Antimicrobial Resistance and Biofilm Production in Uropathogens from Renal Disease Patients Admitted to Tribhuvan University Teaching Hospital, Nepal

Dahal, Anuja; Shrestha, Kamal; Karki, Rashmi; Bhattarai, Saraswati; Aryal, Shiva; Deo, Satish Kumar; Regmi, Balmukunda; Willcox, Mark; Mishra, Shyam Kumar

doi:https://doi.org/10.1155/2023/4867817

Journal of Clinical Pharmacy and Therapeutics

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Abstract Introduction Materials and Methods Results Discussion Conclusion Abbreviations Data Availability Ethical Approval Consent Conflicts of Interest Authors’ Contributions Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 4867817 | https://doi.org/10.1155/2023/4867817

Antimicrobial Resistance and Biofilm Production in Uropathogens from Renal Disease Patients Admitted to Tribhuvan University Teaching Hospital, Nepal

Anuja Dahal,¹Kamal Shrestha,²Rashmi Karki,³Saraswati Bhattarai,⁴Shiva Aryal,⁴Satish Kumar Deo,⁵Balmukunda Regmi,¹Mark Willcox,⁶and Shyam Kumar Mishra^2,6

Academic Editor: Keiko Hosohata

Received07 Apr 2023

Revised27 Jun 2023

Accepted03 Jul 2023

Published19 Jul 2023

Abstract

Background. Various antibiotics are prescribed empirically by physicians to cope with infections in renal disease patients. A urinary tract infection (UTI) is often caused by biofilm-forming multidrug-resistant (MDR) uropathogens. This study aimed to analyze the antibiogram of UTI strains from renal disease patients and the biofilm-forming ability of those strains. Methods. 102 patients clinically diagnosed with a UTI and renal disease were recruited into the study from August 2017 to January 2018. Clean-catch midstream urine samples were processed for the isolation and identification of the bacteria following standard methodologies. The antibiogram of the isolates (n = 106) was produced by the Kirby–Bauer disc diffusion method. Detection of biofilm formation was performed in tissue culture plates. Results. The incidence of a UTI in renal disease was 19.1%. Most patients were diagnosed with chronic kidney disease (18.63%), nephrotic syndrome (16.67%), and nephrolithiasis (14.71%). The commonest uropathogens were Escherichia coli (52.8%), Klebsiella pneumoniae (16%), and Enterococcus spp. (15.0%). Ceftriaxone was the most common antibiotic prescribed empirically (37%), whereas nitrofurantoin was the most prescribed antibiotic as adjusted therapy (36.1%). Among the first- and second-line antibiotics, most Gram-negative bacteria were sensitive to amikacin (70.7%), meropenem (70.7%), cefoperazone-sulbactam (70.0%), piperacillin-tazobactam (67.2%), gentamicin (66.7%), and nitrofurantoin (66.7%). Most Gram-positive bacteria were sensitive to doxycycline (90.0%), nitrofurantoin (72.2%), gentamicin (66.7%), and tetracycline (62.5%). All MDR Gram-negative uropathogens were susceptible to colistin sulfate and polymyxin B. Among the 106 isolates, 74.5% produced biofilms and 70.8% were MDR. In 67.0% of cases, including both MDR and biofilm-producing bacteria, the empirical therapy needed adjustment. Conclusions. Aminoglycoside, carbapenem, beta-lactam combination agents, and nitrofuran group of antibiotics may be the optimal first-line empirical therapies for uropathogens in hospitalized renal disease patients. Regular surveillance of resistance patterns and the study of biofilm formation in uropathogens must be performed to ensure effective management of the patients.

1. Introduction

Antimicrobials remain the mainstay of infectious disease treatment; however, the undiscerning use of antibiotics in many countries has resulted in the emergence of multidrug-resistant (MDR) microorganisms [1, 2]. Antimicrobial resistance (AMR) is a serious public health threat recognized by the World Health Organization (WHO) [3]. The spread of antimicrobial resistance and selection of MDR pathogens have most likely been caused by combinations of failure to adherence to proper infection control techniques, irrational use of antibiotics, increased use of antibiotics in animals and plants, availability of antibiotics without a prescription, and counterfeit products of dubious quality [4]. Antibiotic resistance leads to higher medical expenses, prolonged hospital stays, and increased mortality rates [5]. There is an urgent need for change in the way antibiotics are prescribed and consumed. Even if new antibiotics are developed, without behavior change, antibiotic resistance will continue to be a major threat [6]. In the meantime, information about the antibiotic spectrum of activity against existing MDR strains may help reduce the rate of emergence and spread of antimicrobial resistance [7].

An additional factor contributing to antibacterial resistance is biofilm production by bacteria [8]. Biofilm is an association of microorganisms in which microbial cells adhere to each other on living or nonliving surfaces within a self-produced matrix of extracellular polymeric substances [9, 10]. Within biofilms, microbes are 10–100 times more resistant to antimicrobial agents [11]. Reasons for this increase in resistance can be due to the growth patterns of bacteria in biofilms, extracellular substances retarding antibiotic diffusion, and the upregulation of certain genes in bacteria in biofilms [11–14]. The National Institutes of Health (NIH) has estimated that approximately 65% of all microbial infections and 80% of all chronic infections are associated with biofilms [15, 16]. Human diseases in which biofilms have been associated include urinary tract infections (UTIs), catheter infections, middle ear infections, contact lens-associated infections, and less common but more lethal infections such as endocarditis and cystic fibrosis [17–19].

UTIs are commonly encountered by clinicians with an estimated annual global incidence of at least 250 million [20]. Furthermore, the prevalence of UTI increases in patients with preexisting renal disease [21]. This study examined the antibiogram patterns of common uropathogens in renal disease patients and the ability of the strains to form biofilms. This study also aimed to provide evidence for the rational use of antibiotics in patients with renal disease having UTIs.

2. Materials and Methods

A descriptive, hospital-based, cross-sectional study was conducted among renal disease patients diagnosed with UTI and admitted to the 750-bedded Tribhuvan University Teaching Hospital (TUTH), Nepal, from August 2017 to January 2018. The type of uropathogens and their antimicrobial resistance patterns along with biofilm-forming abilities were examined. The “universal sampling” technique was used to determine the sample size for this study. We had taken urine samples of 102 patients, but of them, 4 of the samples had polymicrobes, i.e., 2 uropathogens from each of 4 urine samples. So we treated them like individual isolates and performed antimicrobial susceptibility testing and biofilm analysis. This explains why the sample size varied between patient size (102) and their sociodemographic analysis and uropathogens isolated (106) and their further analysis. Clean catch mid-stream urine specimens (n = 102) were collected aseptically from the patients. Specimen collection, culture, and identification were performed according to standard guidelines [22–24].

The study conformed to the tenets of the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Board of the Institute of Medicine (IOM), Tribhuvan University (Ref. 256(6-11-6)2/074/075). Renal disease patients diagnosed with UTIs provided their approval by signing patient consent forms if ≥ 18 years or parents signing consent forms for younger subjects. Cases of any age, both males and females, were included in the study. Patients diagnosed with renal disease but with no signs of UTIs or who did not agree to sign the patient consent form were excluded from the study. Relevant clinical and epidemiological information was recorded from the patients. Patients with a history of recurrent UTI, kidney transplant patients, or patients under immuno-suppressing drugs were excluded from the study. Hemodialysis patients were also excluded from the study. We did take samples from catheterized patients too. A semistructured data sheet was pretested in the same study area, and pretesting bias was avoided. In the questionnaire, patients of age >16 years were considered legible for enquiring about marital status (children ≤16 years are not included in this variable) and occupation. Children and infants below primary education were also not included in the education level variable. Data entry, data checking, compiling, and editing were performed manually.

2.1. Antibiotic Susceptibility Testing (AST)

All the isolates were subjected to antibiotic susceptibility testing (AST) by the Kirby–Bauer disc diffusion method on the Mueller–Hinton agar (HiMedia, India). The first-, second-, and third-line antibiotics (HiMedia, India) were chosen based on the Clinical and Laboratory Standards Institute (CLSI) 2017 guidelines [22] with some modifications based on the antibiotic testing policy in the microbiology laboratory of TUTH, Nepal. The results were reported as sensitive, intermediate, or resistant as described by CLSI [22]. Initially, all the isolates were subjected to first-line AST of the appropriate antibiotics for Gram-positive or Gram-negative bacteria. If the uropathogen was found to be resistant to more than 3 different classes of antibiotics, then it was tested with the appropriate second-line antibiotics. If any Gram-negative uropathogen was found to be resistant to meropenem or if the isolate was susceptible to only one antibiotic among the battery of second-line antimicrobials, it was further subjected to third-line antibiotic sensitivity testing. If an isolate showed resistance to ≥1 antibiotic from at least 3 different structural classes, it was considered to be multidrug-resistant (MDR) [25, 26].

Biofilm production: The biofilm production assay was performed using the tissue culture plate method [27]. A well-isolated colony of the organism isolated from the clinical specimen was inoculated in 2 mL of brain heart infusion (BHI) broth (HiMedia, India). The broth was incubated at 37°C for 24 h. The cultures were then diluted 1 : 100 with fresh medium (BHI broth supplemented with 1% glucose) in the individual wells of the sterile well of flat bottom microtiter plates so that the final volume in each well was 200 μl. The plates were incubated at 37°C for 24 h. Then, the contents of each well were removed by gentle tapping. The wells were washed with phosphate-buffered saline (pH 7.2) three times and then were stained with 0.1% safranin. After drying the wells, the adhered dye was then dissolved by 100% ethanol. Finally, absorbance of released safranin from each well was measured using OD_490nm. Quantification was performed according to the criteria described by Stepanovic et al., as shown in Table 1 [28].

Here, OD is the average optical density of each isolate and OD_c is the cutoff OD for the microtiter-plate test as three standard deviations above the average optical density of the negative control. Previously identified biofilm-producing in-house clinical isolates were used as the positive control for biofilm production [27].

2.2. Data Analysis

Data analysis was performed using the 17.0 version of Statistical Package for Social Sciences (SPSS) software. Major variables analyzed in this study were sociodemographic data, the result of AST, biofilm production, and days of hospital stay. A descriptive type of analysis was performed to generate frequency and percentage. Chi-square/cross-tabulation was performed to test significance.

3. Results

During the study period, a total of 10,404 urine samples were received by the microbiology laboratory. Among them, 534 samples were obtained from renal disease patients. A total of 102 renal disease patients who had a UTI were recruited to the study. The prevalence of a UTI in renal disease was 19.1%. A total of 106 uropathogens were isolated from the UTI-confirmed urines. A UTI was most seen in renal disease patients of age group 55–64 years (17.6%) followed by 35–44 years (14.7%) and 15–24 years (13.7%) (Table 2).

3.1. Patient Type and Different Wards to Which Patients Were Admitted

Of the 102 patients in the study, the majority were inpatients (95, 93.1%). Most of them were admitted to the nephrology (34, 33.3%) or pediatric (16, 15.7%) wards, whereas the lowest number of the patients was from neurology and surgery (4.9%). The majority of patients were diagnosed with chronic kidney disease (18.6%), followed by nephrotic syndrome (16.7%), nephrolithiasis (14.7%), and acute kidney disease (AKD) (11.8%), as shown in Table 3.

3.2. Types of Uropathogens

A total of 10 different bacterial species accounting for 106 different isolates from 102 urinary samples were isolated and identified. The majority were Gram-negative bacteria (87, 82.1%), and the remaining isolates were Gram-positive. The most common bacteria were Escherichia coli (52.8%), followed by Klebsiella pneumoniae (16.0%) (Table 4). Enterococci were the most common Gram-positive bacteria (Table 4).

3.3. Antibiotic Resistivity Pattern

Against Gram-negative bacteria (GNB), the antibiotics to which more than 50% of strains were resistant were amoxycillin (67, 88.2%), cotrimoxazole (55, 70.5%), ceftriaxone (53, 69.7%), ciprofloxacin (58, 66.7%), and ceftazidime (7, 63.6%) among the first-line antibiotics; amoxycillin-clavulanic acid (52, 98.1%), levofloxacin (44, 75.9%), and cefepime (52, 62.7%) among the second-line antibiotics; and imipenem (9, 60.0%), chloramphenicol (9, 56.3%), and doxycycline (9, 60.0%) among the third-line antibiotics (Table 5).

In Gram-positive bacteria, the first-line antibiotics to which more than 50% of strains were resistant were penicillin (14, 73.7%), ciprofloxacin (15, 79.0%), cotrimoxazole (2, 66.7%), and high-level gentamicin (10, 62.5%).

3.4. Antibiograms of Escherichia coli, Klebsiella, Pseudomonas, and Acinetobacter species

For E. coli isolates (n = 56), the antibiotics to which more than 50% of strains were resistant were amoxycillin (48, 85.7%), cotrimoxazole (38, 67.9%), ciprofloxacin (37, 66.1%), and ceftriaxone (40, 71.4%) among the first-line drugs. The antibiotics to which more than 50% of Klebsiella pneumoniae were resistant were cotrimoxazole (13, 76.5%), ciprofloxacin (11, 64.7%), ceftriaxone (11, 64.7%), and nitrofurantoin (12, 70.6%) among the first-line drugs. For the nonfermenting isolates, Pseudomonas and Acinetobacter, the antibiotics which were found to be more than 50% resistant were ciprofloxacin (8, 72.7%), gentamicin (6, 54.5%), and ceftazidime (7, 63.6%) among the first-line drugs; levofloxacin (4, 66.6%) and meropenem (4, 66.6%) among the second-line drugs; and imipenem (1, 100%) among the third-line drugs.

3.5. Biofilm Formation Distribution among the Uropathogens

Among the uropathogens that formed biofilms (n = 79), the majority were Escherichia coli (51.9%), followed by Klebsiella pneumoniae (20.2%), Pseudomonas aeruginosa (10.1%), Enterococcus faecium (7.5%), and Enterococcus faecalis (3.7%) (Table 6). Among the 41 biofilms producing Escherichia coli, the majority (51.2%) produced moderate levels of biofilm, while out of the 16 biofilms producing Klebsiella pneumoniae, 43.8% produced high levels of biofilm (Table 6).

3.6. Biofilm Production and MDR

Among the 106 isolates, 70.8% were MDR, while 74.5% were biofilm producers (Table 7). The majority of MDR bacteria (54.3%) were found to produce biofilm but of different levels, and the relationship with multidrug resistance was statistically insignificant ( value >0.05).

3.7. Duration of Hospital Stay with Respect to MDR and Biofilm Production

Patients infected with MDR strains had a slightly higher duration of hospital stays (9.01 days; 95% CI (7.71, 10.32)) than patients with non-MDR (6.67 days; 95% CI (5.11, 8.22)). In the case of biofilm production, patients with strong biofilm-producing bacterial isolates had longer hospital stay (10 days) followed by patients with moderate biofilm producers (9 days). Patients having nonbiofilm producers had the least days of hospital stay (Figures 1 and 2).

3.8. The Change in Antibiotic Use after Sensitivity Assessment

The antibiotic use pattern for empirical therapy and adjusted treatment therapy was evaluated. Third-generation cephalosporins (cefixime, ceftriaxone, and ceftazidime) were the most frequently prescribed empirical antibiotics (49.0%), followed by fluoroquinolones which were prescribed in 28% of patients. Once the results of the culture and sensitivity were obtained, the most commonly prescribed antibiotic was nitrofurantoin (36.1%) followed by fluoroquinolones (24.9%) (Table 8).

3.9. Comparison of Empirical Therapy with MDR and Biofilm Production

In 67% of patients, the antibiotic used as an empirical therapy did not match the culture sensitivity results and so had to be prescribed alternative antibiotics. Most of the patients in which the empirically used antibiotic was changed were infected by MDR strains (n = 53) and biofilm-producing bacteria (n = 50) (Table 9).

4. Discussion

The prevalence of renal disease patients is increasing, and it has become a serious threat to the health sector of Nepal. Antimicrobial resistance (AMR) has further aggravated the prognosis of renal disease patients developing UTI. Our study highlights the alarming AMR threat to renal disease patients and why strict antibiotic stewardship practice should be enforced [29]. In this study, the prevalence of a UTI in renal disease was 19.1%. A previous study found a similar prevalence (17%) of a UTI during the first 6 months after renal transplantation [30, 31]. In Nepal, the prevalence of renal disease has been reported to approximately double in males compared to females with a ratio of 1.8 : 1 [32], although the study recruited approximately equal numbers of males and females. The estimated glomerular filtration rate (eGFR) declines in parallel with age [33], and this coincides with increasing trends of CKD prevalence from 7.4% for 18–39 years to 24.2% for 60–70 years [34]. This pattern is also reflected in the current study, with the highest number of renal diseases being seen in the age group of 55–64 years followed by 25–44 years. The current study found that a UTI was commonly caused by Gram-negative bacteria, with E. coli being the most common bacteria followed by K. pneumoniae then Enterococcus species. This is a similar bacteriological profile that has been reported by many others in CKD patients as well as studies of community acquired UTI [35–37].

Antimicrobial resistance is a looming threat to humankind, though its rate varies from place to place, and a common trend shows its rate is increasing. Similar to that, in our study, the resistance rate is high with 70.8% of MDR bacteria which is higher than findings from those in previously conducted studies. Baral found only 41.1% of MDR bacteria in their study in 2012 [38], but a more recent study conducted by Parajuli et al. [39] has reported 64.9% of MDR bacteria causing UTIs and in a more recent study by Shilpakar et al. [40] who have reported that more than 90% of Gram-negative bacteria were MDR. This highlights the difficulties that are likely to be encountered with the treatment of UTI patients in Nepal.

Resistance to amoxycillin, ceftriaxone, cotrimoxazole, and ciprofloxacin among the first-line antibiotics was ≈70% of all isolates [41]. Fortunately, no strains were resistant to the last-line drugs such as polymyxin B and colistin sulfate. Similar findings were reported by the other studies [42]. However, with the known problems of renal toxicity during therapy with polymyxin B and colistin sulfate, careful optimization of the polymyxin dose and drug monitoring is needed [43, 44]. Biofilm production was seen in 74.5% of isolates with the majority being E. coli (51.9%), followed by K. pneumoniae (20.2%) and P. aeruginosa (10.1%). These results agree with, although slightly higher than, those of another study from Nepal that reported biofilm formation in 58.7% of isolates, with strong biofilm formation in 36.5% and weak biofilm formation in 22.1% of isolates [27]. The current study found that biofilm-producing bacteria also tended to be MDR strains. Studies from Egypt and Iran [45, 46] found that the prevalence of MDR and XDR was higher in biofilm-producing strains. Of the biofilm-producing isolates from ventilator-associated pneumonia, 42.2% were MDR, but the relationship was statistically insignificant [47]. 67% of patients had their empirical therapy adjusted after the AST result, and this adjustment was higher in infections with MDR and biofilm-forming isolates. It would be useful in future studies to test the resistance of strains in biofilms. The numbers of ciprofloxacin-resistant Pseudomonas aeruginosa and Staphylococcus aureus strains in biofilms could not be reduced even when four times the minimum inhibitory concentration of ciprofloxacin was used, whereas the numbers of bacteria in biofilms of ciprofloxacin-sensitive strains could be reduced by ≥ 60% by ciprofloxacin at its minimum inhibitory concentration [48, 49].

Infection with MDR bacteria results in longer days in the hospital [50], and the current study found that on average patients with MDR UTI remained in the hospital 2 days longer. Similarly, UTI patients infected with strong biofilm producers remained in the hospital for 3 days longer than patients infected with weak or nonbiofilm producers. This correlation between days of hospital stays with MDR and biofilm formation may be interconnected. It is possible that the greater number of days in the hospital had a selective pressure for the generation of MDR and/or strong biofilm-producing isolates. Regardless of the relationship between MDR and biofilm, both can add significant levels of burden to healthcare providers as well as patients, as well as costs to the hospital system.

5. Conclusion and Recommendations

Overall, the antibiotic resistance patterns in the current study showed most of the empirically used antibiotics were ineffective and over 50% of patients required therapy adjustment. A high percentage of uropathogens were found to be MDR and biofilm producers. The study reflects the crisis in resource-starved large hospital settings in developing countries without significant antibiotic stewardship strategies and the threat posed by increasing drug-resistant UTIs in renal disease. Strategies to inhibit or disperse biofilm formation by bacteria in vivo in renal disease patients should also be considered.

There is a need for the development of a protocol for rational use of antibiotics, and physicians and pharmacists must be aware of the rational use of antibiotics. There should be the use of a narrow spectrum of antibiotics when supported by clinical situations and culture reports. Furthermore, more thorough and routine studies are necessary to monitor for future changes in resistivity patterns. There must be provision for availability of trained pharmacists and microbiologists so that appropriate use of medicines and patient adherence to the treatment can be enhanced.

Abbreviations

UTI:	Urinary tract infection
MDR:	Multidrug resistant
CLSI:	Clinical and Laboratory Standards Institute
MHA:	Mueller–Hinton agar
BHI:	Brain heart infusion
Mg:	Milligram
Ml:	Milliliter
μg:	Microgram
L:	Liter
IOM:	Institute of Medicine
TUTH:	Tribhuvan University Teaching Hospital
WHO:	World Health Organization
CFU:	Colony-forming units
CKD:	Chronic kidney disease
AKD:	Acute kidney disease
SLE:	Systemic lupus erythematosus
DM:	Diabetes mellitus
SPSS:	Statistical Package for Social Sciences
OD:	Optical density
GNB:	Gram-negative bacteria
GPB:	Gram-positive bacteria
AST:	Antibiotic sensitivity test
HLG:	High-level gentamicin
CLED:	Cysteine lactose electrolyte-deficient agar
VUR:	Vesico-ureteral reflux
FSW:	Female surgical ward
MSW:	Male surgical ward
POW:	Postoperative ward
DNA:	Deoxyribonucleic acid
ELISA:	Enzyme-linked immunosorbent assay.

Data Availability

Data are available from corresponding author upon request.

Ethical Approval

Ethical approval was obtained from the Institutional Review Board of the Institute of Medicine (IOM), Tribhuvan University (Ref. 256(6-11-6)2/074/075).

All the patients in the study were informed in detail about the study for collection of clinical and epidemiological information. Confidentiality of all information was maintained. All patients signed the patient consent form prior to getting enrolled in the study.

Conflicts of Interest

The authors declare no conflicts of interest.

Authors’ Contributions

Anuja Dahal and Shyam Kumar Mishra conceptualized the study. Anuja Dahal, Shyam Kumar Mishra, Saraswati Bhatttarai, and Kamal Shrestha curated the data. Anuja Dahal, Shyam Kumar Mishra, Kamal Shrestha, and Shiva Aryal conducted formal analysis. Anuja Dahal, Shyam Kumar Mishra, and Kamal Shrestha carried out investigation. Anuja Dahal, Shyam Kumar Mishra, Kamal Shrestha, and Shiva Aryal designed the methodology. Shyam Kumar Mishra and Balmukunda Regmi supervised the study. Anuja Dahal, Shyam Kumar Mishra, and Mark Willcox were involved in validation. Anuja Dahal wrote the original draft. Anuja Dahal, Shyam Kumar Mishra, and Mark Willcox wrote, reviewed, and edited the manuscript. All the abovementioned authors contributed to interpretation of the study results, drafting and revision of the manuscript, and approved the final version of the manuscript. Anuja Dahal and Shyam Kumar Mishra contributed equally to this work.

Acknowledgments

We are grateful to the Department of Microbiology and Department of Pharmacy, Institute of Medicine, Tribhuvan University, and the Bacteriology Lab of Tribhuvan University Teaching Hospital for providing lab arrangement.

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Copyright © 2023 Anuja Dahal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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