A novel microbead-based microfluidic device for rapid bacterial identification and antibiotic susceptibility testing

2014 ◽  
Vol 33 (12) ◽  
pp. 2223-2230 ◽  
Author(s):  
J. He ◽  
X. Mu ◽  
Z. Guo ◽  
H. Hao ◽  
C. Zhang ◽  
...  
2017 ◽  
Vol 22 (6) ◽  
pp. 585-608 ◽  
Author(s):  
Yiyan Li ◽  
Xing Yang ◽  
Weian Zhao

Rapid bacterial identification (ID) and antibiotic susceptibility testing (AST) are in great demand due to the rise of drug-resistant bacteria. Conventional culture-based AST methods suffer from a long turnaround time. By necessity, physicians often have to treat patients empirically with antibiotics, which has led to an inappropriate use of antibiotics, an elevated mortality rate and healthcare costs, and antibiotic resistance. Recent advances in miniaturization and automation provide promising solutions for rapid bacterial ID/AST profiling, which will potentially make a significant impact in the clinical management of infectious diseases and antibiotic stewardship in the coming years. In this review, we summarize and analyze representative emerging micro- and nanotechnologies, as well as automated systems for bacterial ID/AST, including both phenotypic (e.g., microfluidic-based bacterial culture, and digital imaging of single cells) and molecular (e.g., multiplex PCR, hybridization probes, nanoparticles, synthetic biology tools, mass spectrometry, and sequencing technologies) methods. We also discuss representative point-of-care (POC) systems that integrate sample processing, fluid handling, and detection for rapid bacterial ID/AST. Finally, we highlight major remaining challenges and discuss potential future endeavors toward improving clinical outcomes with rapid bacterial ID/AST technologies.


2013 ◽  
Vol 62 (5) ◽  
pp. 773-777 ◽  
Author(s):  
Guy Prod’hom ◽  
Christian Durussel ◽  
Gilbert Greub

An ammonium chloride procedure was used to prepare a bacterial pellet from positive blood cultures, which was used for direct inoculation of VITEK 2 cards. Correct identification reached 99 % for Enterobacteriaceae and 74 % for staphylococci. For antibiotic susceptibility testing, very major and major errors were 0.1 and 0.3 % for Enterobacteriaceae, and 0.7 and 0.1 % for staphylococci, respectively. Thus, bacterial pellets prepared with ammonium chloride allow direct inoculation of VITEK cards with excellent accuracy for Enterobacteriaceae and a lower accuracy for staphylococci.


2020 ◽  
Vol 41 (S1) ◽  
pp. s520-s521
Author(s):  
Taissa Zappernick ◽  
Robbie Christian ◽  
Sharanie Sims ◽  
Brigid Wilson ◽  
Federico Perez ◽  
...  

Background: The survival of patients with hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) is largely determined by the timely administration of effective antibiotic therapy. Guidelines for the treatment HAP and VAP recommend empiric treatment with broad-spectrum antibiotics and tailoring of antibiotic therapy once results of microbiological testing are available. Objective: We examined the influence of bacterial identification and antibiotic susceptibility testing on antibiotic therapy for patients with HAP or VAP. Methods: We used the US Veterans’ Health Administration (VHA) database to identify a retrospective cohort of patients diagnosed with HAP or VAP between fiscal year 2015 and 2018. We further analyzed patients who were started on empiric antibiotic therapy, for whom microbiological test results from a respiratory sample were available within 7 days and who were alive within 48 hours of sample collection. We used the antibiotic spectrum index (ASI) to compare antibiotics prescribed the day before and the day after availability of bacterial identification and antibiotic susceptibility testing results. Results: We identified 4,669 cases of HAP and VAP in 4,555 VHA patients. The median time from respiratory sample receipt in the laboratory to final result of bacterial identification and antibiotic susceptibility testing was 2.22 days (IQR, 1.31–3.38 days). The most common pathogen was Staphylococcus aureus (n = 994), with methicillin resistance in 58% of those isolates tested. The next most common pathogen was Pseudomonas spp (n = 946 isolates). The susceptibility of antipseudomonal antibiotics, when tested, was as follows: 64% to carbapenems, 74% to cephalosporins, 75% to β-lactam/β-lactamase inhibitors, 69% to fluoroquinolones, and 95% to amikacin. Lactose-fermenting gram-negative bacteria (296 Escherichia coli and 360 Klebsiella pneumoniae) were also common. Among the 3,094 cases who received empiric antibiotic therapy, 607 (20%) had antibiotics stopped the day after antibiotic susceptibility results became available, 920 (30%) had a decrease in ASI, 1,075 (35%) had no change in ASI, and 492 (16%) had an increase in ASI (Fig. 1). Among the 1,098 patients who were not started on empiric antibiotic therapy, only 154 (14%) were started on antibiotic therapy the day after antibiotic susceptibility results became available. Conclusions: Changes in antibiotic therapy occurred in at least two-thirds of cases the day after bacterial identification and antibiotic susceptibility results became available. These results highlight how respiratory cultures can inform the treatment and improve antibiotic stewardship for patients with HAP/VAP.Funding: This study was supported by Accelerate Diagnostics.Disclosures: None


ACS Omega ◽  
2021 ◽  
Author(s):  
Armelle Novelli Rousseau ◽  
Nicolas Faure ◽  
Fabian Rol ◽  
Zohreh Sedaghat ◽  
Joël Le Galudec ◽  
...  

2020 ◽  
Vol 41 (S1) ◽  
pp. s42-s43
Author(s):  
Kimberley Sukhum ◽  
Candice Cass ◽  
Meghan Wallace ◽  
Caitlin Johnson ◽  
Steven Sax ◽  
...  

Background: Healthcare-associated infections caused by antibiotic-resistant organisms (AROs) are a major cause of significant morbidity and mortality. To create and optimize infection prevention strategies, it is crucial to delineate the role of the environment and clinical infections. Methods: Over a 14-month period, we collected environmental samples, patient feces, and patient bloodstream infection (BSI) isolates in a newly built bone marrow transplant (BMT) intensive care unit (ICU). Samples were collected from 13 high-touch areas in the patient room and 4 communal areas. Samples were collected from the old BMT ICU, in the new BMT ICU before patients moved in, and for 1 year after patients moved in. Selective microbiologic culture was used to isolate AROs, and whole-genome sequencing (WGS) was used to determine clonality. Antibiotic susceptibility testing was performed using Kirby-Bauer disk diffusion assays. Using linear mixed modeling, we compared ARO recovery across time and sample area. Results: AROs were collected and cultured from environmental samples, patient feces, and BSI isolates (Fig. 1a). AROs were found both before and after a patient entered the ICU (Fig. 1b). Sink drains had significantly more AROs recovered per sample than any other surface area (P < .001) (Fig. 1c). The most common ARO isolates were Pseudomonas aeruginosa and Stenotrophomonas maltophila (Fig. 1d). The new BMT ICU had fewer AROs recovered per sample than the old BMT ICU (P < .001) and no increase in AROs recovered over the first year of opening (P > .05). Furthermore, there was no difference before versus after patients moved into the hospital (P > .05). Antibiotic susceptibility testing reveal that P. aeruginosa isolates recovered from the old ICU were resistant to more antibiotics than isolates recovered from the new ICU (Fig. 2a). ANI and clonal analyses of P. aeruginosa revealed a large cluster of clonal isolates (34 of 76) (Fig. 2b). This clonal group included isolates found before patients moved into the BMT ICU and patient blood isolates. Furthermore, this clonal group was initially found in only 1 room in the BMT ICU, and over 26 weeks, it was found in sink drains in all 6 rooms sampled (Fig. 2b). Conclusions: AROs are present before patients move into a new BMT ICU, and sink drains act as a reservoir for AROs over time. Furthermore, sink-drain P. aeruginosa isolates are clonally related to isolates found in patient BSIs. Overall, these results provide insight into ARO transmission dynamics in the hospital environment.Funding: Research reported in this publication was supported by the Washington University Institute of Clinical and Translational Sciences grant UL1TR002345 from the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH). The content is solely the responsibility of the authors and does not necessarily represent the official view of the NIH.Disclosures: None


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