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Article

Predisposing Factors Associated with Third-Generation Cephalosporin-Resistant Escherichia coli in a Rural Community Hospital in Thailand

by
Ratchadaporn Ungcharoen
1,*,
Jindanoot Ponyon
2,
Rapeepan Yongyod
1 and
Anusak Kerdsin
1
1
Faculty of Public Health, Kasetsart University Chalermphrakieat Sakon Nakhon Province Campus, Sakon Nakhon 47000, Thailand
2
Thatphanom Crown Prince Hospital, Nakhon Phanom 48110, Thailand
*
Author to whom correspondence should be addressed.
Antibiotics 2025, 14(8), 790; https://doi.org/10.3390/antibiotics14080790
Submission received: 6 June 2025 / Revised: 20 July 2025 / Accepted: 30 July 2025 / Published: 4 August 2025
(This article belongs to the Special Issue Molecular Epidemiology and Mechanisms of Carbapenem Resistance in Clinical Gram-Negative Bacteria)
Versions Notes

Abstract

Background: Various predisposing factors contribute to the emergence and dissemination of the multidrug-resistant (MDR) phenotype in Escherichia coli and Klebsiella pneumoniae. Understanding these factors is crucial for guiding appropriate antimicrobial therapy and infection control strategies. This study investigated the predisposing factors contributing to the MDR characteristics of E. coli and K. pneumoniae isolated in a community hospital in northeastern Thailand. Methods: This case–control study utilized retrospective data from bacterial culture, as well as demographic, clinical, and antibiotic susceptibility records collected during 5 years (January 2016–December 2020). E. coli and K. pneumoniae isolates were analyzed from various clinical samples, including blood, urine, pus, sputum, and other body fluids. Data were analyzed using descriptive statistics and univariate logistic regression. Results: In total, 660 clinical isolates were analyzed (421 E. coli and 239 K. pneumoniae). Blood was the most common source of the detection of E. coli (63.0%) and sputum was the most common source of K. pneumoniae (51.0%). The median ages of patients were 67 and 63 years for E. coli and K. pneumoniae, respectively. E. coli cases were significantly associated with prior antibiotic use (OR = 1.79, 95% CI: 1.17–2.74 p = 0.008). MDR was observed in 50.1% of E. coli and 29.7% of K. pneumoniae (p < 0.001). E. coli compared to K. pneumoniae had lower resistance to third-gen cephalosporins (64.9% versus 95.8%) and carbapenems (8.0% versus 6.9%). ICU admission was the only factor significantly associated with MDR E. coli (OR = 2.40, 95% CI: 1.11–5.20 p = 0.026). No significant differences were observed in gender, age, or comorbidities between MDR cases. Antibiotic usage patterns also differed, with E. coli more likely to receive third-gen cephalosporins compared to carbapenems (OR = 3.02, 95% CI:1.18–7.74 p = 0.021). Conclusions: The use of third-generation cephalosporin may drive MDR E. coli more than K. pneumoniae. Prior antibiotic exposure was linked to E. coli bloodstream infections, while MDR E. coli showed greater clinical severity. These findings highlighted the need for improved antibiotic stewardship in rural hospitals.

1. Introduction

Multidrug-resistant (MDR) microorganisms, such as bacteria and fungi, have the ability to resist multiple classes of antimicrobial agents. According to the World Health Organization (WHO), a pathogen is classified as MDR when it becomes resistant to at least one agent in three or more antimicrobial categories. Multidrug resistance poses a critical public health challenge, particularly with Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pneumoniae), which increasingly exhibit resistance to multiple drug classes. Antimicrobial resistance (AMR) is one of the most critical global health challenges today. Recognized by the WHO as a top 10 global health threat, AMR contributes to increased morbidity, mortality, and healthcare costs worldwide. The escalating burden of AMR is driven by factors such as poor infection control measures, inappropriate antibiotic use, and limited availability of novel antimicrobial agents [1]. Antibiotic-resistant E. coli and K. pneumoniae represent some of the most critical drug-resistant bacterial threats. As members of the Enterobacteriaceae family, these pathogens are of particular clinical importance due to their ability to cause infections across all age groups [2].
E. coli and K. pneumoniae represent the main members of the Gram-negative bacteria that constitute part of the normal human gastrointestinal microbiota. These organisms are recognized as substantially human-based pathogens responsible for a broad spectrum of both hospital-acquired and community-acquired infections, including diarrhea, urinary tract infections (UTIs) [3], bloodstream infections, and various other clinical manifestations [4,5,6]. K. pneumnoniae, a predominantly hospital-acquired opportunistic pathogen, accounts for approximately 30% of all Gram-negative bacterial infections [7]. This organism is associated with diverse clinical presentations, including bloodstream infections, pneumonia, UTIs, meningitis, pyogenic liver abscesses, and wound infections [3,8,9].
The Ministry of Public Health in Thailand [10] reported there are more than 100,000 patients with antimicrobial-resistant infections annually, while more than 30,000 patients die from antimicrobial-resistant infections, and the associated economic loss exceeds THB 40 billion, or approximately 1% of the country’s Gross Domestic Product (GDP) [11]. Commonly, Thai people are able to access antibiotics without prescriptions, such as through buying drugs from private drugstores or pharmacies, including small grocery stores in the community [12]. Inappropriate antibiotic self-medication remains widespread in Thailand, with studies showing most residents use antibiotics without prior professional consultation. Primarily, this practice involves drugs purchased over the counter or reused from previous prescriptions, often for conditions that do not require antibiotics [5,12].
Epidemiological data assessing multidrug-resistant Enterobacteriaceae (MDRE), specifically Escherichia coli and Klebsiella pneumoniae, across various global regions have demonstrated a significant increase in prevalence, with notable geographical variation among countries [13]. The emergence and dissemination of multidrug-resistant E. coli are influenced by multiple interrelated factors. Prior antibiotic use (particularly inappropriate or excessive administration) creates selective pressure favoring resistant strains in both clinical and agricultural settings [14,15,16]. The extensive use of antibiotics in animal husbandry, especially as growth promoters, further exacerbates antimicrobial resistance by fostering resistant bacteria transmissible to humans [16,17,18]. Environmental contamination, including the presence of resistant E. coli in water sources, plays a critical role in spreading resistance [19,20,21]. In healthcare settings, prolonged hospitalization, intensive care unit (ICU) admissions, and invasive devices such as urinary catheters significantly increase the risk of MDR E. coli infections [22,23]. Patient-related factors, such as advanced age, female sex, and comorbidities (such as diabetes mellitus), also contribute to increased susceptibility [22,24]. Importantly, developing countries face a disproportionately high burden of MDR infections, due to limited healthcare infrastructure, inadequate infection control, poor sanitation, and restricted access to clean water [24,25]. Recent evidence has also drawn attention to coinfection-related factors as important contributors to the emergence and persistence of multidrug resistance. Sophonsri et al. [26] reported that coinfection with carbapenem-resistant Pseudomonas aeruginosa or Acinetobacter baumannii frequently occurred in patients infected with carbapenem-resistant Klebsiella pneumoniae, particularly among those with prior carbapenem exposure and a history of pneumonia. In a separate study, Lv et al. [27] identified fiberoptic bronchoscopy, repeated blood transfusion, and previous use of tigecycline as significant risk factors for coinfection involving carbapenem-resistant Klebsiella pneumoniae and Acinetobacter baumannii.
This study investigated the predisposing factors for antimicrobial resistance and the MDR characteristics of E. coli and K. pneumoniae in a community hospital serving a rural population in northeastern Thailand. While the epidemiology of MDR Enterobacteriaceae has been well-studied globally, most data come from urban or tertiary hospitals in high-income countries, which may not reflect rural, resource-limited settings. In rural Thailand, factors such as unregulated antibiotic use, limited diagnostics, inconsistent stewardship, and local health behavior may uniquely drive resistance. Often, community hospitals lack surveillance and infection control programs. Therefore, the current study should fill a crucial gap by identifying risk factors specific to this context, aiming to guide tailored interventions against antimicrobial resistance in rural Thai communities.

2. Results

2.1. E. coli and K. pneumoniae Isolates by Specimen Type

In total, 660 clinical specimens were analyzed, consisting of 421 E. coli isolates and 239 K. pneumoniae isolates. The distribution of these isolates by specimen type is presented in Table 1. Among the E. coli isolates, the highest proportion was in blood (63.0%), followed by urine (26.8%). Sputum represented 5.9% of E. coli isolates, while pus samples accounted for 3.3%. Fluid specimens contributed 1.0%. For K. pneumoniae, in blood, urine, sputum, pus, and fluid, the rates cultured were 32.2%, 10.5%, 51.0%, 3.8%, and 2.5%, respectively. The age range of patients was 2–96 years. The median age of cases for E. coli was 67 (IQR = 22.0) years, and for K. pneumoniae, it was 63 (IQR = 19.5) years.
Among the 421 patients with E. coli isolates, 156 (37.1%) had bloodstream infections. Comorbidities included diabetes mellitus (DM), hypertension (HT), chronic obstructive pulmonary disease (COPD), and chronic kidney disease (CKD). Prior antibiotic use was significantly associated with bloodstream infection (OR = 1.79, 95% CI: 1.17–2.74, p = 0.008). Other factors were not significantly associated with E. coli bloodstream infection: gender (OR = 1.18; 95% CI: 0.77–1.80), age ≥ 60 years (OR = 1.47; 95% CI: 0.96–2.22), diabetes mellitus (OR = 1.58; 95% CI: 0.90–2.77), hypertension (OR = 0.66; 95% CI: 0.39–1.16), COPD (OR = 0.47; 95% CI: 0.12–1.83), CKD (OR = 0.62; 95% CI: 0.23–1.67), and ICU admission (OR = 1.89; 95% CI: 0.83–4.31) (Table 2).

2.2. Multidrug Resistance Patterns of E. coli and K. pneumoniae

Multidrug resistance patterns were observed in 50.1% of E. coli (n = 221) and 29.7% of K. pneumoniae (n = 71) isolates, which are subsets of the total isolates (421 and 239, respectively) identified in this study. The results of this analysis, presented in Table 3, revealed striking differences in resistance profiles between the two pathogens. Multidrug resistance was observed in 211 (50.1%) E. coli and 71 (29.7%) K. pneumoniae isolates (p-value < 0.001, OR = 2.38, 95% CI: 1.70–3.33). There were significant differences in third-gen cephalosporin (p-value < 0.001) and carbapenem (p-value < 0.001) resistance between the two pathogens. The antibiotic susceptibility patterns among the MDR strains are shown in Table 3.
Table 4 presents the distribution of antibiotic resistance between Escherichia coli and Klebsiella pneumoniae and their associated odds ratios (ORs). Comparing the use of third-generation cephalosporins to aminoglycosides and quinolones, E. coli was more likely to be resistant to third-generation cephalosporins than K. pneumoniae, although there was no significant difference (OR = 0.69, 95% CI: 0.48–1.00, p = 0.052). Among the total of 577 cases, E. coli was resistant to third-generation cephalosporins in 137 out of 414 strains (33.1%), whereas K. pneumoniae was resistant in 68 out of 163 strains (41.7%).
In contrast, comparing the use of third-generation cephalosporins to carbapenems, E. coli had a significantly higher likelihood of being resistant to cephalosporins (OR = 3.02, 95% CI: 1.18–7.74, p = 0.021) compared to K. pneumoniae. In a subgroup of 225 cases, E. coli was resistant to third-generation cephalosporins in 137 out of 145 cases (94.5%), whereas K. pneumoniae was susceptible in 68 out of 80 cases (85.0%). These results demonstrate statistically significant differences in antibiotic resistance between E. coli and K. pneumoniae.

2.3. Analysis of Clinical Characteristics

Comparative analysis between MDR E. coli (n = 211) and K. pneumoniae (n = 71) isolates revealed several characteristics. Among MDR E. coli isolates, 112 (53.1%) were from female patients, while for MDR K. pneumoniae, 39 (54.9%) isolates were from male patients (OR = 1.38, 95% CI: 0.80–2.37, p = 0.24). Regarding age distribution, patients aged more than 60 years accounted for 57.8% (n = 122) of MDR E. coli cases and 52.1% of MDR K. pneumoniae cases (OR = 1.26, 95% CI: 0.73–2.16), p = 0.402), suggesting a higher prevalence of MDR distribution among elderly patients, although this difference was not statistically significant.
The comorbidities examined in this study, including diabetes mellitus (DM), hypertension (HT), chronic obstructive pulmonary disease (COPD), and chronic kidney disease (CKD), showed no statistically significant association with either type of MDR organism. Previous antibiotic received (Previous ATB) showed a trend toward association with MDR E. coli infection (OR = 1.790, 95% CI: 0.97–3.30), although this factor did not reach statistical significance (p-value = 0.063).
Importantly, ICU admission had a statistically significant association with MDR E. coli infection (OR = 2.40, 95% CI: 1.11–5.20, p-value = 0.026) compared to K. pneumoniae. This may suggest that MDR E. coli is associated with more severe causes (Table 5).

3. Discussion

MDR E. coli and K. pneumoniae pose a major threat in hospital settings, leading to increased morbidity, mortality, and healthcare costs. Understanding the predisposing factors associated with these infections is crucial for implementing effective prevention and control strategies. These factors range from patient demographics and underlying conditions to hospitalization-related exposures and the selective pressure of antibiotic use [28,29]. By identifying these risks, healthcare providers can target interventions to reduce the spread of MDR organisms and improve patient outcomes [30].
In the current study, prior antibiotic use was more strongly associated with MDR Escherichia coli than with MDR Klebsiella pneumoniae, which is consistent with another study that highlighted species-specific differences in resistance development and antibiotic selective pressures [10]. Typically, MDR E. coli demonstrates high resistance rates to commonly used antimicrobials, such as amoxicillin, cefuroxime, trimethoprim–sulfamethoxazole, tetracycline, and fluoroquinolones, with prior antibiotic exposure recognized as a significant risk factor for colonization or infection with resistant strains [31,32]. In particular, the prolonged or inappropriate use of fluoroquinolones has been linked to increased resistance in E. coli [31]. Mechanistically, prior antibiotic exposure has been shown to disrupt the intestinal microbiota, favoring the overgrowth and persistence of resistant E. coli strains, which may partly explain the stronger association observed in the current study [33].
In contrast, although it has been suggested that prior exposure to antibiotics, such as aminoglycosides, penicillins, colistin, or linezolid, may increase the risk of MDR K. pneumoniae infection, the overall relationship appears less consistent and is likely influenced by the combination and spectrum of the antibiotics administered [34]. Longitudinal comparative data support an overall rise in multidrug resistance among both E. coli and K. pneumoniae isolates, particularly from urinary tract infections; however, the strength and consistency of prior antibiotic use as a risk factor remains more prominent for E. coli [35,36].
Based on the results from the current study, admission to the ICU was significantly associated with E. coli infection compared to K. pneumoniae, with an OR of 2.403 (95% confidence interval (95% CI): 1.111–5.200), indicating that ICU patients were more than twice as likely to acquire E. coli infections than non-ICU patients. However, a study by Moini et al. [37] reported no statistically significant difference in clinical outcomes between drug-resistant and non-resistant E. coli infections. Furthermore, evidence from a study conducted in Thailand indicated that E. coli may have a higher infection rate in ICU settings [38]. In particular, the production of extended-spectrum beta-lactamases (ESBLs) and carbapenemases has been strongly associated with adverse clinical outcomes, including therapeutic failure and increased mortality rates [39]. The ICU environment itself is recognized as a high-risk setting for the emergence and transmission of multidrug resistance. Several contributing factors, such as invasive procedures, prolonged hospitalization, prior use of broad-spectrum antibiotics, and the critical condition of patients, create selective pressure that favors the survival of resistant strains (particularly E. coli), which remains a leading cause of urinary tract infections [40].
Determining whether MDR E. coli or MDR K. pneumoniae imposes a greater clinical burden in ICU patients remains inconclusive. The impact of each pathogen is influenced by a variety of complex factors, including specific resistance mechanisms, pathogen virulence, and individual patient characteristics. Furthermore, comparative studies between MDR E. coli and MDR K. pneumoniae are still relatively limited. Hospital size and setting also play important roles, as variations in clinical context and patient volume may affect infection patterns and outcomes. These considerations highlight the need for a comprehensive and systematic evaluation of existing evidence to accurately assess the relative clinical impact of each organism in terms of mortality, disease severity, and healthcare costs.
Several studies have supported the conclusion that resistance to third-generation cephalosporins differs significantly between E. coli and K. pneumoniae. The current study revealed that receiving cephalosporin tended to induce a greater level of MDR E. coli than of MDR K. pneumoniae compared to the use of carbapenem. Lee et al. [41] reported that the resistance rate to third-generation cephalosporins in E. coli was 22.8%, higher than the 19.6% observed in K. pneumoniae. In addition, the Australian Passive Antimicrobial Resistance Surveillance [42] noted increasing resistance trends in both bacteria, but with differing rates. Furthermore, Lee et al. [41] reported a significant association between antibiotic usage and resistance rates to third-generation cephalosporins in both E. coli and K. pneumoniae, with notable differences in resistance levels. Other studies have highlighted differing resistance mechanisms, such as the production of ESBLs and the dissemination of resistance genes in each species.
Conversely, one study reported no significant difference in third-generation cephalosporin resistance between E. coli and Klebsiella spp. For example, Manninen et al. [43] reported very low resistance rates to second- and third-generation cephalosporins in Finland, with no significant difference between E. coli and Klebsiella spp. Their study suggested that low antibiotic consumption and effective stewardship may have contributed to reduced resistance in both bacteria. Other studies have indicated that cephalosporin resistance may not always correlate directly with resistance to other antibiotic classes in certain clinical contexts.
In summary, resistance to third-generation cephalosporins can vary significantly between E. coli and K. pneumoniae, largely due to genetic mechanisms and the spread of resistance genes, such as ESBL production, which differ in type and frequency between the two species. Furthermore, differences in antibiotic usage patterns and stewardship across regions influence resistance rates. Understanding these differences is crucial for optimizing treatment strategies and implementing effective resistance control measures in both hospital and community settings [42,44,45].
This study has several limitations. First, the relatively small sample size may limit the generalizability of the findings. Second, as the data were collected from a single community hospital, the results may not be representative of the broader population, particularly in urban settings. Third, stratification of prior antibiotic use by specific antibiotic classes was not possible, as this information was not collected. This may have introduced bias, as different antibiotic classes vary in their potential to promote MDR colonization. Additionally, certain clinically relevant variables, such as corticosteroid use, length of hospital stay, and the presence of coinfection, were initially excluded from the analysis. Their omission may have confounded the association observed between prior antibiotic exposure and MDR E. coli infection. Nonetheless, this finding should be interpreted with caution. Future studies with a larger, multicenter design are recommended to improve external validity and better capture population diversity.

4. Materials and Methods

4.1. Study Design and Data Collection

This case–control study analyzed five-year retrospective data (1 January 2016–31 December 2020) of E. coli and K. pneumoniae isolates from clinical specimens at a 120-bed community hospital in northeastern Thailand. Only one isolate per case was enrolled. Statistical significance was determined using two-sided tests and 95% confidence intervals (95% CI).
The study compiled bacterial identification and antimicrobial susceptibility testing (AST) results from all patients admitted to a community hospital during the study period. Microbial laboratory analyses were performed at the provincial hospital with results stored in the MLAB database (Version 5.58.22.02.28). The same standardized protocols for culture, identification, and AST were consistently conducted, according to Laboratory Accreditation under The Association of Medical Technologist of Thailand. AST results were interpreted based on the Clinical and Laboratory Standards Institute (CLSI) guidelines and classified as susceptible, intermediate, or resistant [46]. The selection of diagnostic examinations, including blood, stool, or urine tests, was guided by the clinical presentation and the attending physician’s judgment for each patient. Diagnostic tests were ordered based on the suspected site of infection and relevant comorbidities. This approach ensured that diagnostic and susceptibility testing were appropriately tailored to the clinical context and individual patient conditions.
A cohort of designated patients was established, and relevant clinical factors were extracted from both physical medical records and electronic medical records maintained in the HOSxP system. Additionally, medical history during the study period—including prior antimicrobial exposure and comorbid conditions—was obtained from the electronic records. The hospital provides inpatient care across five divisions: pediatric ward, male ward, female ward, special ward, and intensive care unit (ICU). For analytical purposes, we categorized these as ICU and non-ICU settings, with the latter comprising the pediatric, male, female, and special wards. Since these wards were not organized according to physician specialties but rather for administrative purposes, antimicrobial resistance surveillance was necessary across all units due to the absence of specialized patient classification.
Cases were defined as patients with multidrug-resistant (MDR) E. coli infections, while controls were patients with MDR K. pneumoniae isolates demonstrating resistance to at least three antibiotic classes.
Patients were eligible for inclusion if they met the following criteria:
(1)
Were admitted to Thatphanom Crown Prince Hospital for more than 24 h;
(2)
Had positive microbial culture results for Escherichia coli or Klebsiella pneumoniae;
(3)
Underwent antimicrobial susceptibility testing (AST).
Patients were excluded if they had
(1)
Incomplete biological or geographic data;
(2)
No recorded medical history at Thatphanom Crown Prince Hospital during the study period;
(3)
A hospital stay of less than 24 h.

4.2. Statistical Analysis

Data were checked, cleaned, and double-entered into Microsoft Excel and then exported to Jamovi version 2.3.28. Descriptive statistics were used to characterize resistance patterns, with frequencies reported as percentages. Chi-square tests compared susceptibility rates between antibiotic groups in MDR isolates. Univariate logistic regression analyses examined clinical and demographic differences between E. coli and K. pneumoniae infections, with results expressed as ORs with 95% confidence intervals.

4.3. Ethical Approval

The study was approved by the Ethics Committee of Human Research Nakhon Phanom Provincial Health Office, Ministry of Public Health (Protocol Number REC 014/64).

5. Conclusions

This study suggests that the use of third-generation cephalosporins may be more strongly associated with the emergence of MDR E. coli than with K. pneumoniae in a community hospital setting, highlighting the possible influence of antimicrobial selection pressure in rural healthcare environments. Additionally, prior antibiotic use was linked to an increased risk of E. coli bloodstream infections. While MDR E. coli infections appeared to present with greater clinical severity—as reflected by higher ICU admission rates—these observations warrant further investigation in larger, multicenter studies. Overall, the findings support the need for context-specific antimicrobial stewardship and strengthened infection control strategies in community hospitals.

Author Contributions

Conceptualization: R.U.; methodology: R.U. and A.K.; software: R.U.; formal analysis: R.U.; data cleaning: R.U. and J.P., resources: J.P.; data curation: R.U. and J.P.; writing—original draft preparation: R.U.; writing—review and editing: R.U., J.P., R.Y. and A.K.; project administration: R.U. and A.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Human Research Nakhon Phanom Provincial Health Office, Ministry of Public Health, No. REC 014/64, 30 July 2021.

Informed Consent Statement

Due to the observational nature of the study, the Ethics Committee exempted the need to seek written informed consent. We used an anonymized database designed for this study.

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Acknowledgments

This research was conducted with the co-operation of all the informants and related parties from whom the researcher requested additional information. The Thatphanom Crown Prince Hospital Pharmacy Department, the Infectious Disease Prevention and Control Committee, and the Unit of Microbiology, Nakhon Phanom Hospital, Thailand, provided information and gave permission for this research.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
MDRMultidrug-resistant
MDREMultidrug-resistant Enterobacteriaceae
E. coliEscherichia coli
K. pneumoniaeKlebsiella pneumoniae
ORCrude odds ratio
ORadjAdjusted odds ratio
95%CI95% confidence interval

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Table 1. Descriptive summary of E. coli and K. pneumoniae isolates by specimen type.
Table 1. Descriptive summary of E. coli and K. pneumoniae isolates by specimen type.
CharacteristicE. coli InfectionTotalOR (95% CI)p-Value
Blood
(n = 156)		Other (n = 265)
Gender 0.569
Male68 (43.6)108 (40.8)176ref
Female88 (56.4)157 (59.2)2451.18
(0.77–1.80)
Age group 0.181
<6071 (45.5)103 (38.9)174ref
≥6085 (54.5)162 (61.1)2471.47
(0.96–2.22)
DM 0.353
No125 (80.1)202 (76.2)327ref
Yes31 (19.9)63 (23.8)941.58
(0.90–2.77)
HT 0.42
No119 (76.3)211 (79.6)330ref
Yes37 (23.7)54 (20.4)910.66
(0.39–1.16)
COPD 0.128
No150 (96.2)261 (98.5)411ref
Yes6 (3.8)4 (1.5)100.47
(0.12–1.83)
CKD 0.341
No147 (94.2)255 (96.2)402ref
Yes9 (5.8)10 (3.8)190.62
(0.23–1.67)
Previous ATB 0.008 *
Yes65 (41.7)77 (29.1)1421.79
(1.17–2.74)
No91 (58.3)188 (70.9)279ref
ICU 0.132
No143 (91.7)252 (95.1)3951.89
(0.83–4.31)
Yes13 (8.3)13 (4.9)26ref
*: p-value < 0.05, ref: reference; ATB: antibiotic; ICU: intensive care unit; DM: diabetes mellitus; HT: hypertension; CKD: chronic kidney disease; COPD: chronic obstructive pulmonary disease.
Table 2. Distribution of E. coli and K. pneumoniae by clinical specimens.
Table 2. Distribution of E. coli and K. pneumoniae by clinical specimens.
SpecimenE. coli (n = 421)
n (%)		K. pneumoniae (n = 239)
n (%)
Blood265 (63.0)77 (32.2)
Urine113 (26.8)25 (10.5)
Sputum25 (5.9)122 (51.0)
Pus14 (3.3)9 (3.8)
Fluid4 (1.0)6 (2.5)
Table 3. Antimicrobial susceptibility in clinical isolates of E. coli (n = 211) and K. pneumoniae (n = 71).
Table 3. Antimicrobial susceptibility in clinical isolates of E. coli (n = 211) and K. pneumoniae (n = 71).
Antibiotic TypeE. coli
(n = 211)		K. pneumoniae
(n = 71)		p-Value
RSRS
Aminoglycosides117 (55.5)94 (44.5)36 (50.7)35 (49.3)0.487
Penicillin210 (99.5)1 (0.5)71(100.0)0 (0.0)0.561
3rd-generation Cephalosporins137 (64.9)74 (35.1)68 (95.8)3 (4.2)<0.001 **
Quinolones160 (75.8)51 (24.2)59 (83.1)12 (16.9)0.203
Carbapenems8 (3.8)203 (96.2)12 (6.9)59 (83.1)<0.001 **
**: p-value < 0.001, S: susceptible; R: resistant.
Table 4. Comparison of antimicrobial resistance between Escherichia coli and Klebsiella pneumoniae.
Table 4. Comparison of antimicrobial resistance between Escherichia coli and Klebsiella pneumoniae.
Antibiotic TypeE. coliK. pneumoniaeTotalOR (95% CI)p-Value
RR
3rd generation Cephalosporins137682050.69
(0.48–1.00)		0.052
Aminoglycosides and Quinolones27795372ref
Total414163577
3rd generation Cephalosporins137682053.02
(1.18–7.74)		0.021 *
Carbapenems81220ref
Total14580
*: p-value < 0.05, R: resistant.
Table 5. Characteristics of MDR E. coli compared with MDR K. pneumoniae infections by univariate logistic regression analysis.
Table 5. Characteristics of MDR E. coli compared with MDR K. pneumoniae infections by univariate logistic regression analysis.
CharacteristicsMDROR
(95% CI)		p-Value
E. coli (n = 211)K. pneumoniae (n = 71)
Gender
Male99 (46.9)39 (54.9)ref0.244
Female112 (53.1)32 (45.1)1.38 (0.80–2.37)
Age group (years)
<6089 (42.2)34 (47.9)ref
≥60122 (57.8)37 (52.1)1.26 (0.73–2.16)0.402
DM
No160 (75.8)57 (80.3)ref
Yes51 (24.2)14 (19.7)1.30 (0.67–2.52)0.442
HT
No165 (78.2)58 (81.7)ref
Yes46 (21.8)13 (18.3)1.24 (0.62–2.47)0.532
COPD
No206 (97.6)68 (95.8)ref
Yes5 (2.4)3 (4.2)0.55 (0.13–2.36)0.422
CKD
No203 (96.2)66 (93.0)ref
Yes8 (3.8)5 (7.0)0.52 (0.16–1.65)0.266
Previous ATB
No135 (64.0)54 (76.1)ref
Yes76 (36.0)17 (23.9)1.79 (0.97–3.30)0.063
ICU
No193 (91.5)58 (81.7)ref
Yes18 (8.5)13 (18.3)2.40 (1.11–5.20)0.026 *
*: p-value < 0.05; OR: odds ratio; 95% CI: 95% confidence interval; ref: reference. ATB: antibiotic used; ICU: intensive care unit; DM: diabetes mellitus; HT: hypertension; CKD: chronic kidney disease; COPD: chronic obstructive pulmonary disease.
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Ungcharoen, R.; Ponyon, J.; Yongyod, R.; Kerdsin, A. Predisposing Factors Associated with Third-Generation Cephalosporin-Resistant Escherichia coli in a Rural Community Hospital in Thailand. Antibiotics 2025, 14, 790. https://doi.org/10.3390/antibiotics14080790

AMA Style

Ungcharoen R, Ponyon J, Yongyod R, Kerdsin A. Predisposing Factors Associated with Third-Generation Cephalosporin-Resistant Escherichia coli in a Rural Community Hospital in Thailand. Antibiotics. 2025; 14(8):790. https://doi.org/10.3390/antibiotics14080790

Chicago/Turabian Style

Ungcharoen, Ratchadaporn, Jindanoot Ponyon, Rapeepan Yongyod, and Anusak Kerdsin. 2025. "Predisposing Factors Associated with Third-Generation Cephalosporin-Resistant Escherichia coli in a Rural Community Hospital in Thailand" Antibiotics 14, no. 8: 790. https://doi.org/10.3390/antibiotics14080790

APA Style

Ungcharoen, R., Ponyon, J., Yongyod, R., & Kerdsin, A. (2025). Predisposing Factors Associated with Third-Generation Cephalosporin-Resistant Escherichia coli in a Rural Community Hospital in Thailand. Antibiotics, 14(8), 790. https://doi.org/10.3390/antibiotics14080790

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