Ann Clin Microbiol.  2014 Jun;17(2):58-64. 10.5145/ACM.2014.17.2.58.

Factors Influencing the False Positive Signals of Continuous Monitoring Blood Culture System

• Uh Y
• Jang IH
• Park SD
• Kim KS
• Seo DM
• Yoon KJ
• Choi HK
• Kim YK
• Kim HY

• KMID: 1971095
• DOI: http://doi.org/10.5145/ACM.2014.17.2.58

Abstract

BACKGROUND
The false positive signals of a continuous monitoring blood culture system (CMBCS) increase the reporting time and laboratory cost. This study aimed to determine the highly relevant variables that discriminate false positive signals from true positive signals in a CMBCS.
METHODS
Among 184,363 blood culture sets (aerobic and anaerobic), the signal-positive samples according to a BACTEC FX system (Plus Aerobic/F, BDA; Plus Anaerobic/F, BDN) and BacT/Alert 3D system (Standard Aerobic, BSA; Standard Anaerobic, BSN) between April 2010 and November 2013 were classified into two groups: false positive or true positive signals. The data of 15 parameters between the two groups were then statistically compared.
RESULTS
Among total blood cultures, the positive rates of CMBCS signals according to BDA, BDN, BSA, and BSN were 4.9%, 2.8%, 3.8%, and 3.2%, respectively. The false positive rates of CMBCS signals according to BDA, BDN, BSA, and BSN were 0.6%, 0.1%, 0.1%, and 0.1%, respectively. The blood volume, detection time, time interval between admission and test, C-reactive protein concentration, leukocyte count, delta neutrophil index, and mean peroxidase index showed statistically significant differences between the two groups.
CONCLUSION
There were no variables with diagnostic sensitivity and specificity for discriminating the two groups. Therefore, analysis of bacterial growth curves produced by CMBCS is needed for early and effective detection of false positive signals.

Keyword

Blood; Culture; False positive; Monitoring; Signal

MeSH Terms

Blood Volume
C-Reactive Protein
Leukocyte Count
Neutrophils
Peroxidase
C-Reactive Protein
Peroxidase

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