Hostname: page-component-6bf8c574d5-r4mrb Total loading time: 0 Render date: 2025-03-03T22:58:04.364Z Has data issue: false hasContentIssue false
  • English
  • Français

Does PCR-based pathogen identification reduce mortality in bloodstream infections? Insights from a difference-in-difference analysis

Published online by Cambridge University Press:  14 February 2025

Juan Gago Open the ORCID record for Juan Gago [Opens in a new window] ,
Audrey Renson Open the ORCID record for Audrey Renson [Opens in a new window] ,
Courtney Takats Open the ORCID record for Courtney Takats [Opens in a new window] ,
Victor J. Torres ,
Bo Shopsin  and
Lorna E. Thorpe Open the ORCID record for Lorna E. Thorpe [Opens in a new window]
Juan Gago*
Affiliation:
Division of Epidemiology, Department of Population Health, New York University Grossman School of Medicine, New York, USA
Audrey Renson
Affiliation:
Division of Epidemiology, Department of Population Health, New York University Grossman School of Medicine, New York, USA
Courtney Takats
Affiliation:
Antimicrobial-Resistant Pathogens Program, New York University Grossman School of Medicine, New York 10016, NY, USA
Victor J. Torres
Affiliation:
Division of Infectious Diseases and Immunology, Department of Medicine, New York University Grossman School of Medicine, New York, USA Division of Biostatistics, Department of Population Health, New York University Grossman School of Medicine, New York, USA
Bo Shopsin
Affiliation:
Division of Infectious Diseases and Immunology, Department of Medicine, New York University Grossman School of Medicine, New York, USA Department of Microbiology, New York University Grossman School of Medicine, New York, USA Division of Biostatistics, Department of Population Health, New York University Grossman School of Medicine, New York, USA
Lorna E. Thorpe
Affiliation:
Division of Epidemiology, Department of Population Health, New York University Grossman School of Medicine, New York, USA
*
Corresponding author: Juan Gago; Email: juangago@hsph.harvard.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Background:

Bloodstream infections (BSI) are associated with high mortality rates, particularly when caused by resistant pathogens. Reducing the delay in diagnosis and initiation of appropriate treatment is crucial for improving clinical outcomes. The implementation of polymerase chain reaction (PCR) tests in the diagnostic process offers a promising approach to achieving quicker identification of pathogens, thereby potentially reducing mortality associated with BSI.

Methods:

A difference-in-differences analysis was performed within a New York City hospital system, comparing mortality risk between patients with enterococcal BSI before and after the adoption of BCID2 PCR testing, using as control those with methicillin-sensitive S. aureus BSI, for which diagnostic protocol has been unchanged.

Results:

The study included 548 inpatients; 164 diagnosed with vancomycin-resistant enterococci (VRE) BSI and 384 with MSSA BSI. The mean 30-day mortality risk difference in the period post-intervention estimated in our difference-in-differences model was -6.03 per 100 (95% CI: -10.35 to -1.7), with event study plots suggesting minimal deviation from parallel trends in the pre-treatment period.

Conclusions:

Findings suggest that introduction of BCID2 PCR testing for enterococcal bloodstream infections (BSI) may be associated with a reduction in mortality, however, interpretation of the effects must be approached with caution given the relative imprecision of estimates. Further research with larger samples is essential to establish a definitive conclusion on the impact of rapid PCR testing on mortality in BSI. This is an innovative approach using causal methods to evaluate interventions aimed at the improvement of infection control and antimicrobial treatment strategies.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , First View , pp. 1 - 7
Check for updates
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

Current address: Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, 02115 Boston, Massachusetts

#

Current address: Department of Host-Microbe Interactions, St. Jude Children’s Research Hospital, Memphis, TN 38105.

References

Coulter, S, Roberts, JA, Hajkowicz, K, Halton, K. The use of bloodstream infection mortality to measure the impact of antimicrobial stewardship interventions: assessing the evidence. Infect Dis Rep 2017;9:6849. doi: 10.4081/idr.2017.6849 CrossRefGoogle ScholarPubMed
Kontula, KSK, Skogberg, K, Ollgren, J, Järvinen, A, Lyytikäinen, O. Population-based study of bloodstream infection incidence and mortality rates, Finland, 2004–2018. Emerg Infect Dis 2021;27:2560–2569. doi: 10.3201/eid2710.204826 CrossRefGoogle ScholarPubMed
Zasowski, EJ, Bassetti, M, Blasi, F, et al. A systematic review of the effect of delayed appropriate antibiotic treatment on the outcomes of patients with severe bacterial infections. Chest 2020;158:929–938. doi: 10.1016/j.chest.2020.03.087 CrossRefGoogle ScholarPubMed
Bonine, N, Berger, A, Altincatal, A, et al. Impact of delayed appropriate antibiotic therapy on patient outcomes by antibiotic resistance status from serious gram-negative bacterial infections. Am J Med Sci 2019;357:103–110. doi: 10.1016/j.amjms.2018.11.009 CrossRefGoogle Scholar
Banerjee, R, Teng, CB, Cunningham, SA, et al. Randomized trial of rapid multiplex polymerase chain reaction-based blood culture identification and susceptibility testing. Clin Infect Dis 2015;61:1071–1080. doi: 10.1093/cid/civ447 CrossRefGoogle ScholarPubMed
Billington, EO, Phang, SH, Gregson, DB, et al. Incidence, risk factors, and outcomes for enterococcus spp. blood stream infections: a population-based study. Int J Infect Dis 2014;26:76–82. doi: 10.1016/j.ijid.2014.02.012 CrossRefGoogle ScholarPubMed
Cortazzo, V, D’Inzeo, T, Giordano, L, et al. Comparing BioFire FilmArray BCID2 and BCID panels for direct detection of bacterial pathogens and antimicrobial resistance genes from positive blood cultures. J Clin Microbiol 2021;59:e03163–20. doi: 10.1128/JCM.03163-20 CrossRefGoogle ScholarPubMed
Beuving, J, Wolffs, P, Hansen, W, et al. Impact of same-day antibiotic susceptibility testing on time to appropriate antibiotic treatment of patients with bacteraemia: a randomised controlled trial. Eur J Clin Microbiol Infect Dis 2015;34:831–838. doi: 10.1007/s10096-014-2299-0 CrossRefGoogle ScholarPubMed
Timbrook, T, Morton, J, McConeghy, K, Caffrey, A, Mylonakis, E, LaPlante, K. The effect of molecular rapid diagnostic testing on clinical outcomes in bloodstream infections: a systematic review and meta-analysis. Clin Infect Dis 2017;64:15–23. doi: 10.1093/cid/ciw649 CrossRefGoogle ScholarPubMed
Forrest, G, Roghmann, M, Toombs, L, et al. Peptide nucleic acid fluorescent in situ hybridization for hospital-acquired enterococcal bacteremia: delivering earlier effective antimicrobial therapy. Antimicrob Agents Chemother 2008;52:3558–3563. doi: 10.1128/AAC.00283-08 CrossRefGoogle ScholarPubMed
Roshdy, D, Tran, A, LeCroy, N, et al. Impact of a rapid microarray-based assay for identification of positive blood cultures for treatment optimization for patients with streptococcal and enterococcal bacteremia. J Clin Microbiol 2015;53:1411–1414. doi: 10.1128/JCM.00104-15 CrossRefGoogle ScholarPubMed
MacVane, SH, Hurst, J, Boger, M, Gnann, J. Impact of a rapid multiplex polymerase chain reaction blood culture identification technology on outcomes in patients with vancomycin-resistant Enterococcal bacteremia. Infect Dis 2016;48:732–737. doi: 10.1080/23744235.2016.1185533 CrossRefGoogle ScholarPubMed
Shadish, WR, Cook, TD, Campbell, DT. Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton: Mifflin and Company; 2002:xxi, 623.Google Scholar
Aguero-Rosenfeld, ME. NYU Langone Guideline for Blood Culture Identification 2 (BCID2) PCR. https://nyulangone-my.sharepoint.com/:b:/r/personal/michal_grudzinski_nyulangone_org/Documents/UnfortunateFolder/ellucid_data/documents/manuals%20(2)/AntimicrobialStewardshipProgram/DiagnosticStewardship/BCID2%20Summary.pdf.pdf?csf=1&web=1&e=KDZarF. Published April 5, 2022. Accessed Feb 6, 2025.Google Scholar
Abadie, A. Semiparametric difference-in-differences estimators. Rev Econ Stud 2005;72:1–19.CrossRefGoogle Scholar
Callaway, B, Sant’Anna, PHC. Difference-in-Differences with multiple time periods. J Econom 2021;225:200–230. doi: 10.1016/j.jeconom.2020.12.001 CrossRefGoogle Scholar
Cunningham, S. Causal Inference: The Mixtape. New Haven, CT: Yale University Press; 2021. doi: 10.2307/j.ctv1c29t27 Google Scholar
Prematunge, C, MacDougall, C, Johnstone, J, et al. VRE and VSE bacteremia outcomes in the era of effective VRE therapy: a systematic review and meta-analysis. Infect Control Hosp Epidemiol 2016;37:26–35. doi: 10.1017/ice.2015.228 CrossRefGoogle ScholarPubMed
Yadav, H, Shah, D, Sayed, S, Horton, S, Schroeder, LF. Availability of essential diagnostics in ten low-income and middle-income countries: results from national health facility surveys. Lancet Global Health 2021;9:e1553–e1560. doi: 10.1016/S2214-109X(21)00442-3 CrossRefGoogle ScholarPubMed
Barlam, T, Cosgrove, S, Abbo, L, et al. Implementing an antibiotic stewardship program: guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. Clin Infect Dis 2016;62:E51–E77. doi: 10.1093/cid/ciw118 CrossRefGoogle Scholar
Supplementary material: File

Gago et al. supplementary material

Gago et al. supplementary material
Download Gago et al. supplementary material(File)
File 288 KB