Skip to main content
  • ASM
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Eukaryotic Cell
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems
  • Log in
  • My alerts
  • My Cart

Main menu

  • Home
  • Articles
    • Current Issue
    • Accepted Manuscripts
    • COVID-19 Special Collection
    • Archive
    • Minireviews
  • For Authors
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About AAC
    • Editor in Chief
    • Editorial Board
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • AAC Podcast
    • RSS
    • FAQ
  • Subscribe
    • Members
    • Institutions
  • ASM
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Eukaryotic Cell
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems

User menu

  • Log in
  • My alerts
  • My Cart

Search

  • Advanced search
Antimicrobial Agents and Chemotherapy
publisher-logosite-logo

Advanced Search

  • Home
  • Articles
    • Current Issue
    • Accepted Manuscripts
    • COVID-19 Special Collection
    • Archive
    • Minireviews
  • For Authors
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About AAC
    • Editor in Chief
    • Editorial Board
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • AAC Podcast
    • RSS
    • FAQ
  • Subscribe
    • Members
    • Institutions
Epidemiology and Surveillance

Antimicrobial Susceptibility and Cross-Resistance Patterns among Common Complicated Urinary Tract Infections in U.S. Hospitals, 2013 to 2018

Marya D. Zilberberg, Brian H. Nathanson, Kate Sulham, Andrew F. Shorr
Marya D. Zilberberg
aEviMed Research Group, LLC, Goshen, Massachusetts, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Brian H. Nathanson
bOptiStatim, LLC, Longmeadow, Massachusetts, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kate Sulham
cSpero Therapeutics, Cambridge, Massachusetts, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andrew F. Shorr
dWashington Hospital Center, Washington, DC, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1128/AAC.00346-20
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

ABSTRACT

In the face of increasing rates of antimicrobial resistance in complicated urinary tract infections (cUTIs), clinicians need to understand cross-resistance patterns among commonly encountered pathogens. We performed a multicenter, retrospective cohort study in the Premier database of approximately 180 hospitals, from 2013 to 2018. Using an ICD-9/10-based algorithm, we identified all adult patients hospitalized with cUTIs and included those with a positive blood or urine culture. We examined the microbiology and susceptibilities to common cUTI antimicrobials (3rd-generation cephalosporin [C3], fluoroquinolones [FQ], trimethoprim-sulfamethoxazole [TMP/SMZ], fosfomycin [FFM], and nitrofurantoin [NFT]) singly and in groups of two. Among 28,057 organisms from 23,331 patients, the 3 most common pathogens were Escherichia coli (41.0%; C3r, 15.1%), Klebsiella pneumoniae (12.1%; C3r, 13.2%), and Pseudomonas aeruginosa (11.0%; C3r, 12.0%). E. coli was most frequently resistant to FQ (43.5%) and least to NFT (6.7%). K. pneumoniae was most frequently resistant to NFT (60.8%) and least to FFM (0.1%). P. aeruginosa was most frequently resistant to FQ (34.4%) and least to TMP/SMZ (4.2%). Of the C3r E. coli isolates, 87.1% were also FQr, 63.7% were TMP/SMZr, and 13.3% were NFTr. C3r K. pneumoniae isolates had a 76.5% chance of being FQr, 78.1% were TMP/SMZr, and 77.6% were NFTr. C3r P. aeruginosa coexisted with FQr in 47.3%, TMP/SMZr in 18.9%, and NFTr in 28.7%. Among the most common pathogens isolated from hospitalized patients with cUTIs, the rates of single resistance to common treatments and of cross-resistance to these regimens are substantial. Knowing the patterns of cross-resistance may help clinicians tailor empirical therapy more precisely.

INTRODUCTION

Urinary tract infections (UTIs) in adults account for more than 400 million annual hospitalizations in the United States (1). Moreover, the prevalence of such admissions has nearly doubled between 1998 and 2011 (1). Although during this time, the associated hospital length of stay (LOS) has decreased by 1 day (on average), the median attributable costs of these hospitalizations have doubled from $2,400 to $5,000 over the same time period (1). In short, UTIs represent a major strain on the health care system.

By its very definition, uncomplicated UTI—one that occurs in essentially healthy females with no evidence of systemic involvement—comprises a minority of all UTIs that require hospitalization. The vast majority of hospitalizations for UTIs are considered complicated (cUTI). As such, patients who require inpatient treatment for their cUTIs likely present more challenging treatment dilemmas. Specifically, these patients, in addition to their underlying comorbidities, face a higher risk of harboring a pathogen resistant to commonly employed therapies (2–4).

Of particular concern in the care of patients with cUTIs are increasing rates of resistance to commonly used first-line agents, including 3rd-generation cephalosporins (C3), fluoroquinolones (FQ), and trimethoprim-sulfamethoxazole (TMP/SMZ) (2–5). Because of the frequency of cUTI diagnosis, coupled with escalating rates of antimicrobial resistance (AMR), carbapenems are being more frequently prescribed as first-line therapy for cUTI. This behavior by physicians, although undertaken to ensure the patient receives initially appropriate antibiotic therapy, creates increased selection pressure and fuels further AMR.

One potential way to limit the use of overly broad agents is to understand better the microbiology as it impacts specific infectious syndromes. Pneumonia and cUTI, for example, differ substantially with respect to their pathogen distributions. That is, while Escherichia coli is the most common cause of cUTI, enteric pathogens are rarely causative in pneumonia (6). For this reason, when considering empirical treatment in the setting of cUTI, AMR among E. coli isolates becomes much more salient than in the case of pneumonia. With the rise in AMR, however, there is also an increase in multiply resistant pathogens, which may make empirical choices even trickier. In other words, it would be useful for clinicians to know whether resistance to a single agent of interest may be a marker for resistance to another drug aimed at the same pathogen. To explore patterns of resistance in cUTI to multiple agents, we examined the microbiology and in vitro susceptibilities to commonly used antimicrobial regimens among patients hospitalized with cUTIs, singly and in combination.

(Data from this study have in part been presented at ID Week 2019.)

RESULTS

Study enrollment is depicted in Fig. 1. Among 23,331 patients meeting enrollment criteria, 28,057 organisms of interest were isolated. The vast majority (68.3%) of the isolates cooccurred in blood and urine, while 31.0% were found in urine only. Isolates from blood only comprised <1% of all pathogens. (For hospital characteristics, see Table S3 in the supplemental material.)

FIG 1
  • Open in new tab
  • Download powerpoint
FIG 1

Study enrollment. cUTI, complicated urinary tract infections; LOS, length of stay; cIAI, complicated intraabdominal infection.

The 3 leading pathogens were Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, which together comprised nearly two-thirds of all isolates (Table 1). The 10 most commonly isolated organisms accounted for more than 90% of all cUTIs.

View this table:
  • View inline
  • View popup
  • Download powerpoint
TABLE 1

Organism distribution

Organisms varied with respect to the frequency of susceptibility testing to different antimicrobials: FQ susceptibility was the most and fosfomycin (FFM) the least frequently tested for (Fig. 2; see also Table S4). Of the 3 most commonly isolated cUTI organisms, resistance to C3 was found in 15.1% of E. coli isolates, 13.2% for K. pneumoniae, and 12.0% for P. aeruginosa (Table 2). E. coli was most frequently resistant to FQ (43.5%) and least frequently resistant to nitrofurantoin (NFT) (6.7%). It was never tested for susceptibility to FFM. K. pneumoniae was most frequently resistant to NFT (60.8%) and least frequently resistant to FFM (0.1%), the latter likely due to FFM testing being a rare event (Table S4). P. aeruginosa was most frequently resistant to FQ (34.4%) and least frequently resistant to TMP/SMZ (4.2%). Similarly to E. coli, it was never tested for susceptibility to FFM. NFT and FQ exhibited some of the highest rates of resistance across multiple cUTI pathogens (Table 2).

FIG 2
  • Open in new tab
  • Download powerpoint
FIG 2

Frequencies of susceptibility testing. C3, 3rd-generation cephalosporin; FQ, fluoroquinolone; TMP/SMX, trimethoprim-sulfamethoxazole; FFM, fosfomycin; NFT, nitrofurantoin.

View this table:
  • View inline
  • View popup
  • Download powerpoint
TABLE 2

Prevalence of resistance among 10 most common cUTI pathogens

Table 3 shows the patterns of cross-resistance among the 10 most common cUTI pathogens to combinations of two of the examined antimicrobial regimens. There was a striking overlap between C3r and FQr. Focusing on the most prevalent cUTI pathogen, of the C3r E. coli isolates, 87.1% were also FQr, 63.7% were TMP/SMZr, and 13.3% were NFTr. Conversely, just less than one-third of all FQr E. coli isolates were C3r as well. Similar proportions of C3r E. coli isolates were also TMP/SMZr and NFTr (Table 3). NFT was the drug E. coli isolates were least likely to exhibit cross-resistance to in the presence of resistance to another antimicrobial. (For resistance trends over time, see Table S5a to e).

View this table:
  • View inline
  • View popup
  • Download powerpoint
TABLE 3

Cross-resistance among 10 most common cUTI pathogensa

The prevalence of cross-resistance to C3 and other antimicrobials was high in K. pneumoniae. For example, when C3r, K. pneumoniae had a 76.5% chance of being FQr, 78.1% of being TMP/SMZr, and 77.6% of being NFTr. With the exception of NFTr K. pneumoniae isolates, where cross-resistance to C3, FQ, and TMP/SMZ was <30%, and FFMr, which was rarely tested, the chances of cross-resistance to all the remaining drugs were >50% across the board and, in the case of NFTr, among FQr isolates, as high as 81.9% (Table 3).

As for P. aeruginosa, when C3r was present, FQr coexisted in 47.3% of the isolates compared to relatively lower likelihoods of TMP/SMZr (18.9%) and NFTr (28.7%). Among the pool of FQr P. aeruginosa isolates, the rate of resistance to other therapies was <20% across the board and lowest to TMP/SMZ (5.1%). TMP/SMZr, however, was associated with a high risk (>40%) of resistance to other drugs, as was NFTr (>35%) (Table 3). The patterns of cross-resistance among other less common pathogens are depicted in Table 3.

DISCUSSION

We have demonstrated that the rates of single and cross-resistance to common cUTI regimens used to treat the leading cUTI pathogens are significant: the rate of single TMP/SMZr was >36%, and the rate of FQr exceeded 44%. Although C3r is relatively less common than FQr, its presence signals a high risk for FQr and TMP/SMZr among E. coli isolates, the pathogen that accounts for >40% of all cUTIs. This tight association between C3r and resistance to other frequently utilized anti-UTI therapies has implications for C3r E. coli at the hospital level. That is, institutions with a high prevalence of C3r are likely to have commensurately high levels of resistance to FQ and TMP/SMZ. Even NFTr, though lower than others in the presence of C3r among E. coli isolates, carries a risk of 10%. Similar conclusions can be drawn for K. pneumoniae. When a hospital harbors a high volume of K. pneumoniae isolates resistant to one common antimicrobial, the levels of resistance to others can also be expected to be high, or >50% for C3, FQ, and TMP/SMZ, and lower, albeit still substantial, for NFT. In the case of P. aeruginosa, institutions with a high prevalence of TMP/SMZr or NFTr are also at risk for resistance to the remaining regularly used agents. Put simply, with the current rates of resistance generally encountered in cUTIs, one cannot presume that if a pathogen is resistant to a specific agent that another option will be readily available. This pattern is consistent across a range of pathogens and range of treatment alternatives.

Emerging antimicrobial resistance has complicated clinicians’ choices for empirical therapy in serious infections requiring hospitalization. In many of these infections, when appropriate therapy that covers the presumed pathogen is delayed, outcomes for patients are worse in both clinical and economic terms (7–12). Yet AMR, when present, contributes significantly to the risk of receiving inappropriate empirical coverage (12–14). Because empirical coverage is, by definition, required before definitive culture results become available, a probabilistic approach, in which clinicians make a judgment as to what represents their most reliable option, is necessary. Awareness of the local microbiology and susceptibilities, therefore, can lead to a more informed choice of therapy. Thus, our observations on what resistance patterns tend to occur together is unique in that it is tailored to help clinicians gain a deeper understanding of how to choose empirical treatments. Furthermore, our data analysis facilitates decision making conditioned not only on patterns of resistance to a single drug but also on the risk of additive resistance to commonly prescribed antimicrobial regimens.

It is alarming that the top three non-carbapenem-resistant pathogens responsible for culture-positive cUTIs exhibit high rates of AMR to such common treatments as C3, FQ, and TMP/SMZ. Among those three agents, with the exception of TMP/SMZr P. aeruginosa, all other rates of resistance exceeded the 10% threshold beyond which formal treatment guidelines discourage empirical use (2). Our findings generally confirm the observations of others in that our estimated rates of resistance are similar to those reported in the literature for select pathogens. Additionally, we add to the observations of others by analyzing a more comprehensive group of bacterial isolates (15, 16). It is further important to appreciate that AMR frequently does not occur singly, implying that many of the drugs clinicians rely upon in treating cUTI may be suboptimal choices. However, knowing which groups of AMR travel together, along with an appreciation of local antibiogram patterns, may aid physicians in making more informed treatment decisions.

It is worth noting that fosfomycin susceptibility testing was exceedingly rare. There are likely several reasons for it. First, it is an old drug whose use waned with the introduction of newer agents. Second, given its infrequent use in recent decades, there are no standard breakpoints for fosfomycin in the majority of UTI pathogens (17). Third, since automated fosfomycin testing is not available, it is possible that the frequency of manual testing is underreported. However, its broad spectrum and pharmacodynamics make it potentially attractive as a UTI treatment in the face of surging AMR. Indeed, in some studies, the susceptibility rates of common UTI pathogens to fosfomycin are 90% (18).

Our study has a number of strengths and limitations. Premier, as a large multihospital database, does not suffer from lack of generalizability. As an observational study, however, it is prone to selection bias; we attempted to mitigate its magnitude by defining the cohort prospectively. Misclassification is an issue in any study and particularly when using administrative data. To minimize it, we used a previously published algorithm to identify our cohort. However, this algorithm has not been clinically validated (19). Though there are multiple ways to define cUTI, our definition aligns closely with clinical practice. We developed a restrictive definition for cUTI in order to optimize its specificity. This may have reduced its sensitivity, resulting in the exclusion of at least some cUTI cases. Furthermore, we excluded other potential sources of infection and included microbiology specimens, pharmacy data, and dates of cultures and treatments. This is a descriptive analysis, and adjustment for confounding was not undertaken. In some cases, we report data for antibiotic pathogen susceptibility testing which would either not normally be performed or, if performed, not be reported. This may seem to limit the validity of our findings. While these data do not reflect recommendations for specific testing among these antibiotic-pathogen combinations, we included the results in our paper to illustrate how automated susceptibility testing is currently done in many U.S. hospitals.

In summary, we have demonstrated that, among frequently isolated bacterial pathogens in the setting of hospitalizations with cUTI, resistance to common antimicrobial treatments is high. Moreover, where resistance to a single drug or class is detected, there are variable, but uniformly substantial, risks of resistance to additional drugs in the arsenal used in cUTIs. In addition to considering local antibiograms, understanding the combinations of resistance patterns among common pathogens to common antimicrobial regimens may help target better empirical treatment choices.

MATERIALS AND METHODS

Ethics statement.Because this study used already existing fully deidentified data, it was exempt from IRB review under US 45 CFR 46.101(b)4 (20).

Study design and patient population.We conducted a multicenter, retrospective cohort study of hospitalized patients with culture-positive carbapenem-susceptible cUTI to explore the prevalence and impact of resistance to commonly used noncarbapenem empirical regimens. The case identification approach (see Table S1 in the supplemental material) relied on a previously published algorithm (19). Briefly, we included all adult patients (age, ≥18 years) with a urine culture obtained at any time during hospitalization who received antibiotic treatment on the day of the index culture and continued for ≥3 consecutive days and who met the definition for cUTI (19). Only culture-positive (urine, blood, or both) patients were included in the cohort. Patients with a hospital length of stay (LOS) of <2 days, who fit the definition for a complicated intraabdominal infection (to reduce the risk of misclassification) (see Table S2), who were transferred from another acute care facility, or who grew an organism resistant to at least one carbapenem were excluded (19).

Data source.The data for the study were derived from Premier Research database, an electronic laboratory, pharmacy, and billing data repository for years 2013 through 2018. The database has been described in detail previously (19, 21–23). We used data from a subset of approximately 180 U.S. institutions (of >900 hospitals submitting patient data to Premier) who submitted microbiology data annually during the study time frame.

Microbiology and susceptibilities.Organisms were classified as susceptible (S), intermediate (I), or resistant (R). For the purposes of the current analyses, I and R were grouped together as resistant. For each of the common antimicrobials of interest (C3, FQ, TMP/SMZ, fosfomycin [FFM], and nitrofurantoin [NFT]), we examined specific susceptibility testing to determine the resistance status. Cross-resistance was defined as the risk of resistance to a second antimicrobial if resistance to a single antimicrobial was detected. The results of susceptibility testing represented the findings of the local microbiology laboratories at the participating hospitals.

The first detection of an organism served as the index culture. To be considered culture positive, a qualifying common bacterium had to grow from urine or blood samples from the patient. Organisms of interest included Enterobacteriaceae, P. aeruginosa, Acinetobacter baumannii, Enterococcus faecium, Enterococcus faecalis (19). All microbiology results were based on the local testing done by participating hospitals.

Outcome variables and statistical analyses.We examined the prevalence of antimicrobial resistance singly and cross-resistance between groups of two of the drugs/classes of interest. No hypothesis testing was undertaken. Only descriptive statistics are presented.

Data availability.The data used in this study derive from Premier Research database, a proprietary third-party database available to researchers through a specific agreement with Premier.

ACKNOWLEDGMENTS

This study was supported by a grant from Spero Therapeutics, Cambridge, MA, USA.

M.D.Z. is a consultant to Spero Therapeutics. Her employer, EviMed Research Group, LLC, has received research grant support from Spero Therapeutics. B.H.N.’s employer, OptiStatim, LLC, has received support from EviMed Research Group, LLC. K.S. is an employee of and stockholder in Spero Therapeutics. A.F.S. is a consultant to and has received research grant support from Spero Therapeutics. M.D.Z. and A.F.S. have received grant support and/or have served as consultants to Merck, Melinta, Tetraphase, Pfizer, Astellas, Shionogi, The Medicines Company, Lungpacer, and Theravance.

M.D.Z., K.S., and A.F.S. contributed substantially to the study design, data interpretation, and the writing of the manuscript. B.H.N. had full access to all of the data in the study, takes responsibility for the integrity of the data and the accuracy of the data analysis, and contributed substantially to the study design, data analysis, and the writing of the manuscript. No persons other than the authors participated in the study or the writing of the manuscript.

FOOTNOTES

    • Received 21 February 2020.
    • Returned for modification 4 April 2020.
    • Accepted 26 April 2020.
    • Accepted manuscript posted online 18 May 2020.
  • Supplemental material is available online only.

  • Copyright © 2020 American Society for Microbiology.

All Rights Reserved.

REFERENCES

  1. 1.↵
    1. Simmering JE,
    2. Tang F,
    3. Cavanaugh JE,
    4. Polgreen LA,
    5. Polgreen PM
    . 2017. The increase in hospitalizations for urinary tract infections and the associated costs in the United States, 1998–2011. Open Forum Infect Dis 4:ofw281. doi:10.1093/ofid/ofw281.
    OpenUrlCrossRefPubMed
  2. 2.↵
    1. Gupta K,
    2. Hooton TM,
    3. Naber KG,
    4. Wullt B,
    5. Colgan R,
    6. Miller LG,
    7. Moran GJ,
    8. Nicolle LE,
    9. Raz R,
    10. Schaeffer AJ,
    11. Soper DE, Infectious Diseases Society of America, European Society for Microbiology and Infectious Diseases
    . 2011. International clinical practice guidelines for the treatment of acute uncomplicated cystitis and pyelonephritis in women: a 2010 update by the Infectious Diseases Society of America and the European Society for Microbiology and Infectious Diseases. Clin Infect Dis 52:e103-e120. doi:10.1093/cid/ciq257.
    OpenUrlCrossRef
  3. 3.↵
    1. Sanchez GV,
    2. Master RN,
    3. Karlowsky JA,
    4. Bordon JM
    . 2012. In vitro antimicrobial resistance of urinary Escherichia coli isolates among U.S. outpatients from 2000 to 2010. Antimicrob Agents Chemother 56:2181–2183. doi:10.1128/AAC.06060-11.
    OpenUrlAbstract/FREE Full Text
  4. 4.↵
    1. Raz R,
    2. Chazan B,
    3. Kennes Y,
    4. Colodner R,
    5. Rottensterich E,
    6. Dan M,
    7. Lavi I,
    8. Stamm W, Israeli Urinary Tract Infection Group
    . 2002. Empiric use of trimethoprim-sulfamethoxazole (TMP-SMX) in the treatment of women with uncomplicated urinary tract infections, in a geographical area with a high prevalence of TMP-SMX-resistant uropathogens. Clin Infect Dis 34:1165–1169. doi:10.1086/339812.
    OpenUrlCrossRefPubMedWeb of Science
  5. 5.↵
    1. Zilberberg MD,
    2. Shorr AF
    . 2013. Secular trends in gram-negative resistance among urinary tract infection hospitalizations in the United States, 2000–2009. Infect Control Hosp Epidemiol 34:940–946. doi:10.1086/671740.
    OpenUrlCrossRefPubMed
  6. 6.↵
    1. Jain S,
    2. Self WH,
    3. Wunderink RG,
    4. Fakhran S,
    5. Balk R,
    6. Bramley AM,
    7. Fakhran S,
    8. Balk R,
    9. Bramley AM,
    10. Reed C,
    11. Grijalva CG,
    12. Anderson EJ,
    13. Courtney DM,
    14. Chappell JD,
    15. Qi C,
    16. Hart EM,
    17. Carroll F,
    18. Trabue C,
    19. Donnelly HK,
    20. Williams DJ,
    21. Zhu Y,
    22. Arnold SR,
    23. Ampofo K,
    24. Waterer GW,
    25. Levine M,
    26. Lindstrom S,
    27. Winchell JM,
    28. Katz JM,
    29. Erdman D,
    30. Schneider E,
    31. Hicks LA,
    32. McCullers JA,
    33. Pavia AT,
    34. Edwards KM,
    35. Finelli L, CDC EPIC Study Team
    . 2015. Community-acquired pneumonia requiring hospitalization among U.S. adults. N Engl J Med 373:415–427. doi:10.1056/NEJMoa1500245.
    OpenUrlCrossRefPubMed
  7. 7.↵
    1. Iregui M,
    2. Ward S,
    3. Sherman G,
    4. Fraser VJ,
    5. Kollef MH
    . 2002. Clinical importance of delays in the initiation of appropriate antibiotic treatment for ventilator-associated pneumonia. Chest 122:262–268. doi:10.1378/chest.122.1.262.
    OpenUrlCrossRefPubMedWeb of Science
  8. 8.↵
    1. Zilberberg MD,
    2. Shorr AF,
    3. Micek MT,
    4. Mody SH,
    5. Kollef MH
    . 2008. Antimicrobial therapy escalation and hospital mortality among patients with health-care-associated pneumonia: a single center experience. Chest 134:963–968. doi:10.1378/chest.08-0842.
    OpenUrlCrossRefPubMedWeb of Science
  9. 9.↵
    1. Micek ST,
    2. Kollef KE,
    3. Reichley RM,
    4. Roubinian N,
    5. Kollef MH
    . 2007. Health care-associated pneumonia and community-acquired pneumonia: a single-center experience. Antimicrob Agents Chemother 51:3568–3573. doi:10.1128/AAC.00851-07.
    OpenUrlAbstract/FREE Full Text
  10. 10.↵
    1. Zilberberg MD,
    2. Nathanson BH,
    3. Sulham K,
    4. Fan W,
    5. Shorr AF
    . 2017. 30-day readmission, antibiotics costs and costs of delay to adequate treatment of Enterobacteriaceae UTI, pneumonia, and sepsis: a retrospective cohort study. Antimicrob Resist Infect Control 6:124. doi:10.1186/s13756-017-0286-9.
    OpenUrlCrossRef
  11. 11.↵
    1. Zilberberg MD,
    2. Nathanson BH,
    3. Sulham K,
    4. Fan W,
    5. Shorr AF
    . 2017. Daily cost of delay to adequate antibiotic treatment among patients surviving a hospitalization with community-onset Acinetobacter baumannii pneumonia or sepsis. Crit Care 21:130. doi:10.1186/s13054-017-1719-9.
    OpenUrlCrossRef
  12. 12.↵
    1. Zilberberg MD,
    2. Nathanson BH,
    3. Sulham K,
    4. Fan W,
    5. Shorr AF
    . 2017. Carbapenem resistance, inappropriate empiric treatment and outcomes among patients hospitalized with Enterobacteriaceae urinary tract infection, pneumonia and sepsis. BMC Infect Dis 17:279. doi:10.1186/s12879-017-2383-z.
    OpenUrlCrossRef
  13. 13.↵
    1. Zilberberg MD,
    2. Nathanson BH,
    3. Sulham K,
    4. Fan W,
    5. Shorr AF
    . 2016. Multidrug resistance, inappropriate empiric therapy, and hospital mortality in Acinetobacter baumannii pneumonia and sepsis. Crit Care 20:221. doi:10.1186/s13054-016-1392-4.
    OpenUrlCrossRef
  14. 14.↵
    1. Zilberberg MD,
    2. Shorr AF,
    3. Micek ST,
    4. Vazquez-Guillamet C,
    5. Kollef MH
    . 2014. Multi-drug resistance, inappropriate initial antibiotic therapy and mortality in Gram-negative severe sepsis and septic shock: a retrospective cohort study. Crit Care 18:596. doi:10.1186/s13054-014-0596-8.
    OpenUrlCrossRefPubMed
  15. 15.↵
    1. Bidell MR,
    2. Palchak M,
    3. Mohr J,
    4. Lodise TP
    . 2016. Fluoroquinolone and third-generation-cephalosporin resistance among hospitalized patients with urinary tract infections due to Escherichia coli: do rates vary by hospital characteristics and geographic region? Antimicrob Agents Chemother 60:3170–3173. doi:10.1128/AAC.02505-15.
    OpenUrlAbstract/FREE Full Text
  16. 16.↵
    1. Bouchillon SK,
    2. Badal RE,
    3. Hoban DJ,
    4. Hawser SP
    . 2013. Antimicrobial susceptibility of inpatient urinary tract isolates of Gram-negative bacilli in the United States: results from the Study for Monitoring Antimicrobial Resistance Trends (SMART) program: 2009–2011. Clin Ther 35:872–877. doi:10.1016/j.clinthera.2013.03.022.
    OpenUrlCrossRefPubMed
  17. 17.↵
    CLSI. 2019. Performance standards for antimicrobial susceptibility testing, 29th edition. M100-ED29. Clinical and Laboratory Standards Institute, Wayne, PA.
  18. 18.↵
    1. Maraki S,
    2. Samonis G,
    3. Rafailidis PI,
    4. Vouloumanou EK,
    5. Mavromanolakis E,
    6. Falagas ME
    . 2009. Susceptibility of urinary tract bacteria to fosfomycin. Antimicrob Agents Chemother 53:4508–4510. doi:10.1128/AAC.00721-09.
    OpenUrlAbstract/FREE Full Text
  19. 19.↵
    1. Zilberberg MD,
    2. Nathanson BH,
    3. Sulham K,
    4. Fan W,
    5. Shorr AF
    . 2018. Development and validation of a bedside instrument to predict carbapenem resistance among gram-negative pathogens in complicated urinary tract infections. Infect Control Hosp Epidemiol 39:1112–1114. doi:10.1017/ice.2018.166.
    OpenUrlCrossRef
  20. 20.↵
    US Department of Health and Human Services Office for Human Research Protections. 2016. Human subject regulations decision charts. https://www.hhs.gov/ohrp/regulations-and-policy/decision-charts/index.html. Accessed 19 July 2019.
  21. 21.↵
    1. Rothberg MB,
    2. Pekow PS,
    3. Priya A,
    4. Zilberberg MD,
    5. Belforti R,
    6. Skiest D,
    7. Lagu T,
    8. Higgins TL,
    9. Lindenauer PK
    . 2014. Using highly detailed administrative data to predict pneumonia mortality. PLoS One 9:e87382. doi:10.1371/journal.pone.0087382.
    OpenUrlCrossRefPubMed
  22. 22.↵
    1. Rothberg MB,
    2. Haessler S,
    3. Lagu T,
    4. Lindenauer PK,
    5. Pekow PS,
    6. Priya A,
    7. Skiest D,
    8. Zilberberg MD
    . 2014. Outcomes of patients with healthcare-associated pneumonia: worse disease or sicker patients? Infect Control Hosp Epidemiol 35(Suppl 3):S107–S115. doi:10.1017/S0899823X00194073.
    OpenUrlCrossRef
  23. 23.↵
    1. Lagu T,
    2. Stefan MS,
    3. Haessler S,
    4. Higgins TL,
    5. Rothberg MB,
    6. Nathanson BH,
    7. Hannon NS,
    8. Steingrub JS,
    9. Lindenauer PK
    . 2014. The impact of hospital-onset Clostridium difficile infection on outcomes of hospitalized patients with sepsis. J Hosp Med 9:411–417. doi:10.1002/jhm.2199.
    OpenUrlCrossRef
PreviousNext
Back to top
Download PDF
Citation Tools
Antimicrobial Susceptibility and Cross-Resistance Patterns among Common Complicated Urinary Tract Infections in U.S. Hospitals, 2013 to 2018
Marya D. Zilberberg, Brian H. Nathanson, Kate Sulham, Andrew F. Shorr
Antimicrobial Agents and Chemotherapy Jul 2020, 64 (8) e00346-20; DOI: 10.1128/AAC.00346-20

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Print

Alerts
Sign In to Email Alerts with your Email Address
Email

Thank you for sharing this Antimicrobial Agents and Chemotherapy article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Antimicrobial Susceptibility and Cross-Resistance Patterns among Common Complicated Urinary Tract Infections in U.S. Hospitals, 2013 to 2018
(Your Name) has forwarded a page to you from Antimicrobial Agents and Chemotherapy
(Your Name) thought you would be interested in this article in Antimicrobial Agents and Chemotherapy.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Antimicrobial Susceptibility and Cross-Resistance Patterns among Common Complicated Urinary Tract Infections in U.S. Hospitals, 2013 to 2018
Marya D. Zilberberg, Brian H. Nathanson, Kate Sulham, Andrew F. Shorr
Antimicrobial Agents and Chemotherapy Jul 2020, 64 (8) e00346-20; DOI: 10.1128/AAC.00346-20
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Top
  • Article
    • ABSTRACT
    • INTRODUCTION
    • RESULTS
    • DISCUSSION
    • MATERIALS AND METHODS
    • ACKNOWLEDGMENTS
    • FOOTNOTES
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • PDF

KEYWORDS

antimicrobial resistance
complicated UTI
cross-resistance
Hospitalization

Related Articles

Cited By...

About

  • About AAC
  • Editor in Chief
  • Editorial Board
  • Policies
  • For Reviewers
  • For the Media
  • For Librarians
  • For Advertisers
  • Alerts
  • AAC Podcast
  • RSS
  • FAQ
  • Permissions
  • Journal Announcements

Authors

  • ASM Author Center
  • Submit a Manuscript
  • Article Types
  • Ethics
  • Contact Us

Follow #AACJournal

@ASMicrobiology

       

ASM Journals

ASM journals are the most prominent publications in the field, delivering up-to-date and authoritative coverage of both basic and clinical microbiology.

About ASM | Contact Us | Press Room

 

ASM is a member of

Scientific Society Publisher Alliance

 

American Society for Microbiology
1752 N St. NW
Washington, DC 20036
Phone: (202) 737-3600

Copyright © 2021 American Society for Microbiology | Privacy Policy | Website feedback

Print ISSN: 0066-4804; Online ISSN: 1098-6596