Cited by 6Bacterial Identification and Susceptibility TestingAntibiotic Use and ResistanceNeutropenia and Cancer Infections

Real Life Clinical Impact of Antimicrobial Stewardship Actions on the Blood Culture Workflow from a Microbiology Laboratory

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López-Pintor, Jose Maria, Sánchez-López, Javier, Navarro-San Francisco, Carolina, Sánchez-Díaz, Ana Maria, Loza, Elena, Cantón, Rafael·2021·Antibiotics

Abstract

Background: Accelerating the diagnosis of bacteremia is one of the biggest challenges in clinical microbiology departments. The fast establishment of a correct treatment is determinant on bacteremic patients’ outcomes. Our objective was to evaluate the impact of antimicrobial therapy and clinical outcomes of a rapid blood culture workflow protocol in positive blood cultures with Gram-negative bacilli (GNB). Methods: A quasi-experimental before–after study was performed with two groups: (i) control group (conventional work-protocol) and (ii) intervention group (rapid workflow-protocol: rapid identification by Matrix-Assisted Laser Desorption/Ionization-Time-Of-Flight (MALDI-TOF) and antimicrobial susceptibility testing (AST) from bacterial pellet without overnight incubation). Patients were divided into different categories according to the type of intervention over treatment. Outcomes were compared between both groups. Results: A total of 313 patients with GNB-bacteremia were included: 125 patients in the control group and 188 in the intervention. The time from positive blood culture to intervention on antibiotic treatment decreased from 2.0 days in the control group to 1.0 in the intervention group (p < 0.001). On the maintenance of correct empirical treatment, the control group reported 2.0 median days until the clinical decision, while in the intervention group was 1.0 (p < 0.001). In the case of treatment de-escalation, a significant difference between both groups (4.0 vs. 2.0, p < 0.001) was found. A decreasing trend on the change from inappropriate treatments to appropriate ones was observed: 3.5 vs. 1.5; p = 0.12. No significant differences were found between both groups on 7-days mortality or on readmissions in the first 30-days. Conclusions: Routine implementation of a rapid workflow protocol anticipates the report of antimicrobial susceptibility testing results in patients with GNB-bacteremia, decreasing the time to effective and optimal antibiotic therapy.

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  1. [1]Goff D.A. Jankowski C. Tenover F.C. Using rapid diagnostic tests to optimize antimicrobial selection in antimicrobial stewardship programs Pharmacotherapy 2012 32 677 687 10.1002/j.1875-9114.2012.01137.x 23307517 · DOI
  2. [2]Cantón R. de la Pedrosa E.G.G. Economic impact of rapid diagnostic methods in Clinical Microbiology: Price of the test or overall clinical impact Enferm. Infecc. Microbiol. Clin. 2017 35 659 666 10.1016/j.eimc.2017.09.005 29033026 · DOI
  3. [3]Chandrasekaran S. Abbott A. Campeau S. Zimmer B.L. Weinstein M. Thrupp L. Hejna J. Walker L. Ammann T. Kirn T. Direct-from-blood-culture disk diffusion to determine antimicrobial susceptibility of gram-negative bacteria: Preliminary report from the clinical and Laboratory Standards Institute Methods Development and Standardization Working Group J. Clin. Microbiol. 2018 56 1 10 10.1128/JCM.01678-17 29305540 PMC5824059 · DOI
  4. [4]Åkerlund A. Jonasson E. Matuschek E. Serrander L. Sundqvist M. Kahlmeter G. Dzajic E. Hansen D.S. Agergaard C.N. Pätäri-Sampo A. EUCAST rapid antimicrobial susceptibility testing (RAST) in blood cultures: Validation in 55 european laboratories J. Antimicrob. Chemother. 2020 75 3230 3238 10.1093/jac/dkaa333 32789506 PMC7566356 · DOI
  5. [5]Descours G. Desmurs L. Hoang T.L.T. Ibranosyan M. Baume M. Ranc A.G. Fuhrmann C. Dauwalder O. Salka W. Vandenesch F. Evaluation of the Accelerate PhenoTM system for rapid identification and antimicrobial susceptibility testing of Gram-negative bacteria in bloodstream infections Eur. J. Clin. Microbiol. Infect. Dis. 2018 37 1573 1583 10.1007/s10096-018-3287-6 29808350 · DOI
  6. [6]Kim J.H. Kim T.S. Jung H.G. Kang C.K. Jun K.I. Han S. Kim D.Y. Kwon S. Song K.H. Choe P.G. Prospective evaluation of a rapid antimicrobial susceptibility test (QMAC-dRAST) for selecting optimal targeted antibiotics in positive blood culture J. Antimicrob. Chemother. 2019 74 2255 2260 10.1093/jac/dkz168 31038158 · DOI
  7. [7]Korber F. Zeller I. Grünstäudl M. Willinger B. Apfalter P. Hirschl A.M. Makristathis A. SeptiFast versus blood culture in clinical routine—A report on 3 years experience Wien. Klin. Wochenschr. 2017 129 427 434 10.1007/s00508-017-1181-3 28243751 PMC5486735 · DOI
  8. [8]Costa-de-Oliveira S. Teixeira-Santos R. Silva A.P. Pinho E. Mergulhão P. Silva-Dias A. Marques N. Martins-Oliveira I. Rodrigues A.G. Paiva J.A. Potential impact of flow cytometry antimicrobial susceptibility testing on the clinical management of gram-negative bacteremia using the FASTinov® kit Front. Microbiol. 2017 8 2445 10.3389/fmicb.2017.02455 29312169 PMC5733032 · DOI
  9. [9]Huang T.H. Tzeng Y.L. Dickson R.M. FAST: Rapid determinations of antibiotic susceptibility phenotypes using label-free cytometry Cytom. Part A 2018 93 639 648 10.1002/cyto.a.23370 29733508 PMC6056315 · DOI
  10. [10]Silva-Dias A. Pérez-Viso B. Martins-Oliveira I. Gomes R. Rodrigues A.G. Cantón R. Pina-Vaz C. Evaluation of FASTinov Ultrarapid Flow Cytometry Antimicrobial Susceptibility Testing Directly from Positive Blood Cultures J. Clin. Microbiol. 2021 59 e0054421 10.1128/JCM.00544-21 34346718 PMC8451411 · DOI
  11. [11]Novais Â. Freitas A.R. Rodrigues C. Peixe L. Fourier transform infrared spectroscopy: Unlocking fundamentals and prospects for bacterial strain typing Eur. J. Clin. Microbiol. Infect. Dis. 2019 38 427 448 10.1007/s10096-018-3431-3 30483997 · DOI
  12. [12]Kragh K.N. Gijón D. Maruri A. Antonelli A. Coppi M. Kolpen M. Crone S. Tellapragada C. Hasan B. Radmer S. Effective antimicrobial combination in vivo treatment predicted with microcalorimetry screening J. Antimicrob. Chemother. 2021 76 1001 1009 10.1093/jac/dkaa543 33442721 PMC7953322 · DOI
  13. [13]Lu H. Caen O. Vrignon J. Zonta E. El Harrak Z. Nizard P. Baret J.C. Taly V. High throughput single cell counting in droplet-based microfluidics Sci. Rep. 2017 7 1366 10.1038/s41598-017-01454-4 28465615 PMC5431057 · DOI
  14. [14]Ibrahim E.H. Sherman G. Ward S. Fraser V.J. Kollef M.H. The influence of inadequate antimicrobial treatment of bloodstream infections on patient outcomes in the ICU setting Chest 2000 118 146 155 10.1378/chest.118.1.146 10893372 · DOI · Paper page
  15. [15]Kerremans J.J. Verboom P. Stijnen T. Hakkaart-van Roijen L. Goessens W. Verbrugh H.A. Vos M.C. Rapid identification and antimicrobial susceptibility testing reduce antibiotic use and accelerate pathogen-directed antibiotic use J. Antimicrob. Chemother. 2008 61 428 435 10.1093/jac/dkm497 18156278 · DOI
  16. [17]López-Pintor J.M. Francisco C.N.-S. Sánchez-López J. García-Caballero A. de Bobadilla E.L.F. Morosini M.I. Cantón R. Direct antimicrobial susceptibility testing from the blood culture pellet obtained for MALDI-TOF identification of Enterobacterales and Pseudomonas aeruginosa Eur. J. Clin. Microbiol. Infect. Dis. 2019 38 1095 1104 10.1007/s10096-019-03498-y 30712228 · DOI
  17. [18]Seddon M.M. Bookstaver P.B. Justo J.A. Kohn J. Rac H. Haggard E. Mediwala K.N. Dash S. Al-Hasan M.N. Role of Early De-escalation of Antimicrobial Therapy on Risk of Clostridioides difficile Infection following Enterobacteriaceae Bloodstream Infections Clin. Infect. Dis. 2018 69 414 420 10.1093/cid/ciy863 30312362 · DOI
  18. [19]Owens R.C. Ambrose P.G. Antimicrobial stewardship and the role of pharmacokinetics–pharmacodynamics in the modern antibiotic era Diagn. Microbiol. Infect. Dis. 2007 57 S77 S83 10.1016/j.diagmicrobio.2006.12.012 17292579 · DOI
  19. [20]Retamar P. Portillo M.M. López-Prieto M.D. Rodríguez-López F. De Cueto M. García M.V. Gómez M.J. Del Arco A. Muñoz A. Sánchez-Porto A. Impact of inadequate empirical therapy on the mortality of patients with bloodstream infections: A propensity score-based analysis Antimicrob. Agents Chemother. 2012 56 472 478 10.1128/AAC.00462-11 22005999 PMC3256027 · DOI
  20. [21]Pouwels K.B. Van Kleef E. Vansteelandt S. Batra R. Edgeworth J.D. Smieszek T. Robotham J.V. Does appropriate empiric antibiotic therapy modify intensive care unit-acquired Enterobacteriaceae bacteraemia mortality and discharge? J. Hosp. Infect. 2017 96 23 28 10.1016/j.jhin.2017.03.016 28434629 · DOI
  21. [22]Battle S.E. Brandon Bookstaver P. Justo J.A. Kohn J. Albrecht H. Al-Hasan M.N. Association between inappropriate empirical antimicrobial therapy and hospital length of stay in Gram-negative bloodstream infections: Stratification by prognosis J. Antimicrob. Chemother. 2017 72 299 304 10.1093/jac/dkw402 27986899 · DOI
  22. [23]Garnacho-Montero J. Gutiérrez-Pizarraya A. Escoresca-Ortega A. Corcia-Palomo Y. Fernández-Delgado E. Herrera-Melero I. Ortiz-Leyba C. Márquez-Vácaro J.A. De-Escalation of empirical therapy is associated with lower mortality in patients with severe sepsis and septic shock Intensiv. Care Med. 2014 40 32 40 10.1007/s00134-013-3077-7 24026297 · DOI
  23. [24]Ramasco F. Figuerola A. Mendez R. Rodríguez Serrano D. von Wernitz A. Hernández-Aceituno A. Sáez C. Cardeñoso L. Martin E. García-Vázquez N. Initial clinical outcomes and prognostic variables in the implementation of a Code Sepsis in a high complexity University Hospital Rev. Esp. Quimioter. 2019 32 238 245 30968675 PMC6609936
  24. [26]Wang H. Wang H. Yu X. Zhou H. Li B. Chen G. Ye Z. Wang Y. Cui X. Zheng Y. Impact of antimicrobial stewardship managed by clinical pharmacists on antibiotic use and drug resistance in a Chinese hospital, 2010–2016: A retrospective observational study BMJ Open 2019 9 e026072 10.1136/bmjopen-2018-026072 PMC6687004 31377693 · DOI

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Authors
López-Pintor, J. M., Sánchez-López, J., Navarro-San Francisco, C., Sánchez-Díaz, A. M., Loza, E., & Cantón, R.
Affiliations
  • Servicio de Microbiología, Hospital Universitario Ramón y Cajal and Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), 28034 Madrid, Spain
  • Instituto de Salud Carlos III (ES)
Venue
Antibiotics
Publisher
MDPI AG
Published
2021-12-09
Volume
10
Issue
12
Pages
1511
ISSN
2079-6382 (ISSN-L)
OpenAlex
W4200611071
Cited by
6
References
0
Citations by year
2025: 2 · 2024: 3 · 2022: 1
FWCI
0.70
Type
journal article
Language
en
Open access
Locations
  • Antibiotics (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Bacterial Identification and Susceptibility Testing
  • Life Sciences › Immunology and Microbiology › Applied Microbiology and Biotechnology › Antibiotic Use and Resistance
  • Health Sciences › Medicine › Oncology › Neutropenia and Cancer Infections
Keywords
antimicrobial stewardship, antimicrobial susceptibility testing, empirical antibiotic therapy, treatment de-escalation, 7-day mortality, hospital readmission

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