Abstract
Purpose: Urinary tract infections (UTIs) are one of the most common indications for antimicrobial use in the emergency department (ED). Appropriate empiric selection is crucial to ensure optimal care while limiting broad-spectrum antibiotic use. The primary objective of this study was to evaluate the relationship between patient-specific risk factors and drug resistant urinary pathogens in patients discharged from the ED and followed by Emergency Medicine Pharmacists (EMPs). Methods: This was a single-center, retrospective chart review of adult (≥18 years old) patients with positive urine cultures discharged from the ED. The association between risk factors and pathogen resistance to ≥1 classes of antibiotics was evaluated using multivariate logistic regression. Risk factors included the following: hospitalization within the previous 30 days, intravenous antibiotic use within 90 days, diabetes, clinical atherosclerotic cardiovascular disease, psychiatric disorder, dementia, current antibiotic use for any indication, previous lifetime history of UTIs, indwelling or intermittent catheterization, hemodialysis, previous lifetime history of a urologic procedure, urinary tract abnormality, immunosuppressive disease or medications, current residence in a nursing or rehabilitation facility, and history of a multidrug resistant organism (MDRO). Results: A total of 1018 patients were included. There was an increase in the odds of antibiotic resistance in patients with cystitis and ≥2 risk factors (Odds Ratio [OR] = 1.70, 95% CI = 1.24-2.32). In those with pyelonephritis, there was a non-significant increase in the odds of resistance for those with ≥2 risk factors (OR = 1.83, 95% CI = 0.98-3.42). Patients with pyelonephritis discharged on inappropriate antibiotics were more likely to return to the ED within 30 days (P = .03). Conclusions: For patients with cystitis discharged from the ED, those with ≥2 patient-specific risk factors had significantly increased odds of antibiotic resistance. Patients with pyelonephritis, but not cystitis, who were discharged on inappropriate antibiotics were more likely to return to the ED within 30 days. In conjunction with an EMP culture follow-up program, the identification of risk factors for antimicrobial resistance can be used to design more patient-specific empiric antibiotic selections.
Keywords: CPR, emergency medicine, genitourinary, anti-infectives
Introduction
Urinary tract infections (UTIs) are among the most common bacterial infections encountered in the emergency department (ED) and patients are often discharged on empirically selected antibiotics. 1 However, as the rates of antimicrobial resistance continue to rise, UTIs are becoming increasingly challenging to treat. 2 Community-acquired urinary pathogens have progressively demonstrated antimicrobial resistance to commonly recommended treatment options such as sulfamethoxazole-trimethoprim (TMP-SMX) and the fluoroquinolone class of medications.2,3 Those practicing in the ED must balance the increasing challenge posed by antimicrobial resistance with the collateral damage that can result from the widespread use of broad-spectrum antibiotics. 4
For the empiric management of other commonly encountered infectious diseases in the ED, such as pneumonia, local resistance patterns are combined with patient-level risk factors to determine the most appropriate agents for empiric therapy as recommended by guidelines. 5 Unfortunately, this is not a widespread practice for approaching empiric UTI treatment in the ED as the available literature does not provide clear guidance regarding how to best approach the interplay of patient-level risk factors and local resistance patterns.6-8 Current Infectious Diseases Society of America (IDSA) UTI guidelines recognize the prevalence of antimicrobial resistance, however they do not provide treatment recommendations based on specific risk factors. 2 Previous studies have suggested that male sex, urinary catheterization, recent antibiotic use (eg, previous 30 days, 3 months, 6 months), and nursing home residence may be risk factors for resistant urinary pathogens.9-20 Other factors, such as ethnicity, recent travel (eg, previous 3 months, 6 months), diabetes, recent hospitalization (eg, previous 30 days, 3 months, 12 months), and current immunosuppression have conflicting evidence regarding their utility as predictors of resistance.9,11,16-23 Substantial inconsistencies also exist in the underlying definition of multidrug resistance in these studies, with some defining it as resistance to 1 antimicrobial anywhere from ≥1 to 3 different classes of antibiotics.9,11,16-19 The current variability in the literature limits the ability of ED prescribers to make well-supported empiric antimicrobial selections based on patient-specific risk factors in this population.
As the practice of Emergency Medicine Pharmacists (EMPs) has become more commonplace, so too has the practice of EMPs doing discharge culture follow-up for patients discharged from the ED.24,25 However, although rapid diagnostic testing is becoming more widely available, at most institutions urine cultures do not have a final result for days, during which time the patient is potentially receiving inappropriate therapy. 26 From a financial standpoint, the patient also has already purchased the empiric antibiotic and would have to incur the cost of a second prescription if the empiric therapy was inappropriate. Through the use of EMP culture follow-up data, institutions have the ability to not only build a more specific antibiogram for their ED, but also identify risk factors for resistant organisms to better guide empiric antimicrobial therapy decisions in this setting. The primary objective of this study was to evaluate the relationship between patient-specific risk factors and antibiotic resistance in UTIs for patients discharged from the ED.
Materials and Methods
This was a single-center, retrospective study conducted at a 700-bed academic Level 1 Trauma center ED with approximately 70 000 visits per year evaluating adult (≥18 years) patients with positive urine cultures who were discharged from the ED between January 1, 2017 and August 1, 2019. Empiric antibiotic selection was determined by individual providers at the time of discharge. At the time of this study, no protocols, algorithms, or clinical decision tools were present at the institution to guide antibiotic prescribing for this indication in the ED. Patients were included if they had a positive urine culture that was speciated and had susceptibility testing conducted by the microbiology lab that was entered into a culture review database. All positive cultures for patients discharged from the ED are reviewed and addressed for appropriateness each day, 7 days a week by EMPs who staff from 1300 to 2330. Appropriateness of antibiotic selection was determined based on the cultured organism antibiotic susceptibilities in conjunction with the clinical judgment of the EMP at the time of culture result following ED discharge as documented in the database. Antibiotic regimens identified for modification were reviewed with an Emergency Medicine Physician on the day of the culture result and if therapy modifications were necessary, patients were contacted the same day by the EMP. If new prescriptions were necessary, these were electronically prescribed as a verbal order by the EMP to the patient’s preferred pharmacy. At the time of this study, no protocol, policy, or collaborative practice agreement existed regarding this process. Follow-up notes were written daily in the electronic medical record by the EMP documenting that the positive culture was reviewed and the manner in which it was addressed, if necessary. The characteristics of each culture, including the organism, susceptibilities, and treatment, were entered daily into a database as a quality control measure and to monitor for resistance patterns. Urine cultures with <10 000 cfu/mL or with mixed flora were not speciated by the microbiology lab and therefore were inherently excluded from analysis, all others were included. This investigation was approved by the institution’s Institutional Review Board.
Study data were collected and managed using REDCap (Research Electronic Data Capture). REDCap access was supported by the South Carolina Clinical & Translational Research Institute, with an academic home at the Medical University of South Carolina, through NIH-NCATS Grant Number UL1 TR001450. 27 Data collection for variables not included in the culture review database were performed by manual chart review and included baseline demographics, serum creatinine, urine culture organism, and antimicrobial sensitivities, return visits to the ED for the same complaint (ie, UTI symptoms), and the clinical diagnosis documented by the treating prescriber at the time of the encounter. As multiple prior studies have assessed patients utilizing age thresholds, age distribution was further assessed based upon ≥50 years of age.3,17,18,28,29 Patient-specific risk factors collected and evaluated included the following based upon chart review and International Classification of Diseases and Related Health Problems, Tenth Revision Coding: hospitalization within the previous 30 days, intravenous antibiotic use within 90 days, diabetes, clinical atherosclerotic cardiovascular disease (eg, previous myocardial infarction, stroke, percutaneous coronary intervention, coronary artery bypass graft surgery), psychiatric disorder (ie, schizophrenia, bipolar disorder), dementia, current antibiotic use for any indication, previous lifetime history of UTIs, indwelling or intermittent catheterization, hemodialysis, previous lifetime history of a urologic procedure (eg, stent placement, transurethral resection of the prostate), urinary tract abnormality (ie, fistula, obstruction), immunosuppressive disease (ie, active malignancy or history of transplant) or medications (ie, prednisone equivalent >20 mg/day, chemotherapy, biologic agent), current residence in a nursing or rehabilitation facility, and history of a multidrug resistant organism (MDRO) at any site (defined as resistance to at least 1 antibiotic from 3 different classes in the last 2 years).
The primary outcome of this study was to determine if patient-specific risk factors were significantly associated with antibiotic resistance (AR), defined as pathogen resistance to ≥1 classes of antibiotics. Secondary outcomes included 30-day return ED visits stratified by appropriate or inappropriate antibiotic selection at discharge, evaluating if patient-specific risk factors were significantly associated with the growth of antibiotic resistant Escherichia coli (E. coli) or the growth of MDRO. All analyses were divided into “cystitis” and “pyelonephritis” based on the diagnosis of the ED provider at the time of the initial encounter. The rationale for separating the 2 categories is due to the different antibiotic treatment options for the 2 distinct presentations.
Statistical analyses were conducted using SPSS v22 (IBM Corp., Armonk, NY). Frequencies and percentages were used to report categorical data, while medians and interquartile ranges were used for continuous data. Pearson’s chi square or Fisher’s Exact tests were used to analyze categorical data, while Mann-Whitney U tests were used for continuous data. Multivariate logistic regression was performed to estimate the odds of antimicrobial resistance for those with ≥2 patient-specific risk factors after adjusting for age and sex to allow for more precise estimates. A P-value of <.05 was considered statistically significant.
Results
Over the study period, 1049 patients were identified as initially meeting criteria for inclusion in the study. Of those, 31 were excluded and the remaining 1018 patients were included in the analysis, with 799 patients having a diagnosis of cystitis and 219 having a diagnosis of pyelonephritis (Table 1). In those with cystitis, patients with AR cultures were significantly more likely to be male (P = .03) and had a significantly higher median age (P = .003) compared to the pan-susceptible (PS) culture group. History of residence in a facility, catheterization, current antibiotic use, and a history of MDRO growth were all significantly more common in the AR group compared to PS group. Among those with pyelonephritis, there were no significant differences between the AR and PS groups with regards to age or sex. There were significantly more patients with a history of diabetes mellitus (P = .02) and a history of MDRO growth (P = .003) in the AR group compared to the PS group. Patients with cystitis that were discharged on initially inappropriate (n = 209) versus appropriate (n = 590) antibiotics were not more likely to return to the ED within 30 days with a related complaint (23.0% vs 21.7%, respectively; P = .73). However, patients with pyelonephritis who were discharged on initially inappropriate (n = 52) versus appropriate (n = 167) antibiotics were more likely to return to the ED within 30 days (32.7% vs 18.6%, respectively; P = .03).
Table 1.
Baseline Characteristics for Patients With Cystitis and Pyelonephritis.
| Cystitis | Pyelonephritis | |||||
|---|---|---|---|---|---|---|
| Antibiotic-resistant (AR) cultures | Pan-susceptible (PS) cultures | P-value | Antibiotic-resistant (AR) cultures | Pan susceptible (PS) cultures | P-value | |
| N = 524 | N = 275 | N = 120 | N = 99 | |||
| Demographics | ||||||
| Age, median (IQR) | 61 (41-72) | 53 (30-70) | .003 | 41 (27-60) | 35 (25-60) | .27 |
| Age≥50 y, n (%) | 337 (64.3) | 153 (55.6) | .02 | 46 (38.3) | 33 (33.3) | .44 |
| Male, n (%) | 151 (28.8) | 60 (21.8) | .03 | 26 (21.7) | 20 (20.2) | .79 |
| Race | .38 | .88 | ||||
| African American, n (%) | 228 (43.5) | 132 (48.0) | 50 (41.7) | 40 (40.4) | ||
| Caucasian, n (%) | 273 (52.1) | 129 (46.9) | 61 (50.8) | 53 (53.5) | ||
| Other, n (%) | 23 (4.4) | 14 (5.1) | 9 (7.5) | 6 (6.1) | ||
| Weight (kg), median (IQR) | 76 (64-93) | 76 (61-89) | .18 | 73 (59-92) | 68 (60-84) | .15 |
| BMI (kg/m2), median (IQR) | 27 (23-33) | 27 (22-32) | .14 | 27 (23-32) | 25 (22-29) | .02 |
| SCr (mg/dL), median (IQR) | 0.9 (0.8-1.2) | 0.9 (0.8-1.1) | .02 | 0.9 (0.8-1.1) | 0.9 (0.8-1.1) | .44 |
| GFR (mL/min), median (IQR) | 78 (53-113) | 87 (51-122) | .20 | 95 (71-107) | 94 (72-121) | .33 |
| Patient-specific risk factors | ||||||
| Diabetes mellitus, n (%) | 140 (26.7) | 59 (21.5) | .10 | 29 (24.2) | 12 (12.1) | .02 |
| Cardiovascular disease, n (%) | 139 (26.5) | 62 (22.5) | .22 | 19 (15.8) | 12 (12.1) | .43 |
| Psychiatric disorder, n (%) | 49 (9.4) | 20 (7.3) | .32 | 7 (5.8) | 3 (3.0) | .32 |
| Dementia, n (%) | 31 (5.9) | 13 (4.7) | .48 | 1 (0.8) | 0 (0) | >.99 |
| Immunosuppression, n (%) | 77 (14.7) | 35 (12.7) | .45 | 12 (10.0) | 10 (10.1) | .98 |
| Previous UTIs, n (%) | 156 (29.8) | 67 (24.4) | .11 | 45 (37.5) | 28 (28.3) | .15 |
| Renal replacement therapy, n (%) | 7 (1.3) | 7 (2.5) | .26 | 4 (3.3) | 4 (4.0) | .78 |
| Residence in facility, n (%) | 31 (5.9) | 6 (2.2) | .02 | 0 (0) | 0 (0) | — |
| Catheterization, n (%) | 91 (17.4) | 33 (12.0) | .047 | 13 (10.8) | 6 (6.1) | .21 |
| Urinary tract abnormality, n (%) | 55 (10.5) | 23 (8.4) | .34 | 7 (5.8) | 9 (9.1) | .36 |
| Current antibiotic use, n (%) | 33 (6.3) | 7 (2.5) | .02 | 13 (10.8) | 5 (5.1) | .12 |
| IV antibiotic within 90 d, n (%) | 84 (16.0) | 31 (11.3) | .07 | 9 (7.5) | 10 (10.1) | .50 |
| Hospitalized within 30-days, n (%) | 86 (18.4) | 35 (12.7) | .17 | 13 (10.8) | 8 (8.1) | .49 |
| History of MDRO, n (%) | 66 (12.6) | 6 (2.2) | <.001 | 13 (10.8) | 1 (1.0) | .003 |
| Patient-specific risk factors ≥2, n (%) | 283 (54.0) | 107 (38.9) | <.001 | 51 (42.5) | 29 (29.3) | .04 |
Note. IQR = interquartile range; BMI = body mass index; SCr = serum creatinine; GFR = glomerular filtration rate; UTI = urinary tract infection; IV = intravenous; MDRO = multi-drug resistant organism.
Regression analysis demonstrated that patients with a diagnosis of cystitis and ≥2 patient-specific risk factors had significantly increased odds of drug resistance to ≥1 classes of antibiotic(s) (Odds Ratio [OR] = 1.70, 95% Confidence Interval [CI] = 1.24-2.32). A similar analysis in those diagnosed with pyelonephritis demonstrated that patients with ≥2 patient-specific risk factors had an increased odds of antimicrobial resistance to ≥1 classes of antibiotic(s), although this was not statistically significant (OR = 1.83, 95% CI = 0.98-3.42). For patients that specifically grew E. coli (n = 614, 60.3%), those with a diagnosis of cystitis had a significantly increased odds of antibiotic resistance in those with ≥2 patient-specific risk factors (OR = 1.91, 95% CI = 1.25-2.92) but this was not true of patients with a diagnosis of pyelonephritis (OR = 1.49, 95% CI = 0.68-3.27). For those patients who specifically grew a MDRO (n = 363, 35.7%), there was a significantly greater odds of growing a MDRO in patients with a diagnosis of cystitis and ≥2 patient-specific risk factors (OR = 1.89, 95% CI = 1.39-2.57), however this was not significant in patients presenting with a diagnosis of pyelonephritis (OR = 1.81, 95% CI = 0.93-3.54).
In order to identify oral antimicrobial therapy with the greatest likelihood of appropriateness in those patients with <2 and those ≥2 patient-specific risk factors, organisms with the same antibiotic susceptibility testing to E.coli (n = 784, 77.0%) were combined and analyzed (Table 2). For those patients with ≥2 patient-specific risk factors, these organisms were significantly more likely to be susceptible to third generation cephalosporins (89.5%) when compared to all other oral agents tested (P < .05 for all comparisons). For those patients with <2 patient-specific risk factors, these organisms were significantly more likely to be susceptible to third generation cephalosporins (91.9%) when compared to all other oral agents tested (P < .05 for all comparisons) with the exception of nitrofurantoin (88.3%, P = .08).
Table 2.
Antibiogram of Common Urinary Pathogens Stratified by Patient-Specific Risk Factors.
| Organism | # Urinary isolates | Amoxicillin/Clavulanate | First-generation Cephalosporin-Uncomplicated | First-generation Cephalosporin–Complicated | Third-generation Cephalosporin | Ciprofloxacin/Levofloxacin | TMP/SMX | Nitrofurantoin |
|---|---|---|---|---|---|---|---|---|
| ≥2 Patient-specific risk factors | ||||||||
| Enterobacter aerogenes, Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, n (%) | 314 (70.1) | 244 (77.7) | 257 (81.8) | 194 (61.8) | 281 (89.5) | 231 (73.6) | 230 (73.2) | 239 (76.1) |
| <2 Patient-specific risk factors | ||||||||
| Enterobacter aerogenes, Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, n (%) | 470 (82.5) | 390 (83.0) | 412 (87.7) | 333 (70.9) | 432 (91.9) | 399 (84.9) | 370 (78.7) | 415 (88.3) |
Note. TMP/SMX = trimethoprim-sulfamethoxazole.
Discussion
Patients presenting with a diagnosis of cystitis and ≥2 patient-specific risk factors had a significantly greater odds of growing an AR pathogen. For patients presenting with a diagnosis of pyelonephritis, the odds of identifying an AR pathogen were also higher although not statistically significant. These results were consistent across the subgroups that isolated only E. coli and MDROs. The selection of appropriate empiric antibiotic therapy may also have clinical significance, as significantly fewer patients with pyelonephritis that received appropriate therapy on discharge returned to the ED within 30 days.
Previous studies have suggested that possible risk factors may exist that are associated with antimicrobial resistance in UTIs presenting to the ED.12,17-20 One single center study evaluated the rates of E.coli susceptibility to levofloxacin and TMP-SMX in 222 patients discharged from an ED. 20 They found that male sex, age, presence of hypertension, diabetes, chronic respiratory disease, nursing home residence, previous antibiotic use, previous diagnosis of a UTI, existence of renal or genitourinary abnormalities, and prior surgical procedures were all significantly associated with resistance. Another single center study included 21 414 urine cultures compiled from inpatients, the ED, and the outpatient setting to evaluate risk factors associated with ESBL-producing E. coli and Klebsiella species. 19 They identified male sex, urinary catheterization, inpatient status, and increasing age as significant risk factors for ESBL infection or colonization. Although the sample size was robust, the inclusion of inpatients, outpatients, and ED urine cultures makes its applicability to the ED challenging as susceptibility patterns for resistant organisms often differ among community and hospital-acquired UTIs. 20 One multi-center study of 11 EDs evaluating factors associated with the resistance of E.coli to TMP-SMX in 403 female patients with pyelonephritis, the authors found that TMP-SMX use within the previous 2 days and Hispanic ethnicity were the only factors associated with antimicrobial resistance. 17 A 2018 systematic review of the available literature attempted to alleviate some of these disparities and evaluated risk factors for multi-drug resistance in UTIs from 25 studies including 31 284 patients. 18 The authors found that the most commonly identified risk factor was previous antibiotic use in 16 of the 20 included studies. Other identified risk factors were urinary catheterization, previous hospitalization, and nursing home residence. Risk factors such as immunosuppression and diabetes had less data evaluating their association with multi-drug resistance and the authors concluded that more research is needed in this area.
Our findings add to and enhance the current literature by expanding the size and diversity of the population investigated, both in terms of diagnosis, organisms, and characteristics. Through the inclusion of all antibiotics tested for susceptibility based on the organism it allows for a greater generalizability of the treatment approach based on risk factors. We found that residence in a facility, current antibiotic use, and history of MDRO occurred more frequently in patients with antibiotic resistance, including MDRO in patients with cystitis. A history of a MDRO was also more frequent among patients with antibiotic resistance in both the cystitis and pyelonephritis patient populations. This finding is consistent with the large multinational study which found that a patient’s previous urine culture could be utilized to predict the organism and susceptibility for empirical treatment. 19 Additional authors have found that choosing an agent concordant with previous microbiologic data significantly increased the chance of accuracy of therapy for MDRO UTIs, even if the previous urinary pathogen was a different species. 30 Further, this study adds to the body of literature by reporting additional data on less commonly evaluated factors. Immunosuppression, due to disease or medication-induced, was not more common in patients with antibiotic resistance. However, a history of diabetes was found to be significantly more common in the AR group only in patients diagnosed with pyelonephritis. Although previous hospitalization and previous UTIs did not occur more frequently in patients with resistance to 1 or more antibiotics, these factors were more common in patients with MDRO.
The importance of appropriate empiric antibiotic selection cannot be overstated. Appropriate empiric antibiotic therapy is associated with a significant increase in the rate of symptom resolution within 3 days (67% vs 45%, P = .001). 22 Some have suggested that the utilization of a 20% resistance prevalence at which an agent is no longer recommended for empirical treatment in the setting of a UTI is a reasonable starting point for identifying therapies to recommend. 2 Based on these results, this would result in amoxicillin/clavulanate, first generation cephalosporins, third generation cephalosporins, fluroquinolones, and nitrofurantoin as options for patients with <2 risk factors and first generation cephalosporins and third generation cephalosporins for those with ≥2 risk factors, prior to adjusting antibiotic selection based on the diagnosis of cystitis or pyelonephritis. This empiric selection should also further be tailored to the interaction of individual risk factors in higher risk individuals. The selection of appropriate empiric antibiotic therapy has the potential to yield not only improved clinical outcomes, but also reduced financial burdens for the patient through fewer costs of additional antibiotic therapy and return ED visits. In conjunction with an EMP culture follow-up program, the identification of risk factors for antimicrobial resistance to assist practitioners in the optimization of empiric antibiotic selection is an important next step in elevating the care of this population.
Limitations to this study include the retrospective, single center design of the review. Not all patients presenting with symptoms of a UTI have their urine cultured and are not reflected in our analysis. Follow-up analysis was limited to ED visits at the study site and did not include clinic or ED visits at another institution. Available information was limited to documentation in the EMR, which may not be all-inclusive with regards to past medical history. Although our overall sample size was robust, the pyelonephritis group was limited in number, which may have contributed to the lack of significant findings. Additionally, an inherent limitation is the limited generalizability given geographic-specific antimicrobial resistance patterns. Also, since resistance may vary based on source, this study concentrates on UTIs and may not be applicable to other sources of infection.
Conclusion
For patients with cystitis discharged from the ED, those with ≥2 patient-specific risk factors had significantly increased odds of antibiotic resistance. Patients with pyelonephritis, but not cystitis, who were discharged on inappropriate antibiotics had an increased likelihood of returning to the ED within 30 days.
Footnotes
Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
ORCID iDs: Erin R. Weeda 
https://orcid.org/0000-0001-7876-5802
Kyle A. Weant
https://orcid.org/0000-0003-0835-7955
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