Fully Automated EUCAST Rapid Antimicrobial Susceptibility Testing (RAST) from Positive Blood Cultures: Diagnostic Accuracy and Implementation

Conversion of a classical microbiology laboratory to a total automation laboratory enhanced by the application of lean principles

Laboratory automation in microbiology improves productivity and reduces sample turnaround times (TATs). However, its full potential can be unlocked through the optimization of workflows by adopting lean principles. This study aimed to explore the relative impact of laboratory automation and continuous improvement events (CIEs) on productivity and TATs. Laboratory automation took place in November 2020 and consisted of the introduction of WASPLab and VITEK MS systems. CIEs were run in May and September 2021. Before the conversion, the laboratory processed about ~492 samples on weekdays and had 10 full-time equivalent (FTE) staff for a productivity of 49 samples/FTE/day. In March 2021, after laboratory automation, the caseload went up to ~621 while the FTEs decreased to 8.5, accounting for productivity improvement to 73 samples/FTE/day. The hypothetical productivity went up to 110 samples/FTE/day following CIEs, meaning that the laboratory could at that point deal with a caseload increase to ~935 with unchanged FTEs. Laboratory conversion also led to an improvement in TATs for all sample types. For vaginal swabs and urine samples, median TATs decreased from 70.3 h [interquartile range (IQR): 63.5-93.1] and 73.7 h (IQR: 35.6-50.7) to 48.2 h (IQR: 44.8-67.7) and 40.0 h (IQR: 35.6-50.7), respectively. Automation alone was responsible for 37.2% and 75.8% of TAT reduction, respectively, while the remaining reduction of 62.8% and 24.2%, respectively, was achieved due to CIEs. The laboratory reached productivity and TAT goals predefined by the management after CIEs. In conclusion, automation substantially improved productivity and TATs, while the subsequent implementation of lean management further unlocked the potential of laboratory automation.IMPORTANCEIn this study, we combined total laboratory automation with lean management to show that appropriate laboratory work organization enhanced the benefit of the automation and substantially contributed to productivity improvements. Globally, the rapid availability of accurate results in the setting of a clinical microbiology laboratory is part of patient-centered approaches to treat infections and helps the implementation of antibiotic stewardship programs backed by the World Health Organization. Locally, from the point of view of laboratory management, it is important to find ways of maximizing the benefits of the use of technology, as total laboratory automation is an expensive investment.

Evaluation of PhenoMATRIX and PhenoMATRIX PLUS for the screening of MRSA from nasal and inguinal/perineal swabs using chromogenic media

The objective of this study was to assess the clinical performances of PhenoMATRIX and PhenoMATRIX PLUS for the screening of methicillin-resistant Staphylococcus aureus (MRSA) from nasal and inguinal/perineal ESwabs using chromogenic media. The automated performances were compared to the manual reading. Additionally, we evaluated PhenoMATRIX PLUS for the automatic release of the negative results to the Laboratory Information System (LIS) and the automatic discharge of the negative plates from the incubators. A total of 6,771 non-duplicate specimens were used by PhenoMATRIX as a machine learning model. The validation of these settings was performed on 17,223 non-duplicate specimens. The MRSA positivity rate was 5% (866/17,223). Validated settings were then used by PhenoMATRIX PLUS on another 1,409 non-duplicate specimens. The sensitivities of PhenoMATRIX and PhenoMATRIX PLUS were 99.8% [95% confidence interval (CI), 99.2%-99.9%] and 100% (95% CI, 92.1%-100%), respectively. The specificities of PhenoMATRIX and PhenoMATRIX PLUS were 99.1% (95% CI, 99.0%-99.2%) and 95.2% (95% CI, 93.8%-96.1%), respectively. All the 1,297 MRSA-negative specimens analyzed by PhenoMATRIX PLUS were automatically released and sent to the LIS immediately after availability of the culture image on the WASPLab (100% accuracy). All negative media plates were automatically discarded. PhenoMATRIX PLUS decreases the time spent by technologists on negative plates and ensures optimal usage of the incubators' capacity.

A prospective study evaluating the effect of a "Diagnostic Stewardship Care-Bundle" for automated blood culture diagnostics

OBJECTIVES

We prospectively implemented a diagnostic stewardship care-bundle checklist, 'Sepsis-48 DSB', with the aim of reducing intervening duration of key steps of automated blood culture diagnostics (aBCD).

METHODS

Sepsis-48 DSB was implemented for automated blood culture bottles (BCBs) received from adult intensive care units (AICUs) during the intervention period (P2; July 2020-June 2021) and intervening durations were compared with those during the retrospective, pre-intervention period (P1; March-June 2020). During both periods, provisional blood culture reports (pBCR) were issued wherein direct microbial identification (dID) was performed in BCBs with Gram-negatives by directly inoculating conventional biochemical tests and direct antimicrobial susceptibility testing (dAST) using EUCAST RAST method. The results were compared with the standard of care (SoC) method (i.e. full incubation followed by identification and AST by VITEKⓇ-2 Compact).

RESULTS

During P2, significant reductions in loading time (LT; median: 63.5 vs. 32 minutes, P < 0.001), time to dID+dAST performance (TTD; 186 vs. 115 minutes, P = 0.0018) and an increase in compliance to bundle targets (LT ≤45: 44% vs. 66%, P = 0.006 and TTD ≤120: 34% vs. 51.7%, P = 0.03) were observed. Using dID+dAST method, results were read 694 minutes earlier than SoC method. Of 176 pBCR, 165 (94%) were concordant with SoC in microbial identification of species. Categorical agreement for any drug-bug combination was 92.7% (1079/1164) and corresponding major, very major, and minor error rates were 8.8% (19/216), 4.9% (45/921), and 1.8% (21/1164), respectively.

CONCLUSION

The 'diagnostic stewardship care-bundle' strategy was successfully implemented with considerable diagnostic accuracy leading to significant reductions in duration of targeted steps of aBCD.

Evaluation of prolonged incubation time of 16-20 h with the EUCAST rapid antimicrobial susceptibility disc diffusion testing method

OBJECTIVES

Antimicrobial resistance rates are continuously increasing, driving the need for rapid antimicrobial susceptibility testing (RAST) results, especially in the treatment of bloodstream infections. The EUCAST RAST method performed directly from positive blood cultures with incubation times from 4 to 8 h was developed in 2018 and is now used in many laboratories. To increase the practicality of the method, an extended incubation time of 16 and 20 h was evaluated in this study.

METHOD

Blood culture bottles were spiked with clinical isolates (n = 325) of the seven most important sepsis pathogens. The EUCAST RAST method was performed, extending the incubation time to 16 and 20 h. Broth microdilution (BMD) was used as a reference, except for screening tests where standard disc diffusion or presence of resistance genes was used.

RESULTS

Inhibition zones were possible to read for all species-agent combinations. For 16 and 20 h, the MIC zone diameter correlations were sufficiently similar to allow establishment of common breakpoints for the time interval of 16-20 h. The proportion of isolates in the area of technical uncertainty was, on average, 6% for all species and the number of errors were low, with <1% false-resistant and <0.5% false-susceptible results.

CONCLUSIONS

This study shows that, for EUCAST RAST, prolonging the recommended incubation to 16-20 h is possible and can be used as a complement when the intended shorter incubation is not possible to achieve. The introduction of the prolonged incubation will increase the usefulness of the EUCAST RAST method in clinical laboratories with limited opening hours.

The Use of Machine Learning for Image Analysis Artificial Intelligence in Clinical Microbiology

The growing transition to digital microbiology in clinical laboratories creates the opportunity to interpret images using software. Software analysis tools can be designed to use human-curated knowledge and expert rules, but more novel artificial intelligence (AI) approaches such as machine learning (ML) are being integrated into clinical microbiology practice. These image analysis AI (IAAI) tools are beginning to penetrate routine clinical microbiology practice, and their scope and impact on routine clinical microbiology practice will continue to grow. This review separates the IAAI applications into 2 broad classification categories: (i) rare event detection/classification or (ii) score-based/categorical classification. Rare event detection can be used for screening purposes or for final identification of a microbe including microscopic detection of mycobacteria in a primary specimen, detection of bacterial colonies growing on nutrient agar, or detection of parasites in a stool preparation or blood smear. Score-based image analysis can be applied to a scoring system that classifies images in toto as its output interpretation and examples include application of the Nugent score for diagnosing bacterial vaginosis and interpretation of urine cultures. The benefits, challenges, development, and implementation strategies of IAAI tools are explored. In conclusion, IAAI is beginning to impact the routine practice of clinical microbiology, and its use can enhance the efficiency and quality of clinical microbiology practice. Although the future of IAAI is promising, currently IAAI only augments human effort and is not a replacement for human expertise.

A prospective study evaluating the effect of a 'Diagnostic Stewardship Care-Bundle' for automated blood culture diagnostics

OBJECTIVES

We prospectively implemented a diagnostic stewardship care-bundle checklist, 'Sepsis-48 DSB', with the aim of reducing intervening duration of key steps of automated blood culture diagnostics (aBCD).

METHODS

Sepsis-48 DSB was implemented for automated blood culture bottles (BCBs) received from adult intensive care units (AICUs) during the intervention period (P2; July 2020-June 2021) and intervening durations were compared with those during the retrospective, pre-intervention period (P1; March-June 2020). During both periods, provisional blood culture reports (pBCR) were issued wherein direct microbial identification (dID) was performed in BCBs with Gram-negatives by directly inoculating conventional biochemical tests and direct antimicrobial susceptibility testing (dAST) using EUCAST RAST method. The results were compared with the standard of care (SoC) method (i.e. full incubation followed by identification and AST by VITEKⓇ-2 Compact).

RESULTS

During P2, significant reductions in loading time (LT) [median: 63.5 vs. 32 minutes, P < 0.001], time to dID+dAST performance (TTD) [186 vs. 115 minutes, P = 0.0018] and an increase in compliance to bundle targets [LT ≤45: 44% vs. 66%, P = 0.006 and TTD ≤120: 34% vs. 51.7%, P = 0.03] were observed. Using dID+dAST method, results were read 694 minutes earlier than SoC method. Of 176 pBCR, 165 (94%) were concordant with SoC in microbial identification of species. Categorical agreement for any drug-bug combination was 92.7% (1079/1164) and corresponding major, very major, and minor error rates were 8.8% (19/216), 4.9% (45/921), and 1.8% (21/1164), respectively.

CONCLUSION

The 'diagnostic stewardship care-bundle' strategy was successfully implemented with considerable diagnostic accuracy leading to significant reductions in duration of targeted steps of aBCD.