Traditional Antibiograms Research Articles

Antimicrobial stewardship and antibiograms: importance of moving beyond traditional antibiograms.

The rapid evolution of resistance, particularly among Gram-negative bacteria, requires appropriate identification of patients at risk followed by administration of appropriate empiric antibiotic therapy. A primary tenet of antimicrobial stewardship programs (ASPs) is the establishment of empiric antibiotic recommendations for commonly encountered infections. An important tool in providing empiric antibiotic therapy recommendations is the use of an antibiogram. While the majority of institutions use a traditional antibiogram, ASPs have an opportunity to enhance antibiogram data. The authors provide the rationale for why ASPs should implement alternative antibiograms, and the importance of incorporating an antibiogram into clinical decision support systems with the goal of providing effective empiric antibiotic therapy.

137. Evaluating a Novel Antibiogram Format for use in Wisconsin Nursing Homes

BackgroundNursing homes (NHs) increasingly use antibiograms to track antibiotic-related outcomes and guide antibiotic choice. Creation of a facility-specific antibiogram is hampered by low number of cultures collected in NHs. A weighted-incidence syndromic combination antibiogram (WISCA) is an alternative approach that may provide more stable estimates of antibiotic activity. In this study, we compare traditional antibiograms and WISCAs in a sample of Wisconsin NHs.MethodsWe created urine-specific antibiograms using traditional and WISCA approaches at facility and regional levels using culture data collected in study NHs from 01/01/2018 – 12/31/2018. Susceptibility results were standardized across laboratories using CLSI breakpoints. Traditional antibiograms were deemed reliable when ≥ 20 isolates were recovered for at least one species and species exceeding this threshold comprised 75% of all isolates. WISCAs were deemed reliable if ≥ 20 urinary isolates were recovered. Bootstrapped regional mean susceptibilities and confidence intervals for traditional antibiograms and WISCAs were calculated. Susceptibilities calculated at the facility-level were compared to regional estimates. Facility-level susceptibility estimates were deemed concordant if within 1 SD, moderately discordant if between 1 and 2 SDs, and severely discordant if greater than 2 SDs of the regional estimate.Results462 urine isolates were obtained from 23 NHs in 2 regions. None of the facility-specific traditional antibiograms met reliability criteria. 10 of 23 facility-specific WISCAs were reliable and increased to 19 of 23 when 2-years of microbiology data were utilized (table). Severe discordance between facility-specific and regional estimates was identified with 62/107 NH species-antibiotic means and 98/119 NH urine isolate-antibiotic means falling outside of 2 SD of corresponding bootstrap regional susceptibility means (figure).Table. Reliability analysis of facility-specific urinary WISCAs and traditional antibiograms. 2-year projection was created using the assumption of similar culture results over 2-years. Figure. Proportion of concordant, moderately discordant, and severely discordant NH mean susceptibilities in comparison to bootstrap regional mean susceptibilities for traditional antibiograms and WISCAs. NH mean susceptibilities from 5 isolates of more were included. ConclusionWISCAs are more reliable than traditional antibiograms for estimating antibiotic susceptibilities using facility-specific data. The high degree of discordance observed between facility-specific and regional antibiograms raises concerns about pooling culture data from multiple facilities.Disclosures All Authors: No reported disclosures

103. Empiric Antibiotic Susceptibility Using a Traditional vs. Syndromic Antibiogram-Implications for Antimicrobial Stewardship Programs

BackgroundA primary tenet of antimicrobial stewardship programs (ASPs) is to establish empiric antibiotic treatment recommendations. While traditional antibiograms are useful, intrinsic variability in susceptibility exists when stratifying by source and/or location. In contrast, a syndromic antibiogram displays the likelihood of adequate coverage for a specific infection syndrome, considering the weighted incidence of pathogens causing that syndrome. The aim of the study was to compare antibiotic susceptibilities using a traditional versus syndromic antibiogram.MethodsBetween 2016–2019, 20 US institutions per year submitted up to 250 consecutive targeted gram-negative pathogens from hospitalized patients as part of the Study for Monitoring Antimicrobial Resistance Trends (SMART). MICs were determined by broth microdilution and interpreted using 2020 CLSI breakpoints, except for imipenem/relebactam (I/R) for which FDA breakpoints were used. The traditional antibiogram included the 3 most common Gram-negative pathogens from all sources and represented critical organisms considered for empiric antibiotic coverage; the syndromic antibiogram included the 3 most commonly isolated Gram-negative pathogens from a respiratory source based on patient location.Results17,561 Gram-negative isolates, including 6,654 lower respiratory isolates were evaluated. The top 3 most common Gram-negative organisms included: E. coli (n=6095, 44%), Klebsiella spp. (n=4097, 30%), P. aeruginosa (n=3649, 26%). Cumulative susceptibilities were comparable using a traditional vs. syndromic antibiogram (Figure 1); however, cefepime (FEP), piperacillin/tazobactam (TZP), and meropenem (MEM) susceptibilities were 5 – 8% lower when stratified by patient location (Figure 2) and ≥10% for P. aeruginosa (Figure 3). Ceftolozane/tazobactam (C/T) and I/R demonstrated ≥90% susceptibility regardless of respiratory source or patient location.Figure 1. Cumulative susceptibility of E. coli, Klebsiella spp, and P. aeruginosa for traditional vs. syndromic antibiogram Figure 2. Syndromic antibiogram evaluating cumulative susceptibility of E. coli (n = 637), Klebsiella spp. (n = 1190) and P. aeruginosa (n = 1997) respiratory isolates stratified by patient location Figure 3. Syndromic antibiogram evaluating susceptibility of P. aeruginosa (n = 1997) respiratory isolates stratified by patient location ConclusionOur analysis demonstrated that susceptibilities were lower for first-line agents when stratified by ICU and P. aeruginosa. ASPs should consider syndromic antibiograms based on source and patient location to optimize empiric antibiotic therapy recommendations.DisclosuresKenneth Klinker, PharmD, Merck & Co, Inc (Employee) Karri A. Bauer, PharmD, Merck Research Laboratories (Employee) C. Andrew DeRyke, PharmD, Merck & Co., Inc. (Employee, Shareholder) Levita K. Hidayat, PharmD BCIDP, Merck & Co (Employee)

182. increasing Odds of Resistance for Subsequent Urinary e. Coli Isolates

BackgroundAnnual cumulative antibiograms are routinely used by clinicians to guide selection of empirical antibiotic therapies. CLSI guidelines recommend that these antibiograms to analyze data yearly, include only final, verified results, include bacterial species with > 30 isolates and to include only the first isolate for each species/patient instance per analysis period. Handling multiple isolates from individual patients in cumulative antibiograms is a controversial topic within the antimicrobial stewardship community. Current practice favors removing subsequent isolates, thereby discarding data reflecting impact of selective antibiotic pressure on resistance patterns in recurring urinary tract infection (UTI).In this study we analyzed a five-year data set of deidentified outpatient antibiotic results from a commercial laboratory to determine whether there were significant differences in resistance patterns between first and subsequent isolates from the same patient.MethodsThe 5-year antibiotic susceptibility data was restricted to urinary Escherichia coli (EC) isolates. Patient occurrence(s) of urinary EC were categorized by frequency: 1st occurrence, 2nd occurrence, 3rd occurrence, and 4th or greater occurrence. A logistic regression analysis using a binary outcome for resistance and independent variable of patient isolate occurrence was run for amoxicillin-clavulanate, ampicillin, ceftriaxone, ciprofloxacin, gentamicin, levofloxacin, nitrofurantoin, and trimethoprim-sulfa.ResultsFrom a logistic regression analysis, we estimate that for each occurrence in the data, an isolate’s odds of resistance were higher for every increase in a patient’s number of occurrences in the data for all antibiotics reported with p values < 0.0001.Table 1: Odds ratios (OR) of resistance for each subsequent urinary EC isolate occurrence over 5 years ConclusionOur findings suggest that individuals with higher numbers of urinary EC occurrences have more resistant EC than the first EC occurrence, with effects that vary by antibiotic class. Although traditional antibiograms include only the first occurrence of urinary EC from a single patient, this approach may underestimate levels of reservoir resistance in a community. Such an underestimation likely impacts efficacy of empiric therapeutic choice, healthcare outcomes, and cost.Disclosures All Authors: No reported disclosures

768. Use of a Machine-Learning-based Prediction Model to Guide Antibiotic De-escalation in the Treatment of Urinary Tract Infections

BackgroundA patient-specific antibiogram (PS-ABG) issues personalized predicted antibiotic susceptibility results by incorporating patient factors into a prediction model. Predictions, reported as percent likelihood of susceptibility, are available to providers in real-time. In this study, we evaluated the performance characteristics of a PS-ABG based on a machine-learning algorithm in predicting susceptibility of Enterobacteriaceae isolated on urine cultures.MethodsThis cross-sectional study included 2,517 urine cultures with Enterobacteriaceae collected from 2,211 unique patients over a 12-week period from January 1 through April 15, 2019 in a single health system. Receiver operating curves (ROC) were generated for commonly prescribed antibiotics to assess discrimination. Threshold values to determine when an antibiotic could be used were then determined based on ROC curves. Brier scores were generated for all antibiotics collectively and for individual antibiotics to evaluate the accuracy of the predictions compared with that of the usual practice (UP) of traditional antibiograms.ResultsThe ability of the PS-ABG to discriminate susceptible and nonsusceptible isolates varied by antibiotic [area under the curve (AUC) range: 0.71 - 0.95]. When all antibiotics were considered, AUC was 0.88 (95% C.I. 0.88 – 0.89). Brier score ranged from 0.0037 - 0.2087, representing between a 9 - 56% improvement compared with UP. For all antibiotics, the software had a 32% improvement over UP (median Brier score 0.0794 v. 0.1114, P < 0.0001). Overall, a susceptibility threshold of 95% was associated with a specificity of 96%. A threshold of 95% was associated with a ≥90% specificity in all agents except for cefepime (specificity 70%) and meropenem (specificity 73%). For cefepime and meropenem, specificity reached 90% at a threshold of 97%.ConclusionThe PS-ABG demonstrated excellent discriminatory power for all antibiotics tested and was more accurate than UP. A cutoff of 95% likelihood of susceptibility affords high specificity for most agents and may be a reasonable threshold for selecting an appropriate antibiotic. A higher susceptibility threshold yields similar specificity for cefepime and meropenem, but this finding is likely a result of the low number of resistant isolates. Disclosures All authors: No reported disclosures.

A decision support system for antibiotic prescription based on local cumulative antibiograms

BackgroundLocal cumulative antibiograms are useful tools with which to select appropriate empiric or directed therapies when treating infectious diseases at a hospital. However, data represented in traditional antibiograms are static, incomplete and not well adapted to decision-making. MethodsWe propose a decision support method for empiric antibiotic therapy based on the Number Needed to Fail (NNF) measure. NNF indicates the number of patients that would need to be treated with a specific antibiotic for one to be inadequately treated. We define two new measures, Accumulated Efficacy and Weighted Accumulated Efficacy in order to determine the efficacy of an antibiotic. We carried out two experiments: the first during which there was a suspicion of infection and the patient had empiric therapy, and the second by considering patients with confirmed infection and directed therapy. The study was performed with 15,799 cultures with 356,404 susceptibility tests carried out over a four-year period. ResultsThe most efficient empiric antibiotics are Linezolid and Vancomycin for blood samples and Imipenem and Meropenem for urine samples. In both experiments, the efficacies of recommended antibiotics are all significantly greater than the efficacies of the antibiotics actually administered (P < 0.001). The highest efficacy is obtained when considering 2 years of antibiogram data and 80% of the cumulated prevalence of microorganisms. ConclusionThis extensive study on real empiric therapies shows that the proposed method is a valuable alternative to traditional antibiograms as regards developing clinical decision support systems for antimicrobial stewardship.

Evaluating Patient-Specific Antibiograms

BackgroundGenerating antibiograms has been standard practice in many hospitals for decades, and many guidelines recommend updating the data on a yearly basis. While effective at summarizing a hospital’s susceptibility data across all patients, likelihoods of susceptibility are not the same for all patients. Traditional antibiograms do not account for the numerous patient-specific factors (age, length of stay, diagnoses, previous antibiotic exposure and susceptibility results, etc.) that are known to influence a patient’s risk of having a resistant organism. We have built models that use patient-specific information to generate patient-specific antibiograms. Three methods for evaluating a model’s performance are presented.MethodsCalculating Brier scores is the commonly used method to evaluate the performance of predictions that give the percentage likelihood of a binary event. We used Brier scores and two new methods we created (dispersion scores and susceptibility histograms) to evaluate patient-specific antibiograms we built. As an example of the methods, we present data from Mar-Jul 2016 on 3012 E. coli isolates and their susceptibility to levofloxacin.ResultsIn the standard institutional antibiogram for the time period 75% of E. coli isolates were susceptible to levofloxacin. Our patient-specific antibiogram had a dispersion score of 73 (100 representing perfect dispersion, the standard antibiogram has a dispersion score of 0). In the susceptibility histogram the patient-specific antibiogram showed a predicted susceptibility of 90% or greater for 1716 (57%) of the 3012 isolates, and the actual susceptibility for that group was 96%. It also showed a predicted susceptibility less than 10% for 438 (15%) of the 3012 isolates, and the actual susceptibility for that group was 1%. Brier scores were 61% better for the patient-specific antibiogram (Brier = 0.24) than for the standard antibiogram (Brier = 0.62).ConclusionBy these methods patient-specific antibiograms are better than standard antibiograms at providing numerical predictions of the likely susceptibility of E. coli to levofloxacin. The methods can be used to guide and evaluate improvement to the models that generate patient-specific antibiograms.Disclosures S. Overly, Teqqa, LLC: Employee, Salary. S. Hayes, Teqqa, LLC: Employee, Salary. J. Mehta, Teqqa, LLC: Employee, Salary. D. Peterson, Teqqa, LLC: Employee, Salary

Development of a urinary-specific antibiogram for gram-negative isolates: Impact of patient risk factors on susceptibility

Traditional antibiograms guide clinicians in selecting appropriate empiric antimicrobials, but they lack data on syndrome/disease-specific susceptibility, isolate location, polymicrobial infections, and patient risk factors. The aim of this study was to develop a urinary-specific antibiogram and to evaluate the impact of risk factors on antimicrobial susceptibility. This retrospective descriptive study used culture and susceptibility data from January 1 to December 31, 2012. A urinary antibiogram specific for Escherichia coli (EC), Proteus mirabilis (PM), Klebsiella pneumoniae (KP), and Pseudomonas aeruginosa (PA) was developed. Urinary and standard antibiogram susceptibilities were compared. Urinary isolates were then stratified by risk factors-residence before admission, age, systemic antimicrobial use for ≤30 days, hospitalization for ≤30 days, and hospital unit-to determine the impact on antimicrobial susceptibility. There were 2,284 urinary isolate encounters. Overall antimicrobial susceptibility was increased, and the prevalence of extended-spectrum β-lactamase-producing isolates was significantly greater (KP, 14% vs 7% [P = .001]; EC, 13% vs 9% [P < .001]; PM, 18% vs 10% [P = .004]) in the urinary antibiogram vs the standard antibiogram. Health care facility residence had the greatest impact on susceptibility for all urinary isolates, especially on fluoroquinolone susceptibility for EC and PM. Using a syndromic antibiogram and incorporating patient risk factors into susceptibility data may be more useful in guiding clinicians in selecting more appropriate empiric therapy.

Weighted-incidence syndromic combination antibiograms to guide empiric treatment of critical care infections: a retrospective cohort study.

IntroductionEmpiric antimicrobial selection for critical care infections must balance the need for timely adequate coverage with the resistance pressure exerted by broadspectrum agents. We estimated the potential of weighted incidence syndromic combination antibiograms (WISCAs) to improve time to adequate coverage for critical care infections. In contrast to traditional antibiograms, WISCAs display the likelihood of coverage for a specific infectious syndrome (rather than individual pathogens), and also take into account the potential for poly-microbial infections and the use of multi-drug regimens.MethodsCases of ventilator-associated pneumonia (VAP) and catheter-related bloodstream infection (CRBSI) were identified over three years using stringent surveillance criteria. Based on the susceptibility profile of the culprit pathogens, we calculated the WISCA percentages of infections that would have been adequately covered by common antimicrobial(s). We then computed the excess percentage coverage offered by WISCA regimens compared to the actual antimicrobials administered to patients by 12 h, 24 h, and 48 h from culture collection.ResultsAmong 163 patients with critical care infection, standard practice only resulted in adequate coverage of 35% of patients by 12 h, 52% by 24 h, and 75% by 48 h. No WISCA mono-therapy regimen offered greater than 85% adequate overall coverage for VAP and CRBSI. A wide range of dual therapy regimens would have conferred greater than 90% adequate coverage, with excess coverage estimated to be as high as +56%, +42% and +18% at 12 h, 24 h and 48 h, respectively. We did not detect a decrease in mortality associated with early adequate treatment, and so could not estimate potential downstream benefits.ConclusionsWISCA-derived empiric antimicrobial regimens can be calculated for patients with intensive care unit (ICU)-acquired infections, and have the potential to reduce time to adequate treatment. Prospective research must confirm whether implementation of WISCA prescribing aids facilitate timely adequate treatment and improved ICU outcomes.

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Introduction: Pseudomonas aeurginosa (PsA) infections in the intensive care unit (ICU) are becoming more difficult to treat due to increasing resistance. Guidelines recommend that ICU providers examine their own resistance patterns to guide empirical antibiotics. Our empirical therapy for presumed PsA infections is piperacillin/tazobactam (PT) plus a fluoroquinolone (FQ). Unfortunately, traditional antibiograms cannot identify optimal combination therapy; whereas a combination antibiogram shows how frequently an organism is resistant to the first antibiotic but susceptible to the second antibiotic and identifies which combination of antibiotics may be most effective. Hypothesis: Developing a combination antibiogram for PsA will allow identification of the most appropriate empirical antibiotic therapy. Methods: All PsA isolates from respiratory and blood cultures in the surgical ICU between 01/08-12/10 were retrospectively reviewed. Only first isolates were included and susceptibility to each antibiotic was recorded according to Clinical Laboratory Standards Institute criteria and pharmacokinetic-pharmacodynamic derived minimum inhibitory concentration breakpoints. In a matrix fashion, the percentage of isolates susceptible to at least one of two combined agents was listed. Results: Fifty-two PsA isolates were included. 65.3% were susceptible to PT and 78.8% to ceftazidime. Tobramycin improved the antimicrobial susceptibility of PT (100%, p=0.001), ceftazidime (100%, p=0.001), cefepime (75 vs 100%, p=0.001), imipenem (44 vs 98%, p=0.001), and meropenem (53 vs 100%, p=0.001). Gentamicin and amikacin only increased the coverage of imipenem to 65% (p=0.048) and 84% (p=0.001), respectively, but they did not significantly improve other beta-lactam coverage. Ciprofloxacin failed to improve upon any of the beta-lactam susceptibilities. Conclusions: Adding tobramycin as a second antibiotic would likely increase the number of patients receiving optimal empirical therapy for PsA. The use of a combination antibiogram at our institution identified ceftazidime or cefepime plus tobramycin as the most optimal empirical therapy, and that FQ use should be abandoned for empirical treatment of PsA.

Constructing Unit-Specific Empiric Treatment Guidelines for Catheter-Related and Primary Bacteremia by Determining the Likelihood of Inadequate Therapy

This study aimed to determine the feasibility of using likelihood of inadequate therapy (LIT), a parameter calculated by using pathogen frequency and in vitro susceptibility for determination of appropriate empiric antibiotic therapy for primary bloodstream infections. Our study demonstrates that LIT may reveal differences in traditional antibiograms.

Antibiogram-Derived Radial Decision Trees: An Innovative Approach to Susceptibility Data Display

Hospital antibiograms (ABGMs) are often presented in the form of large 2-factor (single organism vs. single antimicrobial) tables. Presenting susceptibility data in this fashion, although of value, does have limitations relative to drug resistant subpopulations. As the crisis of antimicrobial drug-resistance continues to escalate globally, clinicians need (1) to have access to susceptibility data that, for isolates resistant to first-line drugs, indicates susceptibility to second line drugs and (2) to understand the probabilities of encountering such organisms in a particular institution. This article describes a strategy used to transform data in a hospital ABGM into a probability-based radial decision tree (RDT) that can be used as a guide to empiric antimicrobial therapy. Presenting ABGM data in the form of a radial decision tree versus a table makes it easier to visually organize complex data and to demonstrate different levels of therapeutic decision-making. The RDT model discussed here may also serve as a more effective tool to understand the prevalence of different resistant subpopulations in a given institution compared to the traditional ABGM.