antimicrobial therapy – Lablogatory

Breakpoint Breakdown II: Breakpoints at the Bedside

A critical task for clinical microbiologists is interpreting antimicrobial susceptibility testing (AST) results for microorganisms recovered from patient specimens. But what happens to that information after it is passed along to the clinical team, and how does it influence patient care at the bedside? In our previous blog, we discussed details concerning how breakpoints are established and identified them as an indispensable component of appropriate and effective antimicrobial prescribing. Here we will discuss the more practical application of breakpoints to guide patient care. To aid in the discussion, I’ve once again recruited two infectious diseases (ID) pharmacists from the UT Southwestern Medical Center to provide their valuable prospective on the use of AST results both at the bedside and to optimize antimicrobial stewardship initiatives.

Applying Breakpoints in Clinical Care

In the most simplistic terms, the reporting of isolate’s categorical susceptibility (susceptible, intermediate, and resistant) provides guidance concerning which antimicrobials will likely be effective to treat an infection.¹ Many microbiology laboratories, however, report additional AST information including minimal inhibitory concentrations (MICs) and phenotypic information concerning resistance mechanisms (e.g. production of Extended Spectrum Beta-Lactamases (ESBLs) or inducible-clindamycin resistance)²_. This more detailed information is often utilized by ID specialists to help guide and optimize beside management.

Unfortunately, several misapplications of AST data can be encountered in clinical care (Image 1). One common error is simply selecting the antimicrobial with the lowest MIC for treatment. This runs contrary to the idea that each antimicrobial has an individualized breakpoint for a given pathogen or pathogen group. Therefore, a low MIC for antimicrobial “A” may be at or near the breakpoint, but higher MIC for antimicrobial “B” may be a dilution or more lower than the breakpoint. Another common misconception is that if the isolate is reported susceptible to a given antimicrobial, that antimicrobial is the optimal choice for the patient, and will work 100% of the time! Very little in medicine is 100%, and this holds true for antimicrobials. Even if the optimal agent is selected based on AST data, there is no guarantee it will be effective in the patient. Many factors influence the effectiveness of antimicrobials including patient characteristics (e.g., immune system, kidney function), drug characteristics (i.e., pharmacokinetics [PK]/pharmacodynamics[PD]), and bug characteristics (e.g., underlying resistance present despite reporting as susceptible or potential for inducible resistance).² This illustrates why clinicians may prefer to have all available information to further aid in optimization of antimicrobial therapy beyond the information provided by categorical reporting.

But why is an MIC needed – isn’t just knowing something is susceptible or resistant enough? In particular, more granular information such as the actual MIC for a given bug-drug combination may aid in more intricate decisions surrounding the choice of agent and dose. One argument for routine reporting of MIC values is the ability to better discern how near the breakpoint the particular MIC is for a given drug. The standard MIC reporting error is plus or minus one doubling dilution. When this is factored in, it may provide additional context as to how near or over the isolates phenotype is to assigned breakpoint.² Clinicians may further couple this with their understanding of PK/PD to determine the optimal agent based on antimicrobial properties and microbial characteristics.

A counter argument is that the MIC values are prone to variation depending on testing modality and may not represent truly what occurs in actual humans (see Mouton JW et al. for more detailed discussion).³ As mentioned above, some argue that MIC reporting leads to misinterpretations of AST by a provider’s tendency to pick the lowest number, and thus prefer categorical reporting for simplification. Provider education and selective or cascade reporting are two strategies that may help clinicians select the optimal agent, but also have inherent limitations. All this taken into consideration, we feel the benefit of antimicrobial optimization supports reporting the MIC.

Applying Breakpoints at the Bedside

Breakpoints and MIC data are utilized at the bedside to avoid utilization of suboptimal agents due to issues with the drug and bug. For example, underlying resistance patterns may not be overtly apparent to clinicians. Depending on an institution’s reporting criteria, an E. coli isolate may be reported as susceptible to piperacillin/tazobactam despite being identified as an ESBL producer. In this instance, piperacillin/tazobactam may be suboptimal for certain infections based on available outcomes data, with some supposition that reported MIC values may be responsible for improper drug selection and treatment failures.⁴ Therefore, clinicians may favor alternative agents for infections despite documented susceptibility. This example also illustrates that certain resistance patterns (e.g., ceftriaxone resistance as surrogate for possible ESBL production) may help alert clinicians to underlying resistance, steering them clear of potential suboptimal agents reported as susceptible.

ID pharmacists often utilize MIC values to determine the optimal agent and dose for a given patient based on a working knowledge of breakpoint relationships and PK/PD. This may be taken a step further in the setting of an infection with a multidrug resistant organism which exhibit MICs in the intermediate or susceptible dose-dependent range. For certain drug-bug combinations with elevated MICs, it may be possible for the ID pharmacist to devise an optimized and personalized therapeutic regimen that will likely overcome the elevated MIC, either as monotherapy or utilizing potential synergistic combinations of different antibiotics.

The application of dose-dependent breakpoints, as seen with daptomycin for Enterococcus faecium, help illustrate the importance of understanding and applying dosing concepts in the context of established clinical breakpoints.¹ This allows the clinician to not only optimize dosing, but also understand that an MIC at or near the breakpoint may warrant combination therapy in the setting of a serious infection. A lack of understanding of the relationship between breakpoints and dosing could potentially lead to an inadvertent assumption that lower FDA-approved doses would be reasonable despite the breakpoint being based on higher dosing strategies. These are just a small sampling of the clinical applications utilized on a daily basis to optimize a particular patient’s antimicrobial therapy.

A more global application of breakpoints occurs within antimicrobial stewardship programs. Antimicrobial stewardship focuses on the appropriate and optimal use of antimicrobials. To aid in this goal, AST reporting is key to developing clinical guidance on treating a variety of infections. Most notably, the optimization of empiric antimicrobial choices is aided by local or institutional susceptibility patterns. The cumulative antibiogram is pivotal to establishing optimal empiric antimicrobial choices across the spectrum of infectious diseases.⁵ Importantly, breakpoints are revised when new or additional clinical information becomes available, further illustrating the need to understand how a given institution implements and applies them. There is always the potential that from one year to the next susceptibilities may drop substantially due to implementation of new breakpoints, not necessarily an increased incidence of pathogens with a certain resistance pattern.⁶In addition, the ability to adopt CLSI breakpoints often lags well beyond the release of the updated breakpoints, necessitating clinicians to be cognizant of changes and carefully assess categorical reporting as it may be discordant with the most up-to-date breakpoints.^1,6This topic will be the focus of our next blog.

More specific application of AST data can be made for either site (e.g., blood, urine, etc.), infection type (e.g., community-acquired pneumonia), or organism-specific MIC distributions. A recent trend in national guideline recommendations centers on ascertaining local susceptibility and pathogen distribution to provide optimal antimicrobial choices for certain infections (e.g., pneumonia).⁷ In addition, focused review of individual pathogen MIC distributions provide another level of detail that helps better define upfront institutional antimicrobial dosing strategies to optimize PK/PD parameters. In conclusion, the reporting of AST data remains a cornerstone for the effective management of infections. Information collected by laboratory technicians provides invaluable information to clinicians. This information helps optimize the selection and dosing of antimicrobial agents at the bedside, which in turn improves the clinical management of patients and infection-related outcomes.

**Image 1: Clinical scenario outlining the application of MIC and breakpoint data at the bedside.**

References

Clinical and Laboratory Standards Institute. Development of In Vitro Susceptibility Testing Criteria and Quality Control Parameters, 5th Edition (M23).
Giuliano C, Patel CR, and Kale-Pradhan PB. A Guide to Bacterial Culture Identification and Results Interpretation. P&T. 2019 April 44(4):192-200.
Mouton JW, Muller AE, Canton R, et al. MIC-based dose adjustment: facts and fables. J Antimicrob Chemother 2018; 73:567-68.
Pogue JM and Heil EL. Laces out Dan! The role of tazobactam based combinations for invasive ESBL infections in a post-MERINO world. E Expert Opin Pharmacother.2019 Dec;20(17):2053-57.
Clinical and Laboratory Standards Institute. Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data; Approved Guideline, 4^th Edition (M39-A4).
Humphries RM, Abbott A, Hindler JA. Understanding and Addressing CLSI Breakpoint Revisions: a Primer for Clinical Laboratories. J Clin Microbiol. 2019 May 24;57(6):e00203-19.
Khalil AC, Metersky ML, Klompas M, et al. Management of Adults with Hospital-acquired and Ventilator-associated Pneumonia: 2016 Clinical Practice Guidelines by the Infectious Diseases Society of America and the American Thoracic Society. Clin Infect Dis. 2016 Sep 1;63(5):e61-e111.

-James Sanders, PharmD, PhD, is an infectious diseases pharmacy specialist and assistant professor at the University of Texas Southwestern Medical Center in Dallas, Texas. His academic and research interests are focused on multi-drug resistant Gram-negative bacteria, surgical site infections and HIV pharmacotherapy.

-Marguerite Monogue, PharmD is an infectious diseases pharmacy specialist and assistant professor at the University of Texas Southwestern Medical Center in Dallas, Texas. She is interested in antimicrobial pharmacokinetics/pharmacodynamics and multi-drug resistant Gram-negative bacteria.

-Andrew Clark, PhD, D(ABMM) is an Assistant Professor at UT Southwestern Medical Center in the Department of Pathology, and Associate Director of the Clements University Hospital microbiology laboratory. He completed a CPEP-accredited postdoctoral fellowship in Medical and Public Health Microbiology at National Institutes of Health, and is interested in antimicrobial susceptibility and anaerobe pathophysiology.

Breakpoint Breakdown

Working bacteriology benches in the clinical microbiology laboratory often comes with its fair share of questions about the susceptibility of patient isolates. In training, we are taught about breakpoints – clinically essential values which determine if an organism is susceptible, resistant, or somewhere in-between for a given drug. These values are readily accessible to us in guidance documents (e.g., CLSI M100, FDA website), and are programmed into instruments to allow for automated interpretation. But, have you ever wondered how these values are derived? Raw microbiological and pharmacological data, patient outcomes, and regulatory considerations must be examined through multiple lenses, and by many different entities, before these values ever make it to the printed page and used clinically. Here, we will highlight some of the “moving parts” of breakpoint determination an effort to demystify this process and gain a better understanding and appreciation of the clinical application of these life-saving measurements. To help, I’ve recruited two of our outstanding infectious disease pharmacists from UT Southwestern Medical Center to enhance this discussion. It’s my hope we will all learn something in the process!

Breakpoint Breakdown – The ABC’s of MICs and ECVs, plus Pharmacology 101!

A breakpoint represents a defined antibiotic concentration or zone of inhibition diameter that serves as a gatekeeper for antimicrobial use. This value categorizes organisms as susceptible, susceptible-dose dependent, intermediate, resistant, or nonsusceptible to various antimicrobials. As such, is an indispensable component of appropriate and effective antimicrobial prescribing.¹ Breakpoints are set through a rigorous examination of data by various national and international organizations which we will discuss in a later post. Determining the optimal value at which a breakpoint should be set is multifactorial, requiring a multidisciplinary approach to incorporate data from bench and bedside. Now, if that introduction sounded daunting, don’t panic! We’re going start at the beginning with basic biological measurements of susceptibility that are needed to begin to establish a breakpoint. For those not currently working in microbiology (or if it’s been a while), a basic understanding of susceptibility testing mechanisms is necessary and we will briefly review here. Bacteria will be the focus for this discussion, but many of these concepts are also broadly applicable to fungi as well.

Determination of susceptibility to an antibiotic can be evaluated by examining the response of a bacterial isolate to antimicrobial exposure. In the laboratory, this is usually achieved through dilution, whereby an isolate may grow at some drug concentrations, and growth is inhibited at others. Dilution of the antimicrobial can come either through directly applying the antibiotic at defined concentrations uniformly to growth media (i.e. broth dilution, agar dilution), or utilizing a diffusion gradient through media when an antibiotic is applied at a single source (i.e. disk diffusion) (Image 1). Application of defined antibiotic concentrations to the growth media allows for a minimal inhibitory concentration (MIC) to be determined, while a diffusion gradient allows for a zone of inhibition to be measured (ZOI). An MIC is the lowest concentration of antimicrobial that inhibits organism growth of an isolate. This value is unique to the isolate that is being tested. However, when establishing a broad measurement which will encompass all isolates of that species (or group of species) such as a breakpoint, it’s easy to imagine that significantly more data is needed.

Image 1. Three methods of antimicrobial susceptibility testing. Kirby-Bauer disk diffusion generates a zone of inhibition – the diameter of that zone is measured and correlated with MIC data to establish breakpoints. Broth and agar dilution are two dilution methods which directly generate an MIC as an endpoint; the lowest concentration of antibiotic in which growth is inhibited. In the broth microdilution experiment, isolate 1 has an MIC of 4μg/mL. In the agar dilution experiment, isolate 2 has an MIC of 1μg/mL.

Thus, a first step in setting an optimal breakpoint begins with an antimicrobial’s in vitro activity against an organism. A descriptive summary of the MIC range across a given species helps define the MIC distribution. This analysis usually includes MICs from hundreds of tested isolates! This MIC distribution helps to define epidemiologic cutoff values (ECV or ECOFF). Like a breakpoint, these values separate the MIC distribution into bacterial populations that are either wild-type, and those with resistance. The wild-type MIC distribution aims to exclude outlier MICs that may represent organisms with acquired resistance (either through mutation or acquisition of resistance determinants) reflected by elevated MICs. An isolate in the population with an MIC above the ECV is likely to have acquired resistance, whereas an isolate with an MIC lower than the ECV likely originates from the wild-type distribution and lacks mechanisms of acquired resistance or reduced susceptibility.² So great, we have an experimental MIC value which separates wild-type organisms from ones that have acquired resistance, why not just stop there and call it a breakpoint? The answer is the ECV does not account for host responses, clinical outcomes, site of infection, pharmacokinetics/pharmacodynamics, dosing, and a number of other important variables which go into establishing a clinical breakpoint. Thus, using ECVs for clinical decision making is challenging.

Now that we have considered some aspects of the microbiological side of the equation, let’s switch gears and look at the host and other factors not addressed by an ECV. Pharmacokinetic (PK) and pharmacodynamic (PD) parameters are key to assessing the clinical applicability of a breakpoint. PK parameters represent how the body handles the antimicrobial, including absorption, distribution, metabolism and elimination, whereas PD parameters represent the effect between the drug and bug. Taken together, PK/PD parameters represent the relationship between drug concentration (PK) and antimicrobial effect (PD) over time. Different antimicrobials have distinct PK and PD characteristics, thus several PK/PD indices are utilized to determine optimal target concentrations or exposures that improve antibacterial efficacy. Common PK/PD indices are the percent of time the free drug concentration remains above an organism’s MIC (fT > MIC), the ratio of free max drug concentration (or peak) to MIC (fCmax/MIC), and the ratio of free drug exposure (area under the curve, AUC) over a 24-hour period to MIC (fAUC/MIC) (Image 2).³

For example, β-lactam antimicrobials require 40-60% fT > MIC for maximum antibacterial efficacy; however, the exact fT > MIC (or other exposure) required for optimal efficacy varies between different β-lactam antimicrobials and bacterial species. Importantly, the desired antimicrobial exposure should be obtainable based on the established breakpoint, meaning the β-lactam of interest should achieve 40-60% fT > breakpoint. Various strategies are employed to optimize PK/PD parameters relative to a given breakpoint (more on that to come in Part 2 of this series). These target exposures are calculated from data for each bug-drug combination.

Of note, the antimicrobial exposure in relation to MIC is often based on antimicrobial blood concentrations. However, this is obviously not always the site of infection. The same bug-drug combination can have multiple breakpoints specific to infection site. For example, central nervous system (CNS) infections may have lower established breakpoints compared with non-CNS infections. The use of a lower breakpoint improves PK/PD target attainment in areas where there may be low drug concentrations, such as the CNS. For CNS-specific breakpoints, only organisms with MICs within the lower range of the MIC distribution will be deemed susceptible. With a lower MIC, the PK/PD exposure may be more obtainable given the potential poor drug penetration to the site of infection.

Outcomes from clinical data are often deemed the most important factor used to determine breakpoints. Treatment successes or failures of an antimicrobial against a specific MIC may provide validity to an established breakpoint or support revision. For example, the piperacillin-tazobactam breakpoint for Pseudomonas aeruginosa, was lowered from 64/4 mcg/mL to 16/4 mcg/mL due to an increase in mortality observed in patients who had organisms with MICs 32 or 64 mcg/mL.⁴ Unfortunately, clinical outcome data is often influenced by other confounders beyond antimicrobial therapy and the organism’s MIC, such as source control and other therapeutic interventions. Furthermore, clinical data for “resistant” organisms may not be available, limiting the assessment of the antimicrobial against organisms with high MICs.

Finally, it is important to remember that breakpoints are not set in stone and change regularly as more data become available. Common reasons for breakpoint revisions include: 1) new PK/PD data suggesting the breakpoint is too low or high based on antimicrobial exposure, 2) identification of novel resistance mechanisms, and 3) new clinical data to suggest poor correlation of clinical response with the established breakpoint. Furthermore, microbiological methods may become more accurate and ultimately affect quantification of the MIC.⁵

In summary, establishing a breakpoint is not a straightforward process and requires an aggregate of information. We are really only scratching the surface of the very complex process here, but hope that this sheds some light on where these important values originate. Various types of data; microbiological, pharmacological, in vitro, in vivo, they all create the story. However, a complete picture is often not available at the time of breakpoint creation, resulting in the need to constantly review and update breakpoints as more data becomes available.

Next post we will discuss how breakpoints are used at the bedside.

References

Clinical and Laboratory Standards Institute. Development of In Vitro Susceptibility Testing Criteria and Quality Control Parameters, 5th Edition (M23).
Turnidge J, Paterson DL. Setting and revising antibacterial susceptibility breakpoints. Clin Microbiol Rev. 2007 Jul;20(3):391-408.
Craig WA. Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clin Infect Dis. 1998 Jan;26(1):1-10; quiz 11-2. doi: 10.1086/516284.
Tam V, et al. Outcomes of bacteremia due to Pseudomonas aeruginosa with reduced susceptibility to piperacillin-tazobactam: implications on the appropriateness of the resistance breakpoint. Clin Infect Dis. 2008 Mar 15;46(6):862-7.
Humphries RM, Abbott A, Hindler JA. Understanding and Addressing CLSI Breakpoint Revisions: a Primer for Clinical Laboratories. J Clin Microbiol. 2019 May 24;57(6):e00203-19.

Antimicrobial Stewardship Down Under

If you’re an infectious disease/antimicrobial stewardship/microbiology geek, then the Australian blog AIMED is relevant to your interests. AIMED focuses on practical antimicrobial prescribing issues of relevance to hospital and community prescribers. It is supported by a local brains trust of General Practitioners, Pharmacologists, Pharmacists, Microbiologists and Infectious Disease Physicians. It also provides internet access to key Hunter New England resources for medical staff including guides to local antibiograms, infection control resources and personnel.

For those who don’t know, AIMED is an acronym for five principles that guide patient treatment with antimicrobials:

Antimicrobial selection and dosage
Indication for antimicrobial treatment
Microbiological assessment
Evaluate patient at 48-72 hours
Duration should be specified

If you’d like to learn more, check out their blog.

CMS Proposes Rule that Promotes Antibiotic Stewardship

In mid-June, CMS proposed a rule that, in part, will help promote antimicrobial stewardship in hospitals. The 60-day comment period is nearing its end, so if you have thoughts on this proposed rule, let them know.

CMS press release

Potential Antimicrobial Therapy Hiding in Plain Sight

Yesterday, Nature published a paper that might help in the fight against MRSA. In a nutshell, German researchers discovered that Staphylococcus lugdunensis–a common bacteria in commensal flora–produces a compound that reduces colonization with MRSA.

From the abstract:

“Notably, human nasal colonization by S. lugdunensis was associated with a significantly reduced S. aureus carriage rate, suggesting that lugdunin or lugdunin-producing commensal bacteria could be valuable for preventing staphylococcal infections.”

Carbapenem-Resistant Enterobacteriaceae Found in Rio de Janeiro’s Water

Recent studies conducted by Brazilian researchers found “super bacteria” in the waters where Olympic athletes will be competing. According to MercoPress, “The Brazilian group’s lead researcher, Renata Picao, said Rio’s “super bacteria” made its way into the city’s waterways through sewage from local hospitals, due to a lack of basic sanitation in the metropolitan area.”

A recent Lab Medicine podcast discusses laboratory testing for CRE. You can listen to it here.

Maryn McKenna writes extensively about antimicrobial resistance. You can watch to her recent TED talk (or read the transcript) to learn why the presence of CRE in Rio’s water is so concerning.

The World’s Most Ambitious Superbug

Researchers from the Walter Reed National Military Medical Center in Maryland discovered a strain of E. coli that carried 15 different genes that confer antibiotic resistance, including the resistance factor MCR, which confers resistance to colistin, a drug of last resort.

This particular E. coli was recovered from the urine of a 49-year-old woman.

The paper is currently available as an accepted manuscript posted online.

You can read Maryn McKenna’s report here.

Antimicrobial Testing–Are We Doing it Wrong?

Antibiotic resistance is a huge concern for microbiologists. In addition to stewardship programs and regulating agricultural use of antibiotics, is it time to re-examine clinical testing paradigms?

A recent study suggests that the typical way microbiologists test for antibiotic susceptibility–meuller-hinton plates and antibiotic disks–might be fallible. When his team tested Salmonella against polymyxin using typical methods, the organism tested sensitive; when the tested the same organism against the same antibiotic using medium that more closely resembled human cells, the organism tested resistant.

Bloomberg Business discusses the paper here. The article is worth your time, even if the info-graphic gives erroneous information (it mentions meuller-hinton broth instead of meuller-hinton agar plates).

Using Evolution to Thwart Resistance

The very act of using antibiotics contributes to antibiotic resistance. Bacteria are exposed to an antimicrobial agent and develop genetic strategies to survive repeated exposures. But what if using antibiotics in a certain sequence could revert resistant strains to the wild type? Researchers from California and Washington DC tested that theory and discovered some promising results.

You can read the PLOS ONE study and the Scientific American article to learn more.

Illinois Summit on Antibiotic Stewardship

Last week, I attended the Illinois Summit on Antimicrobial Stewardship at Northwestern Memorial Hospital. While the target audience was physicians, nurses, pharmacists, and administrators, as a clinical laboratory scientist I found the presentations (with a few caveats, which I’ll get to in a moment) quite informative.

The morning sessions covered the relationship between antibiotic use and resistance patterns; interpretations and implementation of the national guideless for stewardship; and using behavioral science to increase compliance with stewardship programs. Participants spent part of the afternoon in small groups to discuss designing and implementing a stewardship program.

A few notes:

-50% of antibiotics for upper respiratory infections aren’t needed; 50% of antibiotics for inpatients aren’t needed, either

-antibiotics are the only drug where use in one person impacts it effectiveness in another

-based on the literature, antibiotic stewardship programs have at least a transient effect on antibiotic effectiveness—eventually, resistance numbers begin to climb again

-hospital antibiograms are the most widely available measure of resistant organisms, but we aren’t using them as effectively as we could. For example, we typically report that, say, “62.5% of E. coli isolates are resistant to ciprofloxacin,” but we don’t say where those isolates come from. Are they urinary tract infections or upper respiratory infections? What’s the rate of resistance for infected wounds?

-a weighted antibiogram might make empirical treatments for effective. For example, “what % of urinary tract infections are resistant to ciprofloxacin?”

-it’s important to note that the IT department, hospital information systems, and laboratory information systems play a huge role in stewardship programs

-stewardship programs depend on the “5 D’s” Diagnosis, drug selection, dose, duration, and de-escalation of use

-diagnostic uncertainty—driven by lack of early organism identification—drives a significant amount of antibiotic use

-when combined with stewardship, rapid bacterial identification methods such as MALDI-ToF platforms decrease parameters such as length of patient say, time to treatment, etc.

-we can use peer pressure to drive improvements. No one wants to perform worse than the doctor next door

-our efforts might be moot, anyway; other countries take a much laxer stance on antibiotic use

While the laboratory in general and clinical microbiology departments specifically were mentioned during the presentations, I must say they were only mentioned in the context of how little perceived impact we have on stewardship. (“Well, we know the laboratory isn’t going to give us any useful information for another three days…”) It wasn’t until I participated in the small group sessions in the afternoon that attendees at my table admitted that the laboratory is an important piece of the stewardship puzzle. We have mountains of data we can assimilate (antibiogram creation, anyone?). We can bring in new technologies to make identifications faster. We can work closely with the infectious disease doctors to help guide treatment. That brings up a good point—if microbiology labs aren’t in-house, then creating an antibiotic stewardship program becomes that much harder because results can be delayed.

If you’d like to see the powerpoints from the presentations, you can do so by clicking the “downloadable content” tab at Northwestern Memorial Hospital’s antibiotic stewardship page.

–Kelly Swails, MT(ASCP), is a laboratory professional, recovering microbiologist, and web editor for Lab Medicine.