Blood Culture Turnaround Time in U.S. Acute Care Hospitals and Implications for Laboratory Process Optimization

Admission Neutrophil-to-Lymphocyte Ratio Is Superior to WBC Count at Predicting the Presence and Severity of Pediatric Musculoskeletal Infection

BACKGROUND

Accurately determining the presence and severity of pediatric musculoskeletal infection (MSKI) is crucial for effective triage and treatment. Although the white blood-cell (WBC) count is often used as a marker for MSKI, we hypothesized that the use of the WBC count is limited by age-related variability in children. We proposed that the absolute neutrophil-to-lymphocyte ratio (NLR), which has less age-related variability, is a more reliable indicator for both diagnosing and assessing the severity of MSKI. The present study aims to compare the utility of WBC against that of the NLR, as well as C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR), for predicting MSKI presence and severity in children.

METHODS

A retrospective cohort study was conducted with use of a database of pediatric orthopaedic consultations for suspected MSKI between January 2013 and July 2022. Diagnoses were categorized as MSKI or no infection, and the severity of any present infection was stratified as local or disseminated. Admission laboratory values were collected. Statistical modeling was performed to assess the capabilities of the WBC, NLR, CRP, and ESR to diagnose MSKI and to assess infection severity, with cutoff thresholds established for clinical use.

RESULTS

This study included 650 patients (median age, 5.2 years; 63% male; 75% White). Of these, 247 patients had no infection, while 403 were diagnosed with an MSKI. Median WBC count, NLR, CRP, and ESR were all significantly higher in pediatric cases of confirmed MSKI. WBC was a poor predictor of infection severity, whereas NLR, CRP, and ESR each positively correlated with infection severity. At the time of admission, an NLR of 4 was highly specific for detecting the presence of infection, and an NLR of 5.8 was highly specific for predicting infection dissemination. CRP was the best predictor of both infection presence and severity, demonstrating the highest specificity and sensitivity, followed by NLR, which outperformed ESR and WBC.

CONCLUSIONS

Because of considerable age-related variability, the predictive value of the WBC count for pediatric MSKI presence and severity is limited. NLR, which is less affected by age-related variability, is superior at predicting MSKI severity. Although CRP remains the benchmark, the NLR offers a valuable alternative to the WBC. Our study provides a comparative framework for these biomarkers, enhancing MSKI assessment across various clinical settings.

LEVEL OF EVIDENCE

Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Predicting appropriateness of antibiotic treatment among ICU patients with hospital-acquired infection

Antimicrobial resistance is a rising global health threat, leading to ineffective treatments, increased mortality and rising healthcare costs. In ICUs, inappropriate empiric antibiotic therapy is often given due to treatment urgency, causing poor outcomes. This study developed a machine learning model to predict the appropriateness of empiric antibiotics for ICU-acquired bloodstream infections, using data from the MIMIC-III database. To address missing values and dataset imbalances, novel computational methods were introduced. The model achieved an AUROC of 77.3% and AUPRC of 40.4% on validation, with similar results on external datasets from MIMIC-IV and Rambam Hospital. The model also predicted mortality risk, identifying a 30% mortality rate in high-risk patients versus 16.8% in low-risk groups. External validation on the eICU database showed a comparable gap, with mortality rates at 24% for high-risk and 7.7% for low-risk groups. Our study demonstrates the potential of machine learning models to predict inappropriate empiric antibiotic treatment.

Advances in diagnosis and prognosis of bacteraemia, bloodstream infection, and sepsis using machine learning: A comprehensive living literature review

BACKGROUND

Blood-related infections are a significant concern in healthcare. They can lead to serious medical complications and even death if not promptly diagnosed and treated. Throughout time, medical research has sought to identify clinical factors and strategies to improve the management of these conditions. The increasing adoption of electronic health records has led to a wealth of electronically available medical information and predictive models have emerged as invaluable tools. This manuscript offers a detailed survey of machine-learning techniques used for the diagnosis and prognosis of bacteraemia, bloodstream infections, and sepsis shedding light on their efficacy, potential limitations, and the intricacies of their integration into clinical practice.

METHODS

This study presents a comprehensive analysis derived from a thorough search across prominent databases, namely EMBASE, Google Scholar, PubMed, Scopus, and Web of Science, spanning from their inception dates to October 25, 2023. Eligibility assessment was conducted independently by investigators, with inclusion criteria encompassing peer-reviewed articles and pertinent non-peer-reviewed literature. Clinical and technical data were meticulously extracted and integrated into a registry, facilitating a holistic examination of the subject matter. To maintain currency and comprehensiveness, readers are encouraged to contribute manuscript suggestions and/or reports for integration into this living registry.

RESULTS

While machine learning (ML) models exhibit promise in advanced disease stages such as sepsis, early stages remain underexplored due to data limitations. Biochemical markers emerge as pivotal predictors during early stages such as bacteraemia, or bloodstream infections, while vital signs assume significance in sepsis prognosis. Integrating temporal trend information into conventional machine learning models appears to enhance performance. Unfortunately, sequential deep learning models face challenges, showing minimal performance improvements and significant drops in external datasets, potentially due to learning missing patterns within the scarce data available rather than understanding disease dynamics. Real-life implementation receives limited attention, as meeting design requirements proves challenging within existing healthcare infrastructure. The data collected in an event-based fashion during clinical practice is insufficient to fully harness the potential of these data-hungry models. Despite limitations, opportunities abound in leveraging flexible models and exploiting real-time non-invasive data collection technologies such as wearable devices or microneedles. Addressing research gaps in early disease stages, harnessing patient history data often underused, and embracing continual diagnostics beyond treatment initiation are crucial for improving healthcare decision-making support and adoption across the entire management pathway.

CONCLUSIONS

This comprehensive survey illuminates the landscape of ML applications in blood-related infection management, offering insights for future research and clinical practice. Implementing clinical ML-based clinical decision support systems requires balancing research with practical considerations. Current methodologies often lead to complex models lacking transparency and practical validation. Integration into healthcare systems faces regulatory, privacy, and trust challenges. Clear presentations and adherence to standards are essential to boost confidence in machine learning models for real-world healthcare applications.

Multidrug-resistant Gram-negative bacterial infections

Multidrug-resistant Gram-negative bacterial infections cause significant morbidity and mortality globally. These pathogens easily acquire antimicrobial resistance (AMR), further highlighting their clinical significance. Third-generation cephalosporin-resistant and carbapenem-resistant Enterobacterales (eg, Escherichia coli and Klebsiella spp), multidrug-resistant Pseudomonas aeruginosa, and carbapenem-resistant Acinetobacter baumannii are the most problematic and have been identified as priority pathogens. In response, several new diagnostic technologies aimed at rapidly detecting AMR have been developed, including biochemical, molecular, genomic, and proteomic techniques. The last decade has also seen the licensing of multiple antibiotics that have changed the treatment landscape for these challenging infections.

Clinical evaluation of a multiplex droplet digital PCR for diagnosing suspected bloodstream infections: a prospective study

Background

Though droplet digital PCR (ddPCR) has emerged as a promising tool for early pathogen detection in bloodstream infections (BSIs), more studies are needed to support its clinical application widely due to different ddPCR platforms with discrepant diagnostic performance. Additionally, there is still a lack of clinical data to reveal the association between pathogen loads detected by ddPCR and corresponding BSIs.

Methods

In this prospective study, 173 patients with suspected BSIs were enrolled. A multiplex ddPCR assay was used to detect 18 pathogens. The results of ddPCR testing were evaluated in comparison with blood cultures (BCs) and clinical diagnosis. Taking BC as the gold standard, receiver operating characteristic curve and Cohen's kappa agreement were used to investigate whether the pathogen load could predict a corresponding culture-proven BSI for the top five microorganisms detected by ddPCR.

Results

Of the 173 blood samples collected, BC and ddPCR were positive in 48 (27.7%) and 92 (53.2%) cases, respectively. Compared to BC, the aggregate sensitivity and specificity for ddPCR were 81.3% and 63.2%, respectively. After clinical adjudication, the sensitivity and specificity of ddPCR increased to 88.8% and 86.0%, respectively. There were 143 microorganisms detected by ddPCR. The DNA loads of these microorganisms ranged from 30.0 to 3.2×105 copies/mL (median level: 158.0 copies/mL), 72.7% (104/143) of which were below 1,000 copies/mL. Further, statistical analysis showed the DNA loads of Escherichia coli (AUC: 0.954, 95% CI: 0.898-1.000, κ=0.731, cut-off values: 93.0 copies/mL) and Klebsiella pneumoniae (AUC: 0.994, 95% CI: 0.986-1.000, κ=0.834, cut-off values: 196.5 copies/mL) were excellent predictors for the corresponding BSIs. The DNA loads of Pseudomonas aeruginosa (AUC: 0.816, 95% CI: 0.560-1.000, κ=0.167), Acinetobacter baumannii (AUC: 0.728, 95% CI: 0.195-1.000), and Enterococcus spp. (AUC: 0.282, 95% CI: 0.000-0.778) had little predictive value for the corresponding culture-proven BSIs.

Conclusion

Our results indicate that the multiplex ddPCR is a promising platform as a complementary add-on to conventional BC. The DNA loads of E. coli and K. pneumoniae present excellent predictive value for the corresponding BSIs. Further research is needed to explore the predictive potential of ddPCR for other microorganisms.

Examining the effect of direct-from-blood bacterial testing on antibiotic administration and clinical outcomes: a protocol and statistical analysis plan for a pragmatic randomised trial

INTRODUCTION

Patients with suspected bacterial infection frequently receive empiric, broad-spectrum antibiotics prior to pathogen identification due to the time required for bacteria to grow in culture. Direct-from-blood diagnostics identifying the presence or absence of bacteria and/or resistance genes from whole blood samples within hours of collection could enable earlier antibiotic optimisation for patients suspected to have bacterial infections. However, few randomised trials have evaluated the effect of using direct-from-blood bacterial testing on antibiotic administration and clinical outcomes. This manuscript describes the protocol and statistical analysis plan for a randomised trial designed to evaluate the effect of blood cultures plus direct-from-blood bacterial testing results compared with blood culture results alone on antibiotic administration and clinical outcomes.

METHODS AND ANALYSIS

We are conducting a prospective, single-centre, parallel-group, non-blinded, pragmatic, randomised trial. The trial will enrol 500 adult patients presenting to the emergency department at Vanderbilt University Medical Center with suspected bacterial infection who have been initiated on empiric intravenous vancomycin. Eligible patients are randomised 1:1 to receive Food and Drug Administration-approved direct-from-blood bacterial testing in addition to blood cultures or blood cultures alone. The primary outcome is the time to the last dose of intravenous vancomycin within 14 days of randomisation. The secondary outcome is the time to the last dose of systemic antipseudomonal beta-lactam antibiotics within 14 days of randomisation. Additional outcomes include highest stage of acute kidney injury, lowest platelet count and receipt of kidney replacement therapy within 14 days of randomisation, as well as hospital-free days, intensive care unit-free-days and all-cause, in-hospital mortality within 28 days of randomisation. Enrolment began on 13 December 2023.

ETHICS AND DISSEMINATION

The trial involves human participants and was approved by the Vanderbilt University Medical Center institutional review board with a waiver of informed consent (IRB#231229). Results will be submitted in a peer-reviewed journal and presented at scientific conferences.

TRIAL REGISTRATION NUMBER

NCT06069206.

Rapid molecular assays versus blood culture for bloodstream infections: a systematic review and meta-analysis

Background

Timely management of sepsis with early targeted antimicrobial therapy improves patient outcomes. Rapid molecular assays (RMAs) have emerged, enabling the detection of bloodstream infection (BSI) with a shorter turnaround time than blood cultures (BCs). The accuracy of several RMAs has not been comprehensively reviewed. We aimed to identify commercial RMAs reported in the literature and evaluate their diagnostic performance compared to BC.

Methods

A systematic review and meta-analysis was conducted, covering MEDLINE, Cochrane Library, Embase, and Web of Science from inception to September 23, 2024. Eligible studies included patients with suspected or documented BSI, tested with both an RMA (turnaround time of ≤12 h, targeting ≥20 pathogens) and BC. Non-original research articles and animal studies were excluded. The primary outcomes were pooled sensitivity and specificity of RMAs for pathogen detection compared to BC. Bivariate analysis was used to produce summary receiver operating characteristic plots and diagnostic metric measures stratified by different units of analysis (sample versus patient), RMA types, and patient populations. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and Quality Assessment of Diagnostic Accuracy Studies-Comparative (QUADAS-C) tools. The study was registered with PROSPERO, CRD42022377280.

Findings

A total of 63,916 articles were identified, of which 104 were included in the qualitative synthesis and 75 in the quantitative synthesis, covering 17,952 samples and 11,393 patients analyzed separately. Eleven RMAs were identified, with four included in the RMA-based subgroup analysis (LightCycler SeptiFast Test MGRADE®, IRIDICA BAC BSI assay, SepsiTest, MagicPlex Sepsis Test) and five additional ones in the pooled analysis (UMD-SelectNA, VYOO®, MicrobScan assay, MicrobScan-Kairos24/7, REBA Sepsis-ID test). Two RMAs were included in the qualitative synthesis only (InfectID-BSI, Pilot Gene Technology droplet digital polymerase chain reaction). Pooled specificity of RMAs was higher (0.858, 95% confidence interval (CI) 0.830-0.883) than sensitivity (0.659, 95% CI 0.594-0.719) by patient. Sensitivities varied by RMA type from 0.492 (95% CI 0.390-0.594, MagicPlex Sepsis Test) to 0.783 (95% CI 0.662-0.870, IRIDICA BAC BSI assay) by patient. Specificities varied more by patient population, ranging from 0.811 (95% CI 0.716-0.879) in the intensive care population to 0.892 (95% CI 0.838-0.930) in the emergency department population, by patient. Similar metrics were observed when the analysis was done by sample. Risk of bias was judged to be high in all included articles.

Interpretation

Despite their shorter turnaround time, low sensitivity means RMAs cannot replace BCs. However, our data indicate that RMAs may have value as an add-on test by increasing pathogen detection rates. Higher-sensitivity RMAs are needed which could possibly be achieved by expanding pathogen coverage and increasing blood sample volumes. High-quality implementation studies and standardized reporting are required to assess the clinical advantages of RMAs.

Funding

Centre for Translational Medicine, Semmelweis University.

Next-generation rapid phenotypic antimicrobial susceptibility testing

Slow progress towards implementation of conventional clinical bacteriology in low resource settings and strong interest in greater speed for antimicrobial susceptibility testing (AST) more generally has focused attention on next-generation rapid AST technologies. In this Review, we systematically synthesize publications and submissions to regulatory agencies describing technologies that provide phenotypic AST faster than conventional methods. We characterize over ninety technologies in terms of underlying technical innovations, technology readiness level, extent of clinical validation, and time-to-results. This work provides a guide for technology developers and clinical microbiologists to understand the rapid phenotypic AST technology landscape, current development pipeline, and AST-specific validation milestones.

Evaluation of an expanded antibiotic resistance gene panel on prediction of antimicrobial susceptibility results for Gram-negative bacteria in blood cultures

The QIAstat-Dx BCID Panels (RUO) ("QIAstat," QIAGEN, Hilden, Germany) for identification of 13 Gram-negative bacteria and 18 antimicrobial resistance (AMR) gene groups was evaluated. The study was conducted in two phases; in phase 1, analytical performance was evaluated against 154 challenge isolates against whole genome sequencing data. In this phase, sensitivity and specificity of organism identification calls were 153/154 (99.3%) and 1,748/1,749 (99.8%), respectively. For AMR genes, sensitivity was 434/435 (99.8%) and specificity was 2,334/2,337 (99.9%). One false-negative blaIMP, one false-positive blaCTX-M, and two false-positive aac-6'-lb detections were noted in this challenge set of organisms. In phase 2, 101 clinical blood culture isolates of Gram-negative rods were evaluated by the multiplexed PCR versus reference broth microdilution, for the ability of identification combined with AMR genes to predict final susceptibility results. Negative predictive values were 92.8% for ampicillin resistance (100% for Escherichia coli), 93.4% for ceftriaxone, 97.4% for ceftazidime, and 98.7% for cefepime. In constrast, negative predictive values for current standard of care (identification plus detection of blaCTX-M) ranged from 56.5% to 88.8%. This study demonstrated additive value of additional beta-lactamase genes for bacteria isolated from blood cultures.

IMPORTANCE

Prediction of Gram-negative bacteria resistance through detection of resistance genes is complex. This study evaluated a novel, direct-from-blood or bacterial isolate multiplexed PCR for the detection of 17 resistance genes, and evaluated the prediction of antimicrobial susceptibility.

Evaluating the impact of rapid antimicrobial susceptibility testing for bloodstream infections: a review of actionability, antibiotic use and patient outcome metrics

Antimicrobial susceptibility testing (AST) is a core function of the clinical microbiology laboratory and is critical to the management of patients with bloodstream infections (BSIs) to facilitate optimal antibiotic therapy selection. Recent technological advances have resulted in several rapid methods for determining susceptibility direct from positive blood culture that can provide turnaround times in under 8 h, which is considerably shorter than conventional culture-based methods. As diagnostic results do not directly produce a medical intervention, actionability is a primary determinant of the effect these technologies have on antibiotic use and ultimately patient outcomes. Randomized controlled trials and observational studies consistently show that rapid AST significantly reduces time to results and improves antimicrobial therapy for patients with BSI across various methods, patient populations and organisms. To date, the clinical impact of rapid AST has been demonstrated in some observational studies, but randomized controlled trials have not been sufficiently powered to validate many of these findings. This article reviews various metrics that have been described in the literature to measure the impact of rapid AST on actionability, antibiotic exposure and patient outcomes, as well as highlighting how implementation and workflow processes can affect these metrics.

Metagenomics in the Diagnosis of Pneumonia: Protocol for a Systematic Review

BACKGROUND

Causative pathogens are currently identified in only a minority of pneumonia cases, which affects antimicrobial stewardship. Metagenomic next-generation sequencing (mNGS) has potential to enhance pathogen detection due to its sensitivity and broad applicability. However, while studies have shown improved sensitivity compared with conventional microbiological methods for pneumonia diagnosis, it remains unclear whether this can translate into clinical benefit. Most existing studies focus on patients who are ventilated, readily allowing for analysis of bronchoalveolar lavage fluid (BALF). The impact of sample type on the use of metagenomic analysis remains poorly defined. Similarly, previous studies rarely differentiate between the types of pneumonia involved-community-acquired pneumonia (CAP), hospital-acquired pneumonia (HAP), or ventilator-associated pneumonia (VAP)-which have different clinical profiles.

OBJECTIVE

This study aims to determine the clinical use of mNGS in CAP, HAP, and VAP, compared with traditional microbiological methods.

METHODS

We aim to review all studies (excluding case reports of a series of fewer than 10 people) of adult patients with suspected or confirmed pneumonia that compare metagenomic analysis with traditional microbiology techniques, including culture, antigen-based testing, and polymerase chain reaction-based assays. Relevant studies will be identified through systematic searches of the Embase, MEDLINE, Scopus, and Cochrane CENTRAL databases. Screening of titles, abstracts, and subsequent review of eligible full texts will be done by 2 separate reviewers (SQ and 1 of AL, CJ, or CH), with a third clinician (ES) providing adjudication in case of disagreement. Our focus is on the clinical use of metagenomics for patients with CAP, HAP, and VAP. Data extracted will focus on clinically important outcomes-pathogen positivity rate, laboratory turnaround time, impact on clinical decision-making, length of stay, and 30-day mortality. Subgroup analyses will be performed based on the type of pneumonia (CAP, HAP, or VAP) and sample type used. The risk of bias will be assessed using the QUADAS-2 tool for diagnostic accuracy studies. Outcome data will be combined in a random-effects meta-analysis, and where this is not possible, a narrative synthesis will be undertaken.

RESULTS

The searches were completed with the assistance of a medical librarian on January 13, 2024, returning 5750 records. Screening and data extraction are anticipated to be completed by September 2024.

CONCLUSIONS

Despite significant promise, the impact of metagenomic analysis on clinical pathways remains unclear. Furthermore, it is unclear whether the use of this technique will alter depending on whether the pneumonia is a CAP, HAP, or VAP or the sample type that is collected. This systematic review will assess the current evidence base to support the benefit of clinical outcomes for metagenomic analysis, depending on the setting of pneumonia diagnosis or specimen type used. It will identify areas where further research is needed to advance this methodology into routine care.

TRIAL REGISTRATION

PROSPERO CRD42023488096; https://tinyurl.com/3suy7cma.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/57334.

Predicting Pseudomonas aeruginosa drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) is widely used in clinical microbiology laboratories for bacterial identification but its use for detection of antimicrobial resistance (AMR) remains limited. Here, we used MALDI-TOF MS with artificial intelligence (AI) approaches to successfully predict AMR in Pseudomonas aeruginosa, a priority pathogen with complex AMR mechanisms. The highest performance was achieved for modern β-lactam/β-lactamase inhibitor drugs, namely, ceftazidime/avibactam and ceftolozane/tazobactam. For these drugs, the model demonstrated area under the receiver operating characteristic curve (AUROC) of 0.869 and 0.856, specificity of 0.925 and 0.897, and sensitivity of 0.731 and 0.714, respectively. As part of this work, we developed dynamic binning, a feature engineering technique that effectively reduces the high-dimensional feature set and has wide-ranging applicability to MALDI-TOF MS data. Compared to conventional feature engineering approaches, the dynamic binning method yielded highest performance in 7 of 10 antimicrobials. Moreover, we showcased the efficacy of transfer learning in enhancing the AUROC performance for 8 of 11 antimicrobials. By assessing the contribution of features to the model's prediction, we identified proteins that may contribute to AMR mechanisms. Our findings demonstrate the potential of combining AI with MALDI-TOF MS as a rapid AMR diagnostic tool for Pseudomonas aeruginosa.IMPORTANCEPseudomonas aeruginosa is a key bacterial pathogen that causes significant global morbidity and mortality. Antimicrobial resistance (AMR) emerges rapidly in P. aeruginosa and is driven by complex mechanisms. Drug-resistant P. aeruginosa is a major challenge in clinical settings due to limited treatment options. Early detection of AMR can guide antibiotic choices, improve patient outcomes, and avoid unnecessary antibiotic use. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) is widely used for rapid species identification in clinical microbiology. In this study, we repurposed mass spectra generated by MALDI-TOF and used them as inputs for artificial intelligence approaches to successfully predict AMR in P. aeruginosa for multiple key antibiotic classes. This work represents an important advance toward using MALDI-TOF as a rapid AMR diagnostic for P. aeruginosa in clinical settings.

Evaluation of T2 Magnetic Resonance (T2MR®) Technology for the Early Detection of ESKAPEc Pathogens in Septic Patients

Bloodstream infections (BSIs) and sepsis are a major cause of morbidity and mortality. Appropriate early antibiotic therapy is crucial for improving the survival of patients with sepsis and septic shock. T2 magnetic resonance (T2MR®) technology may enable fast and sensitive detection of ESKAPEc pathogens directly from whole-blood samples. We aimed to evaluate concordance between the T2Bacteria® Panel and standard blood culture and its impact on antibiotic therapy decisions. We conducted a single-centre retrospective study on patients with sepsis-induced hypotension or septic shock admitted to general, post-operative/neurosurgical, and cardiothoracic Intensive Care Units who were tested with the T2Bacteria® Panel from January 2021 to December 2022. Eighty-five consecutively admitted patients were included, for a total of 85 paired tests. A total of 48 ESKAPEc pathogens were identified by the T2Bacteria® Panel. The concordance rate between the T2Bacteria® Panel and blood cultures was 81% (69/85), with 20 concordant-positive and 49 concordant-negative cases. For the 25 microorganisms grown from accompanying blood cultures, blood pathogen coverage by the T2Bacteria® Panel was 88%. In this cohort of severely ill septic patients, the T2Bacteria® Panel was highly concordant and was able to detect more ESKAPEc pathogens, with a significantly shorter turn-around time compared to conventional blood cultures. The T2Bacteria® Panel also significantly impacted decisions on antibiotic therapy.

Combination of a Rapid Diagnostic Assay and Antimicrobial Stewardship Intervention for Gram-Negative Bacteremia

Background

Traditional blood cultures for gram-negative bacteremia can take up to 72 hours or more to return results, prolonging the duration of empiric broad-spectrum intravenous antibiotics. The Accelerate Pheno system provides rapid identification and susceptibilities for blood cultures in gram-negative bacteremia. Current data on its clinical utility are mixed overall, so the system requires further research.

Methods

A multicenter, retrospective quasi-experimental study was conducted comparing the Accelerate Pheno rapid diagnostic system with antimicrobial stewardship intervention and traditional blood cultures alone.

Results

A total of 264 patients with blood cultures with gram-negative bacteria growth were included in the final analysis (102 pre-intervention, 162 post-intervention). The antimicrobial stewardship team made 364 recommendations in 152/162 (93.8%) patients in the post group. Duration of intravenous therapy was shorter (P < .001) for the post-intervention group (median, 4.0 days) compared with the pre-intervention group (median, 7.5 days). Hospital length of stay was also shorter (P < .001) for the post-intervention group (median, 5.1 days) compared with the pre-intervention group (median, 7.0 days). Readmission rates within 30 days were reduced (P = .042) post-intervention (13.0%) compared with pre-intervention (22.6%). In the post-intervention group, a larger proportion of patients were transitioned to oral therapy at any point (126/162, 77.8%) compared with pre-intervention (62/102, 60.8%; P < .001).

Conclusions

These results suggest that the Accelerate Pheno system, with active review and intervention by a multidisciplinary antimicrobial stewardship team, is a useful tool in improving both patient-centric and antimicrobial stewardship outcomes.

MALDI-TOF direct identification of positive blood cultures: A four-year analytical evaluation of A Triton based workflow

Rapid and reliable identification of the causal organism in bloodstream infections and sepsis is crucial for both individual patient care and public health. We have implemented a rapid in-house identification protocol (with 10 % Triton) using MALDI-TOF MS for identifying the causative organism in positive blood cultures without prior culture. Our objective was to retrospectively analyze data collected over a four-year period while implementing this rapid in-house identification protocol and to develop a guide for evaluating and reporting the obtained results. Overall, our method utilizing MALDI-TOF MS for rapid in-house identification, demonstrated comparable results to other commercially available and in-house methods reported in the literature. Over the past four years, direct identification has facilitated the distinction between clinically relevant positive blood cultures and irrelevant ones, guiding rapid focus control and appropriate antibiotic treatment. The established guide can serve as a valuable tool in reporting positive blood cultures and associated antibiotic treatments.

Advances in Host Depletion and Pathogen Enrichment Methods for Rapid Sequencing-Based Diagnosis of Bloodstream Infection

Bloodstream infection is a major cause of morbidity and death worldwide. Timely and appropriate treatment can reduce mortality among critically ill patients. Current diagnostic methods are too slow to inform precise antibiotic choice, leading to the prescription of empirical antibiotics, which may fail to cover the resistance profile of the pathogen, risking poor patient outcomes. Additionally, overuse of broad-spectrum antibiotics may lead to more resistant organisms, putting further pressure on the dwindling pipeline of antibiotics, and risk transmission of these resistant organisms in the health care environment. Therefore, rapid diagnostics are urgently required to better inform antibiotic choice early in the course of treatment. Sequencing offers great promise in reducing time to microbiological diagnosis; however, the amount of host DNA compared with the pathogen in patient samples presents a significant obstacle. Various host-depletion and bacterial-enrichment strategies have been used in samples, such as saliva, urine, or tissue. However, these methods have yet to be collectively integrated and/or extensively explored for rapid bloodstream infection diagnosis. Although most of these workflows possess individual strengths, their lack of analytical/clinical sensitivity and/or comprehensiveness demands additional improvements or synergistic application. This review provides a distinctive classification system for various methods based on their working principles to guide future research, and discusses their strengths and limitations and explores potential avenues for improvement to assist the reader in workflow selection.

Blood culture-free ultra-rapid antimicrobial susceptibility testing

Treatment assessment and patient outcome for sepsis depend predominantly on the timely administration of appropriate antibiotics1-3. However, the clinical protocols used to stratify and select patient-specific optimal therapy are extremely slow4. In particular, the major hurdle in performing rapid antimicrobial susceptibility testing (AST) remains in the lengthy blood culture procedure, which has long been considered unavoidable due to the limited number of pathogens present in the patient's blood. Here we describe an ultra-rapid AST method that bypasses the need for traditional blood culture, thereby demonstrating potential to reduce the turnaround time of reporting drug susceptibility profiles by more than 40-60 h compared with hospital AST workflows. Introducing a synthetic beta-2-glycoprotein I peptide, a broad range of microbial pathogens are selectively recovered from whole blood, subjected to species identification or instantly proliferated and phenotypically evaluated for various drug conditions using a low-inoculum AST chip. The platform was clinically evaluated by the enrolment of 190 hospitalized patients suspected of having infection, achieving 100% match in species identification. Among the eight positive cases, six clinical isolates were retrospectively tested for AST showing an overall categorical agreement of 94.90% with an average theoretical turnaround time of 13 ± 2.53 h starting from initial blood processing.

Antibiotic Treatment Practices and Microbial Profile in Diabetic Foot Ulcers: A Retrospective Cohort Study

Aim and objective Diabetic foot ulcers (DFUs) are a frequent complication of diabetes mellitus, impacting more than one in 10 diabetic patients, with roughly half of these ulcers progressing to infection. Existing literature indicates that these infections are predominantly polymicrobial, with gram-positive isolates being the most common. This microbial profile informs the empiric antibiotic strategies employed in first-world countries, often including highly potent nephrotoxic antibiotics. This retrospective cohort study aims to assess the microbial profile and antibiotic treatment practices in patients with infected DFUs at Ochsner LSU Health Shreveport Academic Medical Center in Shreveport, Louisiana, United States. Materials and methods A total of 115 patients diagnosed with infected DFUs were included in the study. Patient records were reviewed to identify bacterial pathogens cultured from foot wounds, antibiotic treatment regimens administered, and the prevalence of acute kidney injury (AKI). Results The study found a predominance of gram-negative isolates (199; 59.4%), facultative anaerobes (246; 73.4%), and polymicrobial infections (67; 78.8%) in infected DFUs. Vancomycin was administered to 95 patients (82.6%), with only a small number subsequently testing positive for methicillin-resistant Staphylococcus aureus (MRSA). Combination therapy with vancomycin and Zosyn was given to 71 patients (61.7%), which increased the potential risk of antibiotic-induced nephrotoxicity. AKI was prevalent, affecting 58 patients (50.4%). Conclusions This study highlights a discrepancy between the microbial profile of infected DFUs and empiric antibiotic treatment practices at Ochsner LSU Health Shreveport Academic Medical Center. The predominance of gram-negative bacteria underscores the need for a polymicrobial, gram-negative-focused empiric treatment approach. Alternative antibiotics with broad-spectrum coverage and minimal nephrotoxicity, such as ceftriaxone, clindamycin, metronidazole, amoxicillin-clavulanate, and linezolid, should be considered. Tailored antibiotic strategies, guided by local microbial profiles and patient-specific factors, are essential to optimize treatment outcomes in this high-risk population.

Rapid Direct Identification of Microbial Pathogens and Antimicrobial Resistance Genes in Positive Blood Cultures Using a Fully Automated Multiplex PCR Assay

This study assessed the performance of the BioFire Blood Culture Identification 2 (BCID2) panel in identifying microorganisms and antimicrobial resistance (AMR) profiles in positive blood cultures (BCs) and its influence on turnaround time (TAT) compared with conventional culture methods. We obtained 117 positive BCs, of these, 102 (87.2%) were correctly identified using BCID2. The discordance was due to off-panel pathogens detected by culture (n = 13), and additional pathogens identified by BCID2 (n = 2). On-panel pathogen concordance between the conventional culture and BCID2 methods was 98.1% (102/104). The conventional method detected 19 carbapenemase-producing organisms, 14 extended-spectrum beta-lactamase-producing Enterobacterales, 18 methicillin-resistant Staphylococcus spp., and four vancomycin-resistant Enterococcus faecium. BCID2 correctly predicted 53 (96.4%) of 55 phenotypic resistance patterns by detecting AMR genes. The TAT for BCID2 was significantly lower than that for the conventional method. BCID2 rapidly identifies pathogens and AMR genes in positive BCs.

Achievement of therapeutic antibiotic exposures using Bayesian dosing software in critically unwell children and adults with sepsis

PURPOSE

Early recognition and effective treatment of sepsis improves outcomes in critically ill patients. However, antibiotic exposures are frequently suboptimal in the intensive care unit (ICU) setting. We describe the feasibility of the Bayesian dosing software Individually Designed Optimum Dosing Strategies (ID-ODS™), to reduce time to effective antibiotic exposure in children and adults with sepsis in ICU.

METHODS

A multi-centre prospective, non-randomised interventional trial in three adult ICUs and one paediatric ICU. In a pre-intervention Phase 1, we measured the time to target antibiotic exposure in participants. In Phase 2, antibiotic dosing recommendations were made using ID-ODS™, and time to target antibiotic concentrations were compared to patients in Phase 1 (a pre-post-design).

RESULTS

175 antibiotic courses (Phase 1 = 123, Phase 2 = 52) were analysed from 156 participants. Across all patients, there was no difference in the time to achieve target exposures (8.7 h vs 14.3 h in Phase 1 and Phase 2, respectively, p = 0.45). Sixty-one courses in 54 participants failed to achieve target exposures within 24 h of antibiotic commencement (n = 36 in Phase 1, n = 18 in Phase 2). In these participants, ID-ODS™ was associated with a reduction in time to target antibiotic exposure (96 vs 36.4 h in Phase 1 and Phase 2, respectively, p < 0.01). These patients were less likely to exhibit subtherapeutic antibiotic exposures at 96 h (hazard ratio (HR) 0.02, 95% confidence interval (CI) 0.01-0.05, p < 0.01). There was no difference observed in in-hospital mortality.

CONCLUSIONS

Dosing software may reduce the time to achieve target antibiotic exposures. It should be evaluated further in trials to establish its impact on clinical outcomes.

Association between blood culture turnaround time and clinical prognosis in emergency department patients with community acquired bloodstream infection: A retrospective study based on electronic medical records

Importance

Previous investigations have found that time to positive blood culture (TTP) is a prognostic factor for clinical outcomes. In fact, what the emergency physician sees from the medical information system is TAT (turnaround time) defined as time required to post a bacterial culture report. We propose a definition of blood culture TAT that more closely aligns with clinical considerations by measuring the time from starting specimen culture to the release of an official blood culture report.We were curious to know whether the duration of TAT is as intricately linked to the prognosis of bacteremia as TTP.

Objectives

To examine the association between TAT and outcomes of adult patients who present to the ED with community acquired bacteremia.

Design

Setting, and Participants: This retrospective study utilized electronic medical records from Kaohsiung Veterans General Hospital (KVGH), a 1000-bed tertiary medical center in Taiwan. Patients were adults aged 18 years and older who presented to ED (Emergency department) for initial diagnosis of community acquired bacteremia from January 1, 2016 to March 31, 2021. Data analysis was performed from December 2022 to January 2023.Main outcomes and measures.The primary outcomes included mortality in the ED, all-cause in-hospital mortality, length of hospital stay, and all-cause 30-day mortality in relation to the individual first report of positive blood culture TAT.

Results

A total of 4011 eligible patients with bacteremia were evaluated, of which 207 patients had a blood culture TAT of ≤48 h. The overall 30-day all-cause mortality rate was 13%. Contrary to expectation, no statistically significant differences were observed in clinical prognosis between the TAT groups (≤48 versus >48 h). Subgroup analyses indicated that the length of TAT did not have a significant effect on clinical prognosis in patients who underwent lactate level assessment. Furthermore, no difference in clinical outcome was noted between TAT groups (≤48 versus >48 h) in terms of Gram-negative bacilli or Gram-positive cocci bacteremia. However, in patients with delayed antibiotic treatment (>3 h), a shorter TAT was significantly associated with a fatal outcome.

Conclusion

In adults with community-acquired bacteremia, this study did not observe a significant association between blood culture TAT and clinical prognosis, except in cases of delayed antibiotic treatment.

Towards personalised anti-microbial and immune approaches to infections in acute care. Can real-time genomic-informed diagnosis of pathogens, and immune-focused therapies improve outcomes for patients? An observational, experimental study protocol

INTRODUCTION

Infection causes a vast burden of disease, with significant mortality, morbidity and costs to health-care systems. However, identifying the pathogen causative infection can be challenging, resulting in high use of broad-spectrum antibiotics, much of which may be inappropriate. Novel metagenomic methods have potential to rapidly identify pathogens, however their clinical utility for many infections is currently unclear. Outcome from infection is also impacted by the effectiveness of immune responses, which can be impaired by age, co-morbidity and the infection itself. The aims of this study are twofold: To compare diversity of organisms identified and time-to-result using metagenomic methods versus traditional culture -based techniques, to explore the potential clinical role of metagenomic approaches to pathogen identification in a range of infections.To characterise the ex vivo function of immune cells from patients with acute infection, exploring host and pathogen-specific factors which may affect immune function and overall outcomes.

METHODS

This is a prospective observational study of patients with acute infection. Patients with symptoms suggestive of an acute infection will be recruited, and blood and bodily fluid relevant to the site of infection collected (for example, sputum and naso-oropharyngeal swabs for respiratory tract infections, or urine for a suspected urinary tract infection). Metagenomic analysis of samples will be compared to traditional microbiology, alongside the antimicrobials received. Blood and respiratory samples such as bronchoalveolar lavage will be used to isolate immune cells and interrogate immune cell function. Where possible, similar samples will be collected from matched participants without a suspected infection to determine the impact of infection on both microbiome and immune cell function.

Diagnostic and antibiotic use practices among COVID-19 and non-COVID-19 patients in the Indonesian National Referral Hospital

BACKGROUND

Little is known about diagnostic and antibiotic use practices in low and middle-income countries (LMICs) before and during COVID-19 pandemic. This information is crucial for monitoring and evaluation of diagnostic and antimicrobial stewardships in healthcare facilities.

METHODS

We linked and analyzed routine databases of hospital admission, microbiology laboratory and drug dispensing of Indonesian National Referral Hospital from 2019 to 2020. Patients were classified as COVID-19 cases if their SARS-CoV-2 RT-PCR result were positive. Blood culture (BC) practices and time to discontinuation of parenteral antibiotics among inpatients who received a parenteral antibiotic for at least four consecutive days were used to assess diagnostic and antibiotic use practices, respectively. Fine and Grey subdistribution hazard model was used.

RESULTS

Of 1,311 COVID-19 and 58,917 non-COVID-19 inpatients, 333 (25.4%) and 18,837 (32.0%) received a parenteral antibiotic for at least four consecutive days. Proportion of patients having BC taken within ±1 calendar day of parenteral antibiotics being started was higher in COVID-19 than in non-COVID-19 patients (21.0% [70/333] vs. 18.7% [3,529/18,837]; p<0.001). Cumulative incidence of having a BC taken within 28 days was higher in COVID-19 than in non-COVID-19 patients (44.7% [149/333] vs. 33.2% [6,254/18,837]; adjusted subdistribution-hazard ratio [aSHR] 1.71, 95% confidence interval [CI] 1.47-1.99, p<0.001). The median time to discontinuation of parenteral antibiotics was longer in COVID-19 than in non-COVID-19 patients (13 days vs. 8 days; aSHR 0.73, 95%Cl 0.65-0.83, p<0.001).

CONCLUSIONS

Routine electronic data could be used to inform diagnostic and antibiotic use practices in LMICs. In Indonesia, the proportion of timely blood culture is low in both COVID-19 and non-COVID-19 patients, and duration of parenteral antibiotics is longer in COVID-19 patients. Improving diagnostic and antimicrobial stewardship is critically needed.

Development and clinical validation of a dual ddPCR assay for detecting carbapenem-resistant Acinetobacter baumannii in bloodstream infections

Objective

Acinetobacter baumannii (A. baumannii, AB) represents a major species of Gram-negative bacteria involved in bloodstream infections (BSIs) and shows a high capability of developing antibiotic resistance. Especially, carbapenem-resistant Acinetobacter baumannii (CRAB) becomes more and more prevalent in BSIs. Hence, a rapid and sensitive CRAB detection method is of urgent need to reduce the morbidity and mortality due to CRAB-associated BSIs.

Methods

A dual droplet digital PCR (ddPCR) reaction system was designed for detecting the antibiotic resistance gene OXA-23 and AB-specific gene gltA. Then, the specificity of the primers and probes, limit of detection (LOD), linear range, and accuracy of the assay were evaluated. Furthermore, the established assay approach was validated on 37 clinical isolates and compared with blood culture and drug sensitivity tests.

Results

The dual ddPCR method established in this study demonstrated strong primer and probe specificity, distinguishing CRAB among 21 common clinical pathogens. The method showed excellent precision (3 × 10-4 ng/μL, CV < 25%) and linearity (OXA-23: y = 1.4558x + 4.0981, R2 = 0.9976; gltA: y = 1.2716x + 3.6092, R2 = 0.9949). While the dual qPCR LOD is 3 × 10-3 ng/μL, the dual ddPCR's LOD stands at 3 × 10-4 ng/μL, indicating a higher sensitivity in the latter. When applied to detect 35 patients with BSIs of AB, the results were consistent with clinical blood culture identification and drug sensitivity tests.

Conclusion

The dual ddPCR detection method for OXA-23 and gltA developed in this study exhibits good specificity, excellent linearity, and a higher LOD than qPCR. It demonstrates reproducibility even for minute samples, making it suitable for rapid diagnosis and precision treatment of CRAB in BSIs.

Novel and Rapid Diagnostics for Common Infections in the Critically Ill Patient

There are several novel platforms that enhance detection of pathogens that cause common infections in the intensive care unit. These platforms have a sample to answer time of a few hours, are often higher yield than culture, and have the potential to improve antibiotic stewardship.

Rapid determination of antimicrobial susceptibility of Gram-negative bacteria from clinical blood cultures using a scattered light-integrated collection device

Background. A bloodstream infection (BSI) presents a complex and serious health problem, a problem that is being exacerbated by increasing antimicrobial resistance (AMR).Gap Statement. The current turnaround times (TATs) for most antimicrobial susceptibility testing (AST) methods offer results retrospective of treatment decisions, and this limits the impact AST can have on antibiotic prescribing and patient care. Progress must be made towards rapid BSI diagnosis and AST to improve antimicrobial stewardship and reduce preventable deaths from BSIs. To support the successful implementation of rapid AST (rAST) in hospital settings, a rAST method that is affordable, is sustainable and offers comprehensive AMR detection is needed.Aim. To evaluate a scattered light-integrated collection (SLIC) device against standard of care (SOC) to determine whether SLIC could accelerate the current TATs with actionable, accurate rAST results for Gram-negative BSIs.Methods. Positive blood cultures from a tertiary referral hospital were studied prospectively. Flagged positive Gram-negative blood cultures were confirmed by Gram staining and analysed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, Vitek 2, disc diffusion (ceftriaxone susceptibility only) and an SLIC device. Susceptibility to a panel of five antibiotics, as defined by European Committee on Antimicrobial Susceptibility Testing breakpoints, was examined using SLIC.Results. A total of 505 bacterial-antimicrobial combinations were analysed. A categorical agreement of 95.5 % (482/505) was achieved between SLIC and SOC. The 23 discrepancies that occurred were further investigated by the broth microdilution method, with 10 AST results in agreement with SLIC and 13 in agreement with SOC. The mean time for AST was 10.53±0.46 h and 1.94±0.02 h for Vitek 2 and SLIC, respectively. SLIC saved 23.96±1.47 h from positive blood culture to AST result.Conclusion. SLIC has the capacity to provide accurate AST 1 day earlier from flagged positive blood cultures than SOC. This significant time saving could accelerate time to optimal antimicrobial therapy, improving antimicrobial stewardship and management of BSIs.

Evaluation of three protocols for direct susceptibility testing for gram negative-Enterobacteriaceae from patient samples in Uganda with SMS reporting

In Uganda, the challenge of generating and timely reporting essential antimicrobial resistance (AMR) data has led to overreliance on empirical antibiotic therapy, exacerbating the AMR crisis. To address this issue, this study aimed to adapt a one-step AMR testing protocol alongside an SMS (Short Message Service) result relay system (SRRS), with the potential to reduce the turnaround time for AMR testing and result communication from 4 days or more to 1 day in Ugandan clinical microbiology laboratories. Out of the 377 samples examined, 54 isolates were obtained. Notably, E. coli (61%) and K. pneumoniae (33%) were the most frequently identified, majority testing positive for ESBL. Evaluation of three AMR testing protocols revealed varying sensitivity and specificity, with Protocol A (ChromID ESBL-based) demonstrating high sensitivity (100%) but no calculable specificity, Protocol B (ceftazidime-based) showing high sensitivity (100%) and relatively low specificity (7.1%), and Protocol C (cefotaxime-based) exhibiting high sensitivity (97.8%) but no calculable specificity. ESBL positivity strongly correlated with resistance to specific antibiotics, including cefotaxime, ampicillin, and aztreonam (100%), cefuroxime (96%), ceftriaxone (93%), and trimethoprim sulfamethoxazole (87%). The potential of integrating an SRRS underscored the crucial role this could have in enabling efficient healthcare communication in AMR management. This study underscores the substantial potential of the tested protocols for accurately detecting ESBL production in clinical samples, potentially, providing a critical foundation for predicting and reporting AMR patterns. Although considerations related to specificity warrant careful assessment before widespread clinical adoption.

Analysis of microbiological tests in patients withholding or withdrawing life-sustaining treatment at the end stage of life in 2 Korean hospitals

OBJECTIVE

We evaluated the adequacy of microbiological tests in patients withholding or withdrawing life-sustaining treatment (WLST) at the end stage of life.

SETTING

The study was conducted at 2 tertiary-care referral hospitals in Daegu, Republic of Korea.

DESIGN

Retrospective cross-sectional study.

METHODS

Demographic findings, clinical and epidemiological characteristics, statistics of microbiological tests, and microbial species isolated from patients within 2 weeks before death were collected in 2 tertiary-care referral hospitals from January to December 2018. We also reviewed the antimicrobial treatment that was given within 3 days of microbiological testing in patients on WLST.

RESULTS

Of the 1,187 hospitalized patients included, 905 patients (76.2%) had WLST. The number of tests per 1,000 patient days was higher after WLST than before WLST (242.0 vs 202.4). Among the category of microbiological tests, blood cultures were performed most frequently, and their numbers per 1,000 patient days before and after WLST were 95.9 and 99.0, respectively. The positive rates of blood culture before and after WLST were 17.2% and 18.0%, respectively. Candida spp. were the most common microbiological species in sputum (17.4%) and urine (48.2%), and Acinetobacter spp. were the most common in blood culture (17.3%). After WLST determination, 70.5% of microbiological tests did not lead to a change in antibiotic use.

CONCLUSIONS

Many unnecessary microbiological tests are being performed in patients with WLST within 2 weeks of death. Microbiological testing should be performed carefully and in accordance with the patient's treatment goals.

The Value of Next-Generation Sequencing in Diagnosis and Therapy of Critically Ill Patients with Suspected Bloodstream Infections: A Retrospective Cohort Study

Bloodstream infection (BSI), a frequent cause of severe sepsis, is a life-threatening complication in critically ill patients and still associated with a high mortality rate. Rapid pathogen identification from blood is crucial for an early diagnosis and the treatment of patients with suspected BSI. For this purpose, novel diagnostic tools on the base of genetic analysis have emerged for clinical application. The aim of this study was to assess the diagnostic value of additional next-generation sequencing (NGS) pathogen test for patients with suspected BSI in a surgical ICU and its potential impact on antimicrobial therapy. In this retrospective single-centre study, clinical data and results from blood culture (BC) and NGS pathogen diagnostics were analysed for ICU patients with suspected BSI. Consecutive changes in antimicrobial therapy and diagnostic procedures were evaluated. Results: 41 cases with simultaneous NGS and BC sampling were assessed. NGS showed a statistically non-significant higher positivity rate than BC (NGS: 58.5% (24/41 samples) vs. BC: 21.9% (9/41); p = 0.056). NGS detected eight different potentially relevant bacterial species, one fungus and six different viruses, whereas BC detected four different bacterial species and one fungus. NGS results affected antimicrobial treatment in 7.3% of cases. Conclusions: NGS-based diagnostics have the potential to offer a higher positivity rate than conventional culture-based methods in patients with suspected BSI. Regarding the high cost, their impact on anti-infective therapy is currently limited. Larger randomized prospective clinical multicentre studies are required to assess the clinical benefit of this novel diagnostic technology.

Combination of machine learning algorithms with natural language processing may increase the probability of bacteremia detection in the emergency department: A retrospective, big-data analysis of 94,482 patients

Background

Prompt diagnosis of bacteremia in the emergency department (ED) is of utmost importance. Nevertheless, the average time to first clinical laboratory finding range from 1 to 3 days. Alongside a myriad of scoring systems for occult bacteremia prediction, efforts for applying artificial intelligence (AI) in this realm are still preliminary. In the current study we combined an AI algorithm with a Natural Language Processing (NLP) algorithm that would potentially increase the yield extracted from clinical ED data.

Methods

This study involved adult patients who visited our emergency department and at least one blood culture was taken to rule out bacteremia. Using both tabular and free text data, we built an ensemble model that leverages XGBoost for structured data, and logistic regression (LR) on a word-analysis technique called bag-of-words (BOW) Term Frequency-Inverse Document Frequency (TF-IDF), for textual data. All algorithms were designed in order to predict the risk for bacteremia with ED patients whose blood cultures were sent to the laboratory.

Results

The study cohort comprised 94,482 individuals, of whom 52% were males. The prevalence of bacteremia in the entire cohort was 9.7%. The model trained on the tabular data yielded an area under the curve (AUC) of 73.7% for XGBoost, while the LR that was trained on the free text achieved an AUC of 71.3%. After checking a range of weights, the best combination was for 55% weight on the XGBoost prediction and 45% weight on the LR prediction. The final model prediction yielded an AUC of 75.6%.

Conclusion

Harnessing artificial intelligence to the task of bacteremia surveillance in the ED settings by a combination of both free text and tabular data analysis improved predictive performance compared to using tabular data alone. We recommend that future AI applications based on our findings should be assimilated into the clinical routines of ED physicians.

Blood culture quality and turnaround time of clinical microbiology laboratories in Chinese Teaching Hospitals: A multicenter study

PURPOSE

Blood culture (BC) remains the gold standard for the diagnosis of bloodstream infections. Improving the quality of clinical BC samples, optimizing BC performance, and accelerating antimicrobial susceptibility test (AST) results are essential for the early detection of bloodstream infections and specific treatments.

METHODS

We conducted a retrospective multicenter study using 450,845 BC specimens from clinical laboratories obtained from 19 teaching hospitals between 1 January 2021 and 31 December 2021. We evaluated key performance indicators (KPIs), turnaround times (TATs), and frequency distributions of processing in BC specimens. We also evaluated the AST results of clinically significant isolates for four different laboratory workflow styles.

RESULTS

Across the 10 common bacterial isolates (n = 16,865) and yeast isolates (n = 1011), the overall median (interquartile range) TATs of AST results were 2.67 (2.05-3.31) and 3.73 (2.98-4.64) days, respectively. The specimen collections mainly occurred between 06:00 and 24:00, and specimen reception and loadings mainly between 08:00 and 24:00. Based on the laboratory workflows of the BCs, 16 of the 19 hospitals were divided into four groups. Time to results (TTRs) from specimen collection to the AST reports were 2.35 (1.95-3.06), 2.61 (1.98-3.32), 2.99 (2.60-3.87), and 3.25 (2.80-3.98) days for groups I, II, III, and IV, respectively.

CONCLUSION

This study shows the related BC KPIs and workflows in different Chinese hospitals, suggesting that laboratory workflow optimization can play important roles in shortening time to AST reports and initiation of appropriate timely treatment.

From Epidemiology of Community-Onset Bloodstream Infections to the Development of Empirical Antimicrobial Treatment-Decision Algorithm in a Region with High Burden of Antimicrobial Resistance

Antimicrobial-resistant (AMR) infections have increased in community settings. Our objectives were to study the epidemiology of community-onset bloodstream infections (BSIs), identify risk factors for AMR-BSI and mortality-related factors, and develop the empirical antimicrobial treatment-decision algorithm. All adult, positive blood cultures at the emergency room and outpatient clinics were evaluated from 08/2021 to 04/2022. AMR was defined as the resistance of organisms to an antimicrobial to which they were previously sensitive. A total of 1151 positive blood cultures were identified. There were 450 initial episodes of bacterial BSI, and 114 BSIs (25%) were AMR-BSI. Non-susceptibility to ceftriaxone was detected in 40.9% of 195 E. coli isolates and 16.4% among 67 K. pneumoniae isolates. A treatment-decision algorithm was developed using the independent risk factors for AMR-BSI: presence of multidrug-resistant organisms (MDROs) within 90 days (aOR 3.63), prior antimicrobial exposure within 90 days (aOR 1.94), and urinary source (aOR 1.79). The positive and negative predictive values were 53.3% and 83.2%, respectively. The C-statistic was 0.73. Factors significantly associated with 30-day all-cause mortality were Pitt bacteremia score (aHR 1.39), solid malignancy (aHR 2.61), and urinary source (aHR 0.30). In conclusion, one-fourth of community-onset BSI were antimicrobial-resistant, and one-third of Enterobacteriaceae were non-susceptible to ceftriaxone. Treatment-decision algorithms may reduce overly broad antimicrobial treatment.

Metagenomic sequencing of post-mortem tissue samples for the identification of pathogens associated with neonatal deaths

Postmortem minimally invasive tissue sampling together with the detailed review of clinical records has been shown to be highly successful in determining the cause of neonatal deaths. However, conventional tests including traditional culture methods and nucleic acid amplification tests have periodically proven to be insufficient to detect the causative agent in the infectious deaths. In this study, metagenomic next generation sequencing was used to explore for putative pathogens associated with neonatal deaths in post-mortem blood and lung tissue samples, in Soweto, South Africa. Here we show that the metagenomic sequencing results corroborate the findings using conventional methods of culture and nucleic acid amplifications tests on post-mortem samples in detecting the pathogens attributed in the causal pathway of death in 90% (18/20) of the decedents. Furthermore, metagenomic sequencing detected a putative pathogen, including Acinetobacter baumannii, Klebsiella pneumoniae, Escherichia coli, and Serratia marcescens, in a further nine of 11 (81%) cases where no causative pathogen was identified. The antimicrobial susceptibility profile was also determined by the metagenomic sequencing for all pathogens with numerous multi drug resistant organism identified. In conclusion, metagenomic sequencing is able to successfully identify pathogens contributing to infection associated deaths on postmortem blood and tissue samples.

Development of an artificial intelligence bacteremia prediction model and evaluation of its impact on physician predictions focusing on uncertainty

Prediction of bacteremia is a clinically important but challenging task. An artificial intelligence (AI) model has the potential to facilitate early bacteremia prediction, aiding emergency department (ED) physicians in making timely decisions and reducing unnecessary medical costs. In this study, we developed and externally validated a Bayesian neural network-based AI bacteremia prediction model (AI-BPM). We also evaluated its impact on physician predictive performance considering both AI and physician uncertainties using historical patient data. A retrospective cohort of 15,362 adult patients with blood cultures performed in the ED was used to develop the AI-BPM. The AI-BPM used structured and unstructured text data acquired during the early stage of ED visit, and provided both the point estimate and 95% confidence interval (CI) of its predictions. High AI-BPM uncertainty was defined as when the predetermined bacteremia risk threshold (5%) was included in the 95% CI of the AI-BPM prediction, and low AI-BPM uncertainty was when it was not included. In the temporal validation dataset (N = 8,188), the AI-BPM achieved area under the receiver operating characteristic curve (AUC) of 0.754 (95% CI 0.737-0.771), sensitivity of 0.917 (95% CI 0.897-0.934), and specificity of 0.340 (95% CI 0.330-0.351). In the external validation dataset (N = 7,029), the AI-BPM's AUC was 0.738 (95% CI 0.722-0.755), sensitivity was 0.927 (95% CI 0.909-0.942), and specificity was 0.319 (95% CI 0.307-0.330). The AUC of the post-AI physicians predictions (0.703, 95% CI 0.654-0.753) was significantly improved compared with that of the pre-AI predictions (0.639, 95% CI 0.585-0.693; p-value < 0.001) in the sampled dataset (N = 1,000). The AI-BPM especially improved the predictive performance of physicians in cases with high physician uncertainty (low subjective confidence) and low AI-BPM uncertainty. Our results suggest that the uncertainty of both the AI model and physicians should be considered for successful AI model implementation.

Detection of antimicrobial impact on gram-negative bacterial cell envelope based on single-cell imaging by scanning electron microscopy

Rapid determination of drug efficacy against bacterial pathogens is needed to detect potentially resistant bacteria and allow for more rational use of antimicrobials. As an indicator of the antimicrobial effect for rapid detection, we found changes in image brightness in antimicrobial-affected bacteria by scanning electron microscopy (SEM). The cell envelopes of unaffected bacteria were stained with phosphotungstic acid (PTA), whereas the entire cells of affected bacteria were stained. Since tungsten density increases backscattered electron intensity, brighter bacterial images indicate lethal damage. We propose a simplified method for determining antimicrobial efficacy by detecting damage that occurs immediately after drug administration using tabletop SEM. This method enabled the visualization of microscopic deformations while distinguishing bacterial-cell-envelope damage on gram-negative bacteria due to image-brightness change. Escherichia coli, Acinetobacter baumannii, Enterobacter cloacae, Klebsiella pneumoniae, and Pseudomonas aeruginosa were exposed to imipenem and colistin, which affect the cell envelope through different mechanisms. Classification of single-cell images based on brightness was quantified for approximately 500 bacteria per sample, and the bright images predominated within 5 to 60 min of antimicrobial treatment, depending on the species. Using intracellular PTA staining and characteristic deformations as indicators, it was possible to determine the efficacy of antimicrobials in causing bacterial-cell-envelope damage.

Laboratory automation, informatics, and artificial intelligence: current and future perspectives in clinical microbiology

Clinical diagnostic laboratories produce one product-information-and for this to be valuable, the information must be clinically relevant, accurate, and timely. Although diagnostic information can clearly improve patient outcomes and decrease healthcare costs, technological challenges and laboratory workflow practices affect the timeliness and clinical value of diagnostics. This article will examine how prioritizing laboratory practices in a patient-oriented approach can be used to optimize technology advances for improved patient care.

Improving Blood Culture Quality with a Medical Staff Educational Program: A Prospective Cohort Study

Purpose

Blood cultures (BCs) are essential laboratory tests for diagnosing blood stream infections. BC diagnostic improvement depends on several factors during the preanalytical phase outside of innovative technologies. In order to evaluate the impact of an educational program on BC quality improvement, a total of 11 hospitals across China were included from June 1st 2020 to January 31st 2021.

Methods

Each hospital recruited 3 to 4 wards to participate. The project was divided into three different periods, pre-implementation (baseline), implementation (educational activities administered to the medical staff) and post-implementation (experimental group). The educational program was led by hospital microbiologists and included professional presentations, morning meetings, academic salons, seminars, posters and procedural feedback.

Results

The total number of valid BC case report forms was 6299, including 2739 sets during the pre-implementation period and 3560 sets during the post-implementation period. Compared with the pre-implementation period, some indicators, such as the proportion of patients who had 2 sets or more, volume of blood cultured, and BC sets per 1000 patient days, were improved in the post-implementation period (61.2% vs 49.8%, 18.56 vs 16.09 sets, and 8.0 vs 9.0mL). While BC positivity and contamination rates did not change following the educational intervention (10.44% vs 11.97%, 1.86% vs 1.94%, respectively), the proportion of coagulase negative staphylococci-positive samples decreased in BSI patients (6.87% vs 4.28%).

Conclusion

Therefore, medical staff education can improve BC quality, especially increasing volume of blood cultured as the most important variable to determine BC positivity, which may lead to improved BSI diagnosis.

Validation of a Multi-Analyte Immunoassay for Distinguishing Bacterial vs. Viral Infections in a Pediatric Cohort

BACKGROUND

Clinical presentation of viral and bacterial infections or co-infections overlaps significantly. Pathogen identification is the gold standard for appropriate treatment. Recently, FDA cleared a multivariate index test called MeMed-BV that distinguishes viral and bacterial infections based on the differential expression of 3 host proteins. Here, we sought to validate MeMed-BV immunoassay on MedKey analyzer in our pediatric hospital following guidelines from the Clinical and Laboratory Standards Institute.

METHODS

The analytical performance of the MeMed-BV test was evaluated with precision (intra- and inter-assay), method comparison and interference studies. The clinical performance (diagnostic sensitivity and specificity) of the MeMed-BV test was assessed by conducting a retrospective cohort study (n=60) using plasma samples from pediatric patients with acute febrile illness who visited the emergency department of our hospital.

RESULTS

MeMed-BV showed acceptable intra- and inter-assay precision with a range of <3 score units in both the high-score bacterial as well as the low-score viral controls. Diagnostic accuracy studies revealed a sensitivity of 94% and specificity of 88% for identifying bacterial infections or co-infections. Our MeMed-BV results showed an excellent agreement (R=0.998) with manufacturer's laboratory data and compared well with ELISA studies. Gross hemolysis and icterus did not affect the assay, but gross lipemia showed a considerable bias in samples with moderate likelihood of viral infection. Importantly, the MeMed-BV test performed better than routinely measured infection-related biomarkers like white blood cell counts, procalcitonin and C-reactive protein in classifying bacterial infections.

CONCLUSION

MeMed-BV immunoassay demonstrated acceptable analytical performance and is reliable for distinguishing viral and bacterial infections or co-infections in pediatric patients. Future studies are warranted to examine the clinical utility, especially with respect to reducing the need for blood cultures and time to treatment for the patient.

Evaluation of a sterile, filter-based, in-house method for rapid direct bacterial identification and antimicrobial susceptibility testing using positive blood culture

This study aimed to assess the performance of our in-house method for rapid direct bacterial identification (ID) and antimicrobial susceptibility testing (AST) using a positive blood culture (BC) broth. For Gram-negative bacteria, 4 mL of BC broth was aspirated and passed through a Sartorius Minisart syringe filter with a pore size of 5 µm. The filtrate was then centrifuged and washed. A small volume of the pellet was used for ID, using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, and for AST, using automated broth microdilution. For Gram-positive cocci, 4 mL of BC broth was passed through the Minisart syringe filter. Then, 4 mL of sterile distilled water was injected in the direction opposite to that of the filtration to collect the bacterial residue trapped in the filter. Compared with the conventional method performed with pure colonies on agar plates, 94.0% (234/249) were correctly identified using the in-house method, with rates of 91.4% (127/139) and 97.3% (107/110) for Gram-positive and Gram-negative isolates, respectively. Of 234 correctly identified isolates, 230 were assessed by AST. Categorical agreement and essential agreement were 93.3% and 94.5%, respectively, with a minor error rate of 3.8%, a major error rate of 3.4%, and a very major error rate of 1.6%. Our in-house preparation method showed good performance in rapid direct ID and AST using positive BC broths compared to the conventional method. This simple method can shorten the conventional turnaround time for ID and AST by at least 1 day, potentially contributing to better patient management.

Antibiotic appropriateness for Gram-negative bloodstream infections: impact of infectious disease consultation

BACKGROUND

We investigated the role of infectious disease consultation (IDC) on therapeutic appropriateness in Gram-negative bloodstream infections (GNBSIs) in a setting with a high proportion of antibiotic resistance. Secondary outcomes were in-hospital mortality and the impact of rapid diagnostic tests (RDTs).

METHODS

Retrospective study on hospitalised patients with GNBSIs. Therapy was deemed appropriate if it had the narrowest spectrum considering infection and patients' characteristics. Interventional-IDC (I-IDC) group included patients with IDC-advised first appropriate or last non-appropriate therapy. Time to first appropriate therapy and survival were evaluated by Kaplan-Meier curves. Factors associated with therapy appropriateness were assessed by multivariate Cox proportional-hazard models.

RESULTS

471 patients were included. High antibiotic resistance rates were detected: quinolones 45.5%, third-generation cephalosporins 37.4%, carbapenems 7.9%. I-IDC was performed in 31.6% of patients (149/471), RDTs in 70.7% (333/471). The 7-day probability of appropriate treatment was 91.9% (95% confidence interval [95%CI]: 86.4-95.8%) vs. 75.8% (95%CI: 70.9-80.4%) with and without I-IDC, respectively (p-value = 0.0495); 85.5% (95%CI: 81.3-89.1%) vs. 69.4% (95%CI: 61.3-77.2%) with and without RDTs, respectively (p-value = 0.0023). Compared to RDTs alone, the combination with I-IDC was associated with a higher proportion of appropriate therapies at day 7: 81.9% (95%CI: 76.4-86.7%) vs. 92.6% (95%CI: 86.3-96.7%). At multivariate analysis, I-IDC and RDTs were associated with time to first appropriate therapy [adjusted hazard-ratio 1.292 (95%CI: 1.014-1.647) and 1.383 (95%CI: 1.080-1.771), respectively], with no impact on mortality.

CONCLUSIONS

In a setting with a high proportion of antibiotic resistance, IDC and RDTs were associated with earlier prescription of appropriate therapy in GNBSIs, without impact on mortality.

Nanopore-Targeted Sequencing Improves the Diagnosis and Treatment of Patients with Serious Infections

Serious infections are characterized by rapid progression, poor prognosis, and difficulty in diagnosis. Recently, a new technique known as nanopore-targeted sequencing (NTS) was developed that facilitates the rapid and accurate detection of pathogenic microorganisms and is extremely suitable for patients with serious infections. The aim of our study was to evaluate the clinical application of NTS in the diagnosis and treatment of patients with serious infections. We developed an NTS technology that could detect microorganisms within a 6-h window based on the amplification of the 16S rRNA gene of bacteria, the internal transcribed spacer region of fungi, and the rpoB gene of Mycobacterium. The NTS detection results were compared with those of blood cultures and anal swabs from 50 patients with blood diseases suffering serious infections. The patient's condition before and after NTS was compared. The response rate and the infection-related mortality after the adjustment of antibiotics based on NTS were calculated. The positivity rate of pathogens was highest in NTS (90%), followed by blood culture (32.6%) and anal swabs (14.6%). After adjusting antibiotics for bacteria and fungi detected by NTS, the patients' condition improved significantly. Moreover, the response rate of anti-infective treatment based on NTS was 93.02% (40/43), and infection-related mortality was reduced to 0. NTS is an effective method to identify pathogens in the blood specimens of patients with serious infections and can guide anti-infection treatment and reduce infection-related mortality. IMPORTANCE We introduce the application of NTS in blood samples of patients with serious infections and expound the efficiency and accuracy of NTS in detecting pathogenic microorganisms. Our work builds on the considerable interest of the scientific community in the management of serious infection. This issue is becoming more pressing, especially since the incidence of blood diseases is increasing year by year and hematopoietic stem cell transplantation (HSCT) has been widely used in benign and malignant blood diseases in recent years. The infection progression of these patients is faster, and the study further demonstrates the effectiveness of NTS in guiding the diagnosis and treatment of patients with severe infections. We firmly believe that this method will guide clinicians to adjust anti-infection strategies and bring significant benefits to patients, and our study will have implications for the future clinical application of NTS in all kinds of patients with serious infections.

Antimicrobial susceptibility testing: An updated primer for clinicians in the era of antimicrobial resistance: Insights from the Society of Infectious Diseases Pharmacists

Antimicrobial susceptibility testing (AST) is a critical function of the clinical microbiology laboratory and is essential for optimizing care of patients with infectious diseases, monitoring antimicrobial resistance (AMR) trends, and informing public health initiatives. Several methods are available for performing AST including broth microdilution, agar dilution, and disk diffusion. Technological advances such as the development of commercial automated susceptibility testing platforms and the advent of rapid diagnostic tests have improved the rapidity, robustness, and clinical application of AST. Numerous accrediting and regulatory agencies are involved in the process of AST and setting and revising breakpoints, including the U.S. Food and Drug Administration and the Clinical and Laboratory Standards Institute. Challenges to optimizing AST include the emergence of new resistance mechanisms, the development of new antimicrobial agents, and generation of new data requiring updates and revisions to established methods and breakpoints. Together, the challenges in AST methods and their interpretation create important opportunities for well-informed clinicians to improve patient outcomes and provide value to antimicrobial stewardship programs, especially in the setting of rapidly changing and increasing AMR. Addressing AST challenges will involve continued development of new technologies along with collaboration between clinicians and the laboratory to facilitate optimal antimicrobial use, combat the increasing burden of AMR, and inform the development of novel antimicrobials. This updated primer serves to reinforce important principles of AST, and to provide guidance on their implementation and optimization.

Multicenter Evaluation of the FilmArray Blood Culture Identification 2 Panel for Pathogen Detection in Bloodstream Infections

The FilmArray Blood Culture Identification 2 panel (BCID2; bioMérieux) is a fully automated PCR-based assay for identifying bacteria, fungi, and bacterial resistance markers in positive blood cultures (BC) in about 1 h. In this multicenter study, we evaluated the performance of the BCID2 panel for pathogen detection in positive BC. Conventional culture and BCID2 were performed in parallel at four tertiary-care hospitals. We included 152 positive BC-130 monomicrobial and 22 polymicrobial cultures-in this analysis. The BCID2 assay correctly identified 90% (88/98) of Gram-negative and 89% (70/79) of Gram-positive bacteria. Five bacterial isolates targeted by the BCID2 panel and recovered from five positive BC, including three polymicrobial cultures, were missed by the BCID2 assay. Fifteen isolates were off-panel organisms, accounting for 8% (15/182) of the isolates obtained from BC. The mean positive percent agreement between the BCID2 assay and standard culture was 97% (95% confidence interval, 95 to 99%), with agreement ranging from 67% for Candida albicans to 100% for 17 targets included in the BCID2 panel. BCID2 also identified the blaCTX-M gene in seven BC, including one for which no extended-spectrum β-lactamase (ESBL)-producing isolate was obtained in culture. However, it failed to detect ESBL-encoding genes in three BC. Two of the 18 mecA/C genes detected by the BCID2 were not confirmed. No carbapenemase, mecA/C, or MREJ targets were detected. The median turnaround time was significantly shorter for BCID2 than for culture. The BCID2 panel may facilitate faster pathogen identification in bloodstream infections. IMPORTANCE Rapid molecular diagnosis combining the identification of pathogens and the detection of antibiotic resistance genes from positive blood cultures (BC) can improve the outcome for patients with bloodstream infections. The FilmArray BCID2 panel, an updated version of the original BCID, can detect 11 Gram-positive bacteria, 15 Gram-negative bacteria, 7 fungal pathogens, and 10 antimicrobial resistance genes directly from a positive BC. Here, we evaluated the real-life microbiological performance of the BCID2 assay in comparison to the results of standard methods used in routine practice at four tertiary care hospitals.

Metagenomic Antimicrobial Susceptibility Testing from Simulated Native Patient Samples

Genomic antimicrobial susceptibility testing (AST) has been shown to be accurate for many pathogens and antimicrobials. However, these methods have not been systematically evaluated for clinical metagenomic data. We investigate the performance of in-silico AST from clinical metagenomes (MG-AST). Using isolate sequencing data from a multi-center study on antimicrobial resistance (AMR) as well as shotgun-sequenced septic urine samples, we simulate over 2000 complicated urinary tract infection (cUTI) metagenomes with known resistance phenotype to 5 antimicrobials. Applying rule-based and machine learning-based genomic AST classifiers, we explore the impact of sequencing depth and technology, metagenome complexity, and bioinformatics processing approaches on AST accuracy. By using an optimized metagenomics assembly and binning workflow, MG-AST achieved balanced accuracy within 5.1% of isolate-derived genomic AST. For poly-microbial infections, taxonomic sample complexity and relatedness of taxa in the sample is a key factor influencing metagenomic binning and downstream MG-AST accuracy. We show that the reassignment of putative plasmid contigs by their predicted host range and investigation of whole resistome capabilities improved MG-AST performance on poly-microbial samples. We further demonstrate that machine learning-based methods enable MG-AST with superior accuracy compared to rule-based approaches on simulated native patient samples.

Fast Track Diagnostic Tools for Clinical Management of Sepsis: Paradigm Shift from Conventional to Advanced Methods

Sepsis is one of the deadliest disorders in the new century due to specific limitations in early and differential diagnosis. Moreover, antimicrobial resistance (AMR) is becoming the dominant threat to human health globally. The only way to encounter the spread and emergence of AMR is through the active detection and identification of the pathogen along with the quantification of resistance. For better management of such disease, there is an essential requirement to approach many suitable diagnostic techniques for the proper administration of antibiotics and elimination of these infectious diseases. The current method employed for the diagnosis of sepsis relies on the conventional culture of blood suspected infection. However, this method is more time consuming and generates results that are false negative in the case of antibiotic pretreated samples as well as slow-growing microbes. In comparison to the conventional method, modern methods are capable of analyzing blood samples, obtaining accurate results from the suspicious patient of sepsis, and giving all the necessary information to identify the pathogens as well as AMR in a short period. The present review is intended to highlight the culture shift from conventional to modern and advanced technologies including their limitations for the proper and prompt diagnosing of bloodstream infections and AMR detection.

Epidemiology and Economic Outcomes Associated with Timely versus Delayed Receipt of Appropriate Antibiotic Therapy among US Patients Hospitalized for Native Septic Arthritis: A Retrospective Cohort Study

Timely administration of appropriate antibiotic therapy is associated with better patient outcomes and lower costs of care compared to delayed appropriate therapy, yet initial treatment is often empiric since causal pathogens are typically unknown upon presentation. The challenge for clinicians is balancing selection of adequate coverage treatment regimens, adherence to antimicrobial stewardship principles to deter resistance, and financial constraints. This retrospective cohort study aimed to assess the magnitude and impact of delayed appropriate antibiotic therapy among patients hospitalized with septic arthritis (SA) in the U.S. from 2017 to 2019 using healthcare encounter data. Timely appropriate therapy was defined as the receipt of antibiotic(s) with in vitro activity against identified pathogens within two days of admission; all other patients were assumed to have received delayed appropriate therapy. Of the 517 patients admitted to hospital for SA who met all selection criteria, 26 (5.0%) received delayed appropriate therapy. In inverse-probability-treatment-weighting-adjusted analyses, the receipt of delayed appropriate therapy was associated with an additional 1.1 days of antibiotic therapy, 1.4 days in length of stay, and $3531 in hospital costs (all vs. timely appropriate therapy; all p ≤ 0.02). Timely appropriate therapy was associated with a twofold increased likelihood of antibiotic de-escalation during the SA admission.

Optimizing antimicrobial therapy in urinary tract infections: A focus on urine culture and sensitivity testing

Objectives: This cross-sectional study was conducted at Jordan university hospital to evaluate the impact of microbial culture data and sensitivity results on optimizing UTI treatment. Methods: All positive urine cultures requested for adult patients (≥18 years) admitted to Jordan University Hospital (JUH) within the period from January 2019-July 2021 were evaluated. The antibiotics prescribed before and after culture data and sensitivity results were compared to evaluate the impact of these diagnostic measures on optimizing UTI treatment. Results: During the study period, 2400 urine cultures revealed positive results. Among those patients, 1,600 (66.7%) were discharged before the availability of culture results and excluded. Of the remaining 800 patients, 701 patients (87.6%) received empiric treatment. After culture and sensitivity results were available, overall, 84 (10.5%) patients had optimization (improvement) in their UTI management after culture results were known, while 6 (0.8%) patients had a worsening in their treatments. Based on the culture results, we found that only 12.4% of patients were appropriately treated before and after the culture results. Moreover, our results revealed that 31.9% were inappropriately treated for their UTIs before and after culture results. Conclusion: This study revealed an alarmingly high rate of inappropriate treatment of UTIs despite the availability of urine culture and sensitivity data, and that culture results were not used to optimize treatment strategies for UTI. This practice can potentially result in poor health-related outcomes and adversely affects efforts to battle AMR. Multifaceted strategies must be implemented to help clinicians follow the best current evidence and current guidelines in their selection of antibiotics for the management of UTIs.

Performance of real-time PCR in suspected haemodialysis catheter-related bloodstream infection: a proof-of-concept study

Background

Catheter-related bloodstream infections (CRBIs) remain a major cause of mortality in haemodialysis (HD) patients with central venous catheters (CVCs), especially because of the non-specific symptomatology and the delay in microbiological diagnosis with possible use of non-optimal empiric antibiotics. Moreover, empiric broad-spectrum antibiotics increase antibiotic resistance development. This study aims to evaluate the diagnostic performance of real-time polymerase chain reaction (rt-PCR) in suspected HD CRBIs compared with blood cultures.

Methods

A blood sample for rt-PCR was collected simultaneously with each pair of blood cultures for suspected HD CRBI. The rt-PCR was performed on the whole blood, without any enrichment stage and with specific DNA primers: 16S (universal bacterial), Staphylococcus spp., Staphylococcus aureus and mecA. Each successive patient with a suspected HD CRBI in the HD centre of Bordeaux University Hospital was included. Performance tests were used to compare the result obtained in each rt-PCR assay with its corresponding routine blood culture.

Results

Eighty-four paired samples were collected and compared for 40 suspected HD CRBI events in 37 patients. Among these, 13 (32.5%) were diagnosed as HD CRBI. All rt-PCRs except mecA (insufficient number of positive samples) showed high diagnostic performances within 3.5 h: 16S (sensitivity 100%, specificity 78%), Staphylococcus spp. (sensitivity 100%, specificity 97%), S. aureus (sensitivity 100%, specificity 99%). Based on the rt-PCR results, antibiotics could be more appropriately targeted, thus cutting anti-cocci Gram-positive therapy from 77% to 29%.

Conclusions

The performance of rt-PCR in suspected HD CRBI events showed fast and high diagnostic accuracy. Its use would improve HD CRBI management with an antibiotic consumption decrease.

Analysis of Blood Culture Collection and Laboratory Processing Practices in Israel

IMPORTANCE

Blood culturing is a critical diagnostic procedure affecting patient outcomes and antibiotic stewardship. Although there are standards for blood culturing, the process is not often measured.

OBJECTIVES

To evaluate processes related to the diagnosis of bloodstream infection and compare them with best practices.

DESIGN, SETTING, AND PARTICIPANTS

A quality improvement study using laboratory data from January 1 to June 30, 2019, was conducted in 28 (96.6%) Israeli acute care hospitals. All blood cultures (BCs) performed on samples from adults and children in a period of 147 hospital-months were analyzed. Data analysis was performed from April 12, 2021, to September 9, 2022.

MAIN OUTCOMES AND MEASURES

True pathogen detection rate, contamination rate, proportion of adults with blood cultures performed, proportion of adult culturing episodes with only 1 set or bottle used, and median time of steps from sample collection to pathogen identification.

RESULTS

The data set consisted of 348 987 BC bottles. Bloodstream infection was detected in a median of 6.7% (IQR, 5.8%-8.2%) of adult culturing episodes and 1.1% (IQR, 0.7%-1.9%) of pediatric episodes. Eleven of 27 hospitals (40.7%) with adult patients met the standard of a contamination rate of less than 3% and only 2 hospitals (7.4%) met the more stringent standard of less than or equal to 1% contamination rate. The percentage of adults with blood cultures ranged from 2.7% to 29.0% (mean [SD], 15.7% [6.0%]). There was an association between sampling rate and pathogen detection until BCs were performed in 17% of adult admissions. The percentage of solitary BCs ranged from 47.8% to 94.4%. An estimated 1745 of 7436 (23.5%) adult bloodstream infections went undetected because solitary BCs were performed, anaerobic bottles were not used, or BCs were not performed. Median processing time was 51.2 (IQR, 33.9-78.0) hours, 3 times the optimal time: 4.4 (IQR, 1.7-12.5) hours for the preanalytical stage, 15.9 (IQR, 10.2-23.6) hours from incubation to growth detection, 4.5 (IQR, 1.5-10.7) hours from detection to Gram stain, and 30.9 (IQR, 22.0-41.9) hours from detection to isolate identification. An 8.6-hour delay was related to off-hours operating of laboratories.

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that the multistep process of blood culturing is not managed comprehensively in Israel, leading to poor clinical practices and delayed results.

Outer membrane vesicles as molecular biomarkers for Gram-negative sepsis: Taking advantage of nature's perfect packages

Sepsis is an often life-threatening response to infection, occurring when host proinflammatory immune responses become abnormally elevated and dysregulated. To diagnose sepsis, the patient must have a confirmed or predicted infection, as well as other symptoms associated with the pathophysiology of sepsis. However, a recent study found that a specific causal organism could not be determined in the majority (70.1%) of sepsis cases, likely due to aggressive antibiotics or localized infections. The timing of a patient's sepsis diagnosis is often predictive of their clinical outcome, underlining the need for a more definitive molecular diagnostic test. Here, we outline the advantages and challenges to using bacterial outer membrane vesicles (OMVs), nanoscale spherical buds derived from the outer membrane of Gram-negative bacteria, as a diagnostic biomarker for Gram-negative sepsis. Advantages include OMV abundance, their robustness in the presence of antibiotics, and their unique features derived from their parent cell that could allow for differentiation between bacterial species. Challenges include the rigorous purification methods required to isolate OMVs from complex biofluids and the additional need to separate OMVs from similarly sized extracellular vesicles, which can share physical properties with OMVs.