Laboratory automation reduces time to report of positive blood cultures and improves management of patients with bloodstream infection

The Impact of Laboratory Automation on the Time to Urine Microbiological Results: A Five-Year Retrospective Study

Total laboratory automation (TLA) is a valuable component of microbiology laboratories and a growing number of publications suggest the potential impact of automation in terms of analysis standardization, streaking quality, and the turnaround time (TAT). The aim of this project was to perform a detailed investigation of the impact of TLA on the workflow of commonly treated specimens such as urine. This is a retrospective observational study comparing two time periods (pre TLA versus post TLA) for urine specimen culture processing. A total of 35,864 urine specimens were plated during the pre-TLA period and 47,283 were plated during the post-TLA period. The median time from streaking to identification decreased from 22.3 h pre TLA to 21.4 h post TLA (p < 0.001), and the median time from streaking to final validation of the report decreased from 24.3 h pre TLA to 23 h post TLA (p < 0.001). Further analysis revealed that the observed differences in TAT were mainly driven by the contaminated and positive samples. Our findings demonstrate that TLA has the potential to decrease turnaround times of samples in a laboratory. Nevertheless, changes in laboratory workflow (such as extended opening hours for plate reading and antibiotic susceptibility testing or decreased incubation times) might further maximize the efficiency of TLA and optimize TATs.

Prospective observational pilot study of the T2Resistance panel in the T2Dx system for detection of resistance genes in bacterial bloodstream infections

Early initiation of antimicrobial therapy targeting resistant bacterial pathogens causing sepsis and bloodstream infections (BSIs) is critical for a successful outcome. The T2Resistance Panel (T2R) detects the following resistance genes within organisms that commonly cause BSIs directly from patient blood samples: blaKPC, blaCTXM-14/15, blaNDM/bla/IMP/blaVIM, blaAmpC, blaOXA, vanA, vanB, and mecA/mecC. We conducted a prospective study in two major medical centers for the detection of circulating resistance genes by T2R in patients with BSIs. T2R reports were compared to antimicrobial susceptibility testing (AST), phenotypic identification, and standard molecular detection assays. Among 59 enrolled patients, 25 resistance genes were identified: blaKPC (n = 10), blaNDM/bla/IMP/blaVIM (n = 5), blaCTXM-14/15 (n = 4), blaAmpC (n = 2), and mecA/mecC (n = 4). Median time-to-positive-T2R in both hospitals was 4.4 hours [interquartile range (IQR): 3.65-4.97 hours] in comparison to that for positive blood cultures with final reporting of AST of 58.34 h (IQR: 45.51-111.2 hours; P < 0.0001). The sensitivity of T2R to detect the following genes in comparison to AST was 100% for blaCTXM-14/15, blaNDM/bla/IMP/blaVIM, blaAmpC, mecA/mecC and 87.5% for blaKPC. When monitored for the impact of significant antimicrobial changes, there were 32 events of discontinuation of unnecessary antibiotics and 17 events of escalation of antibiotics, including initiation of ceftazidime/avibactam in six patients in response to positive T2R results for blaKPC. In summary, T2R markers were highly sensitive for the detection of drug resistance genes in patients with bacterial BSIs, when compared with standard molecular resistance detection systems and phenotypic identification assays while significantly reducing by approximately 90% the time to detection of resistance compared to standard methodology and impacting clinical decisions for antimicrobial therapy.

IMPORTANCE

This is the first reported study to our knowledge to identify key bacterial resistance genes directly from the bloodstream within 3 to 5 hours in patients with bloodstream infections and sepsis. The study further demonstrated a direct effect in modifying initial empirical antibacterial therapy in response to T2R signal to treat resistant bacteria causing bloodstream infections and sepsis.

Benefit analysis of the auto-verification system of intelligent inspection for microorganisms

In recent years, the automatic machine for microbial identification and antibiotic susceptibility tests has been introduced into the microbiology laboratory of our hospital, but there are still many steps that need manual operation. The purpose of this study was to establish an auto-verification system for bacterial naming to improve the turnaround time (TAT) and reduce the burden on clinical laboratory technologists. After the basic interpretation of the gram staining results of microorganisms, the appearance of strain growth, etc., the 9 rules were formulated by the laboratory technologists specialized in microbiology for auto-verification of bacterial naming. The results showed that among 70,044 reports, the average pass rate of auto-verification was 68.2%, and the reason for the failure of auto-verification was further evaluated. It was found that the main causes reason the inconsistency between identification results and strain appearance rationality, the normal flora in the respiratory tract and urine that was identified, the identification limitation of the mass spectrometer, and so on. The average TAT for the preliminary report of bacterial naming was 35.2 h before, which was reduced to 31.9 h after auto-verification. In summary, after auto-verification, the laboratory could replace nearly 2/3 of manual verification and issuance of reports, reducing the daily workload of medical laboratory technologists by about 2 h. Moreover, the TAT on the preliminary identification report was reduced by 3.3 h on average, which could provide treatment evidence for clinicians in advance.

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.

Current State of Laboratory Automation in Clinical Microbiology Laboratory

BACKGROUND

Although it has been 30 years since the first automation systems were introduced in the microbiology laboratory, total laboratory automation (TLA) has only recently been recognized as a valuable component of the laboratory. A growing number of publications illustrate the potential impact of automation. TLA can improve standardization, increase laboratory efficiency, increase workplace safety, and reduce long-term costs.

CONTENT

This review provides a preview of the current state of automation in clinical microbiology and covers the main developments during the last years. We describe the available hardware systems (that range from single function devices to multifunction workstations) and the challenging alterations on workflow and organization of the laboratory that have to be implemented to optimize automation.

SUMMARY

Despite the many advantages in efficiency, productivity, and timeliness that automation offers, it is not without new and unique challenges. For every advantage that laboratory automation provides, there are similar challenges that a laboratory must face. Change management strategies should be used to lead to a successful implementation. TLA represents, moreover, a substantial initial investment. Nevertheless, if properly approached, there are a number of important benefits that can be achieved through implementation of automation in the clinical microbiology laboratory. Future developments in the field of automation will likely focus on image analysis and artificial intelligence improvements. Patient care, however, should remain the epicenter of all future directions and there will always be a need for clinical microbiology expertise to interpret the complex clinical and laboratory information.

Hyper-Virulent Listeria monocytogenes Strains Associated With Respiratory Infections in Central Italy

Listeria monocytogenes (Lm) is a foodborne pathogen causing listeriosis. Invasive forms of the disease mainly manifest as septicaemia, meningitis and maternal-neonatal infections. Lm-associated respiratory infections are very rare and little known. We reported two Lm respiratory infection cases occurred in Central Italy during the summer of 2020, in the midst of the SARS-CoV2 pandemic. In addition to collect the epidemiological and clinical characteristics of the patients, we used Whole Genome Sequencing to study the genomes of the Lm isolates investigating their virulence and antimicrobial profiles and the presence of genetic mobile elements. Both the strains belonged to hypervirulent MLST clonal complexes (CC). In addition to the Listeria Pathogenicity Island 1 (LIPI-1), the CC1 strain also carried LIPI-3 and the CC4 both LIPI-3 and LIPI-4. Genetic determinants for antimicrobial and disinfectants resistance were found. The CC1 genome presented prophage sequences but they did not interrupt the comK gene, involved in the phagosomal escape of Lm. None of the strains carried plasmids. Lm is an important, although rare, opportunistic pathogen for respiratory tract and lung infections. To avoid dangerous diagnostic delays of these severe clinical forms, it is important to sensitize hospital laboratories to this rare manifestation of listeriosis considering Lm in the differential diagnosis of respiratory infections.

Accuracy and Impact on Patient Management of New Tools for Diagnosis of Sepsis: Experience with the T2 Magnetic Resonance Bacteria Panel

The rapid and accurate identification of pathogens responsible for sepsis is essential for prompt and effective antimicrobial therapy. Molecular technologies have been developed to detect the most common causative agents, with high sensitivity and short time to result (TTR). T2 Bacteria Panel (T2), based on a combination of PCR and T2 magnetic resonance, can identify directly in blood samples Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Enterococcus faecium, and Acinetobacter baumannii pathogens. This study evaluates the role of T2 in the diagnosis of sepsis and its impact on patient management, specifically in terms of TTR and the switch from empirical to directed therapy, comparing results of blood culture (BC) and T2 assay in 82 patients with sepsis. T2 significantly improved the detection of the causative agents of sepsis. For pathogens included in the panel, T2 sensitivity was 100% (95% CI 86.3–100.0), significantly higher than that of BC (54.8%, 95% CI 36.0–72.7). The TTR (median, IQR) of positive T2 (3.66 h, 3.59–4.31) was significantly shorter than that of the positive BC (37.58 h, 20.10–47.32). A significant reduction in the duration of empiric therapy and an increase in the percentage of patients with switched therapy was observed in patients with a positive T2 result. In conclusion, T2 can shorten and improve the etiological diagnosis of sepsis with a positive impact on patient management.

Accelerate Pheno™ blood culture detection system: a literature review

Accelerate Pheno™ (ACC) is a fully automated system providing rapid identification of a panel of bacteria and yeasts, and antimicrobial susceptibility testing of common bacterial pathogens responsible for bloodstream infections and sepsis. Diagnostic accuracy for identification ranges from 87.9 to 100%, and antimicrobial susceptibility testing categorical agreement is higher than 91%. The present review includes peer-reviewed studies on ACC published to date. Both interventional and hypothetical studies evidenced the potential positive clinical role of ACC in the management and therapy of patients with bloodstream infections and sepsis, due to the important reduction in time to report, suggesting a crucial impact on the therapeutic management of these patients, provided the presence of a hospital antimicrobial stewardship program, a 24/7 laboratory operating time and a strict collaboration between clinical microbiologist and clinician. Further prospective multicenter studies are necessary to explore the impact of this system on mortality, length of stay and spread of multidrug-resistant organisms.

Laboratory and clinical impacts of an overnight laboratory service

Delayed initiation of effective antimicrobial therapy for sepsis is associated with increased mortality. Whilst automated blood culture machines operate continuously, this does not align with conventional staff working hours and so turn-around-times (TAT) for reporting gram stains to clinicians are 3-7 times longer for blood cultures that flag positive overnight. We retrospectively compared laboratory TATs and clinical outcomes for blood cultures from 183 patients that flagged positive overnight during a 4-month period before and after the implementation of an overnight laboratory service. Enterobacterales and urinary tract infections were the most frequent pathogens and clinical syndrome respectively, and the prevalence of multi-resistant organisms was 15%. Compared with the pre-implementation period, the post-implementation period was associated with shorter median time from blood culture positivity to gram stain (7.4 vs 1.2 h), first genus level identification (7.2 vs 5.8 h) and first antimicrobial susceptibility result (24.1 vs 7.9 h). Similarly, the median time from blood culture positivity to clinicians first being informed was significantly shorter (9.2 vs 1.3 h). After removal of likely contaminants, 78% of patients were on effective empiric antimicrobials and for patients on ineffective empiric antimicrobials, effective therapy was initiated a median of 3.2 h sooner during the post-implementation period, without impact on mortality. Implementation of an overnight laboratory service was associated with significantly faster TAT for reporting blood culture results and more prompt initiation of effective antimicrobials for patients receiving ineffective empiric therapy, improving attainment of sepsis management goals.

Consolidation of Clinical Microbiology Laboratories and Introduction of Transformative Technologies

Clinical microbiology is experiencing revolutionary advances in the deployment of molecular, genome sequencing-based, and mass spectrometry-driven detection, identification, and characterization assays. Laboratory automation and the linkage of information systems for big(ger) data management, including artificial intelligence (AI) approaches, also are being introduced. The initial optimism associated with these developments has now entered a more reality-driven phase of reflection on the significant challenges, complexities, and health care benefits posed by these innovations. With this in mind, the ongoing process of clinical laboratory consolidation, covering large geographical regions, represents an opportunity for the efficient and cost-effective introduction of new laboratory technologies and improvements in translational research and development. This will further define and generate the mandatory infrastructure used in validation and implementation of newer high-throughput diagnostic approaches. Effective, structured access to large numbers of well-documented biobanked biological materials from networked laboratories will release countless opportunities for clinical and scientific infectious disease research and will generate positive health care impacts. We describe why consolidation of clinical microbiology laboratories will generate quality benefits for many, if not most, aspects of the services separate institutions already provided individually. We also define the important role of innovative and large-scale diagnostic platforms. Such platforms lend themselves particularly well to computational (AI)-driven genomics and bioinformatics applications. These and other diagnostic innovations will allow for better infectious disease detection, surveillance, and prevention with novel translational research and optimized (diagnostic) product and service development opportunities as key results.

Evaluation of EUCAST rapid antimicrobial susceptibility testing (RAST) for positive blood cultures in clinical practice using a total lab automation

Our objective was to evaluate EUCAST’s ‘rapid antimicrobial susceptibility testing’ (RAST) directly from positive blood culture that delivers antimicrobial results within 6 h for Staphylococcus aureus, Enterococcus spp., Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa, using total lab automation. Zone diameters from RAST were compared with MIC results. Furthermore, its influence on time to report was investigated. RAST was performed to all positive aerobic and anaerobic blood culture bottles by subculturing them, i.e. onto Mueller-Hinton agar and adding six antibiotic discs covering Gram-negative and Gram-positive therapy (cefoxitin, ampicillin, vancomycin, piperacillin/tazobactam, meropenem and ciprofloxacin). RAST was automatically imaged after 6 h. Zone sizes were measured using a TLA software tool and interpreted according to EUCAST clinical breakpoints. Bacteria were identified using MALDI-TOF MS and MIC results were determined using Vitek2 panels. Categorial agreement between agar diffusion and MIC results was investigated. Additionally, time to RAST and time to Vitek were compared for 100 isolates (20 per species). Between November 2018 and April 2019, 3313 positive mono-bacterial blood culture bottles were collected of which 894 bottles with RAST-validated species were investigated. Among these bottles, 2029 individual antibiotic measurements were compared with MIC results from Vitek2 and 14 very major, 28 major and 12 minor errors were found. A median reduction of 17:30 h in time to report was observed. Introduction of RAST with automatic TLA imaging function could reduce time to report by 17:30 h. Excellent accordance between zone diameter and MIC results, particularly for cefoxitin, vancomycin and meropenem, was observed, but drawbacks due to ATU were seen.

Impact of reduced incubation times on culture and susceptibility testing of urine cultures incubated in the BD Kiestra ReadA Compact incubators

We determined the impact of reducing incubation times for urine cultures incubated in BD Kiestra ReadA Compact incubators. Urine samples (n = 348) were inoculated to solid media, incubated in the ReadA Compacts and processed at 12, 15, and 18 h. Colony size and identification by MALDI-TOF, growth, semi-quantitation, Vitek and disk diffusion susceptibilities from cultures incubated at 12 and 15 h were compared to 18 h. There was no impact on MALDI-TOF performed after 12 and 15 versus 18 h of incubation. Interpretation for 99% of urine cultures was identical at 15 and 18 h. There was no major or very major error for VitekII or disk diffusion testing with >94% and >92% overall agreement for Gram-negative and positives organisms, respectively. Therefore, reducing the maximum incubation times of primary cultures incubated in the ReadA Compacts from 18 h to 15 h did not impact outcomes.

Measurement and prediction of antimicrobial resistance in bloodstream infections by ESKAPE pathogens and Escherichia coli

OBJECTIVES

This study aimed to evaluate a cumulative antimicrobial resistance index (ARI) as a possible key outcome measure of antimicrobial stewardship programmes (ASPs) and a tool to predict the antimicrobial resistance (AMR) trend.

METHODS

Antimicrobial susceptibility for Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp. and Escherichia coli (ESKAPEEc) pathogens recovered from blood cultures during a 5-year period (2014-2018) was analysed to obtain a cumulative ARI. For each antibiotic tested, a score of 0, 0.5 or 1 was assigned for susceptibility, intermediate resistance or resistance, respectively, and the ARI was calculated by dividing the sum of these scores by the number of antibiotics tested. Cumulative ARIs of ESKAPEEc micro-organisms were compared and a mathematical prediction model for AMR trend was obtained.

RESULTS

In total, 1858 ESKAPEEc isolates were included in the study. The cumulative ESKAPEEc mean ARI increased significantly from 0.200 ± 0.01 in 2014 to 0.276 ± 0.02 in 2018 (P < 0.001). In multivariable regression analysis, factors significantly associated with ARI ≥ 0.5 were E. faecium, K. pneumoniae, P. aeruginosa and A. baumannii infection (P < 0.001) and infection occurring after 2014 (P < 0.05). Based on the prediction model obtained, in the absence of any interventional measure, a tendency to pandrug resistance of the ESKAPEEc group could be expected in the next 8-15 years.

CONCLUSION

The ARI could be a useful tool to measure the impact of ASPs on AMR. The increasing incidence of AMR among ESKAPEEc organisms underscores the needing for ASPs.

Laboratory Automation in Clinical Microbiology

Laboratory automation is currently the main organizational challenge for microbiologists. Automating classic workflows is a strenuous process for the laboratory personnel and a huge and long-lasting financial investment. The investments are rewarded through increases in quality and shortened time to report. However, the benefits for an individual laboratory can only be estimated after the implementation and depending on the classic workflows currently performed. The two main components of automation are hardware and workflow. This review focusses on the workflow aspects of automation and describes some of the main developments during recent years. Additionally, it tries to define some terms which are related to automation and specifies some developments which would further improve automated systems.