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Article

Extended-Spectrum β-lactamase-Producing Enterobacteriaceae Shedding in Farm Horses Versus Hospitalized Horses: Prevalence and Risk Factors

by
Anat Shnaiderman-Torban
1,
Shiri Navon-Venezia
2,3,†,
Ziv Dor
2,
Yossi Paitan
4,5,
Haia Arielly
5,
Wiessam Abu Ahmad
6,
Gal Kelmer
1,
Marcus Fulde
7 and
Amir Steinman
1,*,†
1
Koret School of Veterinary Medicine (KSVM), The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot 7610001, Israel
2
Department of Molecular Biology, Faculty of Natural Sciences, Ariel University, Ariel 40700, Israel
3
The Miriam and Sheldon Adelson School of Medicine, Ariel University, Ariel 40700, Israel
4
Department of Clinical Microbiology and Immunology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
5
Clinical Microbiology Lab, Meir Medical Center, Kfar Saba 4428164, Israel
6
Braun School of Public Health and Community Medicine, Hebrew University, Jerusalem 9112102, Israel
7
Institute of Microbiology and Epizootics, Department of Veterinary Medicine at the Freie Universität Berlin, Berlin 14163 Germany
*
Author to whom correspondence should be addressed.
†
These authors had equal contribution.
Animals 2020, 10(2), 282; https://doi.org/10.3390/ani10020282
Submission received: 15 January 2020 / Revised: 6 February 2020 / Accepted: 7 February 2020 / Published: 11 February 2020
(This article belongs to the Special Issue Antimicrobial Resistance in Horses)
Browse Figure
Versions Notes

Abstract

:

Simple summary

This prospective study investigated the prevalence, molecular characteristics and risk factors of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae (ESBL-E) shedding in three equine cohorts: (i) farm horses (13 farms, n = 192); (ii) on admission to a hospital (n = 168) and; (iii) horses hospitalized for ≥72 h re-sampled from cohort (ii) (n = 86). Bacteria were isolated from rectal swabs, identified, antibiotic susceptibility patterns were determined, and medical records and owners’ questionnaires were analyzed for risk factor analysis. ESBL shedding rates significantly increased during hospitalization (77.9%, n = 67/86), compared to farms (20.8%, n = 40/192), and horses on admission (19.6%, n = 33/168). High bacterial species diversity was identified, mainly in cohorts (ii) and (iii), with high resistance rates to commonly used antimicrobials. Risk factors for shedding in farms included horses’ breed (Arabian), sex (stallion), and antibiotic treatment. Older age was identified as a protective factor. We demonstrated a reservoir for antibiotic-resistant bacteria in an equine hospital and farms, with a significant ESBL-E acquisition. In light of our findings, in order to control ESBL spread, we recommend conducting active ESBL surveillance programs alongside antibiotic stewardship programs in equine facilities.

Abstract

We aimed to investigate the prevalence, molecular characteristics and risk factors of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae (ESBL-E) shedding in horses. A prospective study included three cohorts: (i) farm horses (13 farms, n = 192); (ii) on hospital admission (n = 168) and; (iii) horses hospitalized for ≥72 h re-sampled from cohort (ii) (n = 86). Enriched rectal swabs were plated, ESBL-production was confirmed (Clinical and Laboratory Standards Institute (CLSI)) and genes were identified (polymerase chain reaction (PCR)). Identification and antibiotic susceptibility were determined (Vitek-2). Medical records and owners’ questionnaires were analyzed. Shedding rates increased from 19.6% (n = 33/168) on admission to 77.9% (n = 67/86) during hospitalization (p < 0.0001, odds ratio (OR) = 12.12). Shedding rate in farms was 20.8% (n = 40/192), significantly lower compared to hospitalized horses (p < 0.0001). The main ESBL-E species (n = 192 isolates) were E. coli (59.9%, 115/192), Enterobacter sp. (17.7%, 34/192) and Klebsiella pneumoniae (13.0%, 25/192). The main gene group was CTX-M-1 (56.8%). A significant increase in resistance rates to chloramphenicol, enrofloxacin, gentamicin, nitrofurantoin, and trimethoprim-sulpha was identified during hospitalization. Risk factors for shedding in farms included breed (Arabian, OR = 3.9), sex (stallion, OR = 3.4), and antibiotic treatment (OR = 9.8). Older age was identified as a protective factor (OR = 0.88). We demonstrated an ESBL-E reservoir in equine cohorts, with a significant ESBL-E acquisition, which increases the necessity to implement active surveillance and antibiotic stewardship programs.

1. Introduction

Extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae (ESBL-E) poses a clinical challenge to both human and veterinary clinicians. ESBLs confer resistance to penicillins, cephalosporins, and aztreonam and are often accompanied by fluoroquinolone resistance, which even further narrows antibiotic treatment options [1]. Moreover, many ESBL genes are encoded on large plasmids, which enables lateral transfer between different bacterial species, within the same host and between different hosts [2]. In human medicine, ESBL production is associated with increased morbidity, higher overall and infection-related mortality, increased hospital length of stay, delay of targeted appropriate treatment, and higher costs [3,4]. Risk factors for colonization and infection in humans include severe illness with prolonged hospital stays, the presence of invasive medical devices for a prolonged duration and antibiotic use [2].
Within the last decade, a growing burden of ESBL-E in companion animals is being observed, both as gut colonizing bacteria and as infecting pathogens, causing wounds, respiratory, urogenital, gastro-intestinal, umbilical infections, and bacteremia [5,6,7,8]. Horses were described as carriers, as well as infected by ESBL-E, in equine clinics and in farm settings [9,10]. Prevalence of ESBL-producing E. coli carriage in horses varies between 4–44% in different European countries [11,12,13], with a lower carriage prevalence in equine riding centers in comparison with equine clinics [10]. In equine community settings, being stabled in the same yard with a recently hospitalized horse was identified as a risk factor for ESBL-producing E. coli carriage [14]. Risk factor analysis in the level of the farm revealed that the odds of being an ESBL/AmpC-producing E. coli premises were higher among riding schools than breeding premises, if premises housed a horse that had been medically treated with antibiotics within the last three months, and also in premises where the staff consisted of more than five persons [13]. However, risk factors for shedding of different ESBL-E species within horses were not yet reported.
We aimed to investigate and compare ESBL-E shedding in different equine cohorts, including farm horses, horses on admission to an equine hospital and during hospitalization, as well as to determine risk factors for shedding. We hypothesized that shedding rates increase during hospitalization, that previous antibiotic treatment is a risk factor for shedding and that shedding on admission and during hospitalization is associated with clinical signs, prolonged hospitalization, and severe outcome.

2. Materials and Methods

2.1. Equine Study Cohorts, Study Design, and Sampling Methods

This prospective study was performed on 13 farms throughout Israel and in the Koret School of Veterinary Medicine—Veterinary Teaching Hospital (KSVM-VTH). The study was approved by the Internal Research Review Committee of the KSVM-VTH (Reference numbers: KSVM-VTH/15_2015, KSVM-VTH/23_2015). Rectal swabs were collected from the horses with owner consent. On admission, sampling was performed prior to any medical treatment in the hospital. When horses survived and were not discharged, a second sample was taken 72 h post-admission. Farm horses were located in different regions of Israel to roughly represent the population.

2.2. Demographic and Medical Data

For farm horses (cohort (i)), owners’ questionnaires were reviewed for data regarding individual horses, including the originating farm, signalment (age, sex, and breed), duration of the horse’s accommodation in the farm, hospitalization and antibiotic treatments within the previous year.
For hospitalized horses (cohort (ii)), medical records were reviewed for the following information: signalment (age, sex, and breed), geographic origin, previous admission to the hospital within the previous year (yes/no), clinical signs, duration of illness before admission, antibiotic therapy before and during hospitalization, surgical procedures, other medications, hospitalization length, short-term outcome, and admission charge.

2.3. ESBL-E Isolation and Species Identification

Rectal specimens [14] were collected using bacteriological swabs (Meus s.r.l., Piove di Sacco, Italy) and were inoculated directly into a Luria Bertani infusion enrichment broth (Hy-Labs, Rehovot, Israel) to increase the sensitivity of ESBL-E detection [15]. After incubation at 37 °C (18–24 h), enriched samples were plated onto Chromagar ESBL plates (Hy-Labs, Rehovot, Israel), at 37 °C for 24 h. Colonies that appeared after overnight incubation at 37 °C were recorded, and one colony of each distinct color was re-streaked onto a fresh Chromagar ESBL plate to obtain a pure culture. Pure isolates were stored at −80 °C for further analysis.
Isolates were subjected to Vitek-MS (BioMérieux, Inc., Marcy-l’Etoile, France) for species identification or to Vitek-2 (BioMérieux, Inc., Marcy-l’Etoile, France) for species identification and/or antibiotic susceptibility testing (AST-N270 Vitek 2 card). Chloramphenicol, enrofloxacin, and imipenem were analyzed using disc diffusion assay (Oxoid, Basingstoke, UK). ESBL-production was confirmed by combination disk diffusion using cefotaxime and ceftazidime discs (Oxoid, Basingstoke, UK), as well as cefotaxime and ceftazidime with clavulanic acid (Sensi-Discs BD, Breda, The Netherlands). Results were interpreted according to the Clinical and Laboratory Standards Institute (CLSI) guidelines [16]. Multidrug-resistant (MDR) bacteria were defined as such due to their in vitro resistance to three or more classes of antimicrobial agents [17].

2.4. Molecular Characterization of ESBL-E

Isolates were examined for the presence of the blaCTX-M group using a multiplex polymerase chain reaction (PCR) from ESBL-E DNA lysates, as previously described [18]. Isolates that were found to be blaCTX-M PCR negative were further examined for the presence of blaOXA-1, blaOXA2, blaOXA10 [19], blaTEM, and blaSHV groups [20]. ESBL-producing E. coli isolates were subjected to PCR for the detection of mdh and gyrB genes in order to determine the presence of the worldwide pandemic E. coli ST131 lineage [21].

2.5. Sample Size and Statistical Analysis

The minimal sample size (number of animals sampled) for farm horses was calculated using WinPepi, based on an estimated shedding rate of 25% for ESBL-E in equine community livery premises [22] and on the fact that Israel is endemic for ESBL-E [23], with a confidence level of 95% and an acceptable difference of 7%, resulting in n = 147.
The minimal sample size for horses on admission to hospital was based on the expected difference between ESBL-E shedding and non-shedding horses and the percentage of admitted horses that were treated with antibiotics before admission since antibiotic treatment was assumed to be a risk factor for shedding [12]. Since there is no previous study revealing percentages of antibiotic-treated horses and ESBL shedding, data for this calculation was based on a human study [24]. Estimating that 25% of horses on admission are ESBL shedders (representing the equine community) and that 72% and 44% of horses were treated with antimicrobials within shedders and non-shedders, respectively, with a 5% significance level and power of 80%, the total required sample size is 145 horses, including 116 non-shedders and 29 shedders.
Risk assessment was performed using Chi-square or Fisher’s exact tests for association between individual variables, shedding and ESBL-E acquisition. Descriptive statistics were used to describe shedding rates. Continuous variables were analyzed using t-tests or Mann–Whitney U-tests. p ≤ 0.05 was considered statistically significant. For risk factor analysis of farm horses, a logistic regression model (multivariable analysis) was conducted using all the significant variables in the univariable analysis at a significance level of p < 0.2 using the ENTER method (IBM SPSS Statistics 25). Categorical data were summarized by the number of cases (percentage) and confidence intervals (95%) were calculated by Fisher’s (WinPEPI 11.15 Describe A).
In order to compare between shedding rates and antibiotic resistance rates within horses on admission and during hospitalization (cohorts (ii) and (iii), respectively), a mixed effect logistic regression model was conducted (STATA version 13). Resistance was defined as complete resistance (not including “intermediate resistance”). Odds ratio (OR) for a significant change in antibiotic resistance rates is defined as OR for a change in one resistance category (e.g., a change from “susceptible” to “intermediate” or from “intermediate” to “resistant”). A comparison between shedding rates and antibiotic resistance rates between farm horses (cohort (i)) and horses on admission (cohort (ii)) was performed using Chi-square.

3. Results

3.1. Characterization of the Equine Study Populations (Table 1)

Overall, 192 horses were sampled, originating from 13 farms across Israel (June 2016–September 2018). The average number of sampled horses per farm was 15 (range: 3–26 horses).
On admission, 168 horses were sampled (November 2015 to April 2016). Horses were admitted to hospitalization due to the following reasons: gastro-intestinal pathologies (33%, n = 55/168), orthopedic disorders (17%, n = 29/168), healthy (mares of sick neonatal foals or foals of sick mares, 17%, n = 29/168), reproduction disorders (12%, n = 20/168), neonatology disorders (12%, n = 20/168), respiratory disorders (4%, n = 7/168), and others (including ophthalmic, hematology, endocrine, teeth disorders, and tumors, 5%, n = 8/168). The median length of illness before admission was one day (range: several hours–750 d). Horses hospitalized for ≥72 h were re-sampled (n = 86).

3.2. Antibiotic Therapy, Surgical Procedures, Length of Stay, and Outcome

A proportion of 8.3% (n = 16/192) of farm horses was hospitalized within the previous year, ranging from 0–30% between farms. A proportion of 19.8% (n = 38/192) of horses were treated with antibiotics within the previous year, ranging from 0–61% between farms. On admission, 9.5% (n = 16/168) of horses were reported to be previously hospitalized (within a year period), and 16.1% (n = 27/168) of horses were treated with antibiotics within the previous year. Previous hospitalization and antibiotic treatment prevalence rates were not significantly different in comparison with farm horses.
During hospitalization, 50.6% of horses (n = 85/168) were treated with antibiotics, a proportion which is significantly higher than antibiotic treatment in farms and prior to admission (p < 0.0001). Surgical procedures were performed in 36.9% of horses (n = 62/168). The median length of stay was three days (range: several hours-21 d). Out of all horses admitted to hospitalization, 84.4% survived to discharge (n = 142/168).

3.3. Prevalence of ESBL-E Shedding

Within farm horses, shedding rate was 20.8% [n = 40/192, 95% Confidence interval (CI) 15.3–27.3%, Table 1]. Shedding rate on admission was 19.6% (n = 33/168, 95% CI: 13.9–26.5%), which was not statistically different from shedding rate in farms (p = 0.79). Shedding rate of hospitalized horses (re-sampled) was 77.9% (n = 67/86, 95% CI 67.7–86.1%), which was significantly higher than the shedding rate on admission and in farms (p<0.001, OR = 12.12, 95% CI 3.92–37.49). Out of 67 hospitalized shedding horses, 77.6% (n = 52/67, 95% CI 65.8–86.9%) did not shed ESBL-E on admission.

3.4. Distribution of ESBL-E Species and ESBL Genes

Overall, 192 ESBL-E isolates were analyzed (Table A1). Fourteen bacterial species were identified of which three were identified in all cohorts—E. coli, Klebsiella pneumoniae, and Enterobacter cloacae (Figure 1). The most prevalent bacterial species in all cohorts was E. coli, consisting of 79.2% of isolates from farms, 66.7% from horses on admission, and 49.0% from hospitalized horses. However, the prevalence of E. coli decreased in horses on admission and in hospitalized horses, as the diversity of other ESBL-E species increased, from four species in farms to five species on admission and twelve species in hospitalized horses. Nosocomial ESBL-E species that were not identified in farms and on admission included Citrobacter freundii (n = 3/105), Salmonella spp (n = 3/105), K. oxytoca, Citrobacter brakii, E. vulneris, Pantoea spp, Proteus mirabilis, and Raoultella ornithinolytica (n = 1/105 each). The pandemic hypervirulent E. coli ST131 [25] was identified in three horses: two horses on admission and one horse during hospitalization. The main ESBL gene was the blaCTX-M-1 group in all cohorts (total 56.8% of all isolates, Table 2).

3.5. Antibiotic Susceptibility Profiles

Antibiotic resistance rates varied between cohorts, with a significant increase during hospitalization. All isolates from all cohorts were susceptible to imipenem (Table 3).
Among bacteria that grew on Chromagar ESBL plates, the prevalence of MDR bacteria was 89.6%, 71.8%, and 94.3% in farms, horses on admission, and hospitalized horses, respectively. The prevalence rate was significantly higher in isolates originated from hospitalized horses compared to horses on admission (p = 0.001, Table 2).

3.6. Risk Factor Analysis for ESBL-E Shedding

3.6.1. Farm Horses

In univariable analysis, horses’ breed, sex, hospitalization in the previous year, antibiotic treatment in the previous year, and age were significantly associated with ESBL-E shedding (Table A2). Since the Arabian breed was the most prevalent breed sampled, we clustered all other breeds as one category in the multivariable analysis. In a logistic regression model, the breed (Arabian), sex (stallion versus mare, which was the reference in this category), and antibiotic treatment in the previous year were identified as risk factors for shedding. Age greater than one year was identified as a protective factor (Table 4).

3.6.2. Horses on Admission

Signalment (age, sex, and breed), geographic origin, prior hospitalizations in the last year, clinical signs, length of illness before admission, antibiotic therapy before and during hospitalization, surgical procedures, other medications, hospitalization length, short-term outcome, and admission charge were not associated with ESBL-E shedding on admission (Table A2). Sex, hospitalization length, and admission charge resulted in p < 0.2, therefore, were analyzed via a logistic regression model, which did not yield any significant associations (Table A3).

3.6.3. Horses During Hospitalization

There was no association between ESBL shedding 72 h post-admission and on admission, clinical signs on admission, antibiotic treatment during hospitalization, surgical procedures during hospitalization, length of stay, admission charge and outcome (Table A2).

4. Discussion

This study investigates ESBL-E shedding in three equine cohorts, including farm horses, representing community equine, as well as horses on admission to the hospital and during hospitalization. Studies regarding antibiotic-resistant pathogens shedding, either in farm horses or in hospitalized horses were reported previously from different European countries [13,22,26,27]. Our study compares different equine cohorts within the same country. Both community and hospital cohorts are of great interest, from a veterinary and a ‘one health’ perspective, therefore it is highly valuable to compare these cohorts.
We found high ESBL-E shedding rates (Table 2), an increased bacterial species diversity (Figure 1) as well as in the ESBL-E genes variety (Table 2). An increase in shedding rates may be due to the acquisition of bacteria, plasmids or resistance genes. The main bacterial species in all cohorts was E. coli, with decreased incidence on admission and during hospitalization, due to increased incidence of other nosocomial ESBL-producing bacterial species. The main ESBL gene group was CTX-M-1, as was previously reported in community horses [26]. However, on admission and during hospitalization, CTX-M-1 incidence decreases, alongside an increase in the number of ESBL genes. A study conducted in an equine hospital in the UK demonstrated the emergence of ESBL-producing E. coli during a decade [26], whereas we demonstrated a significant increase in ESBL-E shedding during individual horses’ hospitalization. These findings support an urgent necessity in active surveillance and infection control programs in veterinary facilities and hospitals.
In addition, there is a need to set strict antibiotic stewardship programs in veterinary medicine, specifically in companion animals’ facilities, with specific guidance and enforcement. According to a recommendation published by the Committee for Medicinal Products for Veterinary Use (CVMP) of the European Union, there is a need to reserve fluoroquinolones, third and fourth generation cephalosporins for treatment when other options are likely to fail, and whenever possible, treatment should be supported by an antimicrobial susceptibility testing [28]. In practice, fluoroquinolones and cephalosporins are in use in equine medicine, sometimes as a first-line choice [29,30]. In our study, ESBL-E shedding as well as resistance rates for chloramphenicol, enrofloxacin, gentamicin, nitrofurantoin, and trimethoprim-sulpha increased significantly during hospitalization, resulting in a significant increase in MDR bacterial species shedding (Table 2 and Table 3). In light of our findings, as well as increasing resistance rates in other equine studies, we recommend implementing antibiotic stewardships in equine clinics and hospitals [31,32].
We also aimed to determine risk factors for shedding. We did not find significant associations between shedding on admission and during hospitalization to medical data. During the study period, we sampled all horses on admission, which represented a heterogeneous population, including critically ill horses alongside healthy mares, which were hospitalized together with their sick foals. Therefore, the lack of significant risk factors may be due to high variation in the equine population. Many of the pathologies on admission were attributed to the gastro-intestinal system, which might influence the intestinal microbiome. However, clinical signs on admission and during hospitalization were not associated with shedding. In farm horses, we detected several risk factors for ESBL-E shedding (Table 4). The Arabian breed was the main breed within farm horses and horses on admission to hospital. These horses in Israel are used mainly for breeding and shows and are held under intensive management, which may explain the risk for ESBL shedding. Interestingly, we detected the ‘stallion’ sex as a risk factor. In human medicine, it is reported that males are more susceptible to diverse bacterial illnesses than females, including an ESBL-E infection [33], presumably related to hormonal influences [34]. This may explain also our findings in veterinary medicine, however, it requires further investigation. Previous antibiotic treatment was identified as a risk factor as well, in agreement with other human and veterinary studies [2,13]. Age older than one year was identified as a protective factor, which may be due to the maturation of immunity. In a national survey of cattle farms in Israel, the prevalence of ESBL-E was higher in calves versus adult cows, where the use of antimicrobial prophylaxis was more common [35]. In human medicine, elderly age is associated with ESBL-E infections [33]. However, in our study, elderly horses older than 20 years old [36] were not prevalent and consisted of 3% (n = 12/360) of the study population. Therefore, elderly age may not be identified as a risk factor.
Our results should also be addressed from a ‘one health’ perspective. We detected resistant zoonotic bacteria both in farms and in hospital settings, which underlines the necessity for awareness and improved management. The human-animal interaction has great psychological and physical established benefits, with a great emphasis on equine-assisted therapy [37,38,39]. Therefore, there is pronounced importance in establishing safety policies involving therapists, physicians, and veterinarians, in order to ensure safe human-equine interactions in community settings [40]. This also applies to veterinary hospital staff. In a longitudinal study involving veterinary hospital staff and students, a higher level of ESBL-producing E. coli carriage was observed longitudinally [41], which underlines the necessity to implement gold standards biosecurity programs in veterinary hospitals.

5. Conclusions

Multi-drug resistant potentially zoonotic bacteria were detected both in farm horses and in hospitalized horses, with a significantly increased shedding during hospitalization. Therefore, we recommend implementing active surveillance programs alongside with infection control and antibiotic stewardship policies, in order to decrease resistance burden and to allow safe human-equine interactions.

Author Contributions

Conceptualization, A.S.-T., S.N.-V. and A.S.; methodology, S.N.-V. A.S., W.A.A, Y.P. and H.A.; software, W.A.A.; validation, A.S.-T., S.N.-V. and A.S.; formal analysis, A.S.-T., Z.D., Y.P. and H.A.; investigation, A.S.-T.; resources, S.N.-V., A.S., M.F., Y.P., G.K.; data curation, A.S.-T.; writing—original draft preparation, A.S.-T., S.N.-V. and A.S.; writing—review and editing, all authors; visualization, all authors; supervision, S.N.-V. and A.S.; project administration, A.S.-T., S.N.-V. and A.S.; funding acquisition, S.N.-V. and A.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

We are grateful to the KSVM-VTH equine department staff, farm owners, employees, and veterinarians for their collaboration in conducting this study.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Antimicrobial susceptibility profiles of individual isolates.
Table A1. Antimicrobial susceptibility profiles of individual isolates.
Num.Horse Serial NumberIsolateOriginBacterial IDAMCIMPENRCHLGENAMKTMSMDR
111.1.1On admissionEscherichia coli20122001
222.1.1Escherichia coli20022121
333.1.1Escherichia coli20022121
466.1.1Citrobacter sedlakii00000000
577.1.1Klebsiella pneumoniae20122021
61515.1.1Escherichia coli20122121
71515.1.2Klebsiella pneumoniae20202121
81717.1.2Klebsiella pneumoniae20100021
92222.1.1Escherichia coli20022121
102222.1.2Klebsiella pneumoniae20102021
113131.1.1Escherichia coli10022121
123232.1.1Escherichia coli20120021
134646.1.1Enterobacter cloacae20000000
146060.1.1Escherichia coli20100021
157474.1.2Enterobacter cloacae20222221
167777.1.1Escherichia coli20100021
178181.1.1Escherichia coli20122021
18101101.1.1Escherichia coli20222021
19101101.1.2Klebsiella pneumoniae20100020
20107107.1.1Escherichia coli20100021
21112112.1.1Enterobacter cloacae20010000
22113113.1.1Escherichia coli20100000
23120120.1.1Escherichia coli10222121
24121121.1.1Escherichia coli21220001
25136136.1.1Escherichia coli20220021
26136136.1.2Klebsiella pneumoniae20202121
27144144.1.1Escherichia coli20122121
28153153.1.1Escherichia coli20100020
29162162.1.1Escherichia coli20000101
30176176.1.1Escherichia coli20122121
31177177.1.1Escherichia coli10122021
32179179.1.1Escherichia coli10022021
33203203.1.1Klebsiella pneumoniae00002000
34239239.1.1Enterobacter cancerogenus20000000
35244244.1.1Citrobacter sedlakii 00000 0
36267267.1.1Escherichia coli20100021
37278278.1.1Escherichia coli20100021
38288288.1.1Escherichia coli20100021
39290290.1.1Escherichia coli20100021
4011.2.2During hospitalizationKlebsiella pneumoniae00102021
4155.2.1Escherichia coli00022021
4266.2.1Klebsiella pneumoniae10200021
4366.2.2Escherichia coli00000020
4477.2.1Escherichia coli10002021
4577.2.2Klebsiella pneumoniae10222021
4688.2.1Escherichia coli2012 21
4788.2.2Enterobacter cloacae20222021
481515.2.1Escherichia coli10222021
491515.2.2Enterobacter cloacae20122021
501616.2.1Escherichia coli00120021
511616.2.2Enterobacter cloacae20222021
522929.2.1Escherichia coli10222021
532929.2.2Escherichia vulneris00122021
543131.2.1Escherichia coli10222021
553535.2.1Klebsiella pneumoniae10122021
564646.2.1Pantoea spp102220 1
574646.2.2Escherichia coli10222021
584747.2.1Escherichia coli10222021
594747.2.2Enterobacter cloacae20222221
604949.2.2Enterobacter cloacae20122221
615555.2.1Escherichia coli1 122021
625555.2.2Klebsiella pneumoniae10202021
635656.2.2Enterobacter cloacae20222121
645757.2.1Escherichia coli00 0020
656060.2.1Enterobacter cloacae20222021
666060.2.3Escherichia coli10122021
677272.2.3Salmonella group100 2221
687575.2.3Enterobacter cloacae20122021
698484.2.1Escherichia coli00022021
708585.2.1Escherichia coli00122021
718585.2.2Enterobacter cloacae20222021
728787.2.1Escherichia coli00220021
738787.2.2Escherichia coli10222021
748989.2.1Escherichia coli10222021
758989.2.2Klebsiella pneumoniae10202021
769191.2.1Escherichia coli10222221
779191.2.2Enterobacter cloacae20222021
78101101.2.1Escherichia coli10221021
79101101.2.2Klebsiella pneumoniae00120021
80107107.2.1Escherichia coli10222021
81107107.2.2Enterobacter cloacae20222221
82107107.2.4Enterobacter cloacae20122021
83108108.2.2Enterobacter cloacae20122021
84113113.2.1Escherichia coli 22
85115115.2.1Escherichia coli00222021
86115115.2.2Citrobacter freundii20222021
87124124.2.1Escherichia coli00222021
88124124.2.3Salmonella enterica10 2221
89126126.2.2Citrobacter brakii20222121
90127127.2.1Escherichia coli10222121
91127127.2.2Enterobacter cloacae20122021
92136136.2.1Escherichia coli10222121
93136136.2.2Klebsiella pneumoniae10202021
94143143.2.1Escherichia coli00022021
95143143.2.2Citrobacter freundii20022021
96144144.2.1Escherichia coli20122021
97144144.2.2Citrobacter freundii20 2121
98144144.2.3Proteus mirabilis10 2001
99148148.2.1Escherichia coli20000021
100149149.2.1Escherichia coli00022021
101149149.2.2Enterobacter cloacae20122221
102152152.2.2Escherichia coli10202021
103156156.2.1Enterobacter cloacae20122221
104156156.2.2Escherichia coli10222021
105158158.2.2Klebsiella pneumoniae10202021
106161161.2.1Escherichia coli10222021
107161161.2.2Enterobacter cloacae20122021
108167167.2.1Klebsiella pneumoniae10122021
109176176.2.1Escherichia coli10022021
110177177.2.1Escherichia coli10122021
111177177.2.2Enterobacter cloacae20122021
112181181.2.1Enterobacter cloacae201 2121
113181181.2.2Escherichia coli10222021
114183183.2.1Klebsiella pneumoniae10122021
115183183.2.2Escherichia coli10022021
116195195.2.1Escherichia coli10122021
117212212.2.1Escherichia coli001 2000
118216216.2.1Escherichia coli00220020
119219219.2.1Escherichia coli102 2021
120222222.2.1Klebsiella pneumoniae10122021
121222222.2.2Escherichia coli00220021
122223223.2.1Escherichia coli10222001
123224224.2.1Escherichia coli10222021
124224224.2.2Klebsiella pneumoniae10222021
125228228.2.1Klebsiella pneumoniae00202001
126229229.2.1Escherichia coli10222221
127229229.2.2Salmonella enterica10222221
128234234.2.1Raoultella ornithinolytica20122221
129237237.2.1Escherichia coli00020021
130238238.2.1Klebsiella pneumoniae10102021
131243243.2.1Escherichia coli00220021
132243243.2.2Enterobacter cloacae20122021
133246246.2.1Escherichia coli10 1021
134246246.2.2Enterobacter cloacae20222021
135265265.2.1Enterobacter cloacae20122021
136272272.2.1Enterobacter cloacae20122021
137273273.2.1Enterobacter cloacae20122021
138278278.2.1Escherichia coli00120021
139278278.2.2Citrobacter sedlakii002200 1
140278278.2.4Klebsiella pneumoniae00222001
141279279.2.1Klebsiella oxytoca20002121
142279279.2.2Escherichia coli00120021
143289289.2.1Escherichia coli10202021
144H40H40.2FarmsEscherichia coli20100021
145H42H42.1Escherichia coli20122121
146H44H44.1Escherichia coli20122121
147H45H45.2Citrobacter farmeri10122021
148H48H48.2Escherichia coli20222021
149H48H48.3Enterobacter cloacae20122121
150H53H53.1Escherichia coli20100021
151H53H53.2Enterobacter cloacae20122121
152H54H54.1Escherichia coli20222021
153H56H56.1Escherichia coli20122121
154H56H56.2Enterobacter cloacae20122121
155H57H57.1Enterobacter cloacae20122121
156H57H57.2Escherichia coli20122121
157H60H60.2Escherichia coli20100021
158H110H110.1Enterobacter cloacae20000000
159H138H138.1Escherichia coli20000001
160H140H140.1Escherichia coli20022121
161H154H154.2Klebsiella pneumoniae20112001
162H157H157.2Klebsiella pneumoniae20200021
163H230H230.1Escherichia coli10122021
164H230H230.2Enterobacter cloacae20122001
165H231H231.1Escherichia coli00100000
166H233H233.1Escherichia coli10122021
168H234H234.1Escherichia coli00122021
169H234H234.2Enterobacter cloacae20122021
170H235H235.1Escherichia coli10122021
171H236H236.1Escherichia coli00122021
172H237H237.1Escherichia coli10122021
173H238H238.1Escherichia coli00122021
174H241H241.1Escherichia coli10122021
175H242H242.1Escherichia coli10122021
176H243H243.1Escherichia coli10122021
177H245H245.1Escherichia coli10122021
178H246H246.1Escherichia coli10122021
179H247H247.1Escherichia coli00122021
180H248H248.1Escherichia coli00122021
181H250H250.1Escherichia coli00122021
182H251H251.1Escherichia coli00122021
183H253H253.1Escherichia coli00122021
184H254H254.1Escherichia coli00122021
185H256H256.1Escherichia coli00100021
186 H257H257.1Escherichia coli10012021
187H258H258.1Escherichia coli00000020
188H259H259.1Escherichia coli00000020
189H263H263.1Escherichia coli00000020
190H265H265.1Escherichia coli10012021
191H267H267.1Escherichia coli00100021
192H268H268.1Escherichia coli10012021
Susceptible = 0, intermediate susceptibility = 1, resistant = 2. Empty cells mean lack of susceptibility test results due to technical reasons.
Table
Table A2. Results of univariable analysis of variables gleaned from the medical records (horses on admission and during hospitalization) and owners’ questionnaires (farm horses). Variables were evaluated for association with the outcome of ESBL-E shedding status of the individual animal.
Table A2. Results of univariable analysis of variables gleaned from the medical records (horses on admission and during hospitalization) and owners’ questionnaires (farm horses). Variables were evaluated for association with the outcome of ESBL-E shedding status of the individual animal.
Population StudiedVariableClassificationp-Value
Farm horsesBreedQuarter Horse
Arabian
Pacer
Warmblood
Pony
Local		<0.0001
SexFemale
Male
Gelding		0.027
FarmNumbered 1–13
Hospitalization within the previous yearYes/No0.018
Antibiotic treatment within the previous yearYes/No<0.0001
AgeRanged from 0.1–23 y<0.0001
Time in farmRanged from 0–23 y0.36
On admissionBreedQuarter Horse
Arabian
Tennessee Walking horse
Friesian
Mangalarga Marchador
Warmblood
Thoroughbred
Miniature horse
Haflinger
Hannoverian
Single footed horse
Missouri Fox Trotter		0.394
AgeYears0.259
SexFemale
Male
Gelding		0.117
Geographical origin (within the country)North
South
Center		0.879
Hospitalization within the previous yearYes/No0.295
Clinical signs on admissionGastro-intestinal disorder
Neonatology disorder
Ophthalmic disorder
Reproduction
Orthopedic disorder
Hematological disorder
Respiratory disorder
Endocrine disorder
Healthy (mares of sick hospitalized foals)		0.587
Length of illness before admissionDays0.618
Antibiotic treatment within the previous yearYes/No0.587
Length of stayDays0.169
Admission charge-0.056
During hospitalizationShedding on admissionYes/No0.9
Clinical signs on admissionGastro-intestinal disorder
Neonatology disorder
Ophthalmic disorder
Reproduction
Orthopedic disorder
Hematological disorder
Respiratory disorder
Endocrine disorder
Tumor
Teeth lesion
Healthy (mares of sick hospitalized foals)		0.428
Antibiotic treatment during hospitalizationYes/No0.841
OutcomeDischarged/Died0.174
Length of stayDays0.29
Admission charge-0.69
Table
Table A3. Risk factor analysis for ESBL-E shedding by horses on admission to hospital (logistic regression).
Table A3. Risk factor analysis for ESBL-E shedding by horses on admission to hospital (logistic regression).
Risk Factorp-ValueOR
Sex (reference: mare)0.647
Stallion0.4090.571 (95% CI 0.151–2.162)
Gelding0.6390.765 (95% CI 0.25–2.34)
Length of stay0.7661 (95% CI 0.997–1)
Admission charge0.1841 (95% 1–1)

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Animals 10 00282 g001 550
Figure 1. ESBL-E species distribution isolated from cohort (i) farm horses ((A), n = 48 isolates), cohort (ii) horses on admission to the hospital ((B), n = 39 isolates) and cohort (iii) 72 h post-admission ((C), n = 105 isolates).
Figure 1. ESBL-E species distribution isolated from cohort (i) farm horses ((A), n = 48 isolates), cohort (ii) horses on admission to the hospital ((B), n = 39 isolates) and cohort (iii) 72 h post-admission ((C), n = 105 isolates).
Animals 10 00282 g001
Table
Table 1. Characterization of farm horses versus horses on admission to hospital.
Table 1. Characterization of farm horses versus horses on admission to hospital.
Equine CohortBreeds 1Median Age 2 (Years ± SD)Sex Distribution 3
Farm horses (n = 192)41.1% Arabians (n = 79/192)
25% pacers (n = 48/192)
15.1% Quarter horses (n = 29/192)
9.9% Warmbloods (n = 19/192)
5.2% local breed (n = 10/192)
3.7% ponies (n = 7/192)		8 ± 5.3mares (72.4%, n = 139/192)
geldings (12.5%, n = 24/192)
stallions (11.5%, n = 22/192) 4
Horses on admission
(n = 168) 		49.4% Arabians (n = 83/168)
19.6% Quarter horses (n = 33/168)
14.3% pacers (n = 24/168)
7.7% Friesians (n = 13/168)
4.8% Warmbloods (n = 8/168)
4.2% others (n = 7/168)		4.5 ± 5.2 mares (68.5%, n = 115/168) geldings (16.1%, n = 27/168) stallions (15.4%, n = 26/168)
1 Breed distribution was not significantly different for Arabians, Quarter horses, and Warmbloods in comparison to farm horses, and was significantly different for the pacers horses (significantly higher in farms, p = 0.012) and Friesians (significantly higher on admission, p < 0.001); 2 Median age of horses on admission was significantly lower than the median age of farm horses (p < 0.0001); 3 Sex distribution was not significantly different between farm horses and horses on admission; 4 Data was not available for seven horses.
Table
Table 2. Shedding rates of extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-E) in farm horses, on admission, and during hospitalization.
Table 2. Shedding rates of extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-E) in farm horses, on admission, and during hospitalization.
Equine CohortShedding (%)Total No. of ESBL-E IsolatesMDR Isolates (%)blaESBL Gene Group (%)
Farm horses40/192 (20.8)
(95% CI: 15.3–27.3%)		4843/48 (89.6)
(95% CI: 77.3–96.5)		CTX-M-1: 35/48 (72.9)
CTX-M-9: 1/48 (2.1)
CTX-M-25: 1/48 (2.1)
SHV-12: 5/48 (10.4)
Horses on admission33/168 (19.6)
(95% CI: 13.9–26.5%)		3928/39 (71.8)
(95% CI: 55.1–85.0%)		CTX-M-1: 24/39 (61.5)
CTX-M-9: 1/39 (2.5)
SHV-12: 3/39 (7.7)
SHV-2: 1/39 (2.5)
SHV-28: 1/39 (2.5)
Hospitalized horses
(72 h post admission) 1		67/86 (77.9) 2
(95% CI 67.7–86.1%)		10599/105 (94.3)
(95% CI: 87.9–97.9%) 3		CTX-M-1: 50/105 (47.6)
CTX-M-2: 8/105 (7.6)
CTX-M-9: 7/105 (6.7)
CTX-M-25: 1/105 (0.95)
OXA-1: 2/105 (1.9)
SHV-12: 26/105 (24.7)
SHV-228: 1/105 (0.95)
1 Horses re-sampled from cohort “horses on admission”; 2 Shedding rate in hospitalized horses is significantly higher than shedding rate on admission and in farms (p < 0.0001, OR=12.12, 95% CI 3.92–37.49); 3 Prevalence of multidrug-resistant (MDR) isolates is significantly higher in isolates originated from hospitalized horses compared to isolates originated from horses on admission (p < 0.001).
Table
Table 3. Antibiotic 1 resistance rates (percentage) of ESBL-E isolates shed by farm horses, horses on admission, and hospitalized horses.
Table 3. Antibiotic 1 resistance rates (percentage) of ESBL-E isolates shed by farm horses, horses on admission, and hospitalized horses.
Equine CohortAMPAMC 2LEXCAZIMPCHL 3ENR 4AMKGEN 5NIT 6TMS 7
Farms10041.7100100066.66.30754.289.6
On admission10082.110085.0046.217.92.648.75.376.3
During hospitalization96.032.099.090.0085.351.510.884.311.095.0
1 Abbreviations: ampicillin (AMP), amoxicillin-clavulanate (AMC), cephalexin (LEX), ceftazidime (CAZ), imipenem (IMP), chloramphenicol (CHL), enrofloxacin (ENR), amikacin (AMK), gentamicin (GEN), nitrofurantoin (NIT), and Trimethoprim- sulpha (TMS); 2 An increase in resistance rates for AMC on admission compared to farms (p = 0.001) and a decrease during hospitalization compared to admission (p < 0.001, OR = 0.1, 95% CI 0.04, 0.26); 3 An increase in resistance rates for CHL during hospitalization compared to admission (p < 0.001, OR = 6.5, 95% CI 2.8, 15); 4 An increase in resistance rates for ENR during hospitalization compared to admission (p < 0.001, OR = 4.2, 95% CI 1.9, 9.5); 5 An increase in resistance rates for GEN during hospitalization compared to admission (p < 0.001, OR = 12.3, 95% CI 2.9, 52.5); 6 An increase in resistance rates for NIT during hospitalization compared to admission (p < 0.001, OR = 3.7, 95% CI 1.4, 9.5); 7 An increase in resistance rates for TMS during hospitalization compared to admission (p < 0.01, OR = 6, 95% CI 1.9, 19.4).
Table
Table 4. Risk factor analysis for ESBL-E shedding by farm horses (logistic regression model).
Table 4. Risk factor analysis for ESBL-E shedding by farm horses (logistic regression model).
Variablep-valueOdds Ratio (95% CI)
Breed (Arabian versus non-Arabian)0.0063.9 (1.5–10.4)
Sex (reference: mare)0.079-
Stallion0.0293.4 (1.1–12.2)
Gelding0.7440.7 (0.07–6.4)
Age0.0080.9 (0.8–0.97)
Hospitalization within the previous year0.1942.9 (0.6–14.8)
Antibiotic treatment within the previous year<0.00019.8 (3.6–26.8)

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MDPI and ACS Style

Shnaiderman-Torban, A.; Navon-Venezia, S.; Dor, Z.; Paitan, Y.; Arielly, H.; Abu Ahmad, W.; Kelmer, G.; Fulde, M.; Steinman, A. Extended-Spectrum β-lactamase-Producing Enterobacteriaceae Shedding in Farm Horses Versus Hospitalized Horses: Prevalence and Risk Factors. Animals 2020, 10, 282. https://doi.org/10.3390/ani10020282

AMA Style

Shnaiderman-Torban A, Navon-Venezia S, Dor Z, Paitan Y, Arielly H, Abu Ahmad W, Kelmer G, Fulde M, Steinman A. Extended-Spectrum β-lactamase-Producing Enterobacteriaceae Shedding in Farm Horses Versus Hospitalized Horses: Prevalence and Risk Factors. Animals. 2020; 10(2):282. https://doi.org/10.3390/ani10020282

Chicago/Turabian Style

Shnaiderman-Torban, Anat, Shiri Navon-Venezia, Ziv Dor, Yossi Paitan, Haia Arielly, Wiessam Abu Ahmad, Gal Kelmer, Marcus Fulde, and Amir Steinman. 2020. "Extended-Spectrum β-lactamase-Producing Enterobacteriaceae Shedding in Farm Horses Versus Hospitalized Horses: Prevalence and Risk Factors" Animals 10, no. 2: 282. https://doi.org/10.3390/ani10020282

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