Abstract
Background
Urinary tract infections (UTIs) represent a significant global health burden, and rising antimicrobial resistance (AMR) threatens effective empirical treatment. Ibb City lacks contemporary, comprehensive resistance data from large cohorts that are essential to guide treatment decisions and antimicrobial stewardship. This analysis aimed to determine the spectrum of bacterial uropathogens and evaluate the prevalence of multidrug resistance (MDR).
Methods
A retrospective analysis was conducted on 905 non-duplicate, consecutive culture-confirmed UTI cases in Ibb between August 2024 and August 2025. Antimicrobial susceptibility testing was performed for 42 antibiotics across multiple classes using the Kirby-Bauer disk diffusion method. Statistical analyses included descriptive statistics, chi-square tests, Fisher’s exact test, Cochran-Armitage trend test, and Monte Carlo simulation for contingency tables with low expected cell counts.
Results
The majority of cases were recorded among females with 593 cases (65.5%) and young adults aged 19–35 years with 462 cases (51.0%). Escherichia coli was the most frequently isolated pathogen (387, 42.8%), followed by Staphylococcus saprophyticus (300, 33.1%), Staphylococcus aureus (131, 14.5%), Klebsiella spp. (30, 3.3%), Pseudomonas aeruginosa (21, 2.3%), Enterobacter spp. (21, 2.3%), Proteus spp. (12, 1.3%), and Acinetobacter spp. (3, 0.3%). The significant associations were observed between uropathogen distribution and demographic factors, including sex and age group (P < 0.001). The overall MDR prevalence was 27.8% (252/905). MDR prevalence showed a significant positive correlation with age (P < 0.001), increasing progressively from 12.7% in pediatric patients to 38.6% in elderly patients. Enterobacter spp. had the highest MDR rate (42.9%), followed by Proteus spp. (41.7%), E. coli (35.4%), P. aeruginosa (33.3%), S. aureus (19.8%), and S. saprophyticus (19.3%).
Conclusion
The finding revealed an increased burden of antimicrobial resistance in the study area, with an association between rising rates of MDR and advancing age. This necessitates a review of antimicrobial use protocols and the implementation of effective strategies to monitor the spread of antibiotic-resistant strains.
Clinical trial number
Not applicable.
Keywords: Urinary tract infection, Antimicrobial susceptibility, Multidrug resistance, Extended-spectrum beta-lactamase, Antimicrobial stewardship, Yemen
Introduction
Urinary tract infections (UTIs) represent one of the most prevalent bacterial infections worldwide, affecting millions of individuals across all age groups and demographics and posing a significant burden on global healthcare systems [1–2]. They are characterized by the invasion and proliferation of pathogens in any part of the urinary system, leading to a spectrum of clinical manifestations ranging from asymptomatic bacteriuria to severe pyelonephritis and sepsis. The epidemiological and microbiological profiles of UTIs exhibit considerable geographical variation, influenced by local factors such as prescribing practices, sanitation, and underlying patient comorbidities [3–4].
The crisis caused by the spread of antibiotic-resistant bacteria is growing worldwide. A global analysis indicated that antibiotic-resistant bacteria led to approximately 4.71 million deaths, directly causing 1.14 million of them. While deaths among young children due to antibiotic resistance decreased by more than 50% between 1990 and 2021, the increase among the elderly (over 70 years old) exceeded 80% [5]. In addition, the World Health Organization has declared antimicrobial resistance (AMR) among the top ten global health threats facing humanity, with conservative estimates projecting 10 million annual deaths attributable to AMR by 2050 if urgent action is not taken [6]. The emergence and spread of multidrug-resistant (MDR) organisms—microorganisms resistant to at least one agent in three or more antimicrobial categories—are progressively eroding the therapeutic arsenal of modern medicine, complicating treatment protocols, prolonging hospital stays, increasing healthcare costs, and elevating mortality rates across all clinical settings [7].
The etiology of UTIs is predominantly bacterial, with Gram-negative bacilli, particularly Escherichia coli, being the most frequently isolated uropathogen globally, followed by other members of the Enterobacteriaceae family such as Klebsiella spp. and Gram-positive organisms like Staphylococcus aureus and S. saprophyticus [8–9]. Limited studies conducted in Yemen indicated that E. coli, Klebsiella sp., Staphylococci sp., Enterococcus faecalis, and Pseudomonas aeruginosa were isolated from patients with urinary tract infections [10–14]. This pattern has been consistently observed in regional studies, including those conducted in Saudi Arabia [15–16], Libya [17], Ghana [18] and Lebanon [19].
A critical challenge in the management of UTIs is the alarming rise in AMR. Uropathogens are increasingly developing resistance to first-line and commonly prescribed antibiotics, such as ampicillin, trimethoprim-sulfamethoxazole, and fluoroquinolones, rendering empirical treatments ineffective [11, 20]. According to the WHO report [21], the resistance of bacteria causing urinary tract infections increased by 26% globally between 2016 and 2023. In addition, more than 30% of E. coli and K. pneumoniae isolates from UTIs were resistant to common antibiotics, including third-generation cephalosporins, fluoroquinolones, and cotrimoxazole.
Yemen is among the countries lacking an effective healthcare system to address health challenges, particularly given the current dire circumstances of war. The escalating problem of antibiotic-resistant microbes is one of the most prominent and growing health issues in Yemen, resulting from the absence of policies to regulate antibiotic use [22–24]. Furthermore, dispensing antibiotics without proper laboratory testing has led to an increase in antibiotic-resistant infections, posing a serious threat to the Yemeni healthcare system and necessitating urgent action to control their use [25–27]. Some reports coming from different parts of Yemen have documented the spread of antibiotic-resistant bacteria among patients with UTIs. A study by Hassan et al. [14] reported the highest resistance of K. pneumoniae at 100% against amoxicillin and ampicillin, while E. coli showed resistance of 95% and 70.7% against amoxicillin and ampicillin, respectively. Another report by Ghaleb et al. [11] showed that the resistance of E. coli and Klebsiella spp. isolates to cotrimoxazole was 66% and 88%, respectively, and their resistance to nalidixic acid was 71% and 64%, respectively. In addition, Ahmed et al. [13] documented that all K. pneumoniae and P. aeruginosa isolates were multidrug resistant at 100% and 92.3%, respectively. This escalating resistance underscores the necessity for continuous local surveillance of uropathogens and their susceptibility patterns to guide effective empirical therapy [4, 28].
Despite the availability of valuable data on the prevalence of UTI pathogens and their antibiotic susceptibility patterns across various regions of Yemen, a significant gap remains in Ibb, Yemen. Epidemiological and resistance patterns can differ even within a single country because of variations in local antibiotic usage and healthcare access. Therefore, this study aimed to determine the prevalence of bacterial uropathogens causing UTIs and their contemporary antibiotic resistance patterns in patients in Ibb city, Yemen. The findings of this analysis provide crucial, location-specific data to inform clinicians in Ibb, enabling evidence-based decisions for empirical antibiotic therapy, thereby improving patient outcomes and contributing to local antimicrobial stewardship efforts.
Materials and methods
Study design and setting
A descriptive analytical retrospective study was conducted across two selected private medical laboratories based on routinely collected urine culture and antibiotic susceptibility records from August 30, 2024, to August 30, 2025. All eligible urine culture records processed within the study window were reviewed once, and no patient contact occurred. The study was conducted in Ibb City, Yemen, using microbiology records from the following private laboratory network: Al-Ra’fah Laboratories – Ibb and Alpha Laboratory – Ibb. These sites collectively provided a large catchment of patient samples from Ibb City.
Study population and selection criteria
All patients (of any age and sex) referred from hospitals, private clinics, and medical centers in Ibb City, whose urine samples were processed for culture and susceptibility testing at any of the participating laboratories during the study period, were included. The sample size depended on the availability of laboratory records during the study period. A thorough review of all eligible non-duplicate records was conducted during the study period, including data verification and matching with patient identities. If duplication was found in more than one sample for the same patient, only the results from the first sample were included, and the results from subsequent samples were excluded. This approach maximized precision for organism distribution and susceptibility estimates without imposing sampling error. The total number of microbiology laboratory reports assessed was 905 reports with bacterial growth.
Inclusion and exclusion criteria
This analysis included urine cultures showing significant bacteriuria, complete data, bacteriological identification, and antibiotic susceptibility testing during the study period. Conversely, urine cultures showing mixed growth, lacking or incomplete data, cultures that did not identify the microorganism or provide antimicrobial susceptibility test results, and samples collected after the initiation of antibiotic treatment were excluded.
Data collection
Data were extracted from laboratory information systems using a standardized data collection form. The following variables were recorded for each patient: demographic characteristics (age, sex); microbiological data (causative organism identification); antimicrobial susceptibility profiles across multiple classes; and laboratory parameters (Gram stain characteristics).
Antimicrobial susceptibility profile
Susceptibility testing was performed using the Kirby-Bauer disk diffusion method on Mueller-Hinton agar (MHA) according to the Clinical and Laboratory Standards Institute (CLSI, 2021) guidelines [29]. Using a sterile cotton swab, a part of the freshly cultured colonies was picked up and added to a sterile saline solution. The suspension concentration was subsequently adjusted to the 0.5 McFarland standard (5 × 10⁸ CFU/mL). The petri dish plates containing MHA medium were streaked using sterile cotton swabs moistened with the prepared suspension in three different directions and left to stand for 10 min. In addition, the commercially available antibiotic discs (HiMedia Labs, Ltd., India) were placed onto the plates’ surface and incubated overnight at 37 °C (Table 1). Results were interpreted as susceptible, intermediate, or resistant based on CLSI criteria [29]. For analysis purposes, intermediate results were classified as non-susceptible.
Table 1.
Families and classes of antibiotics used in this study
| Class | Antibiotics (disk potency) |
|---|---|
| Quinolones | Ciprofloxacin (5 µg), Levofloxacin (5 µg), Norfloxacin (10 µg), Ofloxacin (5 µg), Lomefloxacin (10 µg), Moxifloxacin (5 µg), Nalidixic Acid (30 µg) |
| Cephalosporins | Cefradine (30 µg), Ceftazidime (30 µg), Cefepime (30 µg), Cefixime (5 µg), Ceftriaxone (30 µg), Cefotaxime (30 µg), Cefadroxil (30 µg), Cefprozil (30 µg), Cefaclor (30 µg), Cefoperazone (75 µg), Cefuroxime (30 µg), Cefalexin (30 µg), Cefdinir (5 µg), Cefpodoxime (10 µg) |
| Carbapenems | Meropenem (10 µg), Imipenem (10 µg) |
| Aminoglycosides | Gentamicin (30 µg), Amikacin (30 µg) |
| Folate Inhibitors | Trimethoprim-Sulfamethoxazole (25 µg) |
| Penicillins | Amoxicillin (25 µg), Ampicillin/Sulbactam (10/10 µg), Piperacillin-Tazobactam (30/6 µg), Amoxicillin-Clavulanate (30 µg), Penicillin (10 U) |
| Nitrofurans | Nitrofurantoin (300 µg) |
| Tetracyclines | Tetracycline (30 µg), Doxycycline (30 µg)0 |
| Macrolides | Erythromycin (15 µg), Clarithromycin (15 µg), Azithromycin (15 µg) |
| Lincosamides | Clindamycin (2 µg), Lincomycin (10 µg) |
| Oxazolidinones | Linezolid (30 µg) |
| Fosfomycins | Fosfomycin (200 µg) |
The efficacy of antibiotics against gram-positive bacteria was assessed independently of gram-negative bacteria based on their clinical significance and spectrum of activity. Subsequently, the multidrug resistance (MDR) rate for gram-positive isolates was calculated independently of gram-negative isolates based on the selected antibiotic classes.
Multidrug resistance analysis
Multidrug resistance (MDR) was defined as acquired non-susceptibility to at least one agent in three or more antimicrobial categories.
Data analysis
Data were entered into a database designed using a Microsoft Excel spreadsheet. Statistical analyses were performed using IBM SPSS Statistics for Windows, version 27.0 (IBM Corp., Armonk, NY, USA). Moreover, descriptive statistics, including frequencies, percentages, means, and standard deviations, were used to present participant characteristics and microbiological findings. In addition, the chi-square test was used to assess the associations between categorical variables. Fisher’s exact test was employed when the expected cell frequencies were < 5. Furthermore, MDR was calculated as the proportion of isolates resistant to three or more antibiotic classes. 95% confidence intervals (95% CI) were calculated for resistance and sensitivity proportions using the Wilson score method. The Cochran-Armitage trend test was used to assess the relationship between age and MDR prevalence. For contingency tables with more than 20% of cells having expected counts less than 5, Monte Carlo simulation with 10,000 sampled tables and 99% confidence intervals was used to obtain reliable p-values. Additionally, a p-value of < 0.05 was considered statistically significant for all analyses.
Result
Demographic characteristics of study participants
A total of 905 patients with urinary tract infections were included in this retrospective analysis. Female patients predominated, accounting for 593 cases (65.5%), while male patients comprised 312 cases (34.5%). Regarding age distribution, young adults aged 19–35 years represented the majority of cases (462; 51.0%), followed by pediatric patients aged 0–18 years (142; 15.7%) and adults aged 36–50 years (154; 17.0%), and elderly patients over 65 years had few cases (57; 6.3%), as listed in Table 2.
Table 2.
Demographic characteristics of study participants with UTIs in Ibb city
| Characteristic | Category | Frequency (n) | Percentage (%) |
|---|---|---|---|
| Sex | Male | 312 | 34.5 |
| Female | 593 | 65.5 | |
| Age Group (years) | Pediatric (0–18) | 142 | 15.7 |
| Young Adult (19–35) | 462 | 51 | |
| Adult (36–50 years) | 154 | 17 | |
| Middle Aged (51–65) | 90 | 9.9 | |
| Elderly (> 65) | 57 | 6.3 |
Distribution of uropathogens
Gram-negative bacteria constituted 477 isolates (52.4%), while gram-positive bacteria accounted for 428 isolates (47.6%). Furthermore, Escherichia coli was the most frequently isolated pathogen, accounting for 387 cases (42.8%), followed by S. saprophyticus (300 cases, 33.1%) and S. aureus (131 cases, 14.5%). Other less common pathogens included Klebsiella spp. (30 cases, 3.3%), Pseudomonas aeruginosa (21, 2.3%), Enterobacter spp. (21 cases, 2.3%), Proteus spp. (12 cases, 1.3%), and Acinetobacter spp. (3 cases, 0.3%), as shown in Fig. 1.
Fig. 1.
Frequency of bacterial uropathogens isolated from UTI patients
Association between sex, age group, and uropathogens
Table 3 demonstrates a significant association between sex and uropathogen distribution (Monte Carlo p = 0.014). Klebsiella spp. were predominantly isolated from males (18, 60.0%), as were Enterobacter spp. (12, 57.1%). In contrast, Acinetobacter spp. was exclusively isolated from women (3, 100%). Escherichia coli was more common in females (254, 65.6%) than in males (133, 34.4%).
Table 3.
Association between sex, age group, and uropathogens isolated from UTI patients in Ibb city
| Demographic Variable | E. coli | S. saprophyticus | S. aureus | Proteus spp. | Klebsiella spp. | P. aeruginosa | Enterobacter spp. | Acinetobacter spp. | Total |
|---|---|---|---|---|---|---|---|---|---|
| n (%) | n (%) | n (%) | n (%) | n (%) | n (%) | n (%) | n (%) | ||
| Sex | |||||||||
| Male | 133 (34.4) | 92 (30.7) | 48 (36.6) | 3 (25.0) | 18 (60.0) | 6 (28.6) | 12 (57.1) | 0 (0.0) | 312 (34.5) |
| Female | 254 (65.6) | 208 (69.3) | 83 (63.4) | 9 (75.0) | 12 (40.0) | 15 (71.4) | 9 (42.9) | 3 (100.0) | 593 (65.5) |
| Monte Carlo p-value | 0.014 | ||||||||
| Age Group | |||||||||
| 0–18 | 51 (13.2) | 53 (17.7) | 27 (20.6) | 3 (25.0) | 3 (10.0) | 2 (9.5) | 1 (4.8) | 2 (66.7) | 142 (15.7) |
| 19–35 | 186 (48.1) | 169 (56.3) | 64 (48.9) | 6 (50.0) | 12 (40.0) | 9 (42.9) | 15 (71.4) | 1 (33.3) | 462 (51.0) |
| 36–50 | 75 (19.4) | 41 (13.7) | 26 (19.8) | 0 (0.0) | 4 (13.3) | 6 (28.6) | 2 (9.5) | 0 (0.0) | 154 (17.0) |
| 51–65 | 43 (11.1) | 24 (8.0) | 13 (9.9) | 0 (0.0) | 6 (20.0) | 4 (19.0) | 0 (0.0) | 0 (0.0) | 90 (9.9) |
| > 65 | 32 (8.3) | 13 (4.3) | 1 (0.8) | 3 (25.0) | 5 (16.7) | 0 (0.0) | 3 (14.3) | 0 (0.0) | 57 (6.3) |
| Monte Carlo p-value | < 0.001 |
A highly significant association was found between age group and uropathogen distribution (Monte Carlo P < 0.001). S. saprophyticus was predominantly isolated from young adults (169 cases, 56.3%). S. aureus was most common in pediatric patients (27 cases, 20.6%) and young adults (64, 48.9%), with only a single isolate (0.8%) in elderly patients. E. coli was most prevalent in young adults (186, 48.1%), with a progressive decline in proportion with advancing age to 8.3% in elderly patients. P. aeruginosa was isolated across all age groups except the older, with the highest proportion in adults aged 36–50 years (6, 28.6%). Acinetobacter spp. were detected only in pediatric patients (2, 66.7%) and young adults (1, 33.3%), as listed in Table 3.
Antibiotic susceptibility and resistance profile
The E. coli isolates were highly non-susceptible to ampicillin-sulbactam (89.4%), cefaclor (83.8%), nalidixic acid (79.5%), cefpodoxime (77.2%), clarithromycin (75.4%), and cefixime (74.6%). In contrast, the antibiotics amikacin and nitrofurantoin demonstrated excellent efficacy against E. coli, with resistance rates of 5.1% and 6.8%, respectively. Furthermore, E. coli isolates exhibited lower resistance to the antibiotics levofloxacin and gentamicin, at rates of 14.6% and 18.8%, respectively. In addition, Klebsiella spp. isolates were completely non-susceptible to ampicillin-sulbactam and clarithromycin (100% each) and highly non-susceptible to cefaclor (95.5%), cefuroxime (90.9%), and nalidixic acid (85.7%). In contrast, levofloxacin and amikacin demonstrated excellent efficacy against resistance, with rates of 4.8% and 16.0%, respectively. Furthermore, less than a quarter of Klebsiella spp. isolates exhibited resistance to ofloxacin, while 34.6% were non-susceptible to gentamicin. P. aeruginosa isolates were most non-susceptible to ampicillin-sulbactam at 88.5%, cefuroxime (76.5%), nalidixic acid, and cefdinir (75% each). Meanwhile, P. aeruginosa isolates showed lower non-susceptible to amikacin (15.0%) and fosfomycin (16.7%). Additionally, less than a third of the P. aeruginosa isolates exhibited resistance to the antibiotics moxifloxacin, cefpodoxime, and cefoperazone (Table 4).
Table 4.
Antibiotic resistance patterns by gram-negative bacteria isolated from UTI patients in Ibb city
| Antibiotic | E. coli (n = 387) | Klebsiella spp. (n = 30) |
P. aeruginosa (n = 21) |
Enterobacter spp. (n = 21) | Proteus spp. (n = 12) | Acinetobacter spp. (n = 3) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| T | NS (%) | T | NS (%) | T | NS (%) | T | NS (%) | T | NS (%) | T | NS (%) | ||
| Nitrofurantoin | 338 | 23 (6.8) | 15 | 5 (33.3) | 18 | 7 (38.9) | 20 | 0 (0.0) | 8 | 0 (0.0) | 3 | 1 (33.3) | |
| Levofloxacin | 335 | 49 (14.6) | 21 | 1 (4.8) | 16 | 7 (43.8) | 19 | 5 (26.3) | 9 | 0 (0.0) | 3 | 3 (100) | |
| Ciprofloxacin | 326 | 126 (38.7) | 23 | 12 (52.2) | 19 | 7 (36.8) | 21 | 9 (42.9) | 7 | 5 (71.4) | 2 | 0 (0.0) | |
| Norfloxacin | 290 | 154 (53.1) | 18 | 10 (55.6) | 18 | 8 (44.4) | 15 | 6 (40) | 9 | 5 (55.6) | 3 | 3 (100) | |
| Ofloxacin | 299 | 105 (35.1) | 21 | 4 (19) | 15 | 6 (40) | 19 | 10 (52.6) | 6 | 0 (0.0) | 3 | 0 (0.0) | |
| Lomefloxacin | 274 | 135 (49.3) | 18 | 12 (66.7) | 12 | 6 (50) | 17 | 10 (58.8) | 7 | 6 (85.7) | 3 | 3 (100) | |
| Moxifloxacin | 155 | 31 (20.0) | 16 | 5 (31.3) | 7 | 2 (28.6) | 8 | 2 (25) | 6 | 0 (0.0) | NA | NA | |
| Doxycycline | 297 | 140 (47.1) | 22 | 11 (50) | 9 | 5 (55.6) | 20 | 4 (20) | 7 | 3 (42.9) | 2 | 0 (0.0) | |
| Piperacillin-Tazobactam | 242 | 132 (54.5) | 25 | 14 (56) | 13 | 8 (61.5) | 15 | 9 (60) | 8 | 3 (37.5) | NA | NA | |
| Ceftazidime | 280 | 192 (68.6) | 23 | 13 (56.5) | 15 | 11 (73.3) | 20 | 15 (75) | 11 | 9 (81.8) | 3 | 3 (100) | |
| Cefepime | 223 | 138 (61.9) | 22 | 11 (50) | 11 | 8 (72.7) | 21 | 14 (66.7) | 7 | 6 (85.7) | 3 | 1 (33.3) | |
| Cefixime | 284 | 212 (74.6) | 19 | 9 (47.4) | 19 | 14 (73.7) | 9 | 7 (77.8) | 7 | 3 (42.9) | 3 | 3 (100) | |
| Ampicillin-Sulbactam | 320 | 286 (89.4) | 19 | 19 (100) | 17 | 15 (88.2) | 21 | 17 (81) | 8 | 8 (100) | 1 | 1 (100) | |
| Nalidixic Acid | 210 | 167 (79.5) | 21 | 18 (85.7) | 8 | 6 (75) | 6 | 5 (83.3) | 6 | 6 (100) | 1 | 1 (100) | |
| Cefprozil | 94 | 67 (71.3) | 4 | 4 (100) | 5 | 2 (40.0) | NA | NA | 1 | 0 (0.0) | NA | NA | |
| Cefaclor | 278 | 233 (83.8) | 22 | 21 (95.5) | 15 | 11 (73.3) | 13 | 9 (69.2) | 10 | 9 (90) | 2 | 2 (100) | |
| Cefoperazone | 291 | 127 (43.6) | 23 | 12 (52.2) | 17 | 5 (29.4) | 14 | 6 (42.9) | 9 | 3 (33.3) | 3 | 0 (0.0) | |
| Cefuroxime | 275 | 158 (57.5) | 22 | 20 (90.9) | 17 | 13 (76.5) | 12 | 7 (58.3) | 7 | 6 (85.7) | 2 | 2 (100) | |
| Ceftriaxone | 293 | 129 (44) | 25 | 18 (72) | 17 | 10 (58.8) | 12 | 1 (8.3) | 10 | 3 (30) | 1 | 0 (0.0) | |
| Cefotaxime | 358 | 180 (50.3) | 24 | 16 (66.7) | 19 | 10 (52.6) | 19 | 17 (89.5) | 10 | 8 (80) | 3 | 1 (33.3) | |
| Clarithromycin | 61 | 46 (75.4) | 4 | 4 (100) | 5 | 2 (40.0) | NA | NA | 1 | 0 (0.0) | NA | NA | |
| Azithromycin | 194 | 62 (32.0) | 15 | 7 (46.7) | 9 | 3 (33.3) | 1 | 0 (0.0) | 5 | 2 (40) | NA | NA | |
| Gentamicin | 330 | 62 (18.8) | 26 | 9 (34.6) | 20 | 7 (35.0) | 14 | 5 (35.7) | 8 | 4 (50) | 3 | 2 (66.7) | |
| Trimethoprim-Sulfamethoxazole | 319 | 138 (43.3) | 27 | 18 (66.7) | 19 | 9 (47.4) | 7 | 0 (0.0) | 11 | 4 (36.4) | 1 | 1 (100) | |
| Cefradine | 41 | 34 (82.9) | NA | NA | NA | NA | 6 | 6 (100) | 4 | 0 (0.0) | NA | NA | |
| Meropenem | 16 | 4 (25.0) | 4 | 1 (25) | 1 | 0 (0.0) | NA | NA | NA | NA | NA | NA | |
| Imipenem | 16 | 2 (12.5) | 2 | 0 (0.0) | 1 | 0 (0.0) | NA | NA | NA | NA | NA | NA | |
| Amikacin | 297 | 15 (5.1) | 25 | 4 (16.0) | 20 | 3 (15.0) | 13 | 4 (30.8) | 7 | 0 (0.0) | 2 | 0 (0.0) | |
| Cefdinir | 162 | 107 (66) | 5 | 5 (100) | 4 | 3 (75.0) | 13 | 7 (53.8) | 3 | 1 (33.3) | 3 | 2 (66.7) | |
| Cefpodoxime | 127 | 98 (77.2) | 2 | 1 (50) | 4 | 1 (25.0) | 16 | 14 (87.5) | 2 | 2 (100) | 3 | 2 (66.7) | |
| Fosfomycin | 104 | 42 (40.4) | 11 | 3 (27.3) | 6 | 1 (16.7) | 11 | 4 (36.4) | 7 | 3 (42.9) | 2 | 0 (0.0) | |
T= tested; NS = non-susceptible; NA = Not Applicable
Furthermore, the resistance of Enterobacter spp. isolates was found to be highly against cefotaxime (89.5%), cefpodoxime (87.5%), nalidixic acid (83.3%), and ampicillin-sulbactam (81%). However, nitrofurantoin and trimethoprim-sulfamethoxazole achieved high therapeutic efficacy against Enterobacter spp. isolates, with sensitivity reaching 100%, while 8.3%, 20%, 26.3%, and 30.8% of isolates were non-susceptible to ceftriaxone, doxycycline, levofloxacin, and amikacin, respectively. In addition, Proteus spp. showed high resistance against ampicillin-sulbactam (100%), nalidixic acid (100%), cefaclor (90%), lomefloxacin (85.7%), cefepime (85.7%), and ceftazidime (81.8%). Meanwhile, none of the Proteus spp. isolates showed any resistance to nitrofurantoin, levofloxacin, ofloxacin, moxifloxacin, or amikacin (Table 4).
The current results show that S. aureus isolates exhibited 100% resistance to penicillin, 95.2% to fosfomycin, and 88.5% to ampicillin-sulbactam. Furthermore, S. saprophyticus showed high resistance to cefalexin (91.9%), ampicillin-sulbactam (90.7%), fosfomycin (87.8%), and cefadroxil (78.4%). In addition, the majority of S. saprophyticus isolates showed moderate to below-moderate resistance to most of the antibiotics used (Table 5).
Table 5.
Antibiotic resistance patterns by gram-positive bacteria isolated from UTI patients in Ibb city
| Antibiotics | S. aureus | S. saprophyticus | ||
|---|---|---|---|---|
| Tested | NS (%) | Tested | NS (%) | |
| Nitrofurantoin | 99 | 17 (17.2) | 224 | 23 (10.3) |
| Levofloxacin | 105 | 0 (0.0) | 248 | 5 (2) |
| Ciprofloxacin | 101 | 24 (23.8) | 246 | 43 (17.5) |
| Ofloxacin | 96 | 4 (4.2) | 236 | 14 (5.9) |
| Lomefloxacin | 68 | 35 (51.5) | 163 | 45 (27.6) |
| Moxifloxacin | 44 | 0 (0.0) | 117 | 1 (0.9) |
| Tetracycline | 64 | 30 (46.9) | 181 | 93 (51.4) |
| Ampicillin-Sulbactam | 104 | 92 (88.5) | 246 | 223 (90.7) |
| Amoxicillin-Clavulanate | 123 | 47 (38.2) | 263 | 128 (48.7) |
| Amoxicillin | 116 | 78 (67.2) | 264 | 174 (65.9) |
| Cefadroxil | 101 | 78 (77.2) | 232 | 182 (78.4) |
| Cefprozil | 67 | 25 (37.3) | 126 | 62 (49.2) |
| Ceftriaxone | 112 | 26 (23.2) | 250 | 39 (15.6) |
| Cefalexin | 68 | 57 (83.8) | 136 | 125 (91.9) |
| Erythromycin | 72 | 48 (66.7) | 164 | 109 (66.5) |
| Clarithromycin | 26 | 19 (73.1) | 63 | 39 (61.9) |
| Clindamycin | 23 | 16 (69.6) | 41 | 28 (68.3) |
| Gentamicin | 111 | 6 (5.4) | 262 | 13 (5) |
| Trimethoprim-Sulfamethoxazole | 110 | 45 (40.9) | 249 | 63 (25.3) |
| Cefradine | 12 | 4 (33.3) | 8 | 1 (12.5) |
| Linezolid | 11 | 8 (72.7) | 39 | 18 (46.2) |
| Cefdinir | 36 | 15 (41.7) | 66 | 20 (30.3) |
| Penicillin | 28 | 28 (100) | 56 | 41 (73.2) |
| Cefpodoxime | 15 | 10 (66.7) | 29 | 21 (72.4) |
| Fosfomycin | 21 | 20 (95.2) | 49 | 43 (87.8) |
NS = non-susceptible
Multidrug resistance (MDR) profile
The current results show that Gram-negative bacterial isolates exhibited the highest resistance to cephalosporins G1 (78.4%), followed by penicillins (74.3%) and cephalosporins G2 (72.4%). Moderate resistance was observed towards cephalosporins G3 (58.6%), tetracyclines (45.7%), and macrolides (42.7%). Additionally, nitrofurantoin demonstrated the highest therapeutic efficacy against Gram-negative bacterial isolates, with a resistance rate of 9%, followed by aminoglycosides (15.0%) and carbapenem (17.5%). This finding revealed that E. coli isolates exhibited high resistance to Cephalosporins G1, reaching 82.9%, which then decreased to 58.2% with Cephalosporins G3, with a slight increase to 61.9% with Cephalosporins G4. Additionally, 4.4% of E. coli isolates were non-susceptible to penicillins. In contrast, nitrofurantoin and aminoglycosides showed high efficacy against E. coli, with non-susceptible rates of 6.8% and 12.3%, respectively (Table 6).
Table 6.
MDR patterns by gram-negative bacteria isolated from UTI patients in Ibb city
| Families of antibiotics | Isolated gram negative bacteria | Total | ||||||
|---|---|---|---|---|---|---|---|---|
| E. coli |
Klebsiella
spp. |
P. aeruginosa | Enterobacter spp. | Proteus spp. |
Acinetobacter
spp. |
|||
| Nitrofurantoin | T | 338 | 15 | 18 | 20 | 8 | 3 | 402 |
| NS (%) | 23 (6.8) | 5 (33.3) | 7 (38.9) | 0 (0.0) | 0 (0.0) | 1 (33.3) | 36 (9.0) | |
| Quinolones | T | 2227 | 153 | 113 | 125 | 58 | 18 | 2694 |
| NS (%) | 790 (35.5) | 67 (43.8) | 49 (43.4) | 47 (37.6) | 22 (37.9) | 11 (61.1) | 986 (36.6) | |
| Tetracyclines | T | 297 | 22 | 9 | 20 | 7 | 2 | 357 |
| NS (%) | 140 (47.1) | 11 (50.0) | 5 (55.6) | 4 (20) | 3 (42.9) | 0 (0.0) | 163 (45.7) | |
| Penicillins | T | 562 | 44 | 30 | 36 | 16 | 1 | 689 |
| NS (%) | 418 (74.4) | 33 (75) | 23 (76.7) | 26 (72.2) | 11 (68.8) | 1 (100) | 512 (74.3) | |
| Cephalosporins G1 | T | 41 | NA | NA | 6 | 4 | NA | 51 |
| NS (%) | 34 (82.9) | NA | NA | 6 (100) | 0 (0.0) | NA | 40 (78.4) | |
| Cephalosporins G2 | T | 647 | 48 | 37 | 25 | 18 | 4 | 779 |
| NS (%) | 458 (70.8) | 45 (93.8) | 26 (70.3) | 16 (64) | 15 (83.3) | 4 (100) | 564 (72.4) | |
| Cephalosporins G3 | T | 1795 | 121 | 95 | 103 | 52 | 19 | 2185 |
| NS (%) | 1045 (58.2) | 74 (61.2) | 54 (56.8) | 67 (65) | 29 (55.8) | 11 (58) | 1280 (58.6) | |
| Cephalosporins G4 | T | 223 | 22 | 11 | 21 | 7 | 3 | 287 |
| NS (%) | 138 (61.9) | 11 (50.0) | 8 (72.7) | 14 (66.7) | 6 (85.7) | 1 (33.3) | 178 (62.0) | |
| Macrolides | T | 255 | 19 | 14 | 1 | 6 | NA | 295 |
| NS (%) | 108 (42.4) | 11 (57.9) | 5 (35.7) | 0 (0.0) | 2 (33.3) | NA | 126 (42.7) | |
| Aminoglycosides | T | 627 | 51 | 40 | 27 | 15 | 5 | 765 |
| NS (%) | 77 (12.3) | 13 (25.5) | 10 (25) | 9 (33.3) | 4 (26.7) | 2 (40) | 115 (15.0) | |
| Oxazolidinones | T | 319 | 27 | 19 | 7 | 11 | 1 | 384 |
| NS (%) | 138 (43.3) | 18 (66.7) | 9 (47.4) | 0 (0.0) | 4 (36.4) | 1 (100) | 170 (44.3) | |
| Carbapenem | T | 32 | 6 | 2 | NA | NA | NA | 40 |
| NS (%) | 6 (18.8) | 1 (16.7) | 0 (0.0) | NA | NA | NA | 7 (17.5) | |
| Fosfomycin | T | 104 | 11 | 6 | 11 | 7 | 2 | 141 |
| NS (%) | 42 (40.4) | 3 (27.3) | 1 (16.7) | 4 (36.4) | 3 (42.9) | 0 (0.0) | 53 (37.6) | |
T= tested; NS = non-susceptible; NA = Not Applicable
Furthermore, 93.8% of Klebsiella spp. isolates were documented as non-susceptible to cephalosporins G2, decreasing to 50% for cephalosporins G4. In addition, Klebsiella spp. isolates exhibited high resistance to penicillins (75%), moderate resistance to tetracyclines (50%), macrolides (57.9%), and low resistance to fosfomycin (27.3%) and carbapenems (16.7%). P. aeruginosa showed the highest resistance to penicillins (76.7%), followed by cephalosporins G4 (72.3%) and cephalosporins G2 (70.3%). The isolates also exhibited moderate resistance to tetracyclines (55.6%) and third-generation cephalosporins G3 (56.8%), as summarized in Table 5.
All Enterobacter spp. isolates showed resistance to cephalosporins G1 (100%), while 72.2% were non-susceptible to penicillins, 66.7% to cephalosporins G4, and 65% to cephalosporins G3. However, Enterobacter spp. isolates exhibited complete susceptibility (100%) to nitrofurantoin and oxazolidinones. Proteus spp. isolates showed high resistance to cephalosporins G4 (85.7%) and G2 (83.3%) and 68.8% to penicillins. In contrast, all isolates showed complete susceptibility to nitrofurantoin and cephalosporins G1. Despite the sample size, Acinetobacter spp. isolates were found to be 100% non-susceptible to the cephalosporin G2, penicillins, and oxazolidinone antibiotic families. Acinetobacter spp. isolates also exhibited low resistance to nitrofurantoin and cephalosporins G4, at 33.3% each. Furthermore, none of the Acinetobacter spp. isolates were found to be non-susceptible to tetracyclines or fosfomycin (Table 6).
The results of this study showed that S. aureus exhibited the lowest resistance to aminoglycosides, fluoroquinolones, and nitrofurantoin, at rates of 5.4%, 15.2%, and 17.2%, respectively. Similarly, S. saprophyticus showed the lowest resistance to aminoglycosides (5%), nitrofurantoin (10.3%), and fluoroquinolones (10.7%). The analysis revealed that first-generation (G1) cephalosporins exhibited a high resistance rate of 90.6% in S. aureus, with a significant decrease in resistance with each subsequent generation, from 37.3% in second-generation (G2) cephalosporins to 31.3% in third-generation cephalosporin antibiotics. In contrast, isolates of S. aureus and S. saprophyticus exhibited broad resistance to penicillins, macrolides, and lincosamides, exceeding 65% in similar cases. Resistance to fosfomycin exceeded 85% in both isolates. Furthermore, tetracyclines and folate pathway inhibitors showed moderate activity against S. aureus isolates, with a resistance rate of less than 50% (Fig. 2).
Fig. 2.
MDR patterns by gram-positive bacteria isolated from UTI patients in Ibb city
Risk factors for multidrug resistance
The overall prevalence rate of MDR was reported at 27.8% (252/905) among UTIs. The results revealed that males have a statistically significant incidence of MDR bacteria (33.7%) compared to females (24.8%), with statistically significant differences (P < 0.001). In addition, the Cochran-Armitage trend test indicated that the prevalence of multidrug-resistant isolates trended markedly upward with age (P < 0.001). The MDR was increased progressively from 22.5% among pediatric patients (32 out of 142 cases) to 43.9% in elderly patients over 65 years (25 out of 57 cases) (Table 7).
Table 7.
Multidrug resistance patterns by sex, age group, and organism among UTIs
| Category | Subgroup | Total Cases | MDR Cases | MDR Prevalence (%) |
|---|---|---|---|---|
| Sex | ||||
| Male | 312 | 105 | 33.7 | |
| Female | 593 | 147 | 24.8 | |
| Age Group | ||||
| Pediatric (0–18) | 142 | 32 | 22.5 | |
| Young Adult (19–35) | 462 | 128 | 27.7 | |
| Adult (36–50) | 154 | 40 | 26.0 | |
| Middle Aged (51–65) | 90 | 27 | 30.0 | |
| Elderly (> 65) | 57 | 25 | 43.9 | |
| Isolated organism | ||||
| Acinetobacter spp. | 3 | 1 | 33.3 | |
| P. aeruginosa | 21 | 7 | 33.3 | |
| Klebsiella spp. | 30 | 9 | 30.0 | |
| E. coli | 387 | 137 | 35.4 | |
| Enterobacter spp. | 21 | 9 | 42.9 | |
| S. aureus | 131 | 26 | 19.8 | |
| Proteus spp. | 12 | 5 | 41.7 | |
| S. saprophyticus | 300 | 58 | 19.3 | |
| Total | 905 | 252 | 27.8 | |
Furthermore, organism-specific analysis revealed that Enterobacter spp. harbored the highest MDR rate at 42.9% (9 out of 21 cases), followed by Proteus spp. at 41.7% (5 out of 12 cases) and E. coli at 35.4% (137 out of 387 cases). Additionally, S. aureus and S. saprophyticus showed lower MDR rates of 19.8% (26/131 cases) and 19.3% (58/300 cases), respectively (Table 7).
Discussion
The results of this analysis showed a predominance of female patients with UTIs compared to that of male patients. This finding is consistent with the well-established epidemiological understanding that UTIs are more common in women than in men owing to anatomical and physiological factors, including a shorter urethra and hormonal influences [30]. Similar reports have documented a higher prevalence among females in Yemen [10, 11, 14, 30], Saudi Arabia [8], and Ethiopia [1].
The higher proportion observed in this study may reflect the inclusion of both community-acquired and healthcare-associated infections, as well as the potential differences in healthcare-seeking behavior between sexes in Yemen. Therefore, awareness campaigns targeting groups most affected by UTIs should be intensified, along with a review of treatment protocols and antibiotic use policies. This age distribution aligns with previous findings that reported majority of UTI cases occurred among patients aged 15 to 65 years in Yemen [11, 13], in Ethiopia [1], and Lebanon [14]. The high proportion of UTIs among young adults, particularly women, is likely attributable to increased sexual activity, pregnancy, and other reproductive health factors that predispose this population to infection. To avoid complications from silent infections in both the fetus and the mother, women, especially those of childbearing age, should be encouraged to practice preventative personal hygiene to curb the spread of UTIs.
This outcome revealed that E. coli was the predominant uropathogen, followed by S. saprophyticus and S. aureus. The predominance of E. coli is consistent with the global literature, where it is recognized as the most common cause of both community-acquired and hospital-acquired UTIs [30–31]. In Yemen, the prevalence of E. coli was reported at 35.4% of UTI cases in Al-Mukalla [32] and 32.7% in Taiz [9], between 42% and 44% in Sana’a [10, 11, 14], and 50% in Hodeidah City [33]. Similarly, E. coli was reported more than 37% of total UTI isolates in Saudi Arabia [15] and 67.1% of the cases in Lebanon [19].
Although our results indicate a higher prevalence of S. saprophyticus than global studies (5–20%) [1, 20], they are consistent with findings recorded in Yemen at 34% [10]. This demonstrates that our results are not an anomaly but reflect an epidemiological pattern specific to the Yemeni study environment. Previous reports indicate that this bacterium is the second most commonly isolated urinary tract pathogen after E. coli, which aligns with our findings [34–35]. This increased prevalence may be attributed to environmental factors, local epidemiological patterns, clinical practices, and variations in laboratory detection techniques. Therefore, conducting future studies to understand the strain patterns of S. saprophyticus bacteria among patients with UTIs is essential to confirm whether these strains possess unique virulence factors or antibiotic resistance.
The significant association between sex and uropathogen distribution revealed important trends. Klebsiella spp. and Enterobacter spp. were predominantly isolated from males, while Acinetobacter spp. were exclusively isolated from females. These findings align with those of studies demonstrating that male patients are more likely to harbor healthcare-associated and antibiotic-resistant pathogens due to factors such as underlying urological abnormalities, catheterization, and prior antibiotic exposure [30]. In contrast, E. coli was more common in females, which is consistent with other reports [2, 9]. This is due to anatomical and physical factors of the female urinary system that allow E. coli and other organisms to travel from the anus to the urinary tract. Strengthening health awareness programs for women in preventative personal hygiene is one of the best ways to reduce the spread of urinary tract infections.
These data revealed a highly significant association between age groups and uropathogen distribution. S. saprophyticus was predominantly isolated from young adults, reinforcing its association with sexually active women. S. aureus was the most common pathogen in pediatric patients and young adults and was rare in elderly patients. This pattern may reflect the higher incidence of community-associated methicillin-resistant S. aureus (MRSA) infections in younger populations and the role of S. aureus in pediatric UTIs [30].
Escherichia coli infection showed a gradual decline with age, from 48.1% in young adults to 8.3% in older adults. This decline may be attributed to the increasing prevalence of other pathogens or the emergence of healthcare-associated pathogens in older populations with greater exposure to healthcare. P. aeruginosa was isolated across all age groups except the elderly, with the highest proportion in adults aged 36–50 years. This distribution suggests that P. aeruginosa UTIs may be associated with occupational exposure or specific risk factors in this age group.
The global health system is currently facing the challenge of antibiotic resistance, a biological evolutionary process rooted in ancient times. The mechanisms of microbial resistance to antibiotics arose long ago, perhaps hundreds of years ago, within complex ecosystems [36]. The majority of E. coli isolates exhibited low sensitivity to ampicillin-sulbactam, cefaclor, nalidixic acid, cefpodoxime, and cefixime. This finding is consistent with studies conducted in Yemen [11, 13, 14] and reports from Saudi Arabia by Al Wutayd et al. [15] and India by Kalal et al. [20]. In contrast, gentamicin, levofloxacin, amikacin, and nitrofurantoin have shown greater effectiveness against E. coli, and these results are consistent with studies in Yemen [10, 14] and studies in other populations [1, 37–39].
Furthermore, Klebsiella spp. isolates were completely resistant to ampicillin-sulbactam and clarithromycin as well as highly insensitive to cefaclor, cefuroxime, and nalidixic acid. Previous reports in Yemen [11, 14] and Ethiopia [1] supported these results. In addition, Klebsiella spp. isolates exhibited high susceptibility to levofloxacin and amikacin, and these findings are consistent with the report by Gondos et al. [10]. In addition, Antibiotic susceptibility testing revealed that amikacin exhibited high efficacy against negative bacterial isolates, consistent with findings from multiple studies in the local [14, 40] and globally [1, 38].
These results show that Gram-negative bacterial isolates exhibited the highest resistance to G1 cephalosporins, penicillins, and G2 cephalosporins. Meanwhile, nitrofurantoin, aminoglycosides, and carbapenems showed the highest efficacy against Gram-negative bacterial isolates. This finding was supported with the study of Addis et al. [1] and Alzahrani et al. [1].
In the current results, E. coli isolates recorded the highest resistance to Cephalosporins G1 and slightly moderate resistance to Cephalosporins G3 and Cephalosporins G4. Furthermore, more than half of the isolates were resistant to cefepime, which is concerning given that this fourth-generation cephalosporin is often used to treat severe infections. This finding contrasts with the study of Noori et al. [2], which reported that 62.6% of E. coli isolates were sensitive to cefepime. Furthermore, the high resistance to third-generation cephalosporins in this study reflects the widespread use of these agents in Yemen and the consequent selection pressure. The findings of this study indicated that the high resistance rates to commonly prescribed agents and third-generation cephalosporins necessitate a reconsideration of empirical treatment protocols. Despite the small sample size, the emergence of highly linezolid-resistant S. aureus isolates is an indication of the bacteria’s ability to resist antibiotics used as a last line of treatment for these bacteria.
Trimethoprim-sulfamethoxazole resistance is substantial, limiting its utility for empirical therapy. Similar resistance rates have been reported in Saudi Arabia [15] and Ethiopia [1], indicating a regional pattern of declining effectiveness of this historically first-line agent. Furthermore, gentamicin resistance was relatively low compared to other antibiotics, supporting its continued use in combination therapy or as an alternative when other agents are not suitable. The outcomes are consistent with findings from other reports [2, 20, 41].
This finding revealed that the overall MDR prevalence of 27.8%, and this is lower than reported previously at 56.0% in Yemen 13], 59.5% in Ethiopia [1], and 30.56% in Bangladesh [37]. The discrepancy in results may be attributed to the study area, sample size, sample collection methods, and diagnostic techniques. Therefore, this finding emphasizes the critical need to implement antibiotic stewardship programs in the study area and to strengthen ongoing surveillance for multidrug-resistant urinary tract pathogens.
The significant positive correlation between age and MDR prevalence represents a crucial finding for clinical risk stratification. The progressive increase in MDR from 22.5% in pediatric patients to 43.9% in elderly individuals highlights the cumulative effect of age-related factors such as increased healthcare exposure, comorbidities, and prior antibiotic use. This age gradient is consistent with findings from Yemen [13], Saudi Arabia [16], and Lebanon [42]. The high MDR rates observed in this study underscore the urgent need for antimicrobial stewardship programs in Yemen. As highlighted by Ghaleb et al. [11] and Ahmed et al. [13], the establishment of stewardship initiatives is essential to reduce selection pressure, preserve the effectiveness of remaining antibiotics, and contain the spread of resistant organisms.
The organism-specific MDR analysis revealed that Enterobacter spp. and Proteus spp. had the highest MDR rate, with 42.9% and 41.7%, respectively, though the small number of isolates limits the generalisability of this finding. In addition, the remaining isolated bacteria, both Gram-positive and Gram-negative, had MDR rates ranging between 35.4% and 19.3%. A different study conducted in Yemen by Ahmed et al. [13] revealed that the highest MDR rates were observed in K. pneumoniae (100.0%), followed by P. aeruginosa (92.3%), E. coli (81.3%), and S. aureus (73.2%). Also, Addis et al. [1] documented that S. aureus recorded the highest MDR rate (80%), followed by K. pneumoniae (41%), E. coli (18%), and Pseudomonas spp. (12%). Adopting innovative strategies, such as the “Trojan Horse Technique,” to combat antibiotic-resistant bacteria, is essential. This technique targets gram-negative bacteria by delivering antibiotics using bacterial nutrient vectors [43]. A promising anti-virulence strategy can also be achieved directly by targeting bacterial metallophores, as these systems are crucial for scavenging essential transition metals necessary for bacterial survival and pathogenesis; thus, their disruption can severely reduce bacterial virulence and prevent infection [44]. Furthermore, bacteriophage therapy (phage therapy) offers a highly specific and evolving alternative. The ability of bacteriophages to target multidrug-resistant strains without disrupting the microbiota of the host makes them a viable alternative to the failure of traditional antibiotic treatments [45].
Significant and limitation of this study
The large sample size used in this analysis will provide valuable local data on the distribution of urinary pathogens in a resource-limited area that has not been previously studied. Moreover, the extensive and varied panel of antimicrobial agents in this analysis will contribute to addressing the knowledge deficit concerning antibiotic resistance patterns among UTI patients in the study area. The findings of this analysis constitute a crucial primary database to guide future public health research. Despite the importance of this study, there are some limitations. The current study relied on secondary data recorded in some private laboratories, which may limit the generalizability of the results to the Ibb Governorate. Due to the absence of clinical data, this analysis is unable to distinguish between community-acquired and healthcare-associated UTIs. Due to limited resources, the genetic patterns of isolated strains causing UTIs were not identified, thus limiting insights into the molecular mechanisms or phylogenetic evolution within the study population. Antibiotic susceptibility assessment was limited to only a few isolates, and these data should be considered preliminary indicators reflecting general trends in the region and not a comprehensive analysis of microbial resistance patterns in the study area. Owing to the lack of necessary data, this study was unable to present the risk factors contributing to the prevalence of UTI pathogens, which would have added significant scientific value. Furthermore, the study was unable to correlate microbial isolates with treatment outcomes or patient clinical trajectories because of insufficient clinical data and treatment details. Due to restrictions in Yemen, reference bacterial strains were not used as controls during identification and antibiotic susceptibility testing.
Conclusions
In light of these findings, we conclude that the epidemiological profile of UTIs in the studied population is characterized by a high prevalence of E. coli, with a notably significant role of S. saprophyticus in young females. The increasing prevalence of uropathogenic bacteria and their resistance to commonly used antibiotics, such as ampicillin, amoxicillin, and many cephalosporins, which are considered first-line treatments, pose a clinical challenge that necessitates comprehensive analytical and molecular studies to assess resistance mechanisms and prevent treatment failure. Although uropathogenic bacteria have shown high laboratory sensitivity to certain antibiotics, such as amikacin and nitrofurantoin, these should not be widely used as treatment options. Their use should be limited to consultation with a specialist physician, considering the patient’s clinical characteristics and the severity of the infection. The significant association between pathogen type and demographic factors, such as age and sex, highlights the variations in microbial distribution across different patient groups. Based on these findings, it is imperative to consider local resistance data and baseline demographics when assessing the trends in antibiotic susceptibility. Strengthening laboratory capacity for the regular assessment of antibiotic susceptibility to pathogens will contribute to identifying appropriate antibiotics and limiting the rise of antibiotic-resistant bacteria. Public awareness campaigns aimed at educating the community about the dangers of indiscriminate and self-medicated antibiotic use are practical measures that contribute to reducing the spread of multidrug-resistant microbes. Updating national policies and legislation on antibiotic use, along with updating the national protocol for prescribing antibiotics to patients, is essential. Furthermore, it is crucial to strengthen partnerships between health sectors to monitor antibiotic-resistant strains and track genetic factors across different regions of Yemen.
Acknowledgements
The authors thank the laboratory officials in Ibb for their cooperation in providing the data for this analysis.
Abbreviations
- WHO
World Health Organization
- AMR
Antimicrobial Resistance
- MDR
Multidrug-Resistant
- XDR
Extensively Drug-Resistant
- PDR
Pandrug-Resistant
- 95% CI
Confidence Intervals
- SPSS
Statistical Package for the Social Sciences
- CLSI
Clinical and Laboratory Standards Institute
- P value
Probability
- UTIs
Urinary Tract Infections
- CLSI
Clinical and Laboratory Standards Institute
- MRSA
Methicillin-resistant Staphylococcus aureus
Author contributions
Mohammed NA and Shomais A designed the study; Alshameri R and Al Mashraqi A collected the data; and Alnawah M, AL-Qaisi H, and Alshoaibi H analyzed and interpreted the data. Mohammed NA and Alshameri R wrote the first draft manuscript. Edrees W and Al-Shehari W reviewed and edited the final manuscript. All authors revised and approved the manuscript for submission.
Funding
No fund.
Data availability
The datasets used and analyzed during this analysis are available from the corresponding author, who will provide any relevant data upon reasonable request.
Declarations
Ethics approval and consent to participate
Initially, prior to data extraction and analysis, the study plan was submitted to the Research Ethics Committee of the Faculty of Medicine and Health Sciences at Ibb University, which granted approval on September 2, 2025 (Reference No.: IBBUNI.AC.YEM.2025.112). It was conducted in accordance with Yemeni public health laws and regulations and the Declaration of Helsinki. Owing to the retrospective nature of the study, which relies on preexisting data from medical records, an exemption from the requirement for informed consent was obtained from the committee. Administrative approvals were obtained from all participating laboratories for data access, with a guarantee of strict confidentiality of all personal information.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Addis T, Mekonnen Y, Ayenew Z, Fentaw S, Biazin H. Bacterial uropathogens and burden of antimicrobial resistance pattern in urine specimens referred to Ethiopian Public Health Institute. PLoS ONE. 2021;16(11):e0259602. 10.1371/journal.pone.0259602. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Noori M, Aghamohammad S, Ashrafian F, Gholami M, Hosseini S. Retrospective cross-sectional study on prevalence and susceptibility pattern of bacterial pathogens causing urinary tract infections at a teaching hospital in Tehran, Iran. Arch Pediatr Infect. 2023;11(2):e120903. 10.5812/pedinfect-120903. [DOI]
- 3.Sharma N, Gupta A, Walia G, Bakhshi R. Pattern of antimicrobial resistance of Escherichia coli isolates from urinary tract infection patients: A three year retrospective study. JAPS. 2016;6(1):062–5. 10.7324/JAPS.2016.600110. [DOI] [Google Scholar]
- 4.Alzahrani MA, Sadoma HM, Mathew S, Alghamdi S, Malik JA, Anwar S. Retrospective analysis of antimicrobial susceptibility of uropathogens isolated from pediatric patients in tertiary hospital at Al-Baha Region, Saudi Arabia. Healthcare. 2021;9(11):1564. 10.3390/healthcare9111564. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Naghavi M, Vollset SE, Ikuta KS, et al. Global burden of bacterial antimicrobial resistance 1990–2021: a systematic analysis with forecasts to 2050. Lancet. 2024;404(10459):1199–226. 10.1016/s0140-6736(24)01867-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.World Health Organization. (2025). Global call to action to address antimicrobial resistance. https://www.who.int/publications/m/item/global-call-to-action-to-address-antimicrobial-resistance
- 7.Shawkat ND, Yassin NA. The prevalence of multidrug-resistant uropathogenic bacterial profile with antibiotic susceptibility patterns among the community and hospitalized patients during COVID waves. Cureus. 2024;16(5):e60613. 10.7759/cureus.60613. [DOI] [PMC free article] [PubMed]
- 8.Almutawif YA, Eid HMA. Prevalence and antimicrobial susceptibility pattern of bacterial uropathogens among adult patients in Madinah, Saudi Arabia. BMC Infect Dis. 2023;23(1):582. 10.1186/s12879-023-08578-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Jendy AS, Al-Ofairi BA. Bacterial pathogens of patients with urinary tract infections and antibiotics susceptibility in Taiz Governorate–Yemen. Al-Mustansiriyah J Sci. 2019;30(1):1–8. 10.23851/mjs.v30i1.530. [DOI] [Google Scholar]
- 10.Gondos AS, Al-Moyed KA, Al-Robasi AB, Al-Shamahy HA, Alyousefi NA. Urinary tract infection among renal transplant recipients in Yemen. PLoS ONE. 2015;10(12):e0144266. 10.1371/journal.pone.0144266. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Ghaleb Y, Al Serouri A, Alamad M, Nasher S, Alsoumainy A. The growing antimicrobial resistance of urinary tract infections, Sana’a-Yemen, 2015. iProceedings. 2018;4(1): e10539. 10.2196/10539. [DOI]
- 12.Edrees WH, Anbar AAM. Prevalence and antibacterial susceptibility of bacterial uropathogens isolated from pregnant women in Sana’a, Yemen. PSM Biol Res. 2020;5(4):157–65. https://psmjournals.org/index.php/biolres/article/view/461. [Google Scholar]
- 13.Ahmed F, Alhamdani E, Al-Wageeh S, et al. Epidemiology and antimicrobial resistance of uropathogens in a tertiary care setting in Yemen: A retrospective study. Archivio Italiano di Urol e Andrologia. 2025;97(3):14129. 10.4081/aiua.2025.14129. [DOI] [PubMed] [Google Scholar]
- 14.Hassan SMA, Al-Moyed KA, Abdu SSA, et al. Antibiotic resistance rates of bacterial isolates from urinary tract infections in diabetic patients in Sana’a, Yemen. Univers J Pharm Res. 2026;11(2):6–11. 10.22270/ujpr.v11i2.1528. [DOI] [Google Scholar]
- 15.Al Wutayd O, Al Nafeesah A, Adam I, Babikir IH. The antibiotic susceptibility patterns of uropathogens isolated in Qassim, Saudi Arabia. J Infect Dev. 2018;12(11):946–52. 10.3855/jidc.10553. [DOI] [PubMed] [Google Scholar]
- 16.Alhazmi AH, Alameer KM, Abuageelah BM, et al. Epidemiology and antimicrobial resistance patterns of urinary tract infections: A cross-sectional study from Southwestern Saudi Arabia. Medicina. 2023;59(8):1411. 10.3390/medicina59081411. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Ajem MS, Alsdig SF, Lawgali YF. Detection of bacterial species causing urinary tract infections in Brega City Region, isolation, identification, and antibiotic sensitivity testing. SJFSSU. 2023;3(1):130–8. 10.37375/sjfssu.v3i1.1040. [DOI] [Google Scholar]
- 18.Afeke I, Adu-Amankwaah J, Hamid A, et al. Urinary tract infections and antimicrobial susceptibility: A retrospective trend analysis of uropathogens in women in Accra, Ghana (2019–2022). PLoS ONE. 2025;20(4):e0321293. 10.1371/journal.pone.0321293. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Sokhn ES, Salami A, El Roz A, et al. Antimicrobial susceptibilities and laboratory profiles of Escherichia coli, Klebsiella pneumoniae, and Proteus mirabilis isolates as agents of urinary tract infection in Lebanon: Paving the way for better Diagnostics. Med Sci. 2020;8(3):32. 10.3390/medsci8030032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kalal BS, Nagaraj S. Urinary tract infections: A retrospective, descriptive study of causative organisms and antimicrobial pattern of samples received for culture, from a tertiary care setting. Germs. 2016;6(4):132–6. 10.11599/germs.2016.1100. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.World Health Organization. Global antibiotic resistance surveillance report. 2025. Available at: https://www.who.int/publications/i/item/9789240116337.
- 22.Ali M, Edrees WH, Al-Shehari WA, Xue G, et al. Antifungal susceptibility pattern of Candida species isolated from pregnant Women. Front Cell Infect Microbiol. 2024;14:1434677. 10.3389/fcimb.2024.1434677. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Al-Hammadi S, Al-Shehari WA, Edrees WH, et al. Prevalence of methicillin-resistant Staphylococcus aureus (MRSA) among patients with oral infections in Sana’a City-Yemen. BMC Oral Health. 2025;25(1047). 10.1186/s12903-025-06247-0. [DOI] [PMC free article] [PubMed]
- 24.Edrees WH, Al-Awar SM. Bacterial contamination of mobile phones of medical laboratory workers at Sana’a city, Yemen and their antimicrobial susceptibility. JPPRes. 2020;8(6):591–9. 10.56499/jppres20.862_8.6.591. [DOI] [Google Scholar]
- 25.Al-Aomary NM, Edrees WH, Al-Ofairi BA, Thabit JM. Nasal carriage of Staphylococcus aureus and its antibacterial susceptibility profiles among food handlers in Sana’a restaurants, Yemen. Israa Univ J Appl Sci. 2024;7(2):55–70. 10.52865/DDHP5456. [DOI] [Google Scholar]
- 26.Alhlale MF, Humaid A, Saleh AH, Alsweedi KS, Edrees WH. Effect of most common antibiotics against bacteria isolated from surgical wounds in Aden Governorate hospitals, Yemen. Univers J Pharm Res. 2020;5(1):21–4. 10.22270/ujpr.v5i1.358. [DOI] [Google Scholar]
- 27.Al-Ofairi BA, Edrees WH, Al-Hadheq AA, et al. Gram-negative bacteria in some clinical specimens and their antibiotics resistance profiles, Sana’a. Yemen Electron J Univ Aden Basic Appl Sci. 2024;5(1):86–94. 10.47372/ejua-ba.2024.1.331. [DOI] [Google Scholar]
- 28.Somashekara SC, Deepalaxmi S, Jagannath N, et al. Retrospective analysis of antibiotic resistance pattern to urinary pathogens in a tertiary care hospital in South India. J Basic Clin Pharm. 2014;5(4):105–8. 10.4103/0976-0105.141948. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Clinical and Laboratory Standards Institute (CLSI). Performance standards for antimicrobial susceptibility testing. M100. 31st ed. Wayne, PA. USA: Clinical and Laboratory Standards Institute; 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Flores-Mireles AL, Walker JN, Caparon M, Hultgren SJ. Urinary tract infections: Epidemiology, mechanisms of infection and treatment options. Nat Rev Microbio. 2015;13:269–84. 10.1038/nrmicro3432. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Alkhyat SH, Maqtari MAA. Prevalence of microorganisms isolates from urinary tract infections at some hospitals in Sana’a City, Yemen. Int J Curr Microbiol App Sci. 2014;3(6):876–85. [Google Scholar]
- 32.Al-Haddad AM, Bin Ghouth AS, El-Hosseiny M. Microbial resistance in patients with urinary tract infections in Al-Mukalla, Yemen. Sudan J Med Sci. 2010;5(2):24–9. 10.4314/sjms.v5i2.57813. [DOI] [Google Scholar]
- 33.AL-Kadassy AM, Baraheem O, Ogaili M. The prevalence of urinary tract infection (UTI) among pregnant women in Hodeidah City. IOSR-JDMS. 2016;15(12):105–9. https://www.iosrjournals.org/iosr-jdms/papers/Vol15-Issue%2012/Version-2/U151202105109.pdf. [Google Scholar]
- 34.Hur J, Lee A, Hong J, et al. Staphylococcus saprophyticus bacteremia originating from urinary tract infections: A case report and literature review. Infect Chemother. 2016;48(2):136–9. 10.3947/ic.2016.48.2.136. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Ehlers S, Merrill SA, Staphylococcus saprophyticus I. 2023. StatPearls - NCBI Bookshelf. https://www.ncbi.nlm.nih.gov/books/NBK482367/ [PubMed]
- 36.Bahmad HF, Ghssein G, Bahmad M, et al. Paleopathology Meets Public Health: Deep-Time Syndemics and the Ecology of Emerging Infections. Pathogens. 2026;15(5):543. 10.3390/pathogens15050543. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Khalil I, Sayed A, Kabir AKMA, et al. Determinants of multidrug-resistant urinary tract infections: A retrospective cross-sectional study from a tertiary care hospital in southern Bangladesh. PLOS Glob Public Health. 2026;6(1):e0005022. 10.1371/journal.pgph.0005022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Adeep M, Nima T, Kezang W, Tshokey T. A retrospective analysis of the etiologic agents and antibiotic susceptibility pattern of uropathogens isolated in the Jigme Dorji Wangchuck National Referral Hospital, Thimphu, Bhutan. BMC Res Notes. 2016;9:54. 10.1186/s13104-015-1728-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Bhargava K, Nath G, Bhargava A, Kumari R, Aseri GK, Jain N. Bacterial profile and antibiotic susceptibility pattern of uropathogens causing urinary tract infection in the eastern part of Northern India. Front Microbiol. 2022;13:965053. 10.3389/fmicb.2022.965053. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Alsumairy H, AlZubiery TK, Alharazi T, Baddah M, Al-Zubeiry A. Antibiogram of the common uropathogenic bacteria among Yemeni patients in Sana’a City: A recent report. IJAR. 2018;6(4):123–30. 10.9734/sajrm/2018/v1i2759. [DOI] [Google Scholar]
- 41.Alzahrani MA, Ali MS, Anwar S. Bacteria causing urinary tract infections and its antibiotic susceptibility pattern at tertiary hospital in Al-Baha Region, Saudi Arabia: A retrospective study. J Pak Med Assoc. 2020;73(11):2087–92. 10.4103/jpbs.jpbs_294_19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Hassan S, Ghssein G, Kassem Z, Alarab S, El Aris J, Ezzeddine Z. Antimicrobial resistance patterns of Escherichia coli isolates from female urinary tract infection patients in Lebanon: An age-specific analysis. Microbiol Res. 2025;16(11):240. 10.3390/microbiolres16110240. [DOI] [Google Scholar]
- 43.Tillotson GS. Trojan Horse Antibiotics-A novel way to circumvent gram-negative bacterial resistance? Infect Dis (Auckl). 2016;9:45–52. 10.4137/idrt.s31567. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Ezzeddine Z, Ghssein G. Towards new antibiotics classes targeting bacterial metallophores. Microb Pathog. 2023;182:106221. 10.1016/j.micpath.2023.106221. [DOI] [PubMed] [Google Scholar]
- 45.Subramanian A. Emerging roles of bacteriophage-based therapeutics in combating antibiotic resistance. Front Microbiol. 2024;15:1384164. 10.3389/fmicb.2024.1384164. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and analyzed during this analysis are available from the corresponding author, who will provide any relevant data upon reasonable request.