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Cited by 163Sepsis Diagnosis and TreatmentAntibiotic Use and ResistanceBacterial Identification and Susceptibility Testing

Association Between Time to Appropriate Antimicrobial Treatment and 30-day Mortality in Patients With Bloodstream Infections: A Retrospective Cohort Study

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Van Heuverswyn, Jasper, Valik, John Karlsson, Desirée van der Werff, Suzanne, Hedberg, Pontus, Giske, Christian, Nauclér, Pontus·2023·Clinical Infectious Diseases
DOI 10.1093/cid/ciac727PMC PMC9907509
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Abstract

Background: Effective antimicrobial treatment is key for survival in bloodstream infection (BSI), but the impact of timing of treatment remains unclear. Our aim was to assess the association between time to appropriate antimicrobial treatment and 30-day mortality in BSI patients. Methods: This was a retrospective cohort study using electronic health record data from a large academic center in Sweden. Adult patients admitted between the years 2012 and 2019, with onset of BSI at the emergency department or general wards, were included. Pathogen-antimicrobial drug combinations were classified as appropriate or inappropriate based on reported in vitro susceptibilities. To avoid immortal time bias, the association between appropriate therapy and mortality was assessed with multivariable logistic regression analysis at pre-specified landmark times. Results: We included 10 628 BSI-episodes, occurring in 9192 unique patients. The overall 30-day mortality was 11.8%. No association in favor of a protective effect between appropriate therapy and mortality was found at the 1, 3 and 6 hours landmark after blood culture collection. At 12 hours, the risk of death increased with inappropriate treatment (adjusted odds ratio 1.17 [95% confidence interval {CI}, 1.01–1.37]) and continued to increase gradually at 24, 48, and 72 hours. Stratifying by high or low SOFA score generated similar odds ratios, with wider confidence intervals. Conclusions: Delays in appropriate antimicrobial treatment were associated with increased 30-day mortality after 12 hours from blood culture collection, but not at 1, 3, and 6 hours, in BSI. These results indicate a benchmark for providing rapid microbiological diagnostics of blood cultures.

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  • Delays in appropriate treatment were associated with increased 30-day mortality.

    “This is an important improvement, as delays were associated with increased 30-day mortality [11].”

    From Lab efficiency and improvements in the management of bloodstream infections: a before and after study (2025) · cites this paper as [11]

    The Conclusions report increased 30-day mortality with delayed appropriate antimicrobial treatment in patients with bloodstream infections, but only after 12 hours from blood culture collection—not at 1, 3, or 6 hours. The citing sentence omits that important timing qualification. (LLM, conf=0.88)

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  1. [1]Laupland KB, Lyytikäinen O, Søgaard M, et al The changing epidemiology of Staphylococcus aureus bloodstream infection: a multinational population-based surveillance study. Clin Microbiol Infect 2013; 19: 465– 71. 22616816
  2. [2]Evans L, Rhodes A, Alhazzani W, et al Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med 2021; 47: 1181– 247. 34599691 PMC8486643
  3. [3]Leibovici L, Paul M, Ezra O. Ethical dilemmas in antibiotic treatment. J Antimicrob Chemother 2012; 67: 12– 6. 21980065
  4. [4]Rhee C, Kadri SS, Dekker JP, et al Prevalence of antibiotic-resistant pathogens in culture-proven sepsis and outcomes associated with inadequate and broad-spectrum empiric antibiotic use. JAMA Netw open 2020; 3: e202899. 32297949 PMC7163409
  5. [5]Friedman ND, Temkin E, Carmeli Y. The negative impact of antibiotic resistance. Clin Microbiol Infect 2016; 22: 416– 22. 26706614
  6. [6]Kariv G, Paul M, Shani V, Muchtar E, Leibovici L. Benchmarking inappropriate empirical antibiotic treatment. Clin Microbiol Infect 2013; 19: 629– 33. 22805537
  7. [7]Kadri SS, Lai YL, Warner S, et al Inappropriate empirical antibiotic therapy for bloodstream infections based on discordant in-vitro susceptibilities: a retrospective cohort analysis of prevalence, predictors, and mortality risk in US hospitals. Lancet Infect Dis 2021; 21: 241– 51. 32916100 PMC7855478
  8. [8]Marquet K, Liesenborgs A, Bergs J, Vleugels A, Claes N. Incidence and outcome of inappropriate in-hospital empiric antibiotics for severe infection: a systematic review and meta-analysis. Crit Care 2015; 19: 63. 25888181 PMC4358713
  9. [10]Ferrer R, Martin-Loeches I, Phillips G, et al Empiric antibiotic treatment reduces mortality in severe sepsis and septic shock from the first hour. Crit Care Med 2014; 42: 1749– 55. 24717459
  10. [11]Nauclér P, Huttner A, van Werkhoven CH, et al Impact of time to antibiotic therapy on clinical outcome in patients with bacterial infections in the emergency department: implications for antimicrobial stewardship. Clin Microbiol Infect 2021; 27: 175– 81. 32120032
  11. [12]McGregor JC, Rich SE, Harris AD, et al A systematic review of the methods used to assess the association between appropriate antibiotic therapy and mortality in bacteremic patients. Clin Infect Dis 2007; 45: 329– 37. 17599310
  12. [13]Suissa S. Immortal time bias in pharmaco-epidemiology. Am J Epidemiol 2008; 167: 492– 9. 18056625
  13. [14]Valik JK, Ward L, Tanushi H, et al Validation of automated sepsis surveillance based on the sepsis-3 clinical criteria against physician record review in a general hospital population: observational study using electronic health records data. BMJ Qual Saf 2020; 29: 735– 45. PMC7467502 32029574
  14. [15]Quan H, Li B, Couris CM, et al Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol 2011; 173: 676– 82. 21330339
  15. [18]Fawcett N, Young B, Peto L, et al ‘Caveat emptor’: the cautionary tale of endocarditis and the potential pitfalls of clinical coding data-an electronic health records study. BMC Med 2019; 17: 169. 31481119 PMC6724235
  16. [20]Valik JK, Mellhammar L, Sundén-Cullberg J, et al Peripheral oxygen saturation facilitates assessment of respiratory dysfunction in the sequential organ failure assessment score with implications for the sepsis-3 criteria. Crit Care Med 2022; 50: e272– 83. 34406170
  17. [21]Rhee C, Chiotos K, Cosgrove SE, et al Infectious Diseases Society of America Position Paper: recommended revisions to the national severe sepsis and septic shock early management bundle (SEP-1) sepsis quality measure. Clin Infect Dis 2021; 72: 541– 52. 32374861 PMC8189682
  18. [22]Liu VX, Fielding-Singh V, Greene JD, et al The timing of early antibiotics and hospital mortality in sepsis. Am J Respir Crit Care Med 2017; 196: 856– 63. 28345952 PMC5649973
  19. [23]Singer M. Antibiotics for sepsis: does each hour really count, or is it incestuous amplification? Am J Respir Crit Care Med 2017; 196: 800– 2. 28504905
  20. [24]López-Cortés LE, Del Toro MD, Gálvez-Acebal J, et al Impact of an evidence-based bundle intervention in the quality-of-care management and outcome of Staphylococcus aureus bacteremia. Clin Infect Dis 2013; 57: 1225– 33. 23929889
  21. [25]Fitzpatrick JM, Biswas JS, Edgeworth JD, et al Gram-negative bacteraemia; a multi-centre prospective evaluation of empiric antibiotic therapy and outcome in English acute hospitals. Clin Microbiol Infect 2016; 22: 244– 51. 26577143
  22. [26]Puskarich MA, Trzeciak S, Shapiro NI, et al Association between timing of antibiotic administration and mortality from septic shock in patients treated with a quantitative resuscitation protocol. Crit Care Med 2011; 39: 2066– 71. 21572327 PMC3158284
  23. [27]de Groot B, Ansems A, Gerling DH, et al The association between time to antibiotics and relevant clinical outcomes in emergency department patients with various stages of sepsis: a prospective multi-center study. Crit Care 2015; 19: 194. 25925412 PMC4440486
  24. [29]Lambregts MMC, Wijnakker R, Bernards AT, Visser LG, Cessie SL, de Boer MGJ. Mortality after delay of adequate empiric antimicrobial treatment of bloodstream infection. J Clin Med 2020; 9: 1378. 32392843 PMC7290963
  25. [30]Yoon YK, Park DW, Sohn JW, et al Effects of inappropriate empirical antibiotic therapy on mortality in patients with healthcare-associated methicillin-resistant Staphylococcus aureus bacteremia: a propensity-matched analysis. BMC Infect Dis 2016; 16: 331. 27418274 PMC4946186
  26. [31]Seok H, Song J, Jeon JH, et al Timing of antibiotics in septic patients: a prospective cohort study. Clin Microbiol Infect 2020; 26: 1495– 500. 32062049
  27. [32]Babich T, Naucler P, Valik JK, et al Risk factors for mortality among patients with Pseudomonas aeruginosa bacteraemia: a retrospective multicentre study. Int J Antimicrob Agents 2020; 55: 105847. 31770625
  28. [33]Kaasch AJ, Rieg S, Kuetscher J, et al Delay in the administration of appropriate antimicrobial therapy in Staphylococcus aureus bloodstream infection: a prospective multicenter hospital-based cohort study. Infection 2013; 41: 979– 85. 23539143
  29. [34]Hranjec T, Rosenberger LH, Swenson B, et al Aggressive versus conservative initiation of antimicrobial treatment in critically ill surgical patients with suspected intensive-care-unit-acquired infection: a quasi-experimental, before and after observational cohort study. Lancet Infect Dis 2012; 12: 774– 80. 22951600 PMC3462590
  30. [35]Falcone M, Bassetti M, Tiseo G, et al Time to appropriate antibiotic therapy is a predictor of outcome in patients with bloodstream infection caused by KPC-producing Klebsiella pneumoniae. Crit Care 2020; 24: 29. 32000834 PMC6993311
  31. [36]Baltas I, Stockdale T, Tausan M, et al Impact of antibiotic timing on mortality from gram-negative bacteraemia in an English district general hospital: the importance of getting it right every time. J Antimicrob Chemother 2021; 76: 813– 9. 33219669
  32. [37]Corl KA, Zeba F, Caffrey AR, et al Delay in antibiotic administration is associated with mortality among septic shock patients with Staphylococcus aureus bacteremia. Crit Care Med 2020; 48: 525– 32. 32205599
  33. [38]Lee C-C, Lee C-H, Hong M-Y, Tang H-J, Ko W-C. Timing of appropriate empirical antimicrobial administration and outcome of adults with community-onset bacteremia. Crit Care 2017; 21: 119. 28545484 PMC5445436
  34. [39]Cain SE, Kohn J, Bookstaver PB, Albrecht H, Al-Has MN. Stratification of the impact of inappropriate empirical antimicrobial therapy for gram-negative bloodstream infections by predicted prognosis. Antimicrob Agents Chemother 2015; 59: 245– 50. 25348527 PMC4291357
  35. [40]Paul M, Shani V, Muchtar E, Kariv G, Robenshtok E, Leibovici L. Systematic review and meta-analysis of the efficacy of appropriate empiric antibiotic therapy for sepsis. Antimicrob Agents Chemother 2010; 54: 4851– 63. 20733044 PMC2976147
  36. [41]Schuttevaer R, Alsma J, Brink A, et al Appropriate empirical antibiotic therapy and mortality: conflicting data explained by residual confounding. PLoS One 2019; 14: e0225478. 31743361 PMC6863559
  37. [43]Morgan CJ. Landmark analysis: a primer. J Nucl Cardiol 2019; 26: 391– 3. 30719655

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Authors
Van Heuverswyn, J., Valik, J. K., Desirée van der Werff, S., Hedberg, P., Giske, C., & Nauclér, P.
Affiliations
  • Department of Medicine, Solna, Division of Infectious Diseases, Karolinska Institutet , Stockholm , Sweden
  • Karolinska University Hospital (SE)
Corresponding author
Valik, John Karlsson
ORCID
Venue
Clinical Infectious Diseases
Publisher
Oxford University Press (OUP)
Published
2022-09-06
Volume
76
Issue
3
Pages
469-478
ISSN
  • 1058-4838 (ISSN-L)
  • 1537-6591
DOI
10.1093/cid/ciac727
PMC
PMC9907509
OpenAlex
W4294723792
Cited by
163
References
4
Citations by year
2026: 47 · 2025: 49 · 2024: 48 · 2023: 15 · 2022: 3
FWCI
20.76
Type
journal article
Language
en
Open access
Licence
Locations
  • Clinical Infectious Diseases (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
  • Swedish Innovation Agency (2021-02699)
  • Region Stockholm ALF-agreement (FoUI-954788)
  • Region Stockholm Health Medicine Technology (FoUI-966658)
  • Swedish Research Council (2021-02271)
  • Karolinska Institutet and ESCMID Young Scientist
Topics
  • Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
  • Life Sciences › Immunology and Microbiology › Applied Microbiology and Biotechnology › Antibiotic Use and Resistance
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Bacterial Identification and Susceptibility Testing
Keywords
bloodstream infection, 30-day mortality, inappropriate antimicrobial therapy, antimicrobial susceptibility, blood culture, SOFA score, landmark analysis, treatment delay
MeSH terms
Adult, Anti-Infective Agents, Anti-Bacterial Agents, Humans, Retrospective Studies, Risk Factors, Bacteremia, Sepsis

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