Abstract
Antimicrobial resistance in urinary tract infections (UTIs) poses a critical public health challenge, yet comparative data between outpatient and inpatient settings remain limited, particularly in Latin America. This study characterized the epidemiology, microbiology, and resistance patterns of UTIs in northwestern Mexico. A retrospective analysis of 1041 patients with UTI (May–November 2024) was conducted. Microorganism identification and antimicrobial susceptibility were determined using the MicroScan WalkAway system in accordance with CLSI guidelines. Results: Outpatients accounted for 80.5% of cases and inpatients for 19.4%, with a 3.1% mortality rate. Escherichia coli predominated (62.9%), with a significant association with outpatients (p = 0.02), whereas Enterobacter cloacae, Acinetobacter spp., Candida tropicalis, and C. albicans were associated with inpatients (p < 0.05). Pediatric patients exhibited distinctive microbiological profiles: Pseudomonas aeruginosa (9.7% vs. 2.1%, p = 0.032), Enterococcus faecalis (33.3% vs. 16.2%, p = 0.001), and Staphylococcus epidermidis (26.6% vs. 6.5%, p = 0.027) were significantly more prevalent than in adults. Multidrug resistance (MDR) was detected in 27.1% of isolates, and extensive drug resistance (XDR) in 3.2%. XDR was associated with Gram-positive bacteria (12.2% vs. 1.4%, p < 0.001). Carbapenem-resistant Enterobacteriaceae (CRE) were identified in 0.9% (7/772) of cases, with 42.9% occurring in outpatients. Hospitalization (OR: 2.01; 95% CI: 1.43–2.83), surgical services (OR: 1.41; 95% CI: 1.02–1.97), and recent surgery (OR: 2.37; 95% CI: 1.04–5.39) were independent predictors of MDR/XDR infections. Conclusions: These findings demonstrate the emergence of CRE within the community and distinctive pediatric resistance patterns, underscoring the need for tailored antimicrobial stewardship strategies in this region.
Keywords: urinary tract infection, outpatients, inpatients, E. coli, antimicrobial resistance, carbapenem resistance
1. Introduction
Urinary tract infections (UTIs) are among the most common diseases worldwide, occurring in both hospitalized and outpatient settings. UTIs are characterized by the growth of microorganisms that cause an inflammatory response in the urinary tract epithelium [1,2]. UTIs account for approximately 150 million cases worldwide each year, and 40% of infections contracted in hospitals are UTIs [3,4]. In Mexico, UTIs are the leading cause of disease in women of reproductive age and the third leading cause of morbidity [5]. UTIs are more prevalent in women than in men. Approximately seven million women suffer from an outpatient UTI each year, and the direct medical costs of UTIs in the United States are estimated to be around $2.19 billion, with an additional $6 billion in costs worldwide [6].
Various microorganisms, including bacteria and fungi, can cause urinary tract infections (UTIs). Bacteria are the most prevalent cause of UTIs, accounting for nearly 95% of cases. The primary etiological agents in UTIs are Gram-negative bacteria, including Escherichia coli (E. coli), which accounts for approximately 60% of cases, followed by Klebsiella pneumoniae (K. pneumoniae). Staphylococcus is the most prevalent Gram-positive bacterium, and Candida is the most pervasive fungus [7]. These microorganisms are the most common in UTIs in both adults and children.
UTIs in hospitalized or outpatient patients can persist and progress from acute to chronic infections. Several factors may contribute to this phenomenon, but the most critical factor is the microorganism’s antimicrobial resistance [8]. High levels of antibiotic resistance have been reported in E. coli isolated from patients with UTIs. For example, resistance to ampicillin ranges from 28% to 40% in countries such as Austria, Greece, Portugal, and the United States. Additionally, high resistance to gentamicin (50%), aminopenicillin+ beta-lactamase inhibitor (50%), ciprofloxacin (45%), and cefuroxime (33%) was observed among E. coli isolates from patients with UTIs worldwide between 2003 and 2010 [8]. High levels of antibiotic resistance in UTIs are a public health problem that must be prioritized to treat these infections effectively.
Urinary tract infections (UTIs) are associated with various factors, including poor hygiene and immune system disorders. However, the factors associated with high antibiotic resistance in UTIs are unclear. Identifying the clinical and epidemiological factors associated with antimicrobial resistance in patients with UTIs will help treat infections promptly and accurately, preventing progression to severe or fatal cases. The objective of this study was to: (i) determine the epidemiological and clinical factors of outpatients and inpatients (of all ages) with UTIs; (ii) identify the microorganisms that caused UTIs in outpatients and inpatients and relate them to age groups; (iii) determine the antimicrobial resistance of the microorganisms that caused UTIs; and (iv) associate characteristics of patients with UTIs (epidemiological and clinical) with antimicrobial resistance in northwestern Mexico.
2. Materials and Methods
2.1. Subjects of Study
This historical, analytical, observational study with a retrospective approach included inpatients and outpatients diagnosed with urinary tract infection (UTI) between May and November 2024 at the Mexican Social Security Institute’s Regional General Hospital No. 1 in northwestern Mexico. UTI was diagnosed based on signs and symptoms, as well as a positive urine culture for a microorganism with 1 × 105 CFU/mL [9,10]. Patients with negative urine cultures and those without a clinical history were excluded. The research was evaluated and approved by the Research Ethics Committee (Local Health Research Committee 2506) of the IMSS Family Medicine Unit No. 46. The registration number is R-2025-2506-045.
2.2. Data Collection
Various data were collected from patients’ medical records with UTIs. Epidemiological data included age, sex, demographics, and the hospital department of origin. Clinical data included weight, height, and body mass index (BMI), which was classified according to WHO standards as underweight, normal weight, overweight, or obesity grades I, II, or III [11]. Other clinical data included metabolic diseases (e.g., hypertension, type 2 diabetes, obesity, kidney disease, and dyslipidemia), pregnancy, use of invasive devices, mortality, routine urinalysis, and biochemical analysis.
2.3. Microorganisms Isolated from UTI and Antimicrobial Resistance
Urine samples from patients with signs and symptoms of a UTI were processed to isolate microorganisms and determine their antimicrobial resistance. The MicroScan WalkAway 96 automated system (Beckman Coulter, Brea, CA, USA) was used to identify microorganisms and determine antimicrobial resistance according to the manufacturer’s instructions. Gram-positive, Gram-negative, and fungal organisms were isolated from patients, and bacterial and fungal species were identified. Regarding antimicrobial resistance, we tested antibiotics and antifungal agents recommended by the Mexican healthcare system. Antibiotic susceptibility was interpreted according to CLSI guidelines [12], and resistance was classified as follows: in bacteria, resistance to ≥3 distinct antibiotic categories was defined as multidrug resistance (MDR). Bacteria resistant to ≥6 categories of antibiotics were classified as extensively drug-resistant (XDR) [13]. In fungi: MDR were resistant to more than one antifungal agent from two classes, and XDR were resistant to more than one antifungal agent from three classes [14,15].
2.4. Statistical Analysis
The Kolmogorov–Smirnov test was used to assess the normality of the data. For quantitative variables, the central tendency (mean) and dispersion (standard deviation and variance) were used. For qualitative variables, percentages and frequencies were used. The chi-square test and binary logistic regression were used in univariate and multivariate analyses to identify associations. A p-value of less than 0.05 was considered statistically significant. Based on their distributions, the Kruskal–Wallis test or ANOVA was used for qualitative variables. SPSS version 20 (IBM Corp., Armonk, NY, USA) was used for statistical analysis.
3. Results
3.1. Epidemiological and Clinical Characteristics of Patients with Urinary Tract Infection
A total of 1041 patients were included in this study, of whom 80.5% (839) were outpatients and 19.4% (202) were inpatients (Table 1). By age group, 4.6% (48/1041) were children (under 18 years of age), 47.7% (497/1041) were adults (18 to 59 years of age), and 45.7% (487/1041) were elderly (60 years of age or older). Among the patients, 76.3% (795/1041) were female, and 23.4% (244/1041) were male. Additionally, 87.9% (879/1041) were from urban areas, and 7.1% (74/1041) were from rural areas. Most urinary tract infections were diagnosed in the family medicine department (36.5%, 380 of 1041), followed by the internal medicine department (29.6%, 309 of 1041). Other departments where UTIs were diagnosed included emergency medicine (12.9%), gynecology, urology, surgery, nephrology, and pediatrics (Table 1). A comparison of outpatients and inpatients revealed that adults, women, and patients from the family medicine and emergency medicine departments were more prevalent among outpatients (p ≤ 0.05). Conversely, pediatric patients, older adults, men, and patients from the departments of internal medicine, gynecology, surgery, and traumatology were more prevalent among inpatients (p ≤ 0.05).
Table 1.
Epidemiological Characteristics of Inpatient and Outpatient Patients with Urinary Tract Infections.
| Characteristics | Total | Outpatient n (%) | Inpatient n (%) | p-Value * |
|---|---|---|---|---|
| n = 1041 | n = 839 (80.5) | n = 202 (19.4) | ||
| Age groups | ||||
| Pediatrics (<18 years) | 48 (4.6) | 33 (0.4) | 15 (7.4) * | 0.03 |
| Adults (18–59 years) | 497 (47.7) | 428 (51.0) * | 69 (34.1) | <0.001 |
| Older adult (≥60 years) | 487 (46.7) | 369 (43.9) | 118 (58.4) * | <0.001 |
| Sex, n (%) | ||||
| Female | 795 (76.3) | 653 (77.8) * | 142 (70.2) | 0.02 |
| Male | 244 (23.4) | 184 (21.9) | 60 (29.7) * | 0.02 |
| Not determined | 23 (0.1) | 23 (2.7) | 0 (0.0) | |
| Demography | ||||
| Urban | 915 (87.9) | 734 (87.4) | 181 (89.6) | 0.104 |
| Rural | 74 (7.1) | 58 (6.9) | 16 (7.9) | 0.647 |
| Not determined | 52 (4.9) | 47 (5.6) | 5 (2.4) | - |
| Hospital service | ||||
| Family medicine | 380 (36.5) | 376 (44.8) * | 4 (1.9) | <0.001 |
| Internal medicine | 309 (29.6) | 221 (26.3) | 88 (43.5) * | <0.001 |
| Emergency Department/ICU | 135 (12.9) | 119 (14.1) * | 16 (7.9) | 0.019 |
| Gynecology and Obstetrics | 63 (6.0) | 35 (4.1) | 28 (13.8) * | <0.001 |
| Urology | 36 (3.4) | 22 (2.6) | 14 (6.9) | 0.005 |
| Not determined | 35 (3.3) | 35 (4.1) | 0 (0.0) | - |
| Surgery | 23 (2.2) | 3 (0.3) | 20 (9.9) * | <0.001 |
| Nephrology | 22 (2.1) | 16 (1.9) | 6 (2.9) | 0.41 |
| Pediatrics | 20 (1.9) | 6 (0.7) | 14 (6.9) * | <0.001 |
| Traumatology and Orthopedics | 18 (1.7) | 6 (0.7) | 12 (5.9) * | <0.001 |
Statistical significance was obtained using Fisher’s exact test. p value *: ≤0.05 statistically significant.
As shown in Table 2, the clinical characteristics of patients with UTIs are as follows: 3.4% (36/1041) were underweight, 18.7% (195/1041) were normal weight, 36.5% (379/1041) were grade I obese, 8.5% (86/1041) were grade II obese, 7.1% (74/1041) were grade III obese. The most prevalent metabolic disease was hypertension, affecting 43.9% (458/1041) of patients. It was followed by type 2 diabetes (36.5%; 380 patients), obesity (27.9%; 291 patients), kidney disease (20.5%; 214 patients), and dyslipidemia (8.3%; 87 patients). 15.3% (160/1041) of patients were pregnant, and 3.1% (32/1041) died (Table 2). Among patients with urinary tract infections, 10.5% (110/1041) had urinary catheters, and 12.2% (128/1041) had undergone surgery within the past month. Thirty-four percent (316/1041) of patients had leukocyte esterase present in their urine analysis, 28.6% (298/1041) had nitrites, 15.8% (165/1041) had protein, 3.9% (41/1041) had ketones, 18.1% (188/1041) had erythrocytes, 23.9% (249/1041) had 10–85 leukocytes, 14.6% (153/1041) had moderate to abundant epithelial cells, 32% (334/1041) had moderate to abundant bacteria, and 13.9% (145/1041) had hematuria. The primary biochemical characteristics of patients with urinary tract infections are shown in Table 2 and are as follows: creatinine, 1.42 mg/dL; blood urea nitrogen, 15.5 mg/dL; leukocytes, 6.84%; erythrocytes, 3.34%; hemoglobin, 9.49 g/dL; hematocrit, 28.3%; lymphocytes, 18.4%; and neutrophils, 47.4%.
Table 2.
Clinical Characteristics of Outpatient and Inpatient Patients with Urinary Tract Infections.
| Characteristics | Total | Outpatient n (%) | Inpatient n (%) | p-Value * |
|---|---|---|---|---|
| n = 1041 | n = 839 (80.5) | n = 202 (19.4) | ||
| BMI category | ||||
| Low weight | 36 (3.4) | 26 (3.0) | 10 (4.9) | 0.196 |
| Normal weight (18.5–24.9) | 195 (18.7) | 158 (18.8) | 37 (18.3) | 0.866 |
| Overweight (25–29.9) | 380 (36.5) | 308 (36.7) | 72 (35.6) | 0.777 |
| Obesity grade I (30–34.9) | 199 (19.1) | 174 (20.7) * | 25 (12.3) | 0.007 |
| Obesity grade II (35–39.9) | 89 (8.5) | 72 (8.5) | 17 (8.4) | 0.94 |
| Obesity grade III (≥40) | 74 (7.1) | 62 (7.3) | 12 (5.9) | 0.472 |
| Not determined | 68 (6.5) | 39 (4.6) | 29 (14.3) | - |
| Metabolic disease | ||||
| High blood pressure | 458 (43.9) | 358 (42.6) | 100 (49.5) | 0.079 |
| Type 2 diabetes | 380 (36.5) | 295 (35.1) | 85 (42.1) | 0.067 |
| Obesity | 291 (27.9) | 252 (30.0) * | 39 (19.3) | 0.002 |
| Kidney disease | 214 (20.5) | 164 (19.5) | 50 (24.7) | 0.167 |
| Dyslipidemia | 87 (8.3) | 75 (8.9) | 12 (5.9) | 0.1 00 |
| Pregnancy | 160 (15.3) | 132 (15.7) | 28 (19.2) | 0.508 |
| Invasive devices | ||||
| Bladder catheter | 110 (10.5) | 33 (3.9) | 77 (38.1) * | <0.001 |
| Previous Surgery (last month) | 128 (12.2) | 76 (9.0) | 52 (25.7) * | <0.001 |
| Mortality | 32 (3.1) | 2 (0.2) | 30 (14.8) * | <0.001 |
| General Urine Test | ||||
| Leukocyte esterase | 316 (30.4) | 228 (27.2) | 88 (43.6) * | <0.001 |
| Nitrites | 298 (28.6) | 260 (31.0) * | 38 (18.8) | <0.001 |
| Proteins | 165 (15.8) | 97 (11.5) | 68 (33.7) * | <0.001 |
| Ketones | 41 (3.9) | 13 (1.2) | 28 (13.9) * | <0.001 |
| Erythrocytes | 188 (18.1) | 104 (12.4) | 84 (41.6) * | <0.001 |
| Leukocytes 10 to 85 U | 249 (23.9) | 170 (13.0) | 79 (41.6) * | <0.001 |
| Moderate to abundant epithelial cells | 153 (14.6) | 125 (12.0) | 28 (13.9) | 0.842 |
| Moderate to abundant bacterial presence | 334 (32.0) | 243 (17.3) | 91 (45.0) * | <0.001 |
| Hematuria | 145 (13.9) | 74 (8.8) | 71 (35.1) * | <0.001 |
| Biochemical traits—Media (SD) | ||||
| Creatinine (mg/dL) | 1.42 ± 8.6 | 1.33 ± 8.34 | 1.79 ± 9.6 | 0.758 |
| Blood uric nitrogen (mg/dL) | 15.5 ± 20.3 | 14.6 ± 16.8 | 21.04 ± 3.4 | 0.248 |
| Leukocytes (%) | 6.84 ± 4.9 | 6.65 ± 4.1 | 7.62 ± 7.7 | 0.739 |
| Erythrocytes (%) | 3.34 ± 2.8 | 3.41 ± 2.5 | 3.07 ± 4.0 * | <0.001 |
| Hemoglobin (g/dL) | 9.49 ± 6.5 | 9.88 ± 9.72 | 7.89 ± 5.1 * | <0.001 |
| Hematocrit (%) | 28.3 ± 16.1 | 29.31 ± 16.1 | 24.2 ± 15.7 * | <0.001 |
| Lymphocytes (%) | 18.4 ± 34.6 | 20.6 ± 37.8 | 9.28 ± 12.4 * | <0.001 |
| Neutrophils (%) | 47.4 ± 28.7 | 47.1 ± 26.9 | 48.8 ± 35.5 * | 0.001 |
Abbreviations: g: grams, dL: deciliter, mg: milligrams, ng, nanograms, L: liters, %: percentage, U: units. Normal value: creatinine: 0.5–12 mg/dL, Blood uric nitrogen 6–20 mg/dL, erythrocytes 4.2–5.4%, hemoglobin: 12–16 gr/dL, lymphocytes: 24–38%, neutrophils 55–70%. Statistical significance was obtained using Fisher’s exact test. * p value: ≤0.05 statistically significant.
Some clinical characteristics were associated with outpatient status. For instance, grade I obesity and metabolic diseases were related to outpatients in the BMI category. Overall, the presence of nitrites in a urine analysis was associated with outpatients (p ≤ 0.05; see Table 2). Urinary catheter use, prior surgeries, and mortality were associated with inpatients (p ≤ 0.05; see Table 2). Most general urine analysis parameters were more frequently observed in inpatients (except for nitrites and moderate-to-abundant epithelial cells). Low biochemical characteristics of erythrocytes, hemoglobin, hematocrit, lymphocytes, and neutrophils were also associated with hospitalized patients (p ≤ 0.05; see Table 2).
3.2. Distribution of the Primary Microorganisms That Cause Urinary Tract Infections in Hospitalized and Outpatient Patients
Table 3 shows the microorganisms isolated from outpatients and inpatients with urinary tract infections. Of these, 80.5% (839 out of 1041) were Gram-negative bacteria, 16.5% (172 out of 1041) were Gram-positive bacteria, and 2.9% (30 out of 1041) were fungi. Among the Gram-negative bacteria, E. coli was the most prevalent (62.9%, or 526 out of 839), followed by K. pneumoniae (17.1%, or 144 out of 839), Proteus mirabilis (P. mirabilis) (9.7%, or 82 out of 839), Enterobacter cloacae (E. cloacae) (2.5%, or 21 out of 839), Pseudomonas aeruginosa (P. aeruginosa) (2.1%, or 10 out of 839), and Citrobacter and Acinetobacter (1.1%, or 10 out of 839) The most prevalent Gram-positive bacteria were Streptococcus haemolyticus (S. haemolyticus) (22.9%, 39/172), Enterococcus faecalis (E. faecalis) (21.5%, 37/172), Streptococcus agalactiae (S. agalactiae) (11.6%, 20/172), Staphylococcus aureus (S. aureus) (9.3%, 16/172), and Staphylococcus epidermidis (S. epidermidis) (8.1%, 14/172) (Table 3). Among fungi, Candida tropicalis (C. tropicalis) was the most prevalent (36.6%, 11/30), followed by Candida albicans (C. albicans) (30%, 9/30), Candida glabrata (C. glabrata) (23.3%, 7/30), and Candida krusei (C. krusei) (6.6%, 2/30). Additionally, 11.8% (123/1041) of cases were polymicrobial (Table 3). The presence of E. coli was associated with outpatients (p ≤ 0.05). Gram-negative bacteria (E. cloacae and Acinetobacter spp.), fungi (C. tropicalis and C. albicans), and hospitalization were generally associated (p ≤ 0.05; Table 3). The distribution of Gram-positive bacteria and polymicrobial infections was similar between outpatient and inpatient settings.
Table 3.
Distribution of the Primary Microorganisms Causing Urinary Tract Infections in Outpatient and Inpatient Patients.
| Microorganisms | Total | Outpatient n (%) | Inpatient n (%) | p-Value * |
|---|---|---|---|---|
| n = 1041 | n = 839 (80.5) | n = 202 (19.4) | ||
| Gram-negative bacteria | 840 (80.5) | 694 (70.0) | 145 (71.7) * | 0.001 |
| Escherichia coli | 526 (62.9) | 438 (63.1) * | 87 (43.0) | 0.02 |
| Klebsiella pneumoniae | 144 (17.1) | 118 (17.0) | 26 (12.8) | 0.659 |
| Proteus mirabilis | 82 (9.7) | 64 (9.2) | 18 (8.9) | 0.255 |
| Enterobacter cloacae | 21 (2.5) | 10 (1.4) | 8 (3.9) * | 0.029 |
| Pseudomonas aeruginosa | 18 (2.1) | 17 (2.4) | 4 (1.9) | 0.967 |
| Citrobacter spp. | 10 (1.1) | 8 (1.1) | 2 (0.9) | 0.962 |
| Acinetobacter spp. | 10 (1.1) | 5 (0.7) | 5 (2.4) * | 0.014 |
| Gram-positive bacteria | 172 (16.5) | 141 (16.8) | 31 (15.3) | 0.616 |
| Staphylococcus haemolyticus | 39 (22.9) | 33 (23.4) | 6 (19.5) | 0.518 |
| Enterococcus faecalis | 37 (21.5) | 30 (21.7) | 7 (22.5) | 0.858 |
| Streptococcus agalactiae | 20 (11.6) | 19 (13.4) | 1 (3.2) | 0.1 00 |
| Staphylococcus aureus | 16 (9.3) | 13 (9.2) | 3 (9.6) | 0.947 |
| Staphylococcus epidermidis | 14 (8.1) | 10 (7.0) | 4 (12.9) | 0.383 |
| Fungus | 30 (2.9) | 4 (0.5) | 26 (12.8) * | <0.001 |
| Candida tropicalis | 11 (36.6) | 1 (25.0) | 11 (42.3) * | <0.001 |
| Candida albicans | 9 (30.0) | 1 (25.0) | 8 (30.7) * | <0.001 |
| Candida glabrata | 7 (23.3) | 0 (0.0) | 7 (26.9) | - |
| Candida krusei | 2 (6.6) | 2 (50.0) | 0 (0.0) | - |
| Polymicrobial infections | 123 (11.8) | 98 (11.6) | 25 (12.3) | 0.738 |
Other Gram-negative bacteria found in patients: Proteus mirabilis, Serratia marcescens, Serratia fonticola, Klebsiella oxytoca, Pseudomonas luteola, Enterobacter aerogenes, Streptococcus salivarius, Proteus penneri, Morganella morganii, Providencia stuartii, Enterobacter aerogenes, Pseudomonas putida, Providencia rettgeri, and Pantoea spp. Other Gram-positive bacteria found in patients: Staphylococcus saprophyticus, Streptococcus mitis, Staphylococcus hominis, Staphylococcus sciuri, Enterococcus faecium, Kocuria kristinae, Kocuria varians, Enterococcus casseliflavus, Streptococcus sanguinis, Streptococcus dysgalactiae, α-hemolytic Streptococcus, Streptococcus uberis, Streptococcus thoraltensis, Streptococcus suis, and Streptococcus sanguinis. Other fungi found in patients: Candida spp. Statistical significance was obtained using Fisher’s exact test. p value *: ≤0.05 statistically significant.
Additionally, the distribution of microorganisms by age group was analyzed (see Table 4). Most microorganisms were evenly distributed among the three age groups: pediatric, adult, and elderly. However, P. aeruginosa was more prevalent in the pediatric group than in the adult group (9.7% vs. 2.1%, p = 0.032) and the elderly group (9.7% vs. 2.1%, p = 0.023). Gram-positive bacteria were generally more prevalent in the pediatric age group than in the geriatric age group (31.2% vs. 6.9%, p = 0.001). E. faecalis (33.3% vs. 16.2%, p = 0.001) and S. epidermidis (26.6% vs. 6.5%, p = 0.027) were more prevalent in the pediatric group than in the adult group.
Table 4.
Distribution of Microorganisms Causing Urinary Tract Infections by Age Group.
| Microorganisms | Total | Age Group | ||||
|---|---|---|---|---|---|---|
| Pediatric < 18 Years n (%) | Adult 18–59 Years n (%) | Older Adult ≥ 60 Years n (%) | p-Value * | |||
| n = 1041 | n = 48 (4.6) | n = 497 (47.7) | n = 487 (46.7) | Pediatric vs. Adult | Pediatric vs. Old Adult | |
| Gram-negative bacteria | 839 (80.5) | 41 (85.4) | 369 (74.2) | 429 (88.9) | 0.113 | 0.614 |
| Escherichia coli | 526 (62.9) | 26 (63.4) | 228 (61.7) | 272 (63.4) | 0.837 | 0.879 |
| Klebsiella pneumoniae | 144 (17.1) | 7 (17.0) | 73 (19.7) | 64 (14.9) | 0.188 | 0.202 |
| Proteus mirabilis | 82 (9.7) | 4 (9.7) | 33 (8.9) | 45 (10.4) | 0.745 | 0.662 |
| Pseudomonas aeruginosa | 21 (2.5) | 4 (9.7) *# | 8 (2.1) | 9 (2.1) | 0.032 | 0.023 |
| Enterobacter cloacae | 18 (2.1) | 0 (0.0) | 10 (2.7) | 8 (1.8) | - | - |
| Citrobacter spp. | 10 (1.1) | 0 (0.0) | 1 (0.2) | 9 (2.0) | - | - |
| Acinetobacter spp. | 10 (1.1) | 0 (0.0) | 3 (0.8) | 7 (1.6) | - | - |
| Gram-positive bacteria | 172 (16.5) | 15 (31.2) # | 123 (24.7) | 34 (6.9) | 0.384 | 0.001 |
| Enterococcus faecalis | 39 (3.7) | 5 (33.3) * | 20 (16.2) | 14 (41.1) | 0.001 | 0.753 |
| Staphylococcus haemolyticus | 37 (3.5) | 4 (26.6) | 27 (21.9) | 6 (17.6) | 0.744 | 0.47 |
| Streptococcus agalactiae | 20 (1.9) | 1 (6.6) | 15 (12.1) | 4 (11.7) | 0.1 00 | 0.141 |
| Staphylococcus aureus | 16 (1.5) | 1 (6.6) | 13 (10.5) | 2 (5.8) | 0.1 00 | 0.1 00 |
| Staphylococcus epidermidis | 14 (1.3) | 4 (26.6) * | 8 (6.5) | 2 (5.8) | 0.027 | 0.062 |
| Fungus | 30 (2.9) | 1 (2.0) | 5 (1.0) | 24 (5.1) | 0.426 | 0.716 |
| Candida tropicalis | 11 (36.6) | 0 (0.0) | 2 (40.0) | 9 (37.5) | - | - |
| Candida albicans | 9 (30.0) | 1 (100) | 1 (20.0) | 7 (29.1) | 0.333 | 0.08 |
| Candida glabrata | 7 (23.3) | 0 (0.0) | 1 (20.0) | 6 (25.0) | - | - |
| Candida krusei | 2 (6.6) | 0 (0.0) | 1 (20.0) | 1 (4.1) | - | - |
| Polymicrobial infections | 123 (11.8) | 2 (4.1) | 59 (11.8) | 62 (12.7) | 0.147 | 0.101 |
Statistical significance was obtained using Fisher’s exact test. *: ≤0.05 statistically significant pediatric vs. adult; #: ≤0.05 statistically significant pediatric vs. older adult.
3.3. Antimicrobial Resistance of Microorganisms Isolated from Patients with Urinary Tract Infections
Table 5 presents antimicrobial resistance data for Gram-negative and Gram-positive bacteria. Overall, 70.2% (710/1011) of the bacteria were resistant to at least one antimicrobial. Of those, 27.1% (274/1011) were multidrug-resistant (MDR), and 3.2% (33/1011) were extensively drug-resistant (XDR). Twenty-nine-point seven percent (301/1011) of the bacteria were sensitive to antibiotics, 66.8% (709/1011) were resistant to one to six antimicrobials, and 33.2% (302/1011) were resistant to seven to 13 antimicrobials (Table 5). A comparison of Gram-negative and Gram-positive bacteria revealed that the XDR category was associated with Gram-positive bacteria (12.2% vs. 1.4%, p < 0.001). The second and third antimicrobials were associated with Gram-negative bacteria (20.9% vs. 6.3%, p < 0.001, and 19.3% vs. 4%, p < 0.001, respectively). The fourth, fifth, sixth, and ninth antimicrobials were also associated with Gram-negative bacteria (9.8% vs. 0.5%, p < 0.001; 8.1% vs. 0.1%, p < 0.001; 6.9% vs. 0.1%, p < 0.001; and 2.3% vs. 0.1%, p = 0.003). Only Gram-negative bacteria were resistant to 10–13 antibiotics (Table 5).
Table 5.
Antimicrobial Resistance of Gram-Negative and Gram-Positive Bacteria Isolated from Patients with Urinary Tract Infections.
| Category | Total Bacteria | Gram-Negative n (%) | Gram-Positive n (%) | p Value |
|---|---|---|---|---|
| n = 1011 (%) | n = 839 (76.6) | n = 172 (23.4) | ||
| At least one antimicrobial | 710 (70.2) | 592 (70.5) | 118 (68.6) | 0.782 |
| MDR | 274 (27.1) | 218 (25.9) | 56 (32.5) | 0.089 |
| XDR | 33 (3.2) | 12 (1.4) | 21 (12.2) * | <0.001 |
| Resistance by number of antimicrobials | ||||
| 0 | 301 (29.7) | 247 (29.4) | 54 (31.9) | 0.647 |
| 1 | 216 (21.3) | 186 (22.1) | 30 (17.4) | 0.185 |
| 2 | 187 (18.4) | 176 (20.9) * | 11 (6.3) | <0.001 |
| 3 | 169 (16.7) | 162 (19.3) * | 7 (4.0) | <0.001 |
| 4 | 70 (6.9) | 50 (5.9) | 20 (11.6) | 0.466 |
| 5 | 22 (2.1) | 5 (0.5) | 17 (9.8) * | <0.001 |
| 6 | 15 (1.4) | 1 (0.1) | 14 (8.1) * | <0.001 |
| 7 | 13 (1.2) | 1 (0.1) | 12 (6.9) * | <0.001 |
| 8 | 3 (0.2) | 0 (0.0) | 3 (1.4) | - |
| 9 | 5 (0.4) | 1 (0.1) | 4 (2.3) * | 0.003 |
| 10 | 1 (0.1) | 1 (0.1) | 0 (0.0) | - |
| 11 | 4 (0.3) | 4 (0.4) | 0 (0.0) | - |
| 12 | 4 (0.3) | 4 (0.4) | 0 (0.0) | - |
| 13 | 1 (0.1) | 1 (0.1) | 0 (0.0) | - |
Of the total patients infected by bacteria (n = 1042), one lacked an antibiogram, which was a Gram-negative bacterium. MDR: multidrug resistant, XDR: extremely resistant. The classification of resistance of bacteria was carried out based on the article by [14], while the classification of fungi was by [15,16]). Statistical significance was obtained using Fisher’s exact test. p value *: ≤0.05 statistically significant.
In addition, antimicrobial resistance was analyzed in outpatient and hospital settings (see Supplementary Table S1). Hospitalized patients were more likely to be resistant to at least one antimicrobial agent (80.6% vs. 70.1%, p = 0.004), multidrug resistant (MDR) (39.2% vs. 24.4%, p < 0.001), and extensively drug resistant (XDR) (7.3% vs. 2.3%, p = 0.002). Outpatients were more likely to be sensitive to antimicrobials (31.9% vs. 19.3%, p < 0.001) and to one antimicrobial agent (22.6% vs. 15.3%, p = 0.033). However, hospitalized patients were more likely to have three (23.8% vs. 15.2%, p = 0.007), six (3.4% vs. 1%, p = 0.032), or seven (3.9% vs. 0.7%, p = 0.002) antimicrobial resistances.
3.4. Carbapenem-Resistant Enterobacteriaceae
Carbapenem resistance was identified in 7 of 772 (0.9%) Enterobacteriaceae isolates, including four E. coli (57.1%), two K. pneumoniae (28.6%), and one P. mirabilis (14.3%). The median age of patients with Carbapenem-resistant Enterobacteriaceae (CRE) was 61 years (range 39–80), with male predominance (71.4%). In the clinical setting, four cases (57.1%) occurred in hospitalized patients, whereas three cases (42.9%) were identified among outpatients attending primary care (Family Medicine) or Internal Medicine consultations. Among comorbidities, diabetes mellitus was present in two patients (28.6%), hypertension in three (42.9%), and chronic kidney disease in one (14.3%). All CRE isolates were classified as MDR, with a high fluoroquinolone co-resistance rate of 83.3% (5/6 tested). No mortality was observed among CRE cases. Detailed characteristics of these patients are presented in Supplementary Table S2.
3.5. Epidemiological and Clinical Factors in Patients with Urinary Tract Infections Associated with Antimicrobial Resistance
We analyzed the epidemiological and clinical factors of patients with urinary tract infections according to four categories of antimicrobial resistance in microorganisms: susceptible (n = 301), three or fewer categories (n = 403), MDR (n = 274), and XDR (n = 33) (see Supplementary Table S3). Epidemiological and clinical factors associated with three or fewer categories included advanced age and the hospital’s surgical department. Older adults, internal medicine, surgery, type 2 diabetes, urinary catheter use, mortality, and the presence of leukocyte esterase, nitrites, protein, erythrocytes, and leukocytes (10–85 U) in the general urine analysis were associated with MDR infection. The following were associated with XDR infection: being an adult or male; receiving services from the nephrology, pediatrics, or traumatology departments; having a low body weight; having kidney disease; having had previous surgery; being pregnant; and having protein, ketones, erythrocytes, and hematuria in a general urine analysis. Next, binary logistic regression was used to assess the association between epidemiological and clinical factors and antimicrobial resistance in patients with UTIs, as shown in Table 6. Hospitalization (OR: 2.01; 95% CI: 1.43–2.83; p < 0.001) and the surgery department (OR: 1.41; 95% CI: 1.02–1.97; p = 0.049) were associated with multidrug resistance. Hospitalization (OR: 2.87; 95% CI: 1.40–5.86; p = 0.003) and previous surgery (OR: 2.37; 95% CI: 1.04–5.39; p = 0.038) were associated with resistance to multiple antimicrobial drugs.
Table 6.
Characteristics of Patients with Urinary Tract Infections Associated with Antibiotic Resistance.
| Characteristics of UTI Patients | Type of Resistance | OR | CI 95% | p Value |
|---|---|---|---|---|
| Hospital services | ||||
| Surgery | MDR | 1.41 | 1.02–1.97 | 0.049 |
| Inpatient | MDR | 2.01 | 1.43–2.83 | <0.001 |
| XDR | 2.87 | 1.40–5.86 | 0.003 | |
| Invasive devices | ||||
| Previous Surgery (last month) | XDR | 2.37 | 1.04–5.39 | 0.038 |
Abbreviation: OR: odds ratio; CI: confidence interval. Binary logistic regression under a multivariate model was used to get associations. Only the statistically significant characteristics of the patients with UTI are shown.
4. Discussion
A urinary tract infection (UTI) is one of the most prevalent infectious diseases worldwide. Several microorganisms can cause UTIs, and most of them are highly resistant to antibiotics. Depending on the severity of the infection, patients may be hospitalized or treated as outpatients, and specific characteristics may be associated with these states or antibiotic resistance. In this study, we demonstrated that the following factors were associated with outpatients and inpatients: epidemiological characteristics (age, sex, and hospital department) and clinical characteristics (BMI, metabolic disease, use of invasive devices, and general urine analysis parameters). UTI mortality in this study was 3.1%. Gram-negative bacteria, such as E. coli and K. pneumoniae, were the most frequently isolated microorganisms. Furthermore, E. coli was associated with outpatients, while E. Cloacae, Acinetobacter spp., C. tropicalis, and C. albicans were associated with inpatients. Additionally, UTIs caused by P. aeruginosa, E. faecalis, and S. epidermidis were more prevalent among pediatric patients. Gram-positive bacteria were more resistant to antibiotics than Gram-negative bacteria. Microorganisms isolated from hospitalized patients were more resistant than those from outpatients. Finally, patient characteristics, such as hospital department (e.g., surgery), prior surgeries, and hospitalizations, were associated with multidrug-resistant (MDR) and/or extensively drug-resistant (XDR) infections.
This study found that some epidemiological characteristics, such as age, sex, and hospital department, were more prevalent among outpatients and inpatients, consistent with other studies [16,17,18]. Regarding clinical characteristics, grade II obesity was associated with urinary tract infections (UTIs) in outpatients. However, the relationship between obesity and UTIs is controversial. Some studies indicate that obesity increases the likelihood of developing UTIs because increased central fat in men may contribute to benign prostatic hyperplasia [19,20,21]; In contrast, Nassaji et al. (2015) found no association between UTIs and BMI in adults, suggesting that obesity is not a risk factor for UTIs [22]. The relationship between obesity and outpatients does not align with findings from other studies. For example, García-Bustos et al. (2021) found that obesity was a predictor of increased hospital stay due to UTI [23]. However, obesity is a risk factor not only for hospitalization due to UTIs but also for other diseases, such as liver disease and COVID-19 [23,24]. The relationship between obesity and outpatients with UTIs in this study may be due to Mexico’s high obesity rate, as it is among the world leaders in obesity [25,26]. Other clinical characteristics observed among patients hospitalized for UTIs included the use of invasive devices and alterations in most general urine test parameters. This is because UTIs that require hospitalization tend to be more aggressive than those that do not.
It is important to note that the association between nitrite positivity and outpatient status should be interpreted in the context of the differential distribution of uropathogens between settings. Nitrite production requires bacterial nitrate reductase activity, an enzyme present in Enterobacteriaceae such as E. coli and K. pneumoniae, but absent in Enterococcus spp., Staphylococcus spp., Pseudomonas aeruginosa, Acinetobacter spp., and Candida species. The significantly higher prevalence of E. coli in outpatients (63.1% vs. 43.0%, p = 0.02) and the association of non-nitrite-producing organisms (E. cloacae, Acinetobacter spp., C. tropicalis, C. albicans) with hospitalized patients explains this finding rather than representing a diagnostic limitation. Furthermore, the high prevalence of urinary catheterization in inpatients (38.1% vs. 3.9%) reduces bladder dwell time, decreasing the opportunity for nitrate-to-nitrite conversion. Regarding epithelial cells, no significant difference was observed between groups (p = 0.842), and all diagnoses were confirmed by quantitative urine culture (≥105 CFU/mL) as the reference standard.
The 3.1% mortality rate from urinary tract infections in this study is consistent with rates found in other studies. For instance, Cornejo-Dávila (2015) reported a 2.9% mortality rate from urinary tract infections in Mexico [27]. Gharbi et al. (2019) reported that the mortality rate from urinary tract infections ranged from 1.6% to 5.4% among patients aged 65 years or older in England [28].
However, our mortality rate is lower than that reported in other studies. For instance, Kitagawa et al. (2019) found a mortality rate of 14.5% in patients with a urinary tract infection and bacteremia caused by P. aeruginosa in Japan [29]. Álvarez-Artero et al. (2021) found a 16.5% mortality rate in Spain for urinary tract infections caused by Enterococcus spp. [30]. In terms of microbiology, E. coli and K. pneumoniae were the most prevalent bacteria in isolates from outpatients and inpatients with UTIs, consistent with other studies [30,31,32]. When analyzing the distribution of UTI-causing microorganisms separately between outpatients and inpatients, E. coli was more commonly identified among outpatients. This result coincides with other studies [26,33,34]. In contrast to other studies, Gram-negative bacteria such as E. cloacae and Acinetobacter spp., as well as the fungi C. tropicalis and C. albicans, were associated with hospitalized UTIs. These bacteria and fungi were previously associated with UTIs in hospitalized patients [35,36,37]. In children, P. aeruginosa, E. faecalis, and S. epidermidis were associated with infection [36,38]. Unlike other studies, we demonstrated not only the prevalence of the main microorganisms causing UTIs in hospitalized and outpatient patients, as well as in children, adults, and older adults, but also a possible association between the presence of these microorganisms and these study groups. However, in some cases, the microorganisms we identified in association with subjects’ conditions or ages differ from those reported as the most prevalent in other studies. The prevalence of microorganisms that cause UTIs (excluding E. coli and K. pneumoniae) may vary by country, subjects’ microbiota, socioeconomic status, or prior antibiotic use [6,39,40].
Our findings revealed a distinctive microbiological profile in pediatric UTI patients that warrants special attention. P. aeruginosa was 4.6-fold more prevalent in children compared to adults and older adults (9.7% vs. 2.1%, p = 0.032), while E. faecalis was twice as common (33.3% vs. 16.2%, p = 0.001) and S. epidermidis was four times more frequent (26.6% vs. 6.5%, p = 0.027). These findings are consistent with international reports. Bitsori et al. demonstrated that P. aeruginosa UTI in children is strongly associated with prior antibiotic use (OR 21.6, 95% CI 4.65–100), previous UTI episodes, and urinary tract malformations [41]. Similarly, the European Society for Pediatric Infectious Diseases (ESPID) guidelines emphasize that P. aeruginosa and Enterococcus spp. are more common in children with recurrent UTIs, urological abnormalities, or prior antibiotic exposure [42].
The clinical relevance of these findings lies in the implications for empirical therapy selection. Standard empirical regimens for pediatric UTI, typically third-generation cephalosporins, do not provide adequate coverage against Enterococcus spp. or P. aeruginosa [43,44]. Our data suggest that clinicians in northwestern Mexico should consider broadening empirical coverage for pediatric patients with recurrent UTIs or known urological abnormalities.
Regarding antibiotic resistance, high levels have been reported in the microorganisms that cause urinary tract infections. Fenta et al. (2020) demonstrated that 66% of urinary tract infections isolated from children in Ethiopia were multidrug-resistant, primarily caused by Gram-negative bacteria [45]. In Nepal, Shrestha et al. (2021) found that 89% of urinary tract infections were multidrug-resistant, with 29.2% resistant to four classes, 21.5% to five classes, and 7.6% to six or more classes [46]. Huang et al. (2022) found that bacteria isolated from urinary tract infections were multidrug-resistant in 0–91.6% and extremely multidrug-resistant in 0–30.4% of cases in China between 2009 and 2020 [36]. The antibiotic resistance rates in these studies are higher than those found in northwestern Mexico. In our study, we identified that 27.1% of the bacteria causing UTIs were multidrug-resistant (MDR) and 3.2% were extensively drug-resistant (XDR).
Additionally, we found that the XDR phenotype was associated with Gram-positive bacteria and that MDR and XDR infections were associated with patients hospitalized for UTIs. However, we found that other countries had similar or lower levels of resistance. For instance, Weber et al. (2025) found that 22% of urinary tract infection (UTI) isolates were multidrug resistant (MDR) in Germany between 2013 and 2022 [47]. In the United States, Ku et al. (2024) reported that 13% of UTI-causing strains were MDR, with 3% resistant to four classes of antibiotics, 1% to five classes, and less than 1% to six classes [48]. Although other countries have higher levels, antibiotic resistance in strains isolated from urinary tract infections was high. The high prevalence of antibiotic resistance could be related to the indiscriminate use of antibiotics in Mexico across clinical practice, food production, and veterinary medicine [48,49,50].
One of the most concerning findings of this study was the identification of CRE in 0.9% of urinary isolates. Although this prevalence appears relatively low compared to that in endemic regions, the clinical and epidemiological significance of this finding cannot be overstated. The World Health Organization classifies CRE as a critical priority pathogen due to minimal therapeutic options and high mortality rates associated with these infections [51].
Particularly alarming was the finding that 42.9% of CRE cases (3/7) occurred in outpatients attending primary care or Internal Medicine consultations, rather than in hospitalized patients with traditional healthcare-associated risk factors. This pattern suggests community dissemination of carbapenem-resistant organisms in northwestern Mexico, a phenomenon increasingly reported in Latin America but rarely documented in Mexican ambulatory settings [52,53]. The presence of CRE in community-dwelling patients without recent hospitalization represents a paradigm shift in the epidemiology of these critical pathogens. It poses significant challenges for empirical antibiotic selection in the outpatient management of UTI. The detection of CRE in outpatients also highlights the importance of obtaining urine cultures before initiating empirical therapy, particularly in patients with recurrent UTIs or prior antibiotic exposure.
Finally, some patient characteristics, such as surgery, prior surgery, and hospitalization, were associated with multidrug-resistant and/or extremely resistant infections. Other studies have also associated patient characteristics with antibiotic resistance in patients with urinary tract infections. For example, Chen et al. (2013) found that urinary catheter use and kidney stones among men were associated with cefazolin resistance in urinary tract infections [54]. Faine et al. (2015) identified three clinical factors associated with multidrug-resistant urinary tract infections in the United States: male sex, chronic hemodialysis, and nursing home residence [55]. He et al. (2024) found that intensive care unit (ICU) stays, including prolonged ICU stays, were associated with ESBL-associated urinary tract infections in children [55]. Identifying characteristics associated with resistance-related urinary tract infections in Mexico will help identify cases at risk of infection by highly antibiotic-resistant microorganisms. With this knowledge, strategies can be developed to promptly treat cases of urinary tract infections complicated by highly antibiotic-resistant organisms.
The distinction between uncomplicated and complicated (or localized and systemic) UTIs has essential implications for the selection of empiric therapy and its duration. Recent guidelines from the EAU (2025) and IDSA (2025) have refined UTI classification to focus on clinical presentation rather than underlying host factors alone [56,57,58]. Although our study did not prospectively apply these classification systems, the significant differences observed between outpatients and inpatients—including higher mortality (14.8% vs. 0.2%), greater catheter use (38.1% vs. 3.9%), and more frequent isolation of healthcare-associated pathogens in inpatients—suggest that hospitalized patients likely had more severe or complicated infections. The higher prevalence of non-E. coli organisms, including Candida species and Acinetobacter spp., among inpatients further supports this interpretation, as pathogen diversity is a recognized feature of complicated UTIs.
This study has several limitations. First, because of its retrospective design, UTIs could not be formally classified according to current frameworks (e.g., uncomplicated/complicated or localized/systemic). The classification of UTI severity requires prospective documentation of specific symptoms, vital signs, and imaging findings that were inconsistently available in medical records. However, several clinical variables in our dataset serve as proxies for infection severity, including hospitalization status, ICU admission, catheter use, mortality, and biochemical parameters. Second, UTIs were not differentiated by anatomical site (lower vs. upper tract) due to the lack of systematic imaging. Third, blood cultures were not routinely obtained, precluding identification of bacteremic cases. Finally, the retrospective design limited access to longitudinal outcome data and to prior antimicrobial treatment data, both of which are recognized risk factors for antimicrobial-resistant UTIs. Future prospective studies in this region should incorporate standardized UTI classification systems, such as the EAU 2025 localized/systemic framework, to better characterize infection severity and guide targeted antimicrobial stewardship interventions [7,59,60]. In addition, prospective studies should systematically capture antibiotic exposure history to better characterize resistance risk factors in this population.
This is the first comprehensive study to report the distribution of primary microorganisms causing UTIs among hospitalized patients, outpatients, and children. Additionally, antibiotic resistance and the characteristics of patients with UTIs associated with antibiotic resistance were analyzed.
5. Conclusions
This study provides evidence that specific epidemiological, clinical, and biochemical characteristics of patients are associated with UTIs in hospitalized and outpatient settings. Mortality in northwestern Mexico was 3.1%. The main microorganisms causing UTIs were E. coli and K. pneumoniae. Some bacteria or fungi were associated with hospitalized patients, outpatients, and children. Additionally, high levels of antibiotic resistance were observed among Gram-positive bacteria and other microorganisms infecting hospitalized patients. The identification of carbapenem-resistant Enterobacteriaceae in both inpatient and outpatient settings signals the community emergence of last-resort antibiotic resistance in northwestern Mexico, warranting urgent implementation of enhanced surveillance and antimicrobial stewardship programs. Finally, patient characteristics, including hospital department (e.g., surgery), prior surgeries, and length of hospitalization, were associated with urinary tract infections caused by multidrug-resistant (MDR) and/or extensively drug-resistant (XDR) microorganisms. These results will help medical staff in our region diagnose urinary tract infections faster in hospitalized patients, outpatients, and children. Additionally, we will be able to provide optimal treatment and prevent mortality from urinary tract infections in patients of all ages. Respecting the identified risk factors will help develop strategies to prevent urinary tract infections caused by multidrug-resistant or extremely drug-resistant microorganisms.
Acknowledgments
We thank Daniel Alberto Lopez Aguado, Eduardo Yamel Morales Lizarraga for their technical assistance in the laboratory.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/pathogens15010092/s1. Table S1: Antimicrobial Resistance in Outpatients and Inpatients; Table S2: Clinical and microbiological characteristics of patients with carbapenem-resistant Enterobacteriaceae urinary tract infections (n = 7); Table S3: Epidemiological and Clinical Factors Related to Antibiotic Resistance in Patients with Urinary Tract Infection.
Author Contributions
Conceptualization, J.M.-H. and U.A.A.-Z.; Data curation, N.L.-S. and H.F.-V.; Formal analysis, J.V.-R., E.R.-T. and F.C.-A.; Investigation, J.M.-S., G.T.-P. and A.C.-R.; Methodology, J.M.-H. and U.A.A.-Z.; Project administration, N.L.-S. and H.F.-V.; Software, J.V.-R., E.R.-T. and F.C.-A.; Supervision, J.M.-S., G.T.-P. and A.C.-R.; Validation, J.M.-H. and U.A.A.-Z.; Visualization, N.L.-S. and H.F.-V.; Writing—original draft, J.M.-H. and U.A.A.-Z.; Writing—review & editing, N.L.-S. and A.C.-R. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
The research was evaluated and approved (27 June 2025) by the Research Ethics Committee (Local Health Research Committee 2506) of the IMSS Family Medicine Unit No. 46. The registration number is R-2025-2506-045.
Informed Consent Statement
Patients and/or the public were not involved in the design, conduct, reporting, or dissemination plans of this research.
Data Availability Statement
The original contributions presented in this study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.
Conflicts of Interest
The authors declare no conflict of interest.
Funding Statement
This research received no external funding.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
References
- 1.Ronald A.R., Nicolle L.E., Stamm E., Krieger J., Warren J., Schaeffer A., Naber K.G., Hooton T.M., Johnson J., Chambers S., et al. Urinary tract infection in adults: Research priorities and strategies. Int. J. Antimicrob. Agents. 2001;17:343–348. doi: 10.1016/S0924-8579(01)00303-X. [DOI] [PubMed] [Google Scholar]
- 2.Nicolle L.E. Urinary tract infection: Traditional pharmacologic therapies. Am. J. Med. 2002;113:35s–44s. doi: 10.1016/S0002-9343(02)01058-6. [DOI] [PubMed] [Google Scholar]
- 3.Stamm W.E., Norrby S.R. Urinary tract infections: Disease panorama and challenges. J. Infect. Dis. 2001;183:S1–S4. doi: 10.1086/318850. [DOI] [PubMed] [Google Scholar]
- 4.Palacios-Ceña D., Florencio L.L., Hernández-Barrera V., Fernandez-de-Las-Peñas C., de Miguel-Diez J., Martínez-Hernández D., Carabantes-Alarcón D., Jimenez-García R., Lopez-de-Andres A., Lopez-Herranz M. Trends in Incidence and Outcomes of Hospitalizations for Urinary Tract Infection among Older People in Spain (2001–2018) J. Clin. Med. 2021;10:2332. doi: 10.3390/jcm10112332. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Calderón-Jaimes E., Casanova-Román G., Galindo-Fraga A., Gutiérrez-Escoto P., Landa-Juárez S., Moreno-Espinosa S., Rodríguez-Covarrubias F., Simón-Pereira L., Valdez-Vázquez R. Diagnosis and treatment of urinary tract infections: A multidisciplinary approach for uncomplicated cases. J. Boletín Médico Hosp. Infant. México. 2013;70:3–10. [Google Scholar]
- 6.Foxman B. Urinary tract infection syndromes: Occurrence, recurrence, bacteriology, risk factors, and disease burden. Infect. Dis. Clin. N. Am. 2014;28:1–13. doi: 10.1016/j.idc.2013.09.003. [DOI] [PubMed] [Google Scholar]
- 7.Wagenlehner F.M.E., Bjerklund Johansen T.E., Cai T., Koves B., Kranz J., Pilatz A., Tandogdu Z. Epidemiology, definition and treatment of complicated urinary tract infections. Nat. Rev. Urol. 2020;17:586–600. doi: 10.1038/s41585-020-0362-4. [DOI] [PubMed] [Google Scholar]
- 8.Kunnath A.P., Suodha Suoodh M., Chellappan D.K., Chellian J., Palaniveloo K. Bacterial Persister Cells and Development of Antibiotic Resistance in Chronic Infections: An Update. Br. J. Biomed. Sci. 2024;81:12958. doi: 10.3389/bjbs.2024.12958. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Tandogdu Z., Wagenlehner F.M. Global epidemiology of urinary tract infections. Curr. Opin. Infect. Dis. 2016;29:73–79. doi: 10.1097/QCO.0000000000000228. [DOI] [PubMed] [Google Scholar]
- 10.Chu C.M., Lowder J.L. Diagnosis and treatment of urinary tract infections across age groups. Am. J. Obstet. Gynecol. 2018;219:40–51. doi: 10.1016/j.ajog.2017.12.231. [DOI] [PubMed] [Google Scholar]
- 11.WHO Consultation Obesity: Preventing and managing the global epidemic. J. World Health Organ. Tech. Rep. Ser. 2000;894:1–253. [PubMed] [Google Scholar]
- 12.WHO . Obesity and Overweight. World Health Organization; Geneva, Switzerland: 2025. [Google Scholar]
- 13.White D., Fedorka-Cray P., Chiller C. The national antimicrobial resistance monitoring system (NARMS); Proceedings of the NMC-Annual Meeting Proceedings; Tampa, FL, USA. 22–25 January 2006. [Google Scholar]
- 14.Magiorakos A.P., Srinivasan A., Carey R., Carmeli Y., Falagas M., Giske C., Harbarth S., Hindler J.F., Kahlmeter G., Olsson-Liljequist B., et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: An international expert proposal for interim standard definitions for acquired resistance. Clin. Microbiol. Infect. 2012;18:268–281. doi: 10.1111/j.1469-0691.2011.03570.x. [DOI] [PubMed] [Google Scholar]
- 15.Arendrup M.C., Patterson T.F. Multidrug-Resistant Candida: Epidemiology, Molecular Mechanisms, and Treatment. J. Infect. Dis. 2017;216:S445–S451. doi: 10.1093/infdis/jix131. [DOI] [PubMed] [Google Scholar]
- 16.Jacobs S.E., Jacobs J.L., Dennis E.K., Taimur S., Rana M., Patel D., Gitman M., Patel G., Schaefer S., Iyer K., et al. Candida auris Pan-Drug-Resistant to Four Classes of Antifungal Agents. Antimicrob. Agents Chemother. 2022;66:e0005322. doi: 10.1128/aac.00053-22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Shao Y., Jia W., Li G. Related factors of bloodstream infections associated with urinary tract infections and pathogenetic characteristics analysis. Eur. J. Med. Res. 2024;29:566. doi: 10.1186/s40001-024-02152-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Kamei J., Fujimura T. Urinary tract infection in patients with lower urinary tract dysfunction. J. Infect. Chemother. Off. J. Jpn. Soc. Chemother. 2023;29:744–748. doi: 10.1016/j.jiac.2023.04.019. [DOI] [PubMed] [Google Scholar]
- 19.Luo X.M., Li Y.Y., Qi X.M., Wu Y.G. Risk factors and etiological characteristics of urinary tract infection in hospitalized continuous ambulatory peritoneal dialysis patients. Eur. Rev. Med. Pharmacol. Sci. 2023;27:3837–3845. doi: 10.26355/eurrev_202305_32289. [DOI] [PubMed] [Google Scholar]
- 20.Saliba W., Barnett-Griness O., Rennert G. The association between obesity and urinary tract infection. Eur. J. Intern. Med. 2013;24:127–131. doi: 10.1016/j.ejim.2012.11.006. [DOI] [PubMed] [Google Scholar]
- 21.Giovannucci E., Rimm E.B., Chute C.G., Kawachi I., Colditz G.A., Stampfer M.J., Willett W.C. Obesity and benign prostatic hyperplasia. Am. J. Epidemiol. 1994;140:989–1002. doi: 10.1093/oxfordjournals.aje.a117206. [DOI] [PubMed] [Google Scholar]
- 22.Nassaji M., Ghorbani R., Tamadon M.R., Bitaraf M. Association between body mass index and urinary tract infection in adult patients. Nephro-Urol. Mon. 2015;7:e22712. doi: 10.5812/numonthly.22712. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Garcia-Bustos V., Escrig A.I.R., López C.C., Estellés R.A., Jerusalem K., Cabañero-Navalón M.D., Massó V.M., Sigona-Giangreco I.-A., Sahuquillo-Arce J.M., Hernández I.C., et al. Prospective cohort study on hospitalised patients with suspected urinary tract infection and risk factors por multidrug resistance. Sci. Rep. 2021;11:11927. doi: 10.1038/s41598-021-90949-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Sundaram V., Kaung A., Rajaram A., Lu S.C., Tran T.T., Nissen N.N., Klein A.S., Jalan R., Charlton M.R., Jeon C.Y. Obesity is independently associated with infection in hospitalised patients with end-stage liver disease. Aliment. Pharmacol. Ther. 2015;42:1271–1280. doi: 10.1111/apt.13426. [DOI] [PubMed] [Google Scholar]
- 25.Cottini M., Lombardi C., Berti A. Obesity is a Major Risk Factor for Hospitalization in Community-Managed COVID-19 Pneumonia. Mayo Clin. Proc. 2021;96:921–931. doi: 10.1016/j.mayocp.2021.01.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Arreola-Ornelas H., Merino-Juárez G.A., Contreras-Loya D., Méndez-Carniado O., Morales-Juárez L., Bernal-Serrano D., Arizmendi-Barrera K.A., Vargas-Martínez C., Razo C., Knaul F.M., et al. Burden of overweight and obesity in Mexico from 1990 to 2021. Gac. Medica Mex. 2023;159:543–556. doi: 10.24875/GMM.M24000836. [DOI] [PubMed] [Google Scholar]
- 27.Cornejo-Dávila V., Palmeros-Rodríguez M.A., Uberetagoyena-Tello de Meneses I., Mayorga-Gómez E., Garza-Sáinz G., Osornio-Sánchez V., Trujillo-Ortiz L., Sedano-Basilio J.E., Cantellano-Orozco M., Martínez-Arroyo C., et al. Management of complicated urinary tract infections in a referral center in Mexico. Int. Urol. Nephrol. 2015;47:229–233. doi: 10.1007/s11255-014-0883-y. [DOI] [PubMed] [Google Scholar]
- 28.Gharbi M., Drysdale J.H., Lishman H., Goudie R., Molokhia M., Johnson A.P., Holmes A.H., Aylin P. Antibiotic management of urinary tract infection in elderly patients in primary care and its association with bloodstream infections and all cause mortality: Population based cohort study. BMJ (Clin. Res. Ed.) 2019;364:l525. doi: 10.1136/bmj.l525. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Kitagawa K., Shigemura K., Yamamichi F., Osawa K., Uda A., Koike C., Tokimatsu I., Shirakawa T., Miyara T., Fujisawa M. Bacteremia complicating urinary tract infection by Pseudomonas aeruginosa: Mortality risk factors. Int. J. Urol. Off. J. Jpn. Urol. Assoc. 2019;26:358–362. doi: 10.1111/iju.13872. [DOI] [PubMed] [Google Scholar]
- 30.Álvarez-Artero E., Campo-Nuñez A., García-García I., García-Bravo M., Cores-Calvo O., Galindo-Pérez I., Pendones-Ulerio J., López-Bernus A., Belhassen-García M., Pardo-Lledías J. Urinary tract infection caused by Enterococcus spp.: Risk factors and mortality. Obs. Study Rev. Clin. Esp. 2021;221:375–383. doi: 10.1016/j.rce.2020.09.005. [DOI] [PubMed] [Google Scholar]
- 31.Stamm W.E. Scientific and clinical challenges in the management of urinary tract infections. Am. J. Med. 2002;113:1s–4s. doi: 10.1016/S0002-9343(02)01053-7. [DOI] [PubMed] [Google Scholar]
- 32.Laupland K.B., Ross T., Pitout J.D., Church D.L., Gregson D.B. Community-onset urinary tract infections: A population-based assessment. Infection. 2007;35:150–153. doi: 10.1007/s15010-007-6180-2. [DOI] [PubMed] [Google Scholar]
- 33.Imirzalioglu C., Hain T., Chakraborty T., Domann E. Hidden pathogens uncovered: Metagenomic analysis of urinary tract infections. Andrologia. 2008;40:66–71. doi: 10.1111/j.1439-0272.2007.00830.x. [DOI] [PubMed] [Google Scholar]
- 34.Otajevwo F.D. Urinary tract infection among symptomatic outpatients visiting a tertiary hospital based in midwestern Nigeria. Glob. J. Health Sci. 2013;5:187–199. doi: 10.5539/gjhs.v5n2p187. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Mlugu E.M., Mohamedi J.A., Sangeda R.Z., Mwambete K.D. Prevalence of urinary tract infection and antimicrobial resistance patterns of uropathogens with biofilm forming capacity among outpatients in morogoro, Tanzania: A cross-sectional study. BMC Infect. Dis. 2023;23:660. doi: 10.1186/s12879-023-08641-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Huang L., Huang C., Yan Y., Sun L., Li H. Urinary Tract Infection Etiological Profiles and Antibiotic Resistance Patterns Varied Among Different Age Categories: A Retrospective Study From a Tertiary General Hospital During a 12-Year Period. Front. Microbiol. 2022;12:813145. doi: 10.3389/fmicb.2021.813145. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Bhargava K., Nath G., Bhargava A., Kumari R., Aseri G.K., 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. doi: 10.3389/fmicb.2022.965053. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Sheikh R.Y., Murdeshwar S., Maheshwari T.K., Chacko S. Microbiological Spectrum and Antibiogram of Urinary Tract Infection in a Tertiary Care Center from the Kingdom of Bahrain. Saudi J. Kidney Dis. Transplant. Off. Publ. Saudi Cent. Organ Transplant. 2022;33:S53–S60. doi: 10.4103/1319-2442.374382. [DOI] [PubMed] [Google Scholar]
- 39.Lu J., Liu X., Wei Y., Yu C., Zhao J., Wang L., Hu Y., Wei G., Wu S. Clinical and Microbial Etiology Characteristics in Pediatric Urinary Tract Infection. Front. Pediatr. 2022;10:844797. doi: 10.3389/fped.2022.844797. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Suleyman G., Alangaden G.J. Nosocomial Fungal Infections: Epidemiology, Infection Control, and Prevention. Infect. Dis. Clin. North Am. 2021;35:1027–1053. doi: 10.1016/j.idc.2021.08.002. [DOI] [PubMed] [Google Scholar]
- 41.Flores-Mireles A.L., Walker J.N., Caparon M., Hultgren S.J. Urinary tract infections: Epidemiology, mechanisms of infection and treatment options. Nat. Rev. Microbiol. 2015;13:269–284. doi: 10.1038/nrmicro3432. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Bitsori M., Maraki S., Koukouraki S., Galanakis E. Pseudomonas aeruginosa urinary tract infection in children: Risk factors and outcomes. J. Urol. 2012;187:260–264. doi: 10.1016/j.juro.2011.09.035. [DOI] [PubMed] [Google Scholar]
- 43.Bryant P.A., Bitsori M., Vardaki K., Vaezipour N., Khan M., Buettcher M. Guidelines for Complicated Urinary Tract Infections in Children: A Review by the European Society for Pediatric Infectious Diseases. Pediatr. Infect. Dis. J. 2025;44:e211–e223. doi: 10.1097/INF.0000000000004790. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.González Rodríguez J.D., Fraga Rodríguez G.M., García Vera C.J., Gómez Fraile A., Martín Sánchez J.I., Mengual Gil J.M., Sangrador C.O., Fuentes B.V., Subías J.E. Update of the Spanish clinical practice guideline for urinary tract infection in infants and children. Summary of recommendations for diagnosis, treatment and follow-up. An. Pediatr. 2024;101:132–144. doi: 10.1016/j.anpedi.2024.06.001. [DOI] [PubMed] [Google Scholar]
- 45.Fenta A., Dagnew M., Eshetie S., Belachew T. Bacterial profile, antibiotic susceptibility pattern and associated risk factors of urinary tract infection among clinically suspected children attending at Felege-Hiwot comprehensive and specialized hospital, Northwest Ethiopia. A prospective study. BMC Infect. Dis. 2020;20:673. doi: 10.1186/s12879-020-05402-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Shrestha G., Wei X., Hann K., Soe K.T., Satyanarayana S., Siwakoti B., Bastakoti S., Mulmi R., Rana K., Lamichhane N. Bacterial Profile and Antibiotic Resistance among Cancer Patients with Urinary Tract Infection in a National Tertiary Cancer Hospital of Nepal. Trop. Med. Infect. Dis. 2021;6:49. doi: 10.3390/tropicalmed6020049. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Weber P., Braß P., Jäger J., Jacquet L., Jansen S., Gäckler A., Jürgens C., Reinold J., Eisenberger U., Rath P.-M., et al. Antibiotic resistance of urinary pathogens after kidney transplantation: A 10-year single-center survey in Germany. Infection. 2025;53:1755–1768. doi: 10.1007/s15010-025-02493-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Ku J.H., Tartof S.Y., Contreras R., Ackerson B.K., Chen L.H., Reyes I.A.C., Pellegrini M., E Schmidt J., Bruxvoort K.J. Antibiotic Resistance of Urinary Tract Infection Recurrences in a Large Integrated US Healthcare System. J. Infect. Dis. 2024;230:e1344–e1354. doi: 10.1093/infdis/jiae233. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Marshall B.M., Levy S.B. Food animals and antimicrobials: Impacts on human health. Clin. Microbiol. Rev. 2011;24:718–733. doi: 10.1128/CMR.00002-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Caruso G. Antibiotic Resistance in Escherichia coli from Farm Livestock and Related Analytical Methods: A Review. J. AOAC Int. 2018;101:916–922. doi: 10.5740/jaoacint.17-0445. [DOI] [PubMed] [Google Scholar]
- 51.Hollis A., Ahmed Z. Preserving antibiotics, rationally. N. Engl. J. Med. 2013;369:2474–2476. doi: 10.1056/NEJMp1311479. [DOI] [PubMed] [Google Scholar]
- 52.World Health Organization . Bacterial Priority Pathogens List, 2024: Bacterial Pathogens of Public Health Importance, to Guide Research, Development, and Strategies to Prevent and Control Antimicrobial Resistance. World Health Organization; Geneva, Switzerland: 2024. [Google Scholar]
- 53.Thomas G.R., Corso A., Pasterán F., Shal J., Sosa A., Pillonetto M., Peral R.T.d.S., Hormazábal J.C., Araya P., Saavedra S.Y., et al. Increased Detection of Carbapenemase-Producing Enterobacterales Bacteria in Latin America and the Caribbean during the COVID-19 Pandemic. Emerg. Infect. Dis. 2022;28:e220415. doi: 10.3201/eid2811.220415. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Chen L.F., Chiu C.T., Lo J.Y., Tsai S.Y., Weng L.S., Anderson D.J., Chen H.-S. Clinical Characteristics and Antimicrobial Susceptibility Pattern of Hospitalized Patients with Community Acquired Urinary Tract Infections at a Regional Hospital in Taiwan. Healthc. Infect. 2013;19:20–25. doi: 10.1071/HI13033. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Faine B.A., Harland K.K., Porter B., Liang S.Y., Mohr N. A clinical decision rule identifies risk factors associated with antimicrobial-resistant urinary pathogens in the emergency department: A retrospective validation study. Ann. Pharmacother. 2015;49:649–655. doi: 10.1177/1060028015578259. [DOI] [PubMed] [Google Scholar]
- 56.He X.T., Chang C.N., Yu C.H., Wang C.C. The risk factors, antimicrobial resistance patterns, and outcomes associated with extended-spectrum β-lactamases-Producing pathogens in pediatric urinary tract infection. Pediatr. Neonatol. 2024;65:242–248. doi: 10.1016/j.pedneo.2023.04.021. [DOI] [PubMed] [Google Scholar]
- 57.Bonkat G., Wagenlehner F., Cai T., Geerlings S., Medina-Polo J., Köves B., Pilatz A., Schneidewind L., Schubert S., Veeratterapillay R., et al. Classification of Urinary Tract Infections in 2025: Moving Beyond Uncomplicated and Complicated. Eur. Urol. Open Sci. 2025;74:103–108. doi: 10.1016/j.euros.2025.03.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.IDSA Complicated Urinary Tract Infections (cUTI): Clinical Guidelines for Treatment and Management. Clin. Infect. Dis. 2025 in press . [Google Scholar]
- 59.EAU Guidelines Panel on Urological Infections . EAU Guidelines on Urological Infections. European Association of Urology; Arnhem, The Netherlands: 2025. [Google Scholar]
- 60.Gupta K., Hooton T.M., Naber K.G., Wullt B., Colgan R., Miller L.G., Moran G.J., Nicolle L.E., Raz R., Schaeffer A.J., et al. International clinical practice guidelines for the treatment of acute uncomplicated cystitis and pyelonephritis in women. Clin. Infect. Dis. 2011;52:e103–e120. doi: 10.1093/cid/ciq257. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The original contributions presented in this study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.