The selection process is illustrated in Figure 2. Screening of 5,231 titles and abstracts and 79 full texts yielded 7 eligible studies (Arpi & Renneberg, 1984; Greene et al., 2012; Karchmer, Giannetta, Muto, Strain, & Farr, 2000; Khair et al., 2013; Krieger, Kaiser, & Wenzel, 1983; Leone et al., 2007; Rogers et al., 2011; Saint et al., 2006). Two articles that used the same sample and similar methodology to examine different risk factors are treated as one study for the purposes of this review (Greene et al., 2012; Rogers et al., 2011). Although both articles examined risk factors for bacteremia after CAB, one article specifically investigated blood transfusions, and the other explored multiple risk factors but not blood transfusions.
Characteristics of the three observational cohort (Arpi & Renneberg, 1984; Khair et al., 2013; Krieger et al., 1983), two case-control (Greene et al., 2012; Rogers et al., 2011; Saint et al., 2006), and two randomized controlled trials (RCTs) (Karchmer et al., 2000; Leone et al., 2007) are outlined in Table 1. For studies that conducted a subgroup analysis for bacteremia, only subgroup sample characteristics are listed. All studies were conducted in acute care hospitals in the United States or Europe. All studies used clinical and microbiology records as their primary sources of data.
The operational definitions of bacteriuria differed, ranging from 103 to 105 colony forming units per milliliter of single or multiple organisms. Five studies included all bacteria (Greene et al., 2012; Karchmer et al., 2000; Krieger et al., 1983; Leone et al., 2007; Rogers et al., 2011; Saint et al., 2006), one specifically included fungal pathogens, and two studies examined one genus (enterococci) (Khair et al., 2013) or species (Staphylococcus aureus) (Arpi & Renneberg, 1984). One study sampled patients with asymptomatic bacteriuria (Leone et al., 2007), and the remainder sampled bacteriuric patients with and without urinary tract symptoms. In two studies, 100% of patients had indwelling urinary catheters (Karchmer et al., 2000; Leone et al., 2007), and in three studies, the proportion of patients with catheters was between 57% and 86% (Arpi & Renneberg, 1984; Khair et al., 2013; Saint et al., 2006). In the two studies missing catheter data (Greene et al., 2012; Krieger et al., 1983; Rogers et al., 2011), all bacteriurias were nosocomial, so it was assumed more than half of the patients had urinary catheters (Hooton et al., 2010). Five of the seven studies examined only nosocomial infections (Greene et al., 2012; Karchmer et al., 2000; Krieger et al., 1983; Leone et al., 2007; Rogers et al., 2011; Saint et al., 2006).
The mean or median age of participants was between 47 and 73 years, and the proportion of males varied from 37% to 95%. The outcome measure in one study was clinical sepsis (Leone et al., 2007); the remaining studies measured bacteremia. Secondary bacteremia was commonly defined as the same organism cultured in urine and blood; however, the amount of time between onset of bacteriuria and bacteremia differed between studies, as did the criteria for a matching organism. The rarity of bacteremia due to CAB is underlined in the small numbers of cases in the cohort studies and RCTs (range 6 to 33). The two case control studies identified 95 and 298 cases.
All seven studies were at high risk of at least one type of bias. Table 2 and Table 3 list the sources of bias by study design. We adapted the NOS for cohort studies by removing one question because the cohort studies in our review were simple observational studies (Arpi & Renneberg, 1984; Khair et al., 2013; Krieger et al., 1983), rather than the classic cohort design where subjects with a known exposure are compared to those not exposed. All three observational cohort studies used positive clinical cultures to define bacteremia, exposing them to ascertainment bias (bacteremia was demonstrated to be present but not absent) and detection bias (neutropenic patients may have had blood cultures drawn more frequently than other patients, biasing results in favor of finding high rates of bacteremia in neutropenic patients). In addition, none of the cohort studies used multivariable analysis to examine bacteremia outcomes, so results were likely confounded by measured and unmeasured factors.
In the two case-control studies, choice of control group created different biases. In one, controls were chosen from a subset of patients who had not had blood cultures drawn rather than from the same population as cases, creating a selection bias that may have exaggerated differences in risk factors (Saint et al., 2006). In the other, controls were chosen from the entire pool of patients; however, because clinical cultures were used to define bacteremia, patients who were bacteremic but who did not have blood cultures drawn (e.g., due to poor access, palliation, or subclinical symptoms) would have been misclassified as control patients (Greene et al., 2012; Rogers et al., 2011). In addition, these case-control studies were vulnerable to residual confounding (e.g., transfusions may be responsible for an association between malignancy and bacteremia), or confounding by indication (e.g., hyperglycemia, rather than insulin administration may be associated with bacteremia).
In one of the two RCTs, the impossibility of blinding clinicians to the intervention may have resulted in differences in care delivery that influenced the rates of bacteremia (Karchmer et al., 2000). In the other RCT, patients with recurrent positive urine cultures who may have been more likely to develop subsequent sepsis were excluded (Leone et al., 2007). Neither RCT was powered to find a difference in bacteremia or sepsis rates, creating a statistical bias toward the null for our outcome of interest.
Overall, the case-control studies were more aptly designed and conducted to answer our review question (Greene et al., 2012; Rogers et al., 2011; Saint et al., 2006). The strengths of the case control studies were adequate sample sizes, independent determination of exposures and outcomes by physician reviewers, consideration of multiple biologically plausible risks, assessment of potential interactions, and control for confounding by logistic regression.
Risks factors for bacteremia identified by the studies are summarized in Table 4. Male gender was identified as a risk factor in three of four studies (Greene et al., 2012; Krieger et al., 1983; Rogers et al., 2011; Saint et al., 2006). Men with CAB were found to have approximately twice the odds of developing bacteremia compared to females. This finding could have been confounded by the indication for catheterization in men (e.g., obstruction), which was not controlled for in any of the studies. Receipt of immunosuppressant medication was identified as an independent risk factor for bacteremia in both studies that examined it (Greene et al., 2012; Rogers et al., 2011; Saint et al., 2006); however, the studies reported very different odds ratios of 1.5 and 8, and when steroids were considered separately the direction of association was age-dependent. Receipt of antimicrobials was found to be protective in three of four studies (Arpi & Renneberg, 1984; Greene et al., 2012; Rogers et al., 2011; Saint et al., 2006), and the fourth study was likely underpowered to find a difference (Leone et al., 2007). Age, race, and service or ward were identified as non-significant factors by all studies that considered them.
Some risk factors were only explored in single studies. Transfusion of red blood cells was an independent risk; recipients had nearly five times the odds of bacteremia compared to non-recipients, and a dose-response was evident (Rogers et al., 2011). Neutropenia from any cause (Greene et al., 2012), liver disease (Greene et al., 2012), and malignancy (Saint et al., 2006) each independently increased the risk of developing bacteremia. Hypertension, human immunodeficiency virus infection, and receipt of statins were not significant predictors in multivariable analyses.
Several findings were contradictory. Urinary tract disease was found to increase risk of bacteremia nearly three-fold in one study (Greene et al., 2012), but was non-significant in three others (Arpi & Renneberg, 1984; Krieger et al., 1983; Saint et al., 2006). This may be because the definitions of urinary tract disease differed among the studies. Similarly, there was no agreement on the risk posed by urinary tract manipulation, defined variously as presence or type of catheter (Karchmer et al., 2000; Krieger et al., 1983), urological procedure (Greene et al., 2012), or surgery (Arpi & Renneberg, 1984). The urinary pathogen Serratia marcescens was more prevalent among patients who developed bacteremia compared to those who did not in an uncontrolled study (Krieger et al., 1983), but pathogen species was not a risk factor in a subsequent study using multivariable analysis (Saint et al., 2006), and vancomycin-resistance was not a significant risk factor for bacteremia in a study of enterococcal bacteriuria (Khair et al., 2013). Smoking was not associated with bacteremia in one case-control study (Greene et al., 2012), putting into question the weak association identified in an earlier case-control study (Saint et al., 2006). Finally, one study identified diabetes mellitus as a risk factor in patients less than 70 years of age (Saint et al., 2006), whereas a subsequent study found that receipt of insulin was a risk factor independent of history of diabetes (Greene et al., 2012).
Urol Nurs. 2015;35(4):191-203. © 2015 Society of Urologic Nurses and Associates