Hostname: page-component-cb9f654ff-qc88w Total loading time: 0 Render date: 2025-07-31T23:34:04.890Z Has data issue: false hasContentIssue false
  • English
  • Français

Clinical consequences of contaminated blood cultures in adult hospitalized patients at an institution utilizing a rapid blood-culture identification system

Published online by Cambridge University Press:  10 December 2020

Sidra Liaquat ,
Lorena Baccaglini ,
Gleb Haynatzki ,
Sharon J. Medcalf  and
Mark E. Rupp Open the ORCID record for Mark E. Rupp [Opens in a new window]
Sidra Liaquat*
Affiliation:
Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska
Lorena Baccaglini
Affiliation:
Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska
Gleb Haynatzki
Affiliation:
Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska
Sharon J. Medcalf
Affiliation:
Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska
Mark E. Rupp*
Affiliation:
Division of Infectious Diseases, University of Nebraska Medical Center, Omaha, Nebraska
*
Author for correspondence: Mark E. Rupp, E-mail: merupp@unmc.edu. Or Sidra Liaquat, E-mail: sidra.liaquat@unmc.edu
Author for correspondence: Mark E. Rupp, E-mail: merupp@unmc.edu. Or Sidra Liaquat, E-mail: sidra.liaquat@unmc.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

To assess the clinical impact of contaminated blood cultures in hospitalized patients during a period when rapid diagnostic testing using a FilmArray Blood Culture Identification (BCID) panel was in use.

Design:

Retrospective cohort study.

Setting:

Single academic medical center.

Participants:

Patients who had blood culture(s) performed during an admission between June 2014 and December 2016.

Methods:

Length of hospital stay and days of antibiotic therapy were assessed in relation to blood-culture contamination using generalized linear models with univariable and multivariable analyses.

Results:

Among 11,474 patients who had blood cultures performed, the adjusted mean length of hospital stay for patients with contaminated blood-culture episodes (N = 464) was 12.3 days (95% confidence interval [CI], 11.4–13.2) compared to 11.5 days (95% CI, 11.0–11.9) for patients (N = 11,010) with negative blood-culture episodes (P = .032). The adjusted mean durations of antibiotic therapy for patients with contaminated and negative blood-culture episodes were 6.0 days (95% CI, 5.3–6.7) and 5.2 days (95% CI, 4.9–5.4), respectively (P = .011).

Conclusions:

Despite the use of molecular-based, rapid blood-culture identification, contamination of blood cultures continues to result in prolonged hospital stay and unnecessary antibiotic therapy in hospitalized patients.

Information

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 42 , Issue 8 , August 2021 , pp. 978 - 984
Check for updates
Copyright
© The Author(s), 2020. 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.)

Article purchase

Temporarily unavailable

References

Magadia, RR, Weinstein, MP. Laboratory diagnosis of bacteremia and fungemia. Infect Dis Clin North Am 2001;15:1009–1024.CrossRefGoogle ScholarPubMed
Lodise, TP, McKinnon, PS, Swiderski, L, Rybak, MJ. Outcomes analysis of delayed antibiotic treatment for hospital-acquired Staphylococcus aureus bacteremia. Clin Infect Dis 2003;36:1418–1423.CrossRefGoogle ScholarPubMed
Bates, DW, Goldman, L, Lee, TH. Contaminant blood cultures and resource utilization. The true consequences of false-positive results. JAMA 1991;265:365–369.CrossRefGoogle ScholarPubMed
Alahmadi, YM, Aldeyab, MA, McElnay, JC, et al. Clinical and economic impact of contaminated blood cultures within the hospital setting. J Hosp Infect 2011;77:233–236.CrossRefGoogle ScholarPubMed
Souvenir, D, Anderson, DE Jr, Palpant, S, et al. Blood cultures positive for coagulase-negative staphylococci: antisepsis, pseudobacteremia, and therapy of patients. J Clin Microbiol 1998;36:1923–1926.CrossRefGoogle ScholarPubMed
Surdulescu, S, Utamsingh, D, Shekar, R. Phlebotomy teams reduce blood-culture contamination rate and save money. Clin Perform Qual Health Care 1998;6:60–62.Google ScholarPubMed
Zwang, O, Albert, RK. Analysis of strategies to improve cost effectiveness of blood cultures. J Hosp Med 2006;1:272–276.CrossRefGoogle ScholarPubMed
Geisler, B, Jilg, N, Patton, RG, Pietzsch, JB. A model to evaluate the impact of hospital-based interventions targeting false-positive blood cultures on economic and clinical outcomes. J Hosp Infect 2019;102:438–444.CrossRefGoogle Scholar
Gilligan, PH. Blood culture contamination: a clinical and financial burden. Infect Control Hosp Epidemiol 2013;34:22–23.CrossRefGoogle ScholarPubMed
Rello, J, Ollendorf, DA, Oster, G, et al. Epidemiology and outcomes of ventilator-associated pneumonia in a large US database. Chest 2002;122:2115–2121.CrossRefGoogle Scholar
Al-Helali, NS, Al-Asmary, SM, Abdel-Fattah, MM, Al-Jabban, TM, Al-Bamri, AL. Epidemiologic study of nosocomial urinary tract infections in Saudi military hospitals. Infect Control Hosp Epidemiol 2004;25:1004–1007.CrossRefGoogle ScholarPubMed
Fridkin, S, Baggs, J, Fagan, R, et al. Vital signs: improving antibiotic use among hospitalized patients. Morb Mortal Wkly Rep 2014;63:194–200.Google ScholarPubMed
Modena, S, Bearelly, D, Swartz, K, Friedenberg, FK. Clostridium difficile among hospitalized patients receiving antibiotics: a case-control study. Infect Control Hosp Epidemiol 2005;26:685–690.CrossRefGoogle ScholarPubMed
Hensgens, MP, Goorhuis, A, Dekkers, OM, Kuijper, EJ. Time interval of increased risk for Clostridium difficile infection after exposure to antibiotics. J Antimicrob Chemother 2012;67:742–748.CrossRefGoogle ScholarPubMed
Slimings, C, Riley, TV. Antibiotics and hospital-acquired Clostridium difficile infection: update of systematic review and meta-analysis. J Antimicrob Chemother 2014;69:881–891.CrossRefGoogle ScholarPubMed
Aranda-Gallardo, M, Morales-Asencio, JM, Canca-Sanchez, JC, et al. Instruments for assessing the risk of falls in acute hospitalized patients: a systematic review and meta-analysis. BMC Health Serv Res 2013;13:122.CrossRefGoogle ScholarPubMed
Borghardt, AT, Prado, TN, Araujo, TM, Rogenski, NM, Bringuente, ME. Evaluation of the pressure ulcers risk scales with critically ill patients: a prospective cohort study. Rev Lat Am Enfermagem 2015;23:28–35.CrossRefGoogle ScholarPubMed
Faul, F, Erdfelder, E, Lang, A-G, Buchner, A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 2007;39:175–191.CrossRefGoogle ScholarPubMed
Bates, DW, Lee, TH. Rapid classification of positive blood cultures. Prospective validation of a multivariate algorithm. JAMA 1992;267:1962–1966.CrossRefGoogle ScholarPubMed
Aliyali, M, Mehravaran, H, Abedi, S, Sharifpour, A, Yazdani Cherati, J. Impact of comorbid ischemic heart disease on short-term outcomes of patients hospitalized for acute exacerbations of COPD. Tanaffos 2015;14:165–171.Google ScholarPubMed
Kuwabara, K, Imanaka, Y, Matsuda, S, et al. The association of the number of comorbidities and complications with length of stay, hospital mortality and LOS high outlier, based on administrative data. Environ Health Prev Med 2008;13:130–137.CrossRefGoogle ScholarPubMed