We developed a bedside instrument to predict carbapenem resistance in complicated urinary tract infections. A model assigning weighted points for admission from an extended care facility (1), history of weight loss (1), early mechanical ventilation (1), age \u3c50 years (2), male gender (3), catheter-associated urinary tract infection (4), prior antibiotics treatment (4), and prior carbapenem-resistant infection (8) exhibited good discrimination (C statistic, 0.721)

Fan, Weihong

Nathanson, Brian H.

Shorr, Andrew F.

Sulham, Kate

Zilberberg, Marya D.

English

ScholarWorks@UMass Amherst

University of Massachusetts AmherstScholarWorks@UMass AmherstBiostatistics and Epidemiology Faculty PublicationsSeries Biostatistics and Epidemiology2018Development and validation of a bedsideinstrument to predict carbapenem resistanceamong gram-negative pathogens in complicatedurinary tract infectionsMarya D. ZilberbergEviMed Research Group/ Universtiy of Massachusetts AmherstBrian H. NathansonOptiStatimKate SulhamThe Medicines Company/ Melinta TherapeuticsWeihong FanThe Medicines CompanyAndrew F. ShorrWashington Hospital CenterFollow this and additional works at: https://scholarworks.umass.edu/bioepi_faculty_pubsThis Article is brought to you for free and open access by the Biostatistics and Epidemiology at ScholarWorks@UMass Amherst. It has been acceptedfor inclusion in Biostatistics and Epidemiology Faculty Publications Series by an authorized administrator of ScholarWorks@UMass Amherst. Formore information, please contact scholarworks@library.umass.edu.Recommended CitationZilberberg, Marya D.; Nathanson, Brian H.; Sulham, Kate; Fan, Weihong; and Shorr, Andrew F., "Development and validation of abedside instrument to predict carbapenem resistance among gram-negative pathogens in complicated urinary tract infections" (2018).Biostatistics and Epidemiology Faculty Publications Series.39 1112-1114 https://doi.org/10.1017/ice.2018.166Infection Control & Hospital Epidemiology (2018), 39, 1112–1114doi:10.1017/ice.2018.166Concise CommunicationDevelopment and validation of a bedside instrument to predictcarbapenem resistance among gram-negative pathogens incomplicated urinary tract infectionsMarya D. Zilberberg MD, MPH1,2, Brian H. Nathanson PhD3, Kate Sulham MPH4,5, Weihong Fan MS4 andAndrew F. Shorr MD, MPH61EviMed Research Group, Goshen, Massachusetts, 2Universtiy of Massachusetts, Amherst, Massachusetts, 3OptiStatim, Longmeadow, Massachusetts,4The Medicines Company, Parsippany, New Jersey, 5Melinta Therapeutics, Lincolnshire, Illinois and 6Washington Hospital Center, Washington, DCAbstractWe developed a bedside instrument to predict carbapenem resistance in complicated urinary tract infections. A model assigning weightedpoints for admission from an extended care facility (1), history of weight loss (1), early mechanical ventilation (1), age <50 years (2), malegender (3), catheter-associated urinary tract infection (4), prior antibiotics treatment (4), and prior carbapenem-resistant infection (8)exhibited good discrimination (C statistic, 0.721).(Received 26 March 2018; accepted 8 June 2018; electronically published July 31, 2018)Carbapenem resistance has arisen with alarming speed.1,2 Currently,>3% of Enterobacteriaceae are carbapenem nonsusceptible, andrates among Pseudomonas aeruginosa and Acinetobacter baumanniiare substantially higher, making it difficult for clinicians to selectinitially appropriate empiric coverage for patients presenting withserious infections.3,4 Although rapid diagnostic testing promises toimprove early antimicrobial therapy targeting, it presents certainlimitations and cannot be utilized without some assessment ofpretest probability for resistance.5 A predictive tool based on clinicalfactors for risk stratification is necessary either as an adjunct to or asubstitute for rapid diagnostic testing.MethodsWe developed a bedside score to predict the risk for carbapenemresistance within a multicenter retrospective cohort of hospitalizedpatients with complicated urinary tract infection (cUTI) diagnosisand a culture positive for P. aeruginosa, A. baumannii, Steno-trophomonas maltophilia (assumed always to be carbapenemresistant), or Enterobacteriaceae (see Supplemental Material).Because this study used fully deidentified retrospective data, it wasexempt from institutional review board review.Adult patients with a cUTI fitting our enrollment criteria wereincluded (see Supplemental Material for enrollment criteria andidentification algorithms). The data for the study were extractedfrom the Premier Research database, an electronic laboratory,pharmacy, and billing data repository, for 2009–2016 (throughthe third quarter of 2006), which contains ~15% of all hospita-lizations nationwide. (A detailed description of the database isavailable in Zilberberg et al.3,4) We used data from 178 USinstitutions submitting microbiology data into the database.Carbapenem resistance was defined as a cultured organismdesignated as intermediate or resistant to imipenem, meropenem,ertapenem, or doripenem. A carbapenem-susceptible organismwas an organism susceptible to either any carbapenem tested or toany third-generation cephalosporin (see Supplemental Material).First detection of a carbapenem-resistant organism (or acarbapenem-susceptible organism of interest in the absence ofcarbapenem resistance) served as the index culture. Empiricantibiotic treatment was considered appropriate when coveragewithin 2 days of the culture being obtained included thecorresponding organism. All other regimens were deemed inap-propriate empiric treatment. A cUTI was classified as communityonset if it was present on admission or if an index culture wasobtained within the first 2 hospital days.Statistical analysesWe compared the carbapenem-resistant group to the carbapenem-susceptible group with respect to demographics, comorbidities,hospital characteristics and processes, and outcomes. To develop alogistic regression to predict the presence of carbapenem resistance,we used a split-cohort method, with 60% allocated to the trainingcohort and 40% to the validation cohort. We then pared the modelto 10 predictors or fewer for the ease of the end user. Terms wereCite this article: Zilberberg MD, et al. (2018). Development and validation of abedside instrument to predict carbapenem resistance among gram-negative pathogens incomplicated urinary tract infections. Infection Control & Hospital Epidemiology 2018, 39,1112–1114. doi: 10.1017/ice.2018.166Author for correspondence: Marya Zilberberg, MD, MPH, PO Box 303, Goshen, MA01032. E-mail: evimedgroup@gmail.com© The Society for Healthcare Epidemiology of America 2018 . All rights reserved. This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-ncsa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium,provided the same Creative Commons licene is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained forcommercial re-use.culled based on the factor’s prevalence and its contribution to themodel’s predictive ability in the development cohort using a step-wise bootstrapping algorithm and Bayesian information criterion ina series of nested models.6 We assessed the model’s discriminationwith the C statistic and calibration visually in a plot of observedversus expected risk deciles and with the Hosmer-Lemeshow sta-tistic. We then developed a score considering the weight of eachfactor’s regression coefficient to predict the presence of acarbapenem-resistant organism.ResultsAmong 25,285 patients with cUTI, 23,469 patients (92.8%) had acommunity-onset UTI and 1,357 (5.4%) had a UTI caused by acarbapenem-resistant organism. Baseline characteristics, micro-biology, and hospital events can be found in the SupplementalMaterial Tables 5–7.Unadjusted mortality (3.7% vs 2.3%; P< .001) and 30-dayreadmission (24.3% vs 18.0%; P< .001) were higher in the settingof carbapenem resistance than carbapenem susceptibility. Unad-justed median hospital costs were also greater among patientswith carbapenem-resistant infections those with carbapenem-susceptible infections: $10,356 (interquartile range [IQR],$6,509–$18,674 versus $8,613 (IQR, $5,241–$15,316), respectively(P< .001). Postinfection-onset hospital lengths of stay were alsolonger among patients with carbapenem-resistant infections thanthose with carbapenem-susceptible organisms: 5 days (IQR,3–9 days) versus 4 days (IQR, 2–7 days), respectively (P< .001).In a model designed to predict the likelihood of carbapenemresistance in this population, we assigned weighted points pro-portional to the regression coefficients of the following factors:admission from an extended-care facility (1), history of weightloss (1), early mechanical ventilation (1), age <50 (2), male gender(3), catheter-associated UTI (4), prior antibiotics treatment (4),and prior carbapenem-resistant infection (8). The model exhib-ited good discrimination in both the training (C statistic, 0.746)and validation (C statistic, 0.721) sets. It performed better amonghospitals with lower prevalence of carbapenem resistance, asevidenced by a C-statistic drop with an increase in carbapenemresistance prevalence in the validation set: tertile 1, 0.752 (pre-valence of carbapenem resistance, 2.1%); tertile 2, 0.725 (pre-valence of carbapenem resistance, 4.7%); and tertile 3, 0.703(prevalence of carbapenem resistance, 9.2%).The distribution of patients within specific score ranges withthe corresponding proportions of carbapenem resistance is shownin Fig. 1. While most of the cohort (86.5%) fell under 10 points,nearly 15% of those patients with the score of 10 points or moreharbored a carbapenem-resistant organism. Conversely, patientswhose score was below 3, which accounted for 29.9% of all thepatients in the cohort, had a ~1% risk of a cUTI caused by acarbapenem-resistant organism.DiscussionIn a cohort of hospitalized patients with a cUTI (>5% carbape-nem resistant), we developed a bedside predictive score that, byvirtue of its high negative predictive value in the low score ranges,may be useful in helping clinicians rule out the need for empiriccoverage for a carbapenem-resistant organism in a cUTI.Although we did not limit our cohort to community-onsetinfections, the vast majority of the admissions (>92%) had cUTIpresent on hospital day 1. The small fraction of cUTIs thatoccurred as a nosocomial complication reflects well on hospitalinfection control interventions aimed at preventing such com-plications but also highlights the importance of considering therisk of a carbapenem-resistant organism even among patientsfrom a community setting. Other investigators have noted thisphenomenon in multiple pathogen classes, and we confirm itsimportance.7–10Previous investigations have demonstrated that the presence ofresistance alone does not determine the outcome.3,4 Rather,whether the patient receives appropriate initial antibiotic regimenhas a greater effect. Our score, though aiming to aid with suchrisk stratification, does not have perfect precision. However, whencombined with knowledge of local resistance patterns and hos-pital antibiograms, it should facilitate efforts to ensure thatpatients with cUTIs receive appropriate empiric treatment.Moreover, our risk score helps to reinforce efforts toward anti-microbial stewardship by identifying when coverage forcarbapenem-resistant pathogens in this syndrome is clearly notappropriate. Therefore, if applied correctly, this tool can helplimit indiscriminate use of certain broad-spectrum antimicrobials.Our study has a number of strengths and limitations. As a largemulticenter cohort it is representative of US institutions, and thushas broad generalizability. Although our findings are susceptible toselection bias, we mitigated it by setting a priori enrollment criteriaand definitions. Though some misclassification is possible, our cUTIalgorithm was designed to maximize the specificity of the diagnosis,and carbapenem resistance conformed to a standard definition.In summary, the bulk of cUTI admissions are communityonset, and carbapenem-resistant pathogens account for >5% ofall gram-negative organisms at risk for developing carbapenemresistance. Until rapid diagnostics are ready for widespread use,we may need to settle for imperfect but helpful probabilisticmodels like ours to help identify, if not patients at high risk forresistance, those whose low probability of a resistant organismcombined with other aspects of the clinical picture makesnarrower-spectrum agents an adequate first choice for treatment.Supplementary material. To view supplementary material for this article,please visit https://doi.org/10.1017/ice.2018.166Fig. 1. Prediction score for carbapenem resistance in cUTI. Note. cUTI, complicatedurinary tract infection; CR, carbapenem resistant.Infection Control & Hospital Epidemiology 1113Acknowledgments. Although Ms Sulham and Ms Fan are employees of thesponsors and participated in the study as coinvestigators, the larger sponsorshad no role in study design, data analysis or interpretation or publicationdecisions. The data from this study have been presented as an oral pre-sentation at the 28th European Congress of Clinical Microbiology andInfectious Diseases (ECCMID) 2018 meeting.Financial support. This study was funded by The Medicines Company, Par-sippany, New Jersey, and by Melinta Therapeutics, New Haven, Connecticut.Conflicts of interest. Dr Zilberberg is a consultant to The MedicinesCompany and Melinta Therapeutics. Her employer, EviMed Research Group,has received research grant support from The Medicines Company andMelinta Therapeutics. Dr Nathanson’s employer, OptiStatim, has receivedsupport from EviMed Research Group. Ms Sulham was an employee of andstockholder in The Medicines Company and is currently an employee ofMelinta Therapeutics. Ms Fan is an employee of and stockholder in TheMedicines Company. Dr Shorr is a consultant to and has received researchgrant support from The Medicines Company and Melinta Therapeutics. DrsZilberberg and Shorr have received grant support and/or have served asconsultants to Merck, Tetraphase, Pfizer, Astellas, Shionogi, and Theravance.References1. Centers for Disease Control and Prevention (CDC). Vital signs: carbapenem-resistant enterobacteriaceae. Morb Mortal Wkly Rep 2013;62:165–170.2. Braykov NP, Eber MR, Klein EY, Morgan DJ, Laxminarayan R. Trends inresistance to carbapenems and third-generation cephalosporins amongclinical isolates of Klebsiella pneumoniae in the United States, 1999–2010.Infect Control Hosp Epidemiol 2013;34:259–268.3. Zilberberg MD, Nathanson BH, Sulham K, Fan W, Shorr AF.Multidrug resistance, inappropriate empiric therapy, and hospitalmortality in Acinetobacter baumannii pneumonia and sepsis. Crit Care2016;20:221.4. Zilberberg MD, Nathanson BH, Sulham K, Fan W, Shorr AF.Carbapenem resistance, inappropriate empiric treatment and outcomesamong patients hospitalized with Enterobacteriaceae urinary tractinfection, pneumonia and sepsis. BMC Infect Dis 2017;17:279.5. Zilberberg MD, Shorr AF. Impact of prior probabilities of MRSA as aninfectious agent on the accuracy of the emerging molecular diagnostic tests:a model simulation. BMJ Open 2012;18:2(6). doi: 10.1136/bmjopen-2012-001804.6. Austin PC, Tu JV. Bootstrap methods for developing predictive models.Am Statistician 2004;58:131–137.7. Guh AY, Bulens SN, Mu Y, et al. Epidemiology of carbapenem-resistantEnterobacteriaceae in 7 US communities, 2012–2013. JAMA 2015;314:1479–1487.8. Tang HJ, Hsieh CF, Chang PC, et al. Clinical significance of community-and healthcare-acquired carbapenem-resistant Enterobacteriaceae isolates.PLoS One 2016;11(3):e0151897.9. Doi Y, Park YS, Rivera JI, et al. Community-associated extended-spectrum β-lactamase-producing Escherichia coli infection in the UnitedStates. Clin Infect Dis 2013;56:641–648.10. Pitout JD, Nordmann P, Laupland KB, Poirel L. Emergence ofEnterobacteriaceae producing extended-spectrum β-lactamases (ESBLs)in the community. J Antimicrob Chemother 2005;56:52–59.1114 Marya D. Zilberberg et al.

Development and validation of a bedside instrument to predict carbapenem resistance among gram-negative pathogens in complicated urinary tract infections

https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1009&amp;context=bioepi_faculty_pubs

Development and validation of a bedside instrument to predict carbapenem resistance among gram-negative pathogens in complicated urinary tract infections

Abstract

Similar works

Full text

Available Versions

ScholarWorks@UMass Amherst