided into traditional phenotype- and genotype-based methods, both of which are complementary to each other. The genotype-based method using multiplex real-time polymerase chain reaction (PCR) is a rapid and accurate technique that analyzes material at the genetic level by targeting genes simultaneously. Accordingly, we aimed to develop a rapid method for studying the genetic characteristics of antibiotic-resistant bacteria and to provide an experimental guide for the efficient antibiotic resistance gene analysis of mecA detection for MRSA and vanA or vanB detection for VRE using a one-step multiplex qPCR assay at an early stage of infection. As a result, the sensitivity and specificity of the mecA gene for clinical S. aureus isolates, including MRSA and methicillin-susceptible S. aureus, were 97.44% (95% CI, 86.82-99.87%) and 96.15% (95% CI, 87.02-99.32%), respectively. The receiver operating characteristic area under the curve for the diagnosis of MRSA was 0.9798 (*** p < 0.0001). Therefore, the molecular diagnostic method using this newly developed one-step multiplex qPCR assay can provide accurate and rapid results for the treatment of patients with MRSA and VRE infections.

Assessing the Interpretation of Molecular Test Results in the Diagnosis of Bloodstream Infections

A retrospective study at the 4th Military Clinical Hospital in Wroclaw, Poland, assessed PCR testing alongside blood cultures to guide antimicrobial therapy decisions in hospitalized patients, to determine how much time the results of the molecular tests preceded conventional methods. Among 118 patients, Staphylococcus aureus (37%) and Escherichia coli (21%) were the most common bloodstream infection agents. Blood cultures utilized the BacT/ALERT 3D system, and molecular diagnostics were conducted using the FilmArray platform with the BIOFIRE BCID2 panel. Methicillin susceptibility was observed in 66% of S. aureus strains, while 26% of Gram-negative bacilli exhibited an ESBL phenotype. Therapeutic decisions based on molecular test results were often incorrect for S. aureus infections, particularly MSSA (64.5%), but generally accurate for Gram-negative bacilli. The median times from positive blood culture to BCID2 and pathogen identification/susceptibility were 10 h and 52 h, respectively. Molecular diagnostics facilitated faster initiation of appropriate antibiotic therapy, highlighting the need to educate medical staff on proper interpretation. Consulting within an antimicrobial stewardship program (ASP) could enhance the benefits of implementing molecular methods in bloodstream infection diagnostics.

Using the Traditional Ex Vivo Whole Blood Model to Discriminate Bacteria by Their Inducible Host Responses

Whole blood models are rapid and versatile for determining immune responses to inflammatory and infectious stimuli, but they have not been used for bacterial discrimination. Staphylococcus aureus, S. epidermidis and Escherichia coli are the most common causes of invasive disease, and rapid testing strategies utilising host responses remain elusive. Currently, immune responses can only discriminate between bacterial 'domains' (fungi, bacteria and viruses), and very few studies can use immune responses to discriminate bacteria at the species and strain level. Here, whole blood was used to investigate the relationship between host responses and bacterial strains. Results confirmed unique temporal profiles for the 10 parameters studied: IL-6, MIP-1α, MIP-3α, IL-10, resistin, phagocytosis, S100A8, S100A8/A9, C5a and TF3. Pairwise analysis confirmed that IL-6, resistin, phagocytosis, C5a and S100A8/A9 could be used in a discrimination scheme to identify to the strain level. Linear discriminant analysis (LDA) confirmed that (i) IL-6, MIP-3α and TF3 could predict genera with 95% accuracy; (ii) IL-6, phagocytosis, resistin and TF3 could predict species at 90% accuracy and (iii) phagocytosis, S100A8 and IL-10 predicted strain at 40% accuracy. These data are important because they confirm the proof of concept that host biomarker panels could be used to identify bacterial pathogens.

Direct-from-Blood Detection of Pathogens: a Review of Technology and Challenges

Blood cultures have been the staple of clinical microbiology laboratories for well over half a century, but gaps remain in our ability to identify the causative agent in patients presenting with signs and symptoms of sepsis. Molecular technologies have revolutionized the clinical microbiology laboratory in many areas but have yet to present a viable alternative to blood cultures. There has been a recent surge of interest in utilizing novel approaches to address this challenge. In this minireview, I discuss whether molecular tools will finally give us the answers we need and the practical challenges of incorporating them into the diagnostic algorithm.

Deep Learning-Assisted Surface-Enhanced Raman Scattering for Rapid Bacterial Identification

Bloodstream infection (BSI) is characterized by the presence of viable microorganisms in the bloodstream and may induce systemic immune responses. Early and appropriate antibiotic usage is crucial to effectively treating BSI. However, conventional culture-based microbiological diagnostics are time-consuming and cannot provide timely bacterial identification for subsequent antimicrobial susceptibility test (AST) and clinical decision-making. To address this issue, modern microbiological diagnostics have been developed, such as surface-enhanced Raman scattering (SERS), which is a sensitive, label-free, and quick bacterial detection method measuring specific bacterial metabolites. In this study, we aim to integrate a new deep learning (DL) method, Vision Transformer (ViT), with bacterial SERS spectral analysis to build the SERS-DL model for rapid identification of Gram type, species, and resistant strains. To demonstrate the feasibility of our approach, we used 11,774 SERS spectra obtained directly from eight common bacterial species in clinical blood samples without artificial introduction as the training dataset for the SERS-DL model. Our results showed that ViT achieved excellent identification accuracy of 99.30% for Gram type and 97.56% for species. Moreover, we employed transfer learning by using the Gram-positive species identifier as a pre-trained model to perform the antibiotic-resistant strain task. The identification accuracy of methicillin-resistant and -susceptible Staphylococcus aureus (MRSA and MSSA) can reach 98.5% with only 200-dataset requirement. In summary, our SERS-DL model has great potential to provide a quick clinical reference to determine the bacterial Gram type, species, and even resistant strains, which can guide early antibiotic usage in BSI.

The diagnostic value of next-generation sequencing technology in sepsis

Objective

This study aims to assess the clinical utility of next-generation sequencing (NGS) in sepsis diagnosis.

Methods

A prospective study was conducted on patients with a high suspicion of sepsis by unknown pathogens from January 2017 to December 2021. Blood samples were taken from patients to perform NGS, blood culture (BC), leucocyte (WBC), procalcitonin (PCT), creatinine (CREA), Albumin (ALB) and C-reactive protein (CRP) tests.

Results

The feedback time for BC was 3~5 days for bacteria and 5~7 days for fungi, while the turnover time for NGS was only 24 h. The clinical diagnosis was considered the “gold standard”. 83 patients passed our inclusion criteria and were separated into two groups by clinical diagnosis. 62 met the clinical diagnosis criteria for sepsis and 21 were non-sepsis. The data from the two groups were retrospectively compared and analyzed. Of 62 sepsis in 83 patients, 8(9.64%) were diagnosed by both BC and NGS, 51 (61.45%) by NGS only, 1(1.20%) by BC and 2 (2.41%) by conventional testing only; PCT, CREA, CRP levels and the detection rate of NGS and BC were higher in the sepsis group than in the non-sepsis group, while ALB levels were lower (p&lt;0.05). The logistic regression results in our study revealed that NGS and ALB were independent prediction factors for sepsis (p&lt;0.05), the area under the receiver operating characteristic curve (AUC), sensitivity and specificity of NGS for diagnosing sepsis was 0.857, 95.16% and 76.19%, while ALB was 0.728, 58.06%, 80.95%, respectively. The combination’s sensitivity, specificity and AUC of NGS and ALB were 93.55%, 85.71% and 0.935, greater than that of Albumin or NGS only (both p&lt;0.05).

Conclusion

NGS can effectively and quickly identify pathogens, thereby emerges as a promising technology for sepsis diagnosis. Combination of NGS and ALB can be used for early screening and is more powerful than NGS or ALB only.

Clinical evaluation of cell-direct polymerase chain reaction-based nucleic acid lateral flow immunoassay for rapid detection of bacterial pathogens in clinically suspected sepsis: A multi-center study in Japan

Blood culture, a method for identifying causative agents of bacterial sepsis, requires several days. The combination of cell-direct polymerase chain reaction and nucleic acid lateral flow immunoassay (cdPCR-NALFIA) is a simple and sensitive detection method for identifying pathogenic bacteria. Furthermore, this assay, when applied directly to blood samples yields results within 4.5 h, without requiring culture. This study was performed at five hospitals in Japan between 2013 and 2016. Blood samples from 73 patients with clinically suspected sepsis yielded 18 positive blood cultures, and the isolated bacterial species were detectable using cdPCR-NALFIA in nine samples. Thirteen samples were positive on cdPCR-NALFIA. In total, 17 samples confirmed to have bacterial species were detectable using cdPCR-NALFIA and/or blood culture with a true positive rate of 76.5% and 64.7%, respectively. The combination of blood culture and cdPCR-NALFIA could improve the rate of detection of bacterial sepsis.

Utility of Metagenomic Next-Generation Sequencing for Etiological Diagnosis of Patients with Sepsis in Intensive Care Units

The performance of metagenomic next-generation sequencing (mNGS) was evaluated and compared with that of conventional culture testing in patients with sepsis. Prospective blood and bronchoalveolar lavage fluid (BALF) samples from 50 patients with sepsis were tested using cultures (bacterial, fungal, and viral) and mNGS of microbial DNA (blood and BALF) and RNA (BALF). mNGS had higher detection rates than blood culture (88.0% versus 26.0%, P < 0.001) and BALF culture (92.0% versus 76.0%, P = 0.054). RNA-based mNGS has increased the detection rate of several bacteria, fungi, and viruses, but not mycobacteria and Toxoplasma gondii. The number of multiple detections per specimen was higher in BALF (92.0%) than in blood (78.0%) samples, and the highest number of pathogens detected in a single specimen was 32. Among blood samples, compared to cultures, mNGS detected significantly more bacteria (P < 0.001), fungi (P = 0.012), and viruses (P < 0.001), whereas BALF mNGS had a higher detection rate for bacteria (P < 0.001) and viruses (P < 0.001). The percentage of mNGS-positive samples was significantly higher than that of culture-positive samples for several Gram-negative bacteria, some Gram-positive bacteria, and viruses, but not fungi. Mycobacteria had a higher detection rate by culture than by mNGS, but the difference was not significant due to the small sample size. The positive and negative agreements with 95% confidence intervals of mNGS and culture were 62.0% (50.4 to 72.7) and 96.8% (96.5 to 97.1), respectively. mNGS offers a sensitive diagnostic method for patients with sepsis and is promising for the detection of multipathogen infections. Clinical correlation is advised to interpret mNGS data due to the lack of unified diagnostic criteria.

IMPORTANCE Delays in effective antimicrobial therapy have resulted in decreased survival rates among patients with sepsis. However, current culture-based diagnostic methods have low sensitivity because of concurrent antibiotic exposure and fastidious and atypical causative organisms. Among patients with sepsis, we showed that mNGS methods had higher positive rates than culture methods, especially for bacteria, viruses, and multipathogen infections, which are difficult to culture and detect in patients treated with antibiotics. RNA-based mNGS has increased the detection rate of several bacteria, fungi, and viruses, but not mycobacteria and Toxoplasma gondii. mNGS also showed a high negative percent agreement with cultures. However, the interpretation of mNGS data should be combined with clinical data and conventional methods considering the lack of unified diagnostic criteria.

A metagenomic DNA sequencing assay that is robust against environmental DNA contamination

Metagenomic DNA sequencing is a powerful tool to characterize microbial communities but is sensitive to environmental DNA contamination, in particular when applied to samples with low microbial biomass. Here, we present Sample-Intrinsic microbial DNA Found by Tagging and sequencing (SIFT-seq) a metagenomic sequencing assay that is robust against environmental DNA contamination introduced during sample preparation. The core idea of SIFT-seq is to tag the DNA in the sample prior to DNA isolation and library preparation with a label that can be recorded by DNA sequencing. Any contaminating DNA that is introduced in the sample after tagging can then be bioinformatically identified and removed. We applied SIFT-seq to screen for infections from microorganisms with low burden in blood and urine, to identify COVID-19 co-infection, to characterize the urinary microbiome, and to identify microbial DNA signatures of sepsis and inflammatory bowel disease in blood.

An antibiotic concentration gradient microfluidic device integrating surface-enhanced Raman spectroscopy for multiplex antimicrobial susceptibility testing

Antimicrobial susceptibility testing (AST) is a key measure in clinical microbiology laboratories to enable appropriate antimicrobial administration. During an AST, the determination of the minimum inhibitory concentration (MIC) is an important step in which the bacterial responses to an antibiotic at a series of concentrations obtained in separate bacterial growth chambers or sites are compared. However, the preparation of different antibiotic concentrations is time-consuming and labor-intensive. In this paper, we present a microfluidic device that generates a concentration gradient for antibiotics that is produced by diffusion in the laminar flow regime along a series of lateral microwells to encapsulate bacteria for antibiotic treatment. All the AST preparation steps (including bacterium loading, antibiotic concentration generation, buffer washing, and isolated bacterial growth with an antibiotic) can be performed in a single chip. The viable bacterial cells in each microwell after the antibiotic treatment are then quantified by their surface-enhanced Raman scattering (SERS) signals that are acquired after placing a uniform SERS-active substrate in contact with all the microwells. For proof-of-concept, we demonstrated the AST performance of this system on ampicillin (AMP)-susceptible and -resistant E. coli strains. Compared with the parameters for conventional AST methods, the AST procedure based on this chip requires only 20 μL of bacteria solution and 5 h of operation time. This result indicates that this integrated system can greatly shorten and simplify the tedious and labor-intensive procedures required for current standard AST methods.

The Impact of the FilmArray-Based Detection of Microbial Pathogens from Positive Blood Culture Vials on the Time to Optimal Antimicrobial Regimen in Intensive Care Units of the Helios University Clinic Wuppertal, Germany

The role of empirical therapy and time to first effective treatment, including the antimicrobial stewardship program, are decisive in patients presenting with bloodstream infections (BSI). The FilmArray^® Blood Culture Identification Panel (FA BCID 1.0) detects 24 bacterial and fungal pathogens as well as 3 resistance genes from positive blood cultures in approximately 70 min. In this paper, we evaluate the impact of the additional FA BCID analysis on the time to an optimal antimicrobial therapy and on the length of stay in the ICU, ICU mortality, and PCT level reduction. This retro-/prospective trial was conducted in BSI patients in the ICU at a German tertiary care hospital. A total of 179 individual patients with 200 episodes of BSI were included in the prospective intervention group, and 150 patients with 170 episodes of BSI in the retrospective control group. In the intervention group, BSI data were analyzed including the MALDI-TOF MS (matrix assisted laser desorption ionization time-of-flight mass spectrometry) and FA BCID results from January 2019 to August 2020; the data from the control group, including the MALDI-TOF results, were collected retrospectively from the year 2018. The effective and appropriate antimicrobial regimen occurred in a median of 17 hours earlier in the intervention versus control group (p = 0.071). Furthermore, changes in the antimicrobial regimens of the intervention group that did not immediately lead to an optimal therapy occurred significantly earlier by a median of 24 hours (p = 0.029). Surrogate markers, indicating an earlier recovery of the patients from the intervention group, such as length of stay at the ICU, duration of mechanical ventilation, or an earlier reduction in PCT level, were not significantly affected. However, mortality did not differ between the patient groups. A postulated reduction of the antimicrobial therapy, in those cases in which coagulase-negative Staphylococcus species were identified, did occur in the control group, but not in the intervention group (p = 0.041). The implementation of FA BCID into the laboratory workflow can improve patient care by optimizing antimicrobial regimen earlier in BSI patients as it provides rapid and accurate results for key pathogens associated with BSI, as well as important antimicrobial resistance markers, e.g., mecA or vanA.

Direct Testing for KPC-Mediated Carbapenem Resistance from Blood Samples Using a T2 Magnetic Resonance Based Assay

Molecular-based carbapenem resistance testing in Gram-negative bacterial bloodstream infections (BSIs) is currently limited because of the reliance on positive blood culture (BC) samples. The T2Resistance™ panel may now allow the detection of carbapenemase- and other β-lactamase encoding genes directly from blood samples. We detected carbapenem resistance genes in 11 (84.6%) of 13 samples from patients with BC-documented BSIs (10 caused by KPC-producing Klebsiellapneumoniae and 1 caused by VIM/CMY-producing Citrobacter freundii). Two samples that tested negative for carbapenem resistance genes were from patients with BC-documented BSIs caused by KPC-producing K. pneumoniae who were receiving effective antibiotic therapy. In conclusion, our findings suggest that the T2Resistance™ panel can be a reliable tool for diagnosing carbapenem-resistant Gram-negative bacterial BSIs.

A Pragmatic Machine Learning Model To Predict Carbapenem Resistance

Infection caused by carbapenem-resistant (CR) organisms is a rising problem in the United States. While the risk factors for antibiotic resistance are well known, there remains a large need for the early identification of antibiotic-resistant infections. Using machine learning (ML), we sought to develop a prediction model for carbapenem resistance. All patients >18 years of age admitted to a tertiary-care academic medical center between 1 January 2012 and 10 October 2017 with ≥1 bacterial culture were eligible for inclusion. All demographic, medication, vital sign, procedure, laboratory, and culture/sensitivity data were extracted from the electronic health record. Organisms were considered CR if a single isolate was reported as intermediate or resistant. Patients with CR and non-CR organisms were temporally matched to maintain the positive/negative case ratio. Extreme gradient boosting was used for model development. In total, 68,472 patients met inclusion criteria, with 1,088 patients identified as having CR organisms. Sixty-seven features were used for predictive modeling. The most important features were number of prior antibiotic days, recent central venous catheter placement, and inpatient surgery. After model training, the area under the receiver operating characteristic curve was 0.846. The sensitivity of the model was 30%, with a positive predictive value (PPV) of 30% and a negative predictive value of 99%. Using readily available clinical data, we were able to create a ML model capable of predicting CR infections at the time of culture collection with a high PPV.

A new molecular method for rapid etiological diagnosis of sepsis with improved performance

The value of blood cultures for confirming the clinical diagnosis of sepsis is suboptimal. There is growing interest in the potential of real-time PCR technology by detection of minute amounts of pathogen DNA in patient blood samples with results available within 4-6 h. Adopting a two-step approach, we evaluated the compliance of two versions of the MicrobScan assay on a total of 748 patients with suspected bloodstream infections. The results obtained with a second version of the MicrobScan assay are characterized by increased specificity (from 95.1 to 98.2%) and sensitivity (from 76.7 to 85.1), increased throughput and the possibility of simultaneously testing different kinds of samples collected from the potential sites of infection and utilizing different syndromic panels.

Sheathless and high-throughput elasto-inertial bacterial sorting for enhancing molecular diagnosis of bloodstream infection

Purification of bacteria from human blood samples is essential for rapid identification of pathogens by molecular methods, enabling faster and more accurate diagnosis of bloodstream infection than conventional gold standard blood culture methods. The inertial microfluidic method has been broadly studied to isolate biological cells of interest in various biomedical applications due to its label-free and high-throughput advantages. However, because of the bacteria's tininess, which ranges from 0.5 μm to 3 μm, they are challenging to be effectively focused and sorted out in existing inertial microfluidic devices that work well with biological cells larger than 10 μm. Efforts have been made to sort bacterial cells by utilizing extremely small channel dimensions or employing a sheath flow, which thus results in limitations on the throughput and ease of operation. To overcome this challenge, we develop a method that integrates a non-Newtonian fluid with a novel channel design to allow bacteria to be successfully sorted from larger blood cells in a channel dimension of 120 μm × 20 μm without the use of sheath flows. The throughput of this device with four parallel channels is above 400 μL per minute. The real-time polymerase chain reaction (qPCR) analysis indicates that our inertial sorting approach has a nearly 3-fold improvement in pathogen recovery compared with the commonly used lysis-centrifugation method at pathogen abundances as low as 102 cfu mL-1. With the rapid and simple purification and enrichment of bacterial pathogens, the present inertial sorting method exhibits an ability to enhance the fast and accurate molecular diagnosis of bloodstream bacterial infection.

Monocyte distribution width (MDW) parameter as a sepsis indicator in intensive care units

OBJECTIVES

Patients in Intensive Care Units (ICU) are a high-risk population for sepsis, recognized as a major cause of admission and death. The aim of the current study was to evaluate the diagnostic accuracy and prognostication of monocyte distribution width (MDW) in sepsis for patients admitted to ICU.

METHODS

Between January and June 2020, we conducted a prospective observational study during the hospitalization of 506 adult patients admitted to the ICU. MDW was evaluated in 2,367 consecutive samples received for routine complete blood counts (CBC) performed once a day and every day during the study. Sepsis was diagnosed according to Sepsis-3 criteria and patients enrolled were classified in the following groups: no sepsis, sepsis and septic shock.

RESULTS

MDW values were significantly higher in patients with sepsis or septic shock in comparison to those within the no sepsis group [median 26.23 (IQR: 23.48-29.83); 28.97 (IQR: 21.27-37.21); 21.99 (IQR: 19.86-24.36) respectively]. ROC analysis demonstrated that AUC is 0.785 with a sensitivity of 66.88% and specificity of 77.79% at a cut-off point of 24.63. In patients that developed an ICU-acquired sepsis MDW showed an increase from 21.33 [median (IQR: 19.47-21.72)] to 29.19 [median (IQR: 27.46-31.47)]. MDW increase is not affected by the aetiology of sepsis, even in patients with COVID-19. In sepsis survivors a decrease of MDW values were found from the first time to the end of their stay [median from 29.14 (IQR: 26.22-32.52) to 25.67 (IQR: 22.93-30.28)].

CONCLUSIONS

In ICU, MDW enhances the sepsis detection and is related to disease severity.

Real-time PCR versus MALDI-TOF MS and culture-based techniques for diagnosis of bloodstream and pyogenic infections in humans and animals

AIMS

This study was applied to evaluate the usefulness of a high-throughput sample preparation protocol prior to the application of quantitative real-time PCR (qPCR) for the early diagnosis of bloodstream and pyogenic infections in humans and animals compared to matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) and classical culture.

METHODS AND RESULTS

Saponin-mediated selective host cell lysis combined with DNase-1 was applied for processing of whole blood and pus clinical samples collected from suspected cases of septicaemia and pyogenic infections in humans and animals. The pre-PCR processing strategy enabled the recovery of microbial cells with no changes in their colony forming units immediately after the addition of saponin. DNase-1 was efficient for removing the DNAs from the host cells as well as dead cells with damaged cell membranes. The metagenomic qPCR and MALDI-TOF MS could identify the bacterial community of sepsis at species level with a concordance of 97·37% unlike the conventional culture. According to qPCR results, Staphylococcus aureus (24·24%) was predominated in animal pyogenic infections, whereas Klebsiella pneumonia (31·81%) was commonly detected in neonatal sepsis.

CONCLUSIONS

Saponin combined with DNase-1 allowed the efficient recovery of microbial DNA from blood and pus samples in sepsis using qPCR assay.

SIGNIFICANCE AND IMPACT OF THE STUDY

Metagenomic qPCR could identify a broad range of bacteria directly from blood and pus with more sensitivity, higher discriminatory power and shorter turnaround time than those using MALDI-TOF MS and conventional culture. This might allow a timely administration of a prompt treatment.

Efficient Early Diagnosis of Sepsis Using Whole-Blood PCR-Reverse Blot Hybridization Assay Depending on Serum Procalcitonin Levels

Sepsis is one of the medical emergencies, and its early detection, within the first hours of development, and proper management improve outcomes. Molecular diagnostic assays using whole blood collected from patients with suspected sepsis have been developed, but the decision making is difficult because of the possibility of false positives, due to contamination. Here, we evaluated the performance of the reverse blot hybridization assay (REBA) Sepsis-ID test for the detection of sepsis-causing microorganisms using whole-blood samples. In addition, the concentrations of C-reactive protein (CRP) and procalcitonin (PCT) were determined to evaluate whether these biomarkers can provide criteria for performing REBA Sepsis-ID in clinical settings. For this study, EDTA-anticoagulated whole blood was simultaneously collected for REBA Sepsis-ID and blood culture from 440 patients with suspected sepsis, from January to October 2015. In addition, CRP and PCT concentrations were measured in 227 patients. The overall positive rates of REBA Sepsis-ID and blood culture were 16.6% (73/440) and 13.9% (61/440), respectively. The pathogen-positive rates of REBA Sepsis-ID and blood culture were 9.8% (43/440) and 9.5% (42/440), respectively. The areas under the receiver operating characteristic (AUROC) curves of PCT and CRP for predicting pathogen-positive results of REBA Sepsis-ID were 0.72 and 0.69, respectively. The PCT concentrations in the group of patients aged ≥50 years were significantly higher than those in the group aged <50 years. After adjusting for age, the PCT AUROC value was 0.77 for predicting pathogen-positive results of REBA Sepsis-ID. The optimal cutoff values of PCT concentrations for subsequent application of REBA Sepsis-ID were 0.12 ng/mL in all patients and 0.22 ng/mL in patients aged ≥50 years. Our observations showed that REBA Sepsis-ID using whole blood was advantageous for the early detection of sepsis-causing microorganisms, and the PCT concentration could be used to determine the necessity of using REBA Sepsis-ID in clinical settings. The application of REBA Sepsis-ID using whole blood, based on the PCT concentration, may contribute to a highly efficient detection of sepsis-causing microorganisms.

Rapid antibiotic susceptibility testing of bacteria from patients' blood via assaying bacterial metabolic response with surface-enhanced Raman spectroscopy

Blood stream infection is one of the major public health issues characterized with high cost and high mortality. Timely effective antibiotics usage to control infection is crucial for patients’ survival. The standard microbiological diagnosis of infection however can last days. The delay in accurate antibiotic therapy would lead to not only poor clinical outcomes, but also to a rise in antibiotic resistance due to widespread use of empirical broad-spectrum antibiotics. An important measure to tackle this problem is fast determination of bacterial antibiotic susceptibility to optimize antibiotic treatment. We show that a protocol based on surface-enhanced Raman spectroscopy can obtain consistent antibiotic susceptibility test results from clinical blood-culture samples within four hours. The characteristic spectral signatures of the obtained spectra of Staphylococcus aureus and Escherichia coli—prototypic Gram-positive and Gram-negative bacteria—became prominent after an effective pretreatment procedure removed strong interferences from blood constituents. Using them as the biomarkers of bacterial metabolic responses to antibiotics, the protocol reported the susceptibility profiles of tested drugs against these two bacteria acquired from patients’ blood with high specificity, sensitivity and speed.

Blood culture contamination in a tertiary care hospital of Saudi Arabia. A one-year study

Objectives:

To monitor blood culture contamination (BCC) rates in a tertiary care hospital in Saudi Arabia.

Methods:

Blood cultures submitted to the Microbiology Laboratory of King Fahad Hospital, Madina, Saudi Arabia between January and December 2017 were analyzed prospectively. Positive blood cultures were either designated as true bacteremia with confirmed bloodstream infection or BCC.

Results:

Among 5,536 blood cultures from 2201 patients, 364 (6.6%) mirrored BCC. There was an upward trend in contamination rates in specific months. With respect to total blood cultures from respective units over a one-year period, medical ward contributed to the highest contamination rate (10.3%). Blood culture contamination rate in the wards ranged from 4.5-10.3%, with a higher contamination rate in elderly, aged 60-80 years. Staphylococcus epidermidis (S. epidermidis) was the most frequent contaminant (44.5%).

Conclusion:

The escalated contamination rates in September to October may be attributed to difficulty in sampling blood by the less competent nurses during annual pilgrimage season. High influx of patients and shortage of trained nurses may have resulted in increased incidence in December-January and March-April. The prevalence of skin-resident S. epidermidis may be due to improper aseptic conditions. Ours is the first report on evaluation of BCC rates in Madina and call for renewed efforts in this direction.