Rapid phenotypic methods to improve the diagnosis of bacterial bloodstream infections: meeting the challenge to reduce the time to result

Dubourg, G; Lamy, Brigitte; Ruimy, Raymond

doi:10.1016/j.cmi.2018.03.031

Cited by 74 publications

(69 citation statements)

References 90 publications

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“…The first, identification after short-term incubation on an agar plate, has yielded good results but still requires 4 to 8 h to identify 80% of bacteria at the species level (7-9), resulting in evident workflow issues. The other approach is to identify bacteria directly from blood culture bottles (BCBs) (10-13), which we adopted in our study because of its potential to significantly speed up bacterial identification (14). However, the protocols described so far, such as the manufacturer's instructions for the Sepsityper kit (Bruker) (15), are still relatively time-consuming and arduous for routine use (12,(16)(17)(18)(19), so there is still need for a quick, simple, reliable method of direct bacterial identification that would benefit patients.…”

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confidence: 99%

Direct Identification of 80 Percent of Bacteria from Blood Culture Bottles by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry Using a 10-Minute Extraction Protocol

et al. 2019

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Matrix-assisted laser desorption ionization–time of flight mass spectrometry is not widely used to identify bacteria directly from positive blood culture bottles (BCBs) because of overlong protocols. The objective of this work was to develop and evaluate a simple extraction protocol for reliable identification from BCBs. The 10-min protocol was applied over a 5-month period. Direct identifications on day 0 were compared with those obtained from colonies on day 1 [log(score) of ≥2]. We evaluated a range of seven log(score) thresholds on day 0 from 1.4 to 2.0 to find the lower confidence score that provides the higher percentage of direct identifications without loss of accuracy. With a log(score) threshold of ≥1.5 at day 0, our protocol allowed us to identify 80% of bacteria in 632 BCBs (96% of Enterobacteriaceae, 95% of Staphylococcus aureus, 92% of enterococci, and 62% of streptococci). At least one bacterial species of the mixture was identified in 77% of the polymicrobial samples. The rapidity and reliability of the protocol were factors in its adoption for routine use, allowing us to save up to 24 h in identifying 80% of the bacteria in the BCBs and, thus, to supply useful information to adapt antibiotic therapy when necessary. We currently provide reliable daily direct identifications of staphylococci, enterococci, Enterobacteriaceae, Pseudomonas aeruginosa, and beta-hemolytic streptococci.

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confidence: 99%

Direct Identification of 80 Percent of Bacteria from Blood Culture Bottles by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry Using a 10-Minute Extraction Protocol

et al. 2019

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“…All rapid phenotypic AST methods will face the above discussed biological challenges to some extent, and whether a specific method will turn out to be viable will hinge on if the benefit of the rapid read-outs for a subgroup of patient isolates outweigh the increase in false or unclear readouts as well as the increased cost (9). Thus, rapid phenotypic AST methods will likely never completely replace traditional AST testing, but instead serve as an important addition to be used for example for critically ill patients (12).…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The traditional methods for AST currently used in most clinical microbiology laboratories are reliable and inexpensive but comparatively slow with turnaround times (TATs) commonly of 2-3 days (12). Progress has recently been made to decrease TATs, in part through automation of existing methods but also as a result of the implementation of new technologies (12). For example, recent developments of the rapid disc diffusion test with new breakpoints (4, 6 and 8 hour readouts) developed by EUCAST allow for TATs of around 24 hours, although not for all samples (13).…”

Section: Introductionmentioning

confidence: 99%

“…Many new rapid AST methods under development are phenotypic tests, as genotypic tests for selected resistance markers currently cannot reliably predict antibiotic susceptibility due to the complexity of the bacterial resistome (14)(9) (12). The latest developments in resistance screening methods include mass spectrometry to identify resistance-associated proteins and degradation products of antibiotics, PCR-based techniques to detect resistance markers, RNA microarrays, and whole genome sequencing together with AI-based deep learning tools (14) (15).…”

Section: Introductionmentioning

confidence: 99%

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A high-throughput fluidic chip for rapid phenotypic antibiotic susceptibility testing

Wistrand-Yuen

Malmberg

Fatsis-Kavalopoulos

et al. 2019

Preprint

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Many patients with severe infections receive inappropriate empirical treatment and rapid detection of bacterial antibiotic susceptibility can in this context improve clinical outcome and reduce mortality. We have to this end developed a high-throughput fluidic chip for rapid phenotypic antibiotic susceptibility testing of bacteria. A total of 21 clinical isolates of Escherichia coli, Klebsiella pneumoniae and Staphylococcus aureus were acquired from the EUCAST Development Laboratory and tested against amikacin, ceftazidime and meropenem (Gramnegative bacteria) or gentamicin, ofloxacin and tetracycline (Gram-positive bacteria). The bacterial samples were mixed with agarose and loaded in 8 separate growth chambers in the fluidic chip. The chip was thereafter connected to a reservoir lid containing different antibiotics and a pump used to draw growth media with or without antibiotics into the chip for generation of diffusion-limited antibiotic gradients in the growth chambers. Bacterial microcolony growth was monitored using darkfield time-lapse microscopy and quantified using a cluster image analysis algorithm. Minimum inhibitory concentration (MIC) values were automatically obtained by tracking the growth rates of individual microcolonies in different regions of antibiotic gradients. Stable MIC values were obtained within 2-4 hours and the results showed categorical agreement to reference MIC values as determined with broth microdilution in 86% of the cases. ImportancePrompt and effective antimicrobial therapy is crucial for the management of patients with severe bacterial infections but is becoming increasingly difficult to provide due to emerging antibiotic resistance. The traditional methods for antibiotic susceptibility testing (AST) used in most clinical laboratories are reliable but slow with turnaround times of 2-3 days, which necessitates the use of empirical therapy with broad-spectrum antibiotics. There is a great need for fast and reliable AST methods that enable start of targeted treatment within a few hours to improve patient outcome and reduce overuse of broad-spectrum antibiotics. The high-throughput fluidic chip for phenotypic AST described in the present study enables data on antimicrobial resistance within 2-4 hours allowing for an early initiation of appropriate antibiotic therapy.

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Breakthrough Solution for Antimicrobial Resistance Detection: Surface‐Enhanced Raman Spectroscopy‐based on Artificial Intelligence

Al‐Shaebi,

Akdeniz,

Ahmed

et al. 2023

Adv Materials Inter

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Antimicrobial resistance (AMR) is a global crisis, responsible for ≈700 000 annual deaths, as reported by the World Health Organization. To counteract this growing threat to public health, innovative solutions for early detection and characterization of drug‐resistant bacterial strains are imperative. Surface‐enhanced Raman spectroscopy (SERS) combined with artificial intelligence (AI) technology presents a promising avenue to address this challenge. This review provides a concise overview of the latest advancements in SERS and AI, showcasing their transformative potential in the context of AMR. It explores the diverse methodologies proposed, highlighting their advantages and limitations. Additionally, the review underscores the significance of SERS in tandem use with machine learning (ML) and deep learning (DL) in combating AMR and emphasizes the importance of ongoing research and development efforts in this critical field. Future developments for this technology could transform the way antimicrobial resistance (AMR) is addressed and pave the way for novel approaches to the protection of public health worldwide.

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Rapid phenotypic methods to improve the diagnosis of bacterial bloodstream infections: meeting the challenge to reduce the time to result

Cited by 74 publications

References 90 publications

Direct Identification of 80 Percent of Bacteria from Blood Culture Bottles by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry Using a 10-Minute Extraction Protocol

Direct Identification of 80 Percent of Bacteria from Blood Culture Bottles by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry Using a 10-Minute Extraction Protocol

A high-throughput fluidic chip for rapid phenotypic antibiotic susceptibility testing

Breakthrough Solution for Antimicrobial Resistance Detection: Surface‐Enhanced Raman Spectroscopy‐based on Artificial Intelligence

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