#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Appropriate empirical antibiotic therapy and mortality: Conflicting data explained by residual confounding


Autoři: Romy Schuttevaer aff001;  Jelmer Alsma aff001;  Anniek Brink aff001;  Willian van Dijk aff001;  Jurriaan E. M. de Steenwinkel aff002;  Hester F. Lingsma aff003;  Damian C. Melles aff002;  Stephanie C. E. Schuit aff001
Působiště autorů: Department of Internal Medicine, Section Acute Medicine, Erasmus MC, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands aff001;  Department of Medical Microbiology and Infectious Diseases, Erasmus MC, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands aff002;  Department of Public Health, Erasmus MC, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands aff003;  Department of Medical Microbiology and Immunology, Meander MC, Amersfoort, The Netherlands aff004
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0225478

Souhrn

Objective

Clinical practice universally assumes that appropriate empirical antibiotic therapy improves survival in patients with bloodstream infection. However, this is not generally supported by previous studies. We examined the association between appropriate therapy and 30-day mortality, while minimizing bias due to confounding by indication.

Methods

We conducted a retrospective cohort study between 2012 and 2017 at a tertiary university hospital in the Netherlands. Adult patients with bloodstream infection attending the emergency department were included. Based on in vitro susceptibility, antibiotic therapy was scored as appropriate or inappropriate. Primary outcome was 30-day mortality. To control for confounding, we performed conventional multivariable logistic regression and propensity score methods. Additionally, we performed an analysis in a more homogeneous subgroup (i.e. antibiotic monotherapy).

Results

We included 1.039 patients, 729 (70.2%) received appropriate therapy. Overall 30-day mortality was 10.4%. Appropriately treated patients had more unfavorable characteristics, indicating more severe illness. Despite adjustments, we found no association between appropriate therapy and mortality. For the antibiotic monotherapy subgroup (n = 449), patient characteristics were more homogeneous. Within this subgroup, appropriate therapy was associated with lower mortality (Odds Ratios [95% Confidence Intervals] ranging from: 0.31 [0.14; 0.67] to 0.40 [0.19; 0.85]).

Conclusions

Comparing heterogeneous treatment groups distorts associations despite use of common methods to prevent bias. Consequently, conclusions of such observational studies should be interpreted with care. If possible, future investigators should use our method of attempting to identify and analyze the most homogeneous treatment groups nested within their study objective, because this minimizes residual confounding.

Klíčová slova:

Antibiotics – Blood – Body temperature – Critical care and emergency medicine – Intensive care units – Oxygen – Respiratory infections


Zdroje

1. Goto M, Al-Hasan MN. Overall burden of bloodstream infection and nosocomial bloodstream infection in North America and Europe. Clin Microbiol Infect. 2013;19(6):501–9. Epub 2013/03/12. doi: 10.1111/1469-0691.12195 [pii]. 23473333.

2. Cross A, Levine MM. Patterns of bacteraemia aetiology. Lancet Infect Dis. 2017;17(10):1005–6. Epub 2017/08/19. S1473-3099(17)30491-7 [pii] doi: 10.1016/S1473-3099(17)30491-7 28818542.

3. Dellinger RP. The Surviving Sepsis Campaign: Where have we been and where are we going? Cleve Clin J Med. 2015;82(4):237–44. Epub 2015/05/09. doi: 10.3949/ccjm.82gr.15001 25955458.

4. Kollef MH. Broad-spectrum antimicrobials and the treatment of serious bacterial infections: getting it right up front. Clin Infect Dis. 2008;47 Suppl 1:S3–13. Epub 2008/09/09. doi: 10.1086/590061 18713047.

5. Gradel KO, Jensen US, Schonheyder HC, Ostergaard C, Knudsen JD, Wehberg S, et al. Impact of appropriate empirical antibiotic treatment on recurrence and mortality in patients with bacteraemia: a population-based cohort study. BMC Infect Dis. 2017;17(1):122. Epub 2017/02/09. doi: 10.1186/s12879-017-2233-z [pii]. 28166732; PubMed Central PMCID: PMC5294810.

6. 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(11):4851–63. Epub 2010/08/25. AAC.00627-10 [pii] doi: 10.1128/AAC.00627-10 20733044; PubMed Central PMCID: PMC2976147.

7. 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. Epub 2015/04/19. doi: 10.1186/s13054-015-0795-y [pii]. 25888181; PubMed Central PMCID: PMC4358713.

8. Cain SE, Kohn J, Bookstaver PB, Albrecht H, Al-Hasan MN. Stratification of the impact of inappropriate empirical antimicrobial therapy for Gram-negative bloodstream infections by predicted prognosis. Antimicrob Agents Chemother. 2015;59(1):245–50. Epub 2014/10/29. AAC.03935-14 [pii] doi: 10.1128/AAC.03935-14 25348527; PubMed Central PMCID: PMC4291357.

9. Fitzpatrick JM, Biswas JS, Edgeworth JD, Islam J, Jenkins N, Judge R, 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(3):244–51. Epub 2015/11/19. S1198-743X(15)00974-X [pii] doi: 10.1016/j.cmi.2015.10.034 26577143.

10. Savage RD, Fowler RA, Rishu AH, Bagshaw SM, Cook D, Dodek P, et al. The Effect of Inadequate Initial Empiric Antimicrobial Treatment on Mortality in Critically Ill Patients with Bloodstream Infections: A Multi-Centre Retrospective Cohort Study. PLoS One. 2016;11(5):e0154944. Epub 2016/05/07. doi: 10.1371/journal.pone.0154944 PONE-D-16-05657 [pii]. 27152615; PubMed Central PMCID: PMC4859485.

11. Thom KA, Shardell MD, Osih RB, Schweizer ML, Furuno JP, Perencevich EN, et al. Controlling for severity of illness in outcome studies involving infectious diseases: impact of measurement at different time points. Infect Control Hosp Epidemiol. 2008;29(11):1048–53. Epub 2008/09/27. doi: 10.1086/591453 [pii]. 18817505; PubMed Central PMCID: PMC2716043.

12. Corona A, Bertolini G, Lipman J, Wilson AP, Singer M. Antibiotic use and impact on outcome from bacteraemic critical illness: the BActeraemia Study in Intensive Care (BASIC). J Antimicrob Chemother. 2010;65(6):1276–85. Epub 2010/03/26. dkq088 [pii] doi: 10.1093/jac/dkq088 20335186.

13. Anderson DJ, Moehring RW, Sloane R, Schmader KE, Weber DJ, Fowler VG Jr., et al. Bloodstream infections in community hospitals in the 21st century: a multicenter cohort study. PLoS One. 2014;9(3):e91713. Epub 2014/03/20. doi: 10.1371/journal.pone.0091713 PONE-D-13-34754 [pii]. 24643200; PubMed Central PMCID: PMC3958391.

14. Alam N, Oskam E, Stassen PM, Exter PV, van de Ven PM, Haak HR, et al. Prehospital antibiotics in the ambulance for sepsis: a multicentre, open label, randomised trial. Lancet Respir Med. 2018;6(1):40–50. Epub 2017/12/03. S2213-2600(17)30469-1 [pii] doi: 10.1016/S2213-2600(17)30469-1 29196046.

15. McGregor JC, Rich SE, Harris AD, Perencevich EN, Osih R, Lodise TP Jr., 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(3):329–37. Epub 2007/06/30. CID41730 [pii] doi: 10.1086/519283 17599310.

16. Hernán MA, Robins JM. Causal Inference: Boca Raton: Chapman & Hall/CRC, forthcoming; 2019.

17. Bax HV, N.; Hunfeld, N. SWAB Erasmus MC 2018. Available from: https://erasmusmc.swabid.nl/.

18. Verbrugh HA. Mapping antibiotic use and resistance in the Netherlands: SWAB and NethMap. Neth J Med. 2003;61(11):341–2. Epub 2004/02/11. 14768715.

19. Prevention CfDCa. Bloodstream Infection Event (Central Line-Associated Bloodstream Infection and Non-central Line Associated Bloodstream Infection) 2019 [April 18, 2019]. Available from: https://www.cdc.gov/nhsn/pdfs/pscmanual/4psc_clabscurrent.pdf.

20. Trick WE, Zagorski BM, Tokars JI, Vernon MO, Welbel SF, Wisniewski MF, et al. Computer algorithms to detect bloodstream infections. Emerg Infect Dis. 2004;10(9):1612–20. Epub 2004/10/23. doi: 10.3201/eid1009.030978 15498164; PubMed Central PMCID: PMC3320282.

21. Zachariasse JM, Seiger N, Rood PP, Alves CF, Freitas P, Smit FJ, et al. Validity of the Manchester Triage System in emergency care: A prospective observational study. PLoS One. 2017;12(2):e0170811. Epub 2017/02/06. doi: 10.1371/journal.pone.0170811 PONE-D-16-22878 [pii]. 28151987; PubMed Central PMCID: PMC5289484.

22. Shapiro NI, Wolfe RE, Wright SB, Moore R, Bates DW. Who needs a blood culture? A prospectively derived and validated prediction rule. J Emerg Med. 2008;35(3):255–64. Epub 2008/05/20. S0736-4679(08)00444-7 [pii] doi: 10.1016/j.jemermed.2008.04.001 18486413.

23. Friedman ND, Kaye KS, Stout JE, McGarry SA, Trivette SL, Briggs JP, et al. Health care—associated bloodstream infections in adults: a reason to change the accepted definition of community-acquired infections. Ann Intern Med. 2002;137(10):791–7. Epub 2002/11/19. 200211190–00007 [pii]. doi: 10.7326/0003-4819-137-10-200211190-00007 12435215.

24. McGinley A, Pearse RM. A national early warning score for acutely ill patients. BMJ. 2012;345:e5310. Epub 2012/08/10. doi: 10.1136/bmj.e5310 22875955.

25. Brink A, Alsma J, Verdonschot R, Rood PPM, Zietse R, Lingsma HF, et al. Predicting mortality in patients with suspected sepsis at the Emergency Department; A retrospective cohort study comparing qSOFA, SIRS and National Early Warning Score. PLoS One. 2019;14(1):e0211133. Epub 2019/01/27. doi: 10.1371/journal.pone.0211133 PONE-D-18-21448 [pii]. 30682104; PubMed Central PMCID: PMC6347138.

26. Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, 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(6):676–82. Epub 2011/02/19. kwq433 [pii] doi: 10.1093/aje/kwq433 21330339.

27. Brookhart MA, Schneeweiss S, Rothman KJ, Glynn RJ, Avorn J, Sturmer T. Variable selection for propensity score models. Am J Epidemiol. 2006;163(12):1149–56. Epub 2006/04/21. kwj149 [pii] doi: 10.1093/aje/kwj149 16624967; PubMed Central PMCID: PMC1513192.

28. Graham JW, Olchowski AE, Gilreath TD. How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prev Sci. 2007;8(3):206–13. Epub 2007/06/06. doi: 10.1007/s11121-007-0070-9 17549635.

29. Glynn RJ, Schneeweiss S, Sturmer T. Indications for propensity scores and review of their use in pharmacoepidemiology. Basic Clin Pharmacol Toxicol. 2006;98(3):253–9. Epub 2006/04/14. PTOpto_293 [pii] doi: 10.1111/j.1742-7843.2006.pto_293.x 16611199; PubMed Central PMCID: PMC1790968.

30. Austin PC. An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies. Multivariate Behav Res. 2011;46(3):399–424. Epub 2011/08/06. doi: 10.1080/00273171.2011.568786 21818162; PubMed Central PMCID: PMC3144483.

31. Austin PC. Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis. Stat Med. 2016;35(30):5642–55. Epub 2016/08/24. doi: 10.1002/sim.7084 27549016; PubMed Central PMCID: PMC5157758.

32. Rassen JA, Glynn RJ, Rothman KJ, Setoguchi S, Schneeweiss S. Applying propensity scores estimated in a full cohort to adjust for confounding in subgroup analyses. Pharmacoepidemiol Drug Saf. 2012;21(7):697–709. Epub 2011/12/14. doi: 10.1002/pds.2256 22162077; PubMed Central PMCID: PMC3383902.


Článek vyšel v časopise

PLOS One


2019 Číslo 11
Nejčtenější tento týden
Nejčtenější v tomto čísle
Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

plice
INSIGHTS from European Respiratory Congress
nový kurz

Současné pohledy na riziko v parodontologii
Autoři: MUDr. Ladislav Korábek, CSc., MBA

Svět praktické medicíny 3/2024 (znalostní test z časopisu)

Kardiologické projevy hypereozinofilií
Autoři: prof. MUDr. Petr Němec, Ph.D.

Střevní příprava před kolonoskopií
Autoři: MUDr. Klára Kmochová, Ph.D.

Všechny kurzy
Kurzy Podcasty Doporučená témata Časopisy
Přihlášení
Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se

#ADS_BOTTOM_SCRIPTS#