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Journal of Drug Delivery and Therapeutics
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Open Access Full Text Article Research Article
Urinary Tract Infection at MZH: Prevalence, Etiologic Organisms, Antimicrobial Susceptibility Patterns, and Predictors of Antibiotic Resistance: A Cross- Sectional Analytical Study
Ashraf Alakkad ¹*, Zill Huma Hussain ², Anwar Adwan ¹, Sowjanya Bhupathiraju ¹, Mohamed Sharaf ¹
¹ Department of Internal Medicine, Madinat Zayed Hospital, Al Dhafra Region, UAE ² Department of Pharmacy, Madinat Zayed Hospital, Al Dhafra Region, UAE
|
Article Info: Article History: Received 19 June 2026 Reviewed 30 July 2026 Accepted 23 Aug 2026 Published 15 Sep 2026
Cite this article as: Alakkad A, Hussain ZH, Adwan A, Bhupathiraju S, Sharaf M, Urinary Tract Infection at MZH: Prevalence, Etiologic Organisms, Antimicrobial Susceptibility Patterns, and Predictors of Antibiotic Resistance: A Cross-Sectional Analytical Study, Journal of Drug Delivery and Therapeutics. 2026; 16(9):47-51 DOI: https://doi.org/10.22270/jddt.v16i9.7983
For Correspondence: Ashraf Alakkad, Department of Internal Medicine, Madinat Zayed Hospital, Al Dhafra Region, UAE. |
Abstract
Background: Urinary tract infections (UTIs) are among the most common bacterial infections globally. Rising antimicrobial resistance (AMR) limits the effectiveness of empirical therapy. Local susceptibility data are essential for guiding treatment, particularly in regions with high antibiotic utilization. Methods: A cross-sectional analytical study was conducted at Madinat Zayed Hospital (MZH) from January to December 2024 among adult inpatients with culture-confirmed UTIs. Demographic, clinical, microbiological, and treatment variables were collected.Antimicrobial susceptibility testing followed CLSI 2024 standards using Kirby–Bauer disk diffusion and MIC methods [4]. Resistance was defined at the isolate level as non-susceptibility (resistant or intermediate) to the antibiotic group assigned for that isolate. Binary logistic regression identified independent predictors of resistance. Results: Ninety-eight patients were included (mean age 56.54 ± 22.39 years; 50% male). Escherichia coli was the predominant organism (49.0%), followed by Klebsiella pneumoniae (20.4%) and Pseudomonas aeruginosa (12.2%). Overall, 26 isolates (26.5%) were classified as resistant, 69 (70.4%) as sensitive, and 3 (3.1%) as intermediate. Aminoglycosides demonstrated the highest sensitivity rate (92.0%), while cephalosporins showed the highest resistance rate (40.5%). In multivariable logistic regression, Gram-negative organism type (adjusted odds ratio [AOR] 3.41, 95% CI 1.22–9.56, p = 0.019) and cephalosporin exposure on admission (AOR 2.87, 95% CI 1.03–7.98, p = 0.044) were independently associated with resistance. Model fit was acceptable (Hosmer–Lemeshow p = 0.42); Nagelkerke R² = 0.19 indicated modest explanatory power. Conclusion: UTIs at MZH were predominantly caused by Gram-negative organisms, with notable resistance to cephalosporins and penicillins. Aminoglycosides remained highly effective in vitro. Early cephalosporin exposure and Gram-negative species were independent predictors of resistance. These findings support culture- guided therapy and continued antimicrobial stewardship. Given the modest sample size and limited number of resistance events, the regression results should be interpreted as hypothesis-generating. Keywords: urinary tract infection, antimicrobial resistance, E. coli, susceptibility pattern, logistic regression, Gram-negative bacteria |
Urinary tract infections (UTIs) are among the most common bacterial infections worldwide, with more than 150 million cases annually [1,5]. They represent a major cause of morbidity, healthcare utilization, and antimicrobial consumption. In the Gulf region, UTIs account for a substantial proportion of infectious presentations and remain a frequent reason for hospital admission.
Globally, Gram-negative bacteria—particularly Escherichia coli—are the predominant uropathogens [2,6]. Other important organisms include Klebsiella spp., Proteus spp., Enterobacter spp., Citrobacter spp., Pseudomonas aeruginosa, Enterococcus spp., Staphylococcus spp., and occasionally Candida species. Empirical therapy typically relies on broad-spectrum antibiotics; however, widespread antimicrobial use has
accelerated resistance, reducing the effectiveness of commonly used agents such as cephalosporins and fluoroquinolones.
Resistance patterns vary significantly across regions, making local surveillance essential for guiding empirical therapy and stewardship programs. Madinat Zayed Hospital (MZH) serves a large population in the Al Dhafra region of the United Arab Emirates and manages a substantial number of UTI-related admissions. Despite this burden, published local data on UTI pathogens and resistance patterns have been limited.
This study aims to describe the prevalence of culture- confirmed UTIs among adult inpatients at MZH, identify the common microorganisms isolated, evaluate their antimicrobial susceptibility patterns, and explore demographic and clinical predictors of antimicrobial resistance.
A cross-sectional analytical study was conducted at Madinat Zayed Hospital (MZH), Al Dhafra Region, UAE, from January to December 2024. The study included all adult inpatients with culture-confirmed UTIs.
General Objective: To describe the bacterial organisms isolated from hospitalized adult patients with culture- confirmed urinary tract infection at MZH, evaluate their antimicrobial susceptibility patterns, and identify independent predictors of antimicrobial resistance.
All adult patients (≥18 years) of either sex admitted with a diagnosis of urinary tract infection confirmed by urine culture were included, regardless of whether they were already receiving antibiotic therapy at the time of admission. Patients younger than 18 years were excluded.
Sample size was calculated using Cochran’s formula, assuming a 50% prevalence (to maximize sample size), 95% confidence level, and 10% margin of error. The minimum required sample size was 96; 98 patients were ultimately included.
A non-probability consecutive sampling method was used: all eligible patients meeting inclusion criteria during the study period were enrolled until the target sample size was reached.
Table 1 summarizes the age distribution of the study cohort.
Data extracted from medical records included: demographics (age, sex), clinical presentation, medical history, urinalysis and urine culture results, antibiotic exposure within 48 hours before culture (classified by major antibiotic class), antimicrobial susceptibility results, length of hospital stay, and antibiotic therapy at discharge.
Testing followed CLSI 2024 standards using Kirby–Bauer disk diffusion and automated broth microdilution (MIC) for selected antibiotics. Molecular detection of resistance mechanisms was not performed. Antibiotic classes evaluated included cephalosporins, aminoglycosides, penicillins, fluoroquinolones, oxazolidinones, and antifungal agents.
Definition of resistance (primary outcome): An isolate was classified as “resistant” if it demonstrated a resistant or intermediate result to the antibiotic group that was recorded as the primary therapeutic class for that isolate. Isolates with fully susceptible results to the assigned class were classified as “sensitive.” This isolate-level definition was used for all descriptive tables and for the binary logistic regression outcome.
Data were analyzed using SPSS version 26. Descriptive statistics (means, standard deviations, frequencies, and percentages) summarized continuous and categorical variables. Fisher’s exact test was used for associations between categorical variables because many cells had expected counts <5. Binary logistic regression was performed to identify independent predictors of resistance. Variables entered into the model were age (continuous), sex, organism type (Gram-negative vs Gram-positive), and cephalosporin exposure on admission. Model fit was assessed with the Hosmer– Lemeshow goodness-of-fit test and Nagelkerke R² [10]. A two-sided p-value <0.05 was considered statistically significant. Given the modest number of resistance events (n = 26), results of the multivariable model are presented as hypothesis-generating.
The study was approved by the Al Dhafra Region Institutional Review Ethics Committee (ADHIREC). Patient confidentiality was maintained throughout. Informed consent was waived because of the retrospective design and use of de-identified data.
|
Variable |
N |
Minimum |
Maximum |
Mean (SD) |
|
Age (years) |
98 |
21 |
104 |
56.54 (22.39) |
Table 1. Age of patients (n = 98).
The mean age was 56.54 ± 22.39 years (range 21–104). Exactly 49 patients (50%) were male and 49 (50%) were female, indicating equal sex distribution in this cohort.
|
Susceptibility |
Frequency |
Percent |
|
Resistant |
26 |
26.5% |
|
Sensitive |
69 |
70.4% |
|
Intermediate |
3 |
3.1% |
|
Total |
98 |
100% |
Table 2. Overall susceptibility pattern of isolates (n = 98).
Of 98 isolates, 69 (70.4%) were sensitive, 26 (26.5%) were resistant, and 3 (3.1%) showed intermediate susceptibility. The 26.5% resistance rate is clinically relevant in a setting where empirical therapy is frequently initiated before culture results become available.
|
Organism |
Frequency |
Percent |
Cumulative % |
|
Escherichia coli |
48 |
49.0% |
49.0% |
|
Klebsiella pneumoniae |
20 |
20.4% |
69.4% |
|
Pseudomonas aeruginosa |
12 |
12.2% |
81.6% |
|
Enterococcus faecalis |
8 |
8.2% |
89.8% |
|
Streptococcus agalactiae (Group B) |
3 |
3.1% |
92.9% |
|
Staphylococcus haemolyticus |
3 |
3.1% |
96.0% |
|
Citrobacter freundii |
1 |
1.0% |
97.0% |
|
Proteus mirabilis |
1 |
1.0% |
98.0% |
|
Enterococcus faecium |
1 |
1.0% |
99.0% |
|
Enterobacter cloacae |
1 |
1.0% |
100.0% |
|
Total |
98 |
100% |
|
Table 3. Distribution of isolated organisms (n = 98).
Escherichia coli was the most frequent pathogen (48 isolates, 49.0%), followed by Klebsiella pneumoniae (20, 20.4%) and Pseudomonas aeruginosa (12, 12.2%). Gram-negative organisms accounted for 81.6% of all isolates (80/98), confirming their dominant role in this inpatient cohort.
|
Organism |
Resistant |
Sensitive |
Intermediate |
Total |
|
Escherichia coli |
12 (25.0%) |
33 (68.8%) |
3 (6.3%) |
48 |
|
Klebsiella pneumoniae |
8 (40.0%) |
12 (60.0%) |
0 |
20 |
|
Pseudomonas aeruginosa |
3 (25.0%) |
9 (75.0%) |
0 |
12 |
|
Staphylococcus haemolyticus |
3 (100%) |
0 |
0 |
3 |
|
Enterococcus faecalis |
0 |
8 (100%) |
0 |
8 |
|
Other organisms* |
0 |
7 (100%) |
0 |
7 |
|
Total |
26 |
69 |
3 |
98 |
Table 4. Organism-specific antimicrobial susceptibility pattern. *Other organisms: Citrobacter freundii (1), Streptococcus agalactiae (3), Proteus mirabilis (1), Enterococcus faecium (1), Enterobacter cloacae (1).
Escherichia coli showed 25.0% resistance (12/48). Klebsiella pneumoniae exhibited a higher resistance rate of 40.0% (8/20). All three Staphylococcus haemolyticus isolates were resistant. Enterococcus faecalis and the remaining low-frequency organisms were fully sensitive. When assessed statistically, Fisher’s exact test indicated a significant association between organism type and susceptibility outcome (p = 0.005). Because several cells had expected counts <5, the p-value should be interpreted with appropriate caution. MIC values were consistent with disk diffusion findings, with elevated MICs among resistant isolates.
On admission, 59 patients (60.2%) were receiving a penicillin, 29 (29.6%) a cephalosporin, and 10 (10.2%) a fluoroquinolone. Thus every patient had documented antibiotic exposure at the time of admission.
At discharge, 30 patients (30.6%) left without an antibiotic prescription. Penicillins and fluoroquinolones were each prescribed to 24 patients (24.5%), cephalosporins to 18 (18.4%), and oxazolidinones to 2 (2.0%). The reduction in cephalosporin use from admission to discharge is consistent with de-escalation practices.
|
Antibiotic Group |
Resistant |
Sensitive |
Intermediate |
Total |
|
Cephalosporins |
17 (40.5%) |
25 (59.5%) |
0 |
42 |
|
Aminoglycosides |
1 (4.0%) |
23 (92.0%) |
1 (4.0%) |
25 |
|
Penicillins |
6 (31.6%) |
11 (57.9%) |
2 (10.5%) |
19 |
|
Fluoroquinolones |
2 (66.7%) |
1 (33.3%) |
0 |
3 |
|
Oxazolidinones |
0 |
5 (100%) |
0 |
5 |
|
Antifungals |
0 |
2 (100%) |
0 |
2 |
|
Not assigned / missing |
0 |
2 |
0 |
2 |
|
Total |
26 |
69 |
3 |
98 |
Table 5. Susceptibility pattern by antibiotic group (n = 98). Note: totals reflect the antibiotic group assigned as the primary therapeutic class for each isolate. Two isolates lacked a recorded antibiotic-group assignment.
Cephalosporins showed the highest resistance rate (40.5%). Aminoglycosides demonstrated the highest sensitivity (92.0%). Penicillins occupied an intermediate position (31.6% resistance). Oxazolidinones and antifungal agents were fully sensitive in the few isolates
for which they were the assigned class. Fisher’s exact test showed a significant association between antibiotic group and susceptibility (p = 0.005); sparse cells again warrant cautious interpretation.
|
Predictor |
AOR |
95% CI |
p-value |
|
Age (per year) |
1.02 |
0.99–1.05 |
0.12 |
|
Male sex (ref: Female) |
0.85 |
0.32–2.25 |
0.74 |
|
Gram-negative organism (ref: Gram-positive) |
3.41 |
1.22–9.56 |
0.019 |
|
Cephalosporin exposure on admission (ref: no) |
2.87 |
1.03–7.98 |
0.044 |
Table 6. Multivariable binary logistic regression for predictors of antimicrobial resistance (n = 98). Model fit: Hosmer– Lemeshow χ² = 8.02, p = 0.42; Nagelkerke R² = 0.19.
Gram-negative organism type (AOR 3.41, 95% CI 1.22– 9.56, p = 0.019) and cephalosporin exposure on admission (AOR 2.87, 95% CI 1.03–7.98, p = 0.044) were independently associated with resistance. Age and sex were not significant. The model explained approximately 19% of the variance in the outcome. With only 26 resistance events, the analysis is under- powered for robust multivariable inference; the findings should therefore be regarded as hypothesis-generating and require confirmation in larger cohorts.
This study provides a local overview of the etiology and antimicrobial susceptibility of culture-confirmed UTIs among adult inpatients at MZH during 2024. Gram- negative organisms predominated (81.6%), with Escherichia coli accounting for nearly half of all isolates—consistent with both global and regional literature [2,3,6,8]. Klebsiella pneumoniae and Pseudomonas aeruginosa were the next most common
pathogens, reflecting the contribution of healthcare- associated and opportunistic organisms in a hospitalized population [7,9].
The overall resistance rate of 26.5% is clinically meaningful. Aminoglycosides retained high in-vitro activity (92% sensitive), supporting their continued role in selected complicated or resistant infections, while recognizing their nephrotoxicity risk, especially in older adults. In contrast, cephalosporins showed a 40.5% resistance rate—the highest among major classes— raising concern about their routine use as first-line empirical therapy.
Klebsiella pneumoniae exhibited a higher resistance rate (40%) than E. coli (25%). Although ESBL and carbapenemase testing were not performed, the observed cephalosporin resistance pattern is compatible with β-lactamase-mediated mechanisms that are increasingly reported among Enterobacterales worldwide. The inclusion of MIC testing strengthened phenotypic results; absence of molecular ESBL/carbapenemase testing limits deeper characterization.
Multivariable analysis identified two independent predictors of resistance: Gram-negative organism type and cephalosporin exposure on admission. These associations are biologically plausible—Gram-negative species more frequently harbor transferable resistance determinants, and early broad-spectrum cephalosporin use exerts selective pressure. However, the modest sample size, limited number of events, and incomplete adjustment for potential confounders (catheter use, prior hospitalization, comorbidities, community- versus healthcare-associated infection) mean that the regression results should be interpreted cautiously and treated as hypothesis-generating.
Therapy duration was short (<5 days) for the large majority of patients. This pattern may reflect early clinical improvement, stewardship-driven de-escalation, or institutional discharge practices; it was not associated with antibiotic class. Length-of-stay analyses suggested that aminoglycosides were used more often in patients with prolonged hospitalization, most likely reflecting greater clinical severity rather than a causal effect of the drug class itself.
Overall, the findings reinforce the value of routine urine culture and susceptibility testing, the need to avoid unnecessary early cephalosporin exposure when narrower options are appropriate, and the importance of continuous local AMR surveillance to guide empirical regimens and stewardship policies.
Several limitations should be considered when interpreting these results:
Gram-negative organisms, particularly Escherichia coli, were the leading causes of culture-confirmed urinary tract infections among adult inpatients at Madinat Zayed
Hospital in 2024. Although the majority of isolates remained susceptible to the tested agents, a clinically important minority demonstrated resistance, especially to cephalosporins. Aminoglycosides retained high in- vitro activity. Gram-negative organism type and early cephalosporin exposure were independently associated with resistance in multivariable analysis; these associations require confirmation in larger studies. The findings support routine culture-guided therapy, judicious empirical prescribing, and ongoing local antimicrobial-resistance surveillance.
Funding: The authors received no external funding for this study.
Conflict of Interest: The authors declare no competing interests.
Data Availability: The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.
Author Contributions: All authors contributed to study conception, data collection, analysis, manuscript drafting, critical revision, and approved the final manuscript.