model to predict mdr-gnb colonization and infection 1223
antimicrobial therapy for severe sepsis patents, identification of patients colonized by MDR-GNB with nonsevere infections remains important to the implementation of stringent infec- tion control interventions to contain the spread ofMDR-GNB in the hospital setting.12,31 This finding is supported by the observation that in specific settings, such as intensive care units, active microbiological surveillance combined with other measures such as hand hygiene, contact precautions, and staff education, can reduce the transmission of MRSA.32–34 How- ever, universal screening of all patients for MDR-GNB upon admission is resource intensive, with a lack of evidence to support the efficacy of such an approach in reducing hospital MDR-GNB burden. A plausible approach to prevent the transmission of or to limit outbreaks of MDR-GNB infections in hospitals is to screen high-risk groups based on known risk factors or prediction systems that aid in the identification of patients in the community harboring MDR-GNB. This stra- tegic approach was supported in this study in the context of MDR-GNB detection by early clinical culture. In the first stage of the study, surveillance cultures on the low-risk population (ie, those with scores<4) only identified an additional 30 patients with MDR-GNB colonization (30 of 794 or 3.8%). However, surveillance cultures for the 201 high-risk patients (those with scores ≥4) identified an additional 20 MDR-GNB colonized patients who were not detected by decision-driven clinical cultures (20 of 201 or 10.0%). This study provides scientific evaluation of the efficacy of high-risk group surveil- lance strategies as a recommended infection prevention and control measure.
infections in general have a lower degree of antimicrobial resistance than infections acquired in a hospital, there is evidence of an increasing prevalence of MDR-GNB isolates identified in patients in the community.1,4 Most patients with severe sepsis are rushed into ED,30 and emergency physicians are confronted with making critical decisions on appropriate initial antibiotic use to lessen the impacts of severeMDR-GNB infection, as highly antimicrobial-resistant GNB have been increasingly recognized as the cause of community-acquired infections. Therefore, it is imperative to provide new tools for these physicians. A useful risk-stratification tool that assists ED physicians in identifying patients presenting from the commu- nity at increased risk ofMDR-GNB infectionwould enable better treatment outcomes. Our MDR-GNB COP model, though developed from a surveillance-culture–based cohort, successfully stratified patients with an increased risk ofMDR-GNB infection in a separate patient cohort according to distinct demographic and clinical characteristics. Furthermore, of the 998 patients enrolled in the second stage of this study,<30% had a point score ≥4, and>17%(168 of 998) had a score ≥
5.Thus, thisCOPmodel effectively differentiated high-risk populations for MDR-GNB infection and limited the probability of overuse of antibiotics as the result of arbitrary decisions. Our COP model therefore demonstrated its applicability and broad relevance for first-line physicians in their daily practice. In addition to decision-making regarding appropriate initial
In contrast to previously reported scoring models for
the prediction of antimicrobial-resistant GNB colonization, this COP model is the first scoring system that assists first-line physicians in identifying patients presenting from the community who are likely to be harboring MDR-GNB. The score-based COP model is easy for first-line physicians to use. It may assist them in stratifying MDR-GNB colonization risk among patients presenting from the community using clinical information easily obtained in daily practice. The MDR-GNB colonization group was defined by incorporating the results from both the surveillance and early clinical cultures to avoid MDR-GNB–colonized patients going undetected by microbiological surveillance alone13 and to lessen the potential bias from study-group misclassification. Prospectively collected clinical data in this study further minimized the threat from information bias. Finally, though the relationship between MDR-GNB colonization and subsequent infection remains to be clarified, the current study demonstrated the usefulness of a prediction system in risk stratification for both initial colonization status and subsequent infection probability. This study has several limitations. First, we did not obtain
perianal swab cultures in the microbiological surveillance performed in the first stage of this study. Previous studies have indicated that the gastrointestinal tract is an important anatomical site harboring antimicrobial-resistant Enterobacteriaceae35,36; thus, the lack of perianal swab cultures may have caused us to underestimate the MDR-GNB coloni- zation rate and may have introduced an information bias and misclassification of study groups. Second, because our data were derived from a single center, the ability to generalize based on our findings may be limited, due to potential dis- cordance of MDR-GNB prevalence in different hospitals. However, this study still demonstrates the usefulness of a simple decision model in stratifying the risk for MDR-GNB colonization and infection among patients presenting from the community. Finally, in areas where the prevalence of MDR- GNB colonization among patients in the community is lower than the prevalence observed in the current study, the appli- cation of our prediction model would result in a lower positive predictive value and a higher negative predictive value. Clin- icians should consider this important influential factor when adopting this prediction model in their decision making regarding empirical antibiotic therapy. In conclusion, a substantial number of ED patients harboring MDR-GNB at hospital admission were observed. The prediction model developed in this well-designed study can be useful for first-line physicians, assisting in the risk stratification not only for initial MDR-GNB colonization status but also the probability of subsequent MDR-GNB infection. Incorporation of the information provided in this prediction tool is crucial for first-line physicians to aid decision making regarding initial antimicrobial therapy and implementation of empirical infection control interventions to mitigate threats from MDR-GNB colonization and infections.
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