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Surveillance cultures and genotyping of MRSA and MSSA isolates demonstrated the absence of cross-transmission among patients in the MICU, despite ongoing introduction of these pathogens. Reporting culture results and isolating colonized patients, as suggested by some guidelines, would have falsely suggested the success of such infection-control policies.

An algorithm is presented to calculate likelihoods of acquisition routes using only individual patient data concerning period of stay and microbiologic surveillance (without genotyping). The algorithm also produces estimates for the prevalence and the number of acquisitions by each route. The algorithm is applied to colonization data of third-generation cephalosporin-resistant Enterobacteriaceae (CRE) from September 2001 to May 2002 in two intensive care units (ICUs) (n = 277 and n = 180, respectively) of Utrecht, Kingdom of the Netherlands. Genotyping and epidemiologic linkage are used as the reference standard. Surveillance cultures were obtained on admission and twice weekly thereafter. All CREs were genotyped. According to the reference standard, the daily prevalence of CRE in ICU-1 and ICU-2 was 26.1% (standard deviation: 15.4) and 15.1% (standard deviation: 13.4), respectively, with five of 23 (21.7%) and six of 21 (28.6%) cases of acquired colonization being of exogenous origin, respectively. On the basis of the algorithm, the endogenous route was responsible for more acquisitions than the exogenous route (p = 0.003 and p < 0.001 for ICU-1 and ICU-2, respectively). The estimated number of acquisitions is 30 and 27, and the estimated prevalence is 27.6% and 17.6% for ICU-1 and ICU-2, respectively. By use of longitudinal colonization data only, the algorithm determines the relative importance of acquisition routes taking patient dependency into account.

BackgroundWe determined the effects of two antibiotic policies (predominance of either β-lactam antibiotics or fluroquinolones) on acquisition with third-generation cephalosporin-resistant Enterobacteriaceae (CRE) and fluoroquinolone-resistant CRE (FCRE) in two ICUs, with monitoring of other variables that may influence acquisition.MethodsAfter an 8-month baseline period, units were randomized to a predominant β-lactam antibiotic regimen (weekly cycling of ceftriaxone, amoxicillin–clavulanic acid and fluroquinolones) or a fluoroquinolone regimen for 3 months, with cross-over for another 3 months. Acquisition of CRE and FCRE was determined by microbiological surveillance.ResultsDuring baseline, acquisition rates for CRE and FCRE were 14/1,000 and 2/1,000 patient days at risk, respectively. Cross-transmission of CRE accounted for ≤25% of acquisitions, and CRE acquisition was associated with the use of β-lactam antibiotics (amoxicillin–clavulanic acid in particular). As compared to baseline, β-lactam antibiotic use [in defined daily dose (DDD)/1,000 patient days] was reduced from 854 to 526 (−39%) and 555 (−35%) during both intervention periods. Fluoroquinolone use was increased from 150 and 129 DDD/1,000 patient days in baseline and the β-lactam period to 514 DDD/1,000 patient days (+243%) in the fluoroquinolone period. Reductions in β-lactam use were not associated with reduced CRE acquisition [adjusted HRs were 1.0 (95% CR: 0.5–2.2) and 1.1 (95% CI: 0.5–2.5) during both periods, respectively]. Increased use of fluoroquinolones was associated with increased acquisition of FCRE [adjusted HR 4.1 (95% CI: 1.4–11.9; p < 0.01]. Infection control variables remained comparable during all periods.ConclusionA 35–39% reduction of β-lactam exposure was not associated with reduced acquisition of CRE, whereas a 243% increase of fluoroquinolone use increased acquisition of FCRE.

Surveillance, genotyping, and integron analysis identified previously unnoticed outbreaks of integron-carrying ERSC. Cross-transmission appeared to be the dominant route of transmission. Therefore, barrier precautions are necessary to prevent further spread.

No abstract

The colonization dynamics of antibiotic-resistant pathogens in hospital settings are complex, with multiple and continuously interacting variables (e.g., introduction of resistance, infection-control practices, antibiotic use). Quantification of these variables is indispensable in the evaluation of intervention studies, because these variables represent potential confounders. In this article, the complexity of colonization dynamics is described. Through a systematic review, we identified studies that evaluated the modification of antibiotic prescription to reduce antibiotic resistance in intensive care units (n=19), and the extent of confounding-control was determined. Most studies evaluated antimicrobial restriction/substitution (n=12) or antibiotic rotation (n=4). Sixteen studies had a prospective cohort design (before-after), of which 12 were without a control group. Introduction of antibiotic resistance was determined in 10 studies. The relative importance of colonization routes and adherence to infection-control measures were not determined in any study. Therefore, it remains uncertain whether observed changes in the prevalence of antibiotic resistance after intervention were causally related to the intervention. Appropriate choices of study design, primary end point (colonization rates rather than infection rates) and statistical tests, determination of colonization routes, and control of potential confounders are needed to increase validity of intervention studies.

Background Various metrics of hospital antibiotic use might assist in guiding antimicrobial stewardship (AMS). Objectives To compare patient outcomes in association with three methods to measure and feedback information on hospital antibiotic use when used in developing an AMS intervention. Methods Three methods were randomly allocated to 42 clusters from 21 Dutch hospitals: (1) feedback on quantity of antibiotic use [DDD, days-of-therapy (DOT) from hospital pharmacy data], versus feedback on (2) validated, or (3) non-validated quality indicators from point prevalence studies. Using this feedback together with an implementation tool, stewardship teams systematically developed and performed improvement strategies. The hospital length of stay (LOS) was the primary outcome and secondary outcomes included DOT, ICU stay and hospital mortality. Data were collected before (February–May 2015) and after (February–May 2017) the intervention period. Results The geometric mean hospital LOS decreased from 9.5 days (95% CI 8.9–10.1, 4245 patients) at baseline to 9.0 days (95% CI 8.5–9.6, 4195 patients) after intervention (P &lt; 0.001). No differences in effect on LOS or secondary outcomes were found between methods. Feedback on quality of antibiotic use was used more often to identify improvement targets and was preferred over feedback on quantity of use. Consistent use of the implementation tool seemed to increase effectiveness of the AMS intervention. Conclusions The decrease in LOS versus baseline likely reflects improvement in the quality of antibiotic use with the stewardship intervention. While the outcomes with the three methods were otherwise similar, stewardship teams preferred data on the quality over the quantity of antibiotic use.