Abstract
This single-center retrospective observational study aimed to verify whether a diagnosis of bandemia could be a predictive marker for bacteremia. We assessed 970 consecutive patients (median age 73 years; male 64.8%) who underwent two or more sets of blood cultures between April 2015 and March 2016 in both inpatient and outpatient settings. We assessed the value of bandemia (band count > 10%) and the percentage band count for predicting bacteremia using logistic regression models. Bandemia was detected in 151 cases (15.6%) and bacteremia was detected in 188 cases (19.4%). The incidence of bacteremia was significantly higher in cases with bandemia (52.3% vs. 13.3%; odds ratio (OR) = 7.15; 95% confidence interval (CI) 4.91–10.5). The sensitivity and specificity of bandemia for predicting bacteremia were 0.42 and 0.91, respectively. The bandemia was retained as an independent predictive factor for the multivariable logistic regression model (OR, 6.13; 95% CI, 4.02–9.40). Bandemia is useful for establishing the risk of bacteremia, regardless of the care setting (inpatient or outpatient), with a demonstrable relationship between increased risk and bacteremia. A bandemia-based electronic alert for blood-culture collection may contribute to the improved diagnosis of bacteremia.
Highlights
Bacteremia is a form of severe infection associated with a high probability of mortality and substantial financial healthcare costs [1]
The incidence of bandemia was higher in inpatients than in outpatients, while there was no significant differences of the incidence of bacteremia between inpatients and outpatients
The band-count percentage as a concontinuous variable, was an independent predictor for bacteremia, and the was tinuous variable, was an independent predictor for bacteremia, and the area under the receiver-operating characteristic curve (AUROC) was imimproved by adding the band-count percentage as a continuous variable to the baseline proved by adding the band-count percentage as a continuous variable to the baseline prepredictive model including body temperature, white blood cell (WBC)
Summary
Bacteremia is a form of severe infection associated with a high probability of mortality and substantial financial healthcare costs [1]. Bacteremia is a poor prognostic factor for infectious diseases and is one of the leading causes of death in developed countries [2,3]. The 1-month rate of communityacquired bacteremia is 10–19%, and the mortality rate for hospital-acquired bloodstream infection is 17–28% [4,5,6,7]. The clinical rule described by Shapiro et al is highly sensitive in nature; its external validity has been verified and is useful for preventing the misdiagnosis of bacteremia [19,20]
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