- Email: [email protected]
The carbapenem-resistant Enterobacteriaceae score: A bedside score to rule out infection with carbapenem-resistant Enterobacteriaceae among hospitalized patients
American Journal of Infection Control 41 (2013) 180-2
Contents lists available at ScienceDirect
American Journal of Infection Control
American Journal of Infection Control
journal homepage: www.ajicjournal.org
Brief report
The carbapenem-resistant Enterobacteriaceae score: A bedside score to rule out infection with carbapenem-resistant Enterobacteriaceae among hospitalized patients Emily T. Martin MPH, PhD a, *, Ryan Tansek BS b, Vicki Collins MD b, Kayoko Hayakawa MD, PhD b, Odaliz Abreu-Lanfranco MD b, Teena Chopra MD b, Paul R. Lephart PhD c, Jason M. Pogue PharmD d, Keith S. Kaye MD, MPH b, Dror Marchaim MD b a
Department of Pharmacy Practice, Wayne State University, Detroit, MI Division of Infectious Diseases, Detroit Medical Center, Wayne State University, Detroit, MI c Department of Clinical Microbiology, Detroit Medical Center, Detroit, MI d Department of Pharmacy Services, Detroit Medical Center, Detroit, MI b
Key Words: Carbapenem-resistant Enterobacteriaceae CRE Klebsiella pneumoniae carbapenemase Extended-spectrum b-lactamase ESBL Colistin Time to effective therapy
Patients infected with carbapenem-resistant Enterobacteriaceae often experience delays in initiation of appropriate antimicrobial therapy and increased mortality. A score was developed to differentiate bloodstream infections caused by carbapenem-resistant Enterobacteriaceae (16 patients) versus extended-spectrum b-lactamase-producing Enterobacteriaceae (166 patients). A score of 32 demonstrated high area under the curve of 0.80 (95% confidence interval: 0.68-0.92) and a negative predictive value of 97%. Copyright Ó 2013 by the Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
In regions where multidrug-resistant gram-negative pathogens such as carbapenem-resistant Enterobacteriaceae (CRE) and extendedspectrum b-lactamase (ESBL)-producing Enterobacteriaceae are endemic, clinicians often must choose between empiric therapy with carbapenems and polymyxins when confronted with critically ill hospitalized patients. Carbapenems are frequently prescribed as an empiric regimen for severe sepsis, particularly for patients with recent health care-associated exposures who are at risk for infections because of ESBL-producing Enterobacteriaceae.1 Unfortunately, carbapenems by themselves are not considered appropriate treatment against CRE. Patients with CRE bloodstream infections (BSI) often require polymyxin therapy, which is nephrotoxic.2 Delays in initiation of appropriate antibiotic therapy (DAAT) are common in patients with CRE infections.3 DAAT is the strongest independent modifiable predictor for in-hospital mortality among patients with severe sepsis.4
* Address correspondence to Emily T. Martin, MPH, PhD, Department of Pharmacy Practice, 259 Mack Avenue, Detroit, MI 48201. E-mail address: [email protected] (E.T. Martin). These data were previously presented in part at the 51st Interscience Conference on Antimicrobial Agents and Chemotherapy, Chicago, Illinois, September 18, 2011. Supported in part by the National Institute of Health (protocol number 10-0065 to K.S.K.). Conflicts of interest: None to report.
ESBL-producing Enterobacteriaceae and CRE share several epidemiologic features and risk factors and are both common nosocomial pathogens in many regions around the world.5-7 An easy to calculate, accurate score is needed to differentiate between patients with infections because of ESBL-producing Enterobacteriaceae and CRE and to facilitate empiric therapeutic decisions to reduce the likelihood of DAAT among patients with CRE infections and avoid unnecessary treatment with broad-spectrum toxic agents such as polymixins. Our study aim was to develop a simple bedside score to help physicians quantify the likelihood for severe infection caused by CRE as opposed to ESBL-producing Enterobacteriaceae. METHODS The study cohort consisted of patients at the Detroit Medical Center (DMC) who met the following inclusion criteria: BSI caused by CRE or ESBL-producing Enterobacteriaceae, from calendar years 2007-2010, who, on the date of culture, had severe sepsis, septic shock, or multiorgan failure per established criteria.8 Variables collected for each patient included (1) demographics, (2) comorbidities, (3) recent (3 months) exposures to antibiotics, and (4) recent exposures to health care-associated environments and procedures (3 months). The study was approved by the Institutional Review Board prior to its initiation.
0196-6553/$36.00 - Copyright Ó 2013 by the Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.ajic.2012.02.036
E.T. Martin et al. / American Journal of Infection Control 41 (2013) 180-2
181
Table 1 Crude and adjusted associations for candidate and final score variables Variable Resident in long-term care facility Renal disease Neurologic disease Reduced consciousness at time of illness Dependent functional status at admission Diabetes mellitus ICU admission Antibiotic exposure in 3 months prior to admission
OR (95% CI), P value 3.2 2.4 5.6 2.9 4.1 4.0 2.5 3.4
(0.9-11.5), P ¼ .08 (0.8-6.9), P ¼ .11 (1.7-18.1), P ¼ .004 (0.8-10.4), P ¼ .11 (0.9-18.5), P ¼ .07 (1.1-14.7), P ¼ .03 (0.9-7.0), P ¼ .10 (0.7-15.4), P ¼ .12
AOR (95% CI), P value
Score value
4.1 (1.2-14.9), P ¼ .03
14
(0.4-11.0), P ¼ .41 (0.9-13.0), P ¼ .08 (1.0-9.3), P ¼ .06 (0.4-10.2), P ¼ .37
7 12 11 7
2.0 3.4 3.0 2.1
AOR, Adjusted odds ratio; ICU, intensive care unit; OR, odds ratio. NOTE. Renal disease defined as 1.5 mg/dl or requiring hemodialysis or peritoneal dialysis. Neurologic disease defined as a history of neurologic disease including multiple sclerosis, Parkinson’s disease, neurologic tumor, stroke or transient ischemic attack.
Bacteria were identified to the species level by the DMC clinical microbiology laboratory, and susceptibilities were determined to predefined antimicrobials, based on an automated broth microdilution system (MicroScan, Siemens AG, Germany), and in accordance with the 2009 breakpoints set up by the Clinical and Laboratory Standards Institute criteria.9 Carbapenemase production screening was conducted with the modified Hodge test for Enterobacteriacea (Klebsiella species, Escherichia coli, and Enterobacter species), which were resistant to one or more third-generation cephalosporins and had elevated ertapenem minimum inhibitory concentration (MIC) of 2 mg/mL.9 A clinical prediction score was developed through construction of a multivariable regression model for predictors of CRE infection compared with ESBL-producing Enterobacteriaceae. Variables were selected as candidates for multivariate model generation based on the following criteria: (1) crude association (P .15) with CRE infection or (2) a priori identification as a factor of scientific importance, based on previous studies of risk factors for carbapenem resistance.5-7 Factors selected based on crude association were required to have at least 10 CRE infections in the risk category to ensure sufficient numbers of events for the final model. A multivariate model for presence of CRE was generated using stepwise methods (P .15 required for variable entry, P .20 required for variable removal), with a priori factors forced into the final model. Crude odds ratios (OR), adjusted odds ratios (AOR), 95% confidence intervals (95% CI), and P values for all preliminary models and the final model were generated using logistic regression. A clinical prediction score was derived from the final model by multiplying the regression coefficients by a factor of 10. Accuracy was assessed by calculation of sensitivity, specificity, positive predictive value, negative predictive value, and associated 95% CI. A receiver operating characteristic (ROC) curve was generated and area under the curve (AUC) was tested against a null AUC of 0.5. Statistical analyses were all performed using STATA 11.0 (STATA Corp, College Station, TX). RESULTS Overall, 182 patients met inclusion criteria, including 166 patients with BSIs because of ESBL-producing Enterobacteriaceae and 16 patients with BSIs because of CRE. Factors considered for the multivariate model based on crude association with CRE infection included residency in a long-term care facility, renal disease (defined as serum creatinine of 1.5 mg/dl and above), neurologic disease (defined as a history of any neurologic disease, eg, multiple sclerosis, Parkinson’s disease, neurologic malignancy, stroke or transient ischemic attack), reduced consciousness at time of illness, and diabetes mellitus. Factors considered based on a priori determination included dependent functional status at admission, intensive care unit admission, and antibiotic exposure within 3 months prior to
Fig 1. Receiver operating characteristic (ROC) curve of carbapenem-resistant Enterobacteriaceae (CRE) score to predict bloodstream infection because of CRE as opposed to bloodstream infection because of ESBL-producing Enterobacteriaceae. ROC curve indicating sensitivity and specificity of proposed score for the detection of CRE infection. Gray shading indicates 95% confidence interval surrounding the curve, and the diagonal line indicates the null hypothesis, AUC ¼ 0.5, representing random chance.
admission. The resulting regression model and prediction score algorithm are listed in Table 1. The CRE score had an area under ROC curve of 0.80 (95% CI: 0.68-0.92) (Fig 1). A score of 32 to define “high CRE risk” had sensitivity of 81% (95% CI: 76%-87%), specificity of 70% (95% CI: 63%-77%), positive predictive value of 21% (95% CI: 15%-27%), and negative predictive value of 97% (95% CI: 95%99.8%). A secondary analysis was performed to assess the effect of forcing all a priori-identified candidates into the model. The same stepwise model-building procedure was used, allowing any variable to be excluded from the final model. The AUC value based on the results of this second model (AUC ¼ 0.78) showed that this model was inferior to the model used for the development of the clinical prediction score. DISCUSSION This was a pilot investigation aimed to develop a CRE score to assist clinicians in institutions with endemic rates of CRE and ESBL infections. This score predicted CRE infection more accurately than random chance, as shown by the area under ROC curve of 0.80 (95% CI: 0.68-0.92) (Fig 1). Using a value of 32 to define “high CRE risk,” our clinical prediction rule demonstrated reasonably high sensitivity and specificity. The score’s high negative predictive value shows the score’s utility in identifying cases that are unlikely to be
182
E.T. Martin et al. / American Journal of Infection Control 41 (2013) 180-2
due to CRE infection, therefore helping to decrease unnecessary empiric polymyxins use and reduce toxicity.10 This method, once fully validated, has the potential to become valuable tool in identifying patients at low risk of CRE, particularly in institutions in which CRE is becoming increasingly endemic. Avoiding unnecessary polymyxin therapy through a combination of clinical algorithms and new rapid molecular testing technology may decrease the emergence of resistance to polymixins.11 In addition, the use of clinical prediction rules for CRE and other important hospital-associated pathogens offers a potential low-cost avenue to support infection control interventions such as contact isolation. This score development was performed only for Enterobacteriaceae and was specific to patients with BSI. Future work is needed to validate the CRE score in a wider range of hospitalized patients including other geographic regions from other institutions. The development of the CRE score is an initial step in our attempts to utilize bedside algorithms to improve the effectiveness of empiric antimicrobial therapy.
4.
5.
6.
7.
8.
9.
References 1. Peleg AY, Hooper DC. Hospital-acquired infections due to gram-negative bacteria. N Engl J Med 2010;362:1804-13. Epub May 14, 2010. 2. Schwaber MJ, Carmeli Y. Carbapenem-resistant Enterobacteriaceae: a potential threat. JAMA 2008;300:2911-3. Epub December 26, 2008. 3. Patel G, Huprikar S, Factor SH, Jenkins SG, Calfee DP. Outcomes of carbapenemresistant Klebsiella pneumoniae infection and the impact of antimicrobial and
10.
11.
adjunctive therapies. Infect Control Hosp Epidemiol 2008;29:1099-106. Epub November 1, 2008. Paul M, Shani V, Muchtar E, Kariv G, Robenshtok E, Leibovici L. Systematic review and meta-analysis of the efficacy of appropriate empiric antibiotic therapy for sepsis. Antimicrob Agents Chemother 2010;54:4851-63. Epub August 25, 2010. Ben-Ami R, Rodriguez-Bano J, Arslan H, Pitout JD, Quentin C, Calbo ES, et al. A multinational survey of risk factors for infection with extended-spectrum b-lactamase-producing enterobacteriaceae in nonhospitalized patients. Clin Infect Dis 2009;49:682-90. Epub July 23, 2009. Gasink LB, Edelstein PH, Lautenbach E, Synnestvedt M, Fishman NO. Risk factors and clinical impact of Klebsiella pneumoniae carbapenemase-producing K pneumoniae. Infect Control Hosp Epidemiol 2009;30:1180-5. Epub October 29, 2009. Schwaber MJ, Klarfeld-Lidji S, Navon-Venezia S, Schwartz D, Leavitt A, Carmeli Y. Predictors of carbapenem-resistant Klebsiella pneumoniae acquisition among hospitalized adults and effect of acquisition on mortality. Antimicrob Agents Chemother 2008;52:1028-33. Epub December 19, 2007. Dellinger RP, Levy MM, Carlet JM, Bion J, Parker MM, Jaeschke R, et al. Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock: 2008. Crit Care Med 2008;36:296-327. Epub December 26, 2007. CLSI. Performance standards for antimicrobial susceptibility testing. Nineteenth informational supplement. Approved standard M100eS19. Wayne [PA]: Clinical and Laboratory Standards Institute; 2009. Hartzell JD, Neff R, Ake J, Howard R, Olson S, Paolino K, et al. Nephrotoxicity associated with intravenous colistin (colistimethate sodium) treatment at a tertiary care medical center. Clin Infect Dis 2009;48:1724-8. Epub May 15, 2009. Marchaim D, Chopra T, Pogue JM, Perez F, Hujer AM, Rudin S, et al. Outbreak of colistin-resistant, carbapenem-resistant Klebsiella pneumoniae in metropolitan Detroit, Michigan. Antimicrob Agents Chemother 2011;55:593-9. Epub December 1, 2010.
Contents lists available at ScienceDirect
American Journal of Infection Control
American Journal of Infection Control
journal homepage: www.ajicjournal.org
Brief report
The carbapenem-resistant Enterobacteriaceae score: A bedside score to rule out infection with carbapenem-resistant Enterobacteriaceae among hospitalized patients Emily T. Martin MPH, PhD a, *, Ryan Tansek BS b, Vicki Collins MD b, Kayoko Hayakawa MD, PhD b, Odaliz Abreu-Lanfranco MD b, Teena Chopra MD b, Paul R. Lephart PhD c, Jason M. Pogue PharmD d, Keith S. Kaye MD, MPH b, Dror Marchaim MD b a
Department of Pharmacy Practice, Wayne State University, Detroit, MI Division of Infectious Diseases, Detroit Medical Center, Wayne State University, Detroit, MI c Department of Clinical Microbiology, Detroit Medical Center, Detroit, MI d Department of Pharmacy Services, Detroit Medical Center, Detroit, MI b
Key Words: Carbapenem-resistant Enterobacteriaceae CRE Klebsiella pneumoniae carbapenemase Extended-spectrum b-lactamase ESBL Colistin Time to effective therapy
Patients infected with carbapenem-resistant Enterobacteriaceae often experience delays in initiation of appropriate antimicrobial therapy and increased mortality. A score was developed to differentiate bloodstream infections caused by carbapenem-resistant Enterobacteriaceae (16 patients) versus extended-spectrum b-lactamase-producing Enterobacteriaceae (166 patients). A score of 32 demonstrated high area under the curve of 0.80 (95% confidence interval: 0.68-0.92) and a negative predictive value of 97%. Copyright Ó 2013 by the Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
In regions where multidrug-resistant gram-negative pathogens such as carbapenem-resistant Enterobacteriaceae (CRE) and extendedspectrum b-lactamase (ESBL)-producing Enterobacteriaceae are endemic, clinicians often must choose between empiric therapy with carbapenems and polymyxins when confronted with critically ill hospitalized patients. Carbapenems are frequently prescribed as an empiric regimen for severe sepsis, particularly for patients with recent health care-associated exposures who are at risk for infections because of ESBL-producing Enterobacteriaceae.1 Unfortunately, carbapenems by themselves are not considered appropriate treatment against CRE. Patients with CRE bloodstream infections (BSI) often require polymyxin therapy, which is nephrotoxic.2 Delays in initiation of appropriate antibiotic therapy (DAAT) are common in patients with CRE infections.3 DAAT is the strongest independent modifiable predictor for in-hospital mortality among patients with severe sepsis.4
* Address correspondence to Emily T. Martin, MPH, PhD, Department of Pharmacy Practice, 259 Mack Avenue, Detroit, MI 48201. E-mail address: [email protected] (E.T. Martin). These data were previously presented in part at the 51st Interscience Conference on Antimicrobial Agents and Chemotherapy, Chicago, Illinois, September 18, 2011. Supported in part by the National Institute of Health (protocol number 10-0065 to K.S.K.). Conflicts of interest: None to report.
ESBL-producing Enterobacteriaceae and CRE share several epidemiologic features and risk factors and are both common nosocomial pathogens in many regions around the world.5-7 An easy to calculate, accurate score is needed to differentiate between patients with infections because of ESBL-producing Enterobacteriaceae and CRE and to facilitate empiric therapeutic decisions to reduce the likelihood of DAAT among patients with CRE infections and avoid unnecessary treatment with broad-spectrum toxic agents such as polymixins. Our study aim was to develop a simple bedside score to help physicians quantify the likelihood for severe infection caused by CRE as opposed to ESBL-producing Enterobacteriaceae. METHODS The study cohort consisted of patients at the Detroit Medical Center (DMC) who met the following inclusion criteria: BSI caused by CRE or ESBL-producing Enterobacteriaceae, from calendar years 2007-2010, who, on the date of culture, had severe sepsis, septic shock, or multiorgan failure per established criteria.8 Variables collected for each patient included (1) demographics, (2) comorbidities, (3) recent (3 months) exposures to antibiotics, and (4) recent exposures to health care-associated environments and procedures (3 months). The study was approved by the Institutional Review Board prior to its initiation.
0196-6553/$36.00 - Copyright Ó 2013 by the Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.ajic.2012.02.036
E.T. Martin et al. / American Journal of Infection Control 41 (2013) 180-2
181
Table 1 Crude and adjusted associations for candidate and final score variables Variable Resident in long-term care facility Renal disease Neurologic disease Reduced consciousness at time of illness Dependent functional status at admission Diabetes mellitus ICU admission Antibiotic exposure in 3 months prior to admission
OR (95% CI), P value 3.2 2.4 5.6 2.9 4.1 4.0 2.5 3.4
(0.9-11.5), P ¼ .08 (0.8-6.9), P ¼ .11 (1.7-18.1), P ¼ .004 (0.8-10.4), P ¼ .11 (0.9-18.5), P ¼ .07 (1.1-14.7), P ¼ .03 (0.9-7.0), P ¼ .10 (0.7-15.4), P ¼ .12
AOR (95% CI), P value
Score value
4.1 (1.2-14.9), P ¼ .03
14
(0.4-11.0), P ¼ .41 (0.9-13.0), P ¼ .08 (1.0-9.3), P ¼ .06 (0.4-10.2), P ¼ .37
7 12 11 7
2.0 3.4 3.0 2.1
AOR, Adjusted odds ratio; ICU, intensive care unit; OR, odds ratio. NOTE. Renal disease defined as 1.5 mg/dl or requiring hemodialysis or peritoneal dialysis. Neurologic disease defined as a history of neurologic disease including multiple sclerosis, Parkinson’s disease, neurologic tumor, stroke or transient ischemic attack.
Bacteria were identified to the species level by the DMC clinical microbiology laboratory, and susceptibilities were determined to predefined antimicrobials, based on an automated broth microdilution system (MicroScan, Siemens AG, Germany), and in accordance with the 2009 breakpoints set up by the Clinical and Laboratory Standards Institute criteria.9 Carbapenemase production screening was conducted with the modified Hodge test for Enterobacteriacea (Klebsiella species, Escherichia coli, and Enterobacter species), which were resistant to one or more third-generation cephalosporins and had elevated ertapenem minimum inhibitory concentration (MIC) of 2 mg/mL.9 A clinical prediction score was developed through construction of a multivariable regression model for predictors of CRE infection compared with ESBL-producing Enterobacteriaceae. Variables were selected as candidates for multivariate model generation based on the following criteria: (1) crude association (P .15) with CRE infection or (2) a priori identification as a factor of scientific importance, based on previous studies of risk factors for carbapenem resistance.5-7 Factors selected based on crude association were required to have at least 10 CRE infections in the risk category to ensure sufficient numbers of events for the final model. A multivariate model for presence of CRE was generated using stepwise methods (P .15 required for variable entry, P .20 required for variable removal), with a priori factors forced into the final model. Crude odds ratios (OR), adjusted odds ratios (AOR), 95% confidence intervals (95% CI), and P values for all preliminary models and the final model were generated using logistic regression. A clinical prediction score was derived from the final model by multiplying the regression coefficients by a factor of 10. Accuracy was assessed by calculation of sensitivity, specificity, positive predictive value, negative predictive value, and associated 95% CI. A receiver operating characteristic (ROC) curve was generated and area under the curve (AUC) was tested against a null AUC of 0.5. Statistical analyses were all performed using STATA 11.0 (STATA Corp, College Station, TX). RESULTS Overall, 182 patients met inclusion criteria, including 166 patients with BSIs because of ESBL-producing Enterobacteriaceae and 16 patients with BSIs because of CRE. Factors considered for the multivariate model based on crude association with CRE infection included residency in a long-term care facility, renal disease (defined as serum creatinine of 1.5 mg/dl and above), neurologic disease (defined as a history of any neurologic disease, eg, multiple sclerosis, Parkinson’s disease, neurologic malignancy, stroke or transient ischemic attack), reduced consciousness at time of illness, and diabetes mellitus. Factors considered based on a priori determination included dependent functional status at admission, intensive care unit admission, and antibiotic exposure within 3 months prior to
Fig 1. Receiver operating characteristic (ROC) curve of carbapenem-resistant Enterobacteriaceae (CRE) score to predict bloodstream infection because of CRE as opposed to bloodstream infection because of ESBL-producing Enterobacteriaceae. ROC curve indicating sensitivity and specificity of proposed score for the detection of CRE infection. Gray shading indicates 95% confidence interval surrounding the curve, and the diagonal line indicates the null hypothesis, AUC ¼ 0.5, representing random chance.
admission. The resulting regression model and prediction score algorithm are listed in Table 1. The CRE score had an area under ROC curve of 0.80 (95% CI: 0.68-0.92) (Fig 1). A score of 32 to define “high CRE risk” had sensitivity of 81% (95% CI: 76%-87%), specificity of 70% (95% CI: 63%-77%), positive predictive value of 21% (95% CI: 15%-27%), and negative predictive value of 97% (95% CI: 95%99.8%). A secondary analysis was performed to assess the effect of forcing all a priori-identified candidates into the model. The same stepwise model-building procedure was used, allowing any variable to be excluded from the final model. The AUC value based on the results of this second model (AUC ¼ 0.78) showed that this model was inferior to the model used for the development of the clinical prediction score. DISCUSSION This was a pilot investigation aimed to develop a CRE score to assist clinicians in institutions with endemic rates of CRE and ESBL infections. This score predicted CRE infection more accurately than random chance, as shown by the area under ROC curve of 0.80 (95% CI: 0.68-0.92) (Fig 1). Using a value of 32 to define “high CRE risk,” our clinical prediction rule demonstrated reasonably high sensitivity and specificity. The score’s high negative predictive value shows the score’s utility in identifying cases that are unlikely to be
182
E.T. Martin et al. / American Journal of Infection Control 41 (2013) 180-2
due to CRE infection, therefore helping to decrease unnecessary empiric polymyxins use and reduce toxicity.10 This method, once fully validated, has the potential to become valuable tool in identifying patients at low risk of CRE, particularly in institutions in which CRE is becoming increasingly endemic. Avoiding unnecessary polymyxin therapy through a combination of clinical algorithms and new rapid molecular testing technology may decrease the emergence of resistance to polymixins.11 In addition, the use of clinical prediction rules for CRE and other important hospital-associated pathogens offers a potential low-cost avenue to support infection control interventions such as contact isolation. This score development was performed only for Enterobacteriaceae and was specific to patients with BSI. Future work is needed to validate the CRE score in a wider range of hospitalized patients including other geographic regions from other institutions. The development of the CRE score is an initial step in our attempts to utilize bedside algorithms to improve the effectiveness of empiric antimicrobial therapy.
4.
5.
6.
7.
8.
9.
References 1. Peleg AY, Hooper DC. Hospital-acquired infections due to gram-negative bacteria. N Engl J Med 2010;362:1804-13. Epub May 14, 2010. 2. Schwaber MJ, Carmeli Y. Carbapenem-resistant Enterobacteriaceae: a potential threat. JAMA 2008;300:2911-3. Epub December 26, 2008. 3. Patel G, Huprikar S, Factor SH, Jenkins SG, Calfee DP. Outcomes of carbapenemresistant Klebsiella pneumoniae infection and the impact of antimicrobial and
10.
11.
adjunctive therapies. Infect Control Hosp Epidemiol 2008;29:1099-106. Epub November 1, 2008. Paul M, Shani V, Muchtar E, Kariv G, Robenshtok E, Leibovici L. Systematic review and meta-analysis of the efficacy of appropriate empiric antibiotic therapy for sepsis. Antimicrob Agents Chemother 2010;54:4851-63. Epub August 25, 2010. Ben-Ami R, Rodriguez-Bano J, Arslan H, Pitout JD, Quentin C, Calbo ES, et al. A multinational survey of risk factors for infection with extended-spectrum b-lactamase-producing enterobacteriaceae in nonhospitalized patients. Clin Infect Dis 2009;49:682-90. Epub July 23, 2009. Gasink LB, Edelstein PH, Lautenbach E, Synnestvedt M, Fishman NO. Risk factors and clinical impact of Klebsiella pneumoniae carbapenemase-producing K pneumoniae. Infect Control Hosp Epidemiol 2009;30:1180-5. Epub October 29, 2009. Schwaber MJ, Klarfeld-Lidji S, Navon-Venezia S, Schwartz D, Leavitt A, Carmeli Y. Predictors of carbapenem-resistant Klebsiella pneumoniae acquisition among hospitalized adults and effect of acquisition on mortality. Antimicrob Agents Chemother 2008;52:1028-33. Epub December 19, 2007. Dellinger RP, Levy MM, Carlet JM, Bion J, Parker MM, Jaeschke R, et al. Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock: 2008. Crit Care Med 2008;36:296-327. Epub December 26, 2007. CLSI. Performance standards for antimicrobial susceptibility testing. Nineteenth informational supplement. Approved standard M100eS19. Wayne [PA]: Clinical and Laboratory Standards Institute; 2009. Hartzell JD, Neff R, Ake J, Howard R, Olson S, Paolino K, et al. Nephrotoxicity associated with intravenous colistin (colistimethate sodium) treatment at a tertiary care medical center. Clin Infect Dis 2009;48:1724-8. Epub May 15, 2009. Marchaim D, Chopra T, Pogue JM, Perez F, Hujer AM, Rudin S, et al. Outbreak of colistin-resistant, carbapenem-resistant Klebsiella pneumoniae in metropolitan Detroit, Michigan. Antimicrob Agents Chemother 2011;55:593-9. Epub December 1, 2010.