Multidrug-resistant Pseudomonas aeruginosa and its coexistence with β-lactamases at a tertiary care hospital in a low-resource setting: a cross-sectional study with an association of risk factors

Abstract

Background:

Pseudomonas aeruginosa is known to cause hospital-acquired infections. This bacterium produces β-lactamase enzymes that enzymatically degrade β-lactam drugs, reducing their efficacy.

Objective:

The objective of this investigation was to examine the occurrence, susceptibility, and production of various β-lactamases by multidrug-resistant P. aeruginosa (MDR-PA) and to determine the risk factors associated with extensively drug-resistant P. aeruginosa (XDR-PA) and their β-lactamases.

Design:

A descriptive cross-sectional study was conducted to investigate the occurrence, susceptibility, and β-lactamase production of MDR-PA and the risk factors associated with XDR-PA. The study involved collecting and analyzing 390 specimens from different 390 participants over a period from August 2021 to April 2023.

Methods:

The study utilized standard methodologies to screen and characterize P. aeruginosa. The antimicrobial-resistant patterns and presence of MDR-PA and XDR-PA were determined following standard guidelines supported by the Clinical Laboratory Standards Institute (CLSI) using various methods such as the disk diffusion method and colistin disk elution tests. Combined disk and inhibitor-based tests were used to determine extended-spectrum β-lactamases (ESBL), Metallo-β-lactamases (MBL), and AmpC-β-lactamases (AmpC) using two different methods. Clinical data were extracted from the medical records and patient requisition forms provided by clinicians. Clinical data were extracted for XDR-PA and β-lactamases applying binary logistic regression by adjusting for the confounding factors.

Results:

In our study, the antimicrobial-resistant pattern showed significant differences (p < 0.05) in the antibiotic-resistant pattern among β-lactamase and non-β-lactamase. The prevalence of MBL-P. aeruginosa was determined to be 13.5%, while ESBL accounted for 23.8%, and AmpC accounted for 20.5%. Coexistence of MBL + ESBL, ESBL + AmpC, MBL + AmpC, and MBL + ESBL + AmpC was determined to be 5.3%, 2.8%, 2.3%, and 4.1%, respectively. Among the nine assessed risk factors in a multivariate regression model, prolonged hospital stays (odd ratio = 11.2, 95% CI 3.7–33.8) provided substantial risk compared to other risk factors for the colonization of XDR-PA. Similarly, in a multivariate model, previous therapy with immunosuppressant drugs (OR = 6.7, 95% CI 1.5–29.3) was found to be the leading risk factor for the colonization of β-lactamase producers P. aeruginosa.

Conclusion:

Identification of XDR-PA and β-lactamases among MDR-PA isolates is crucial to prevent the use of unnecessary antibiotics. Early and prompt diagnosis of drug-resistant pathogens prevents treatment failure and encourages proper antibiotic therapy. Therefore, it is necessary to implement strict policies on the use of antibiotics without proper diagnosis.

Keywords

AmpC-β-lactamases extended-spectrum β-lactamases extensively drug resistant metallo β-lactamases multidrug resistant

Introduction

Pseudomonas aeruginosa belongs to the family Pseudomonadaceae and is a Gram-negative bacterium that is found predominantly in a health care setting and can reproduce on medical devices and various hospital surroundings by forming biofilms.^1,2 The frequent isolation of P. aeruginosa in hospital-acquired infections can be life-threatening and highly resistant to antibiotics.^3,4 The prevalence of hospital-acquired P. aeruginosa cases is greater than that of community-acquired infections.⁵ Numerous isolates of P. aeruginosa connected to nosocomial infection are responsible for a wide range of infections, such as bacteremia, urinary tract infection (UTI), and ventilator-associated pneumonia.¹ P. aeruginosa is known to be the fourth most prevalent nosocomial pathogen that leads to 27%–48% mortality rates among critically ill patients.^6,7

The emergence of multidrug-resistant P. aeruginosa (MDR-PA) and extensively drug-resistant P. aeruginosa (XDR-PA) complicates treatment options and necessitates the development of new therapeutic strategies. These bacteria often acquire resistance through various mechanisms, such as overexpression of naturally occurring cephalosporins, production of extended-spectrum β-lactamases (ESBL), AmpC β-lactamases, and Metallo-β-lactamases (MBL).⁸

Regarding the risk factors associated with MDR-PA and XDR-PA infections in a healthcare setting, there are notable knowledge gaps. To provide prompt and effective care, this study aims to improve the detection of the presence of ESBL, AmpC, and MBL in resource-limited settings and to identify risk factors that indicate the colonization of XDR-PA. This study was conducted to highlight the predisposing factors that raise the odds of obtaining infections by multidrug-resistant (MDR) and extensively drug-resistant (XDR) subtypes that can produce β-lactamases in tertiary care in Nepal. To date, there has not been sufficient research in Nepal that describes MDR-PA or XDR-PA infections, and only a few studies are available that describe a few parameters of risk factors independently associated with MDR-PA.⁹ Therefore, the objectives of this cross-sectional study were to: (a) estimate the prevalence of XDR-PA among the MDR-PA; (b) determine the rate of ESBL, AmpC, and MBL producers in the MDR population, and; (c) assess various risk factors for the colonization of XDR-PA and β-lactamase producers isolated from various clinical samples obtained from patients attending a tertiary care hospital in Nepal.

Methods

Supporting data collection

Sociodemographic characteristics (age and gender), clinical conditions (UTI, respiratory tract infection, bacterial peritonitis, pleural effusion, sepsis, soft skin infection, wound, and burned infection), as well as risk factors associated with colonization of XDR and β-lactamases (mechanical ventilation, chronic kidney disease, long hospital stay, and previous treatment with immunosuppressive drugs and antibiotics), were obtained by a combination of direct interview, medical records, and the patient’s sample requisition form.

Study area, design, and participants

A descriptive cross-sectional study was conducted in the Grande International Hospital from August 2021 to April 2023. The recruitment of 390 participants was done based on the isolation of MDR-PA, and sample collection lasted until the end of December 2022. The study involved patients attending both outpatient and inpatient departments. Different types of clinical samples from different patients were identified by clinicians working in the outpatient department, medical wards, intensive care unit (ICU), and emergency medicine department. Samples were then collected by nurses, experienced phlebotomists, and laboratory technicians with proper guidance from microbiologists and clinicians. Patients of all ages were included in the study. Patients with P. aeruginosa resistant to at least three different classes of antimicrobial agents were included in the study. Participants whose cultures, biochemical tests, and AST reports showed bacteria other than P. aeruginosa or bacteria resistant to fewer than three different antimicrobial classes were excluded from the study.

Processing of clinical specimen for culture

Clinical specimens, including urine, respiratory samples, body fluids, wound swabs, and blood, were processed following some modifications of standardized microbiological procedures. A clean-catch midstream urine sample was collected in a leak-proof container, inoculated onto cysteine lysine electrolyte-deficient (CLED) agar, and incubated at 37°C for 24 h. Bacterial growth was quantified using Kar’s semi-quantification method based on colony counts. Respiratory specimens, such as bronchoalveolar lavage (BAL), endotracheal aspirates, tracheostomy aspirates, and sputum, along with body fluids such as cerebrospinal fluid (CSF), pleural fluid, ascitic fluid, and bile, were first centrifuged at 10,000×g. The resulting sediment was used for Gram staining and cultured on both blood agar and MacConkey agar, then incubated at 37°C for 48 h. Wound swabs were collected in sterile containers, inoculated onto blood agar and MacConkey agar, and incubated at 37°C for 48 h. Blood samples were processed using the BACTEC automated system with BD BACTEC vials and incubated for up to 72 hr. Any growth detected by the BACTEC Alert System was further subcultured on blood agar and MacConkey agar to isolate pure bacterial colonies of P. aeruginosa.^10,11

Identification of P. aeruginosa

Initial identification

The isolated colonies of bacteria on the agar plates (CLED for urine specimens and blood and Mac-Conkey agar for all other clinical specimens) were primarily studied for colony morphologies such as shape, size, elevation, margin, and pigmentation as well as their aroma. The odor (fruity/earthy) released by a bacterium and the bacterial pigmentations (pyocyanin, pyoverdin, pyorubin, and pyomelanin) were found to be very useful initial key characteristics of P. aeruginosa in an agar plate.¹²

Biochemical identification

The initial identification of P. aeruginosa was later confirmed by a series of biochemical tests, including catalase tests, oxidase tests, triple sugar iron agar tests, sulfite indole motility tests, Simmon citrate utilization tests, and Christensen’s urea hydrolysis tests, as suggested by Bergey’s manual of bacteriology.¹³

Antimicrobial susceptibility test

After the observation of growth in culture plates, the standardized inoculum of each isolate was maintained by comparing its turbidity with a freshly prepared 0.5 McFarland solution, and the bacteria were inoculated onto Mueller-Hinton agar (MHA) plates. Antimicrobial susceptibility testing of the isolated P. aeruginosa was further proceeded to the disk diffusion assay to estimate the sensitivity of the tested antimicrobials against various antibiotic disks following the Clinical and Laboratory Standards Institute (CLSI) guidelines 2024.¹⁴ The following antibiotics based on CLSI guidelines were applied and allowed to diffuse in an agar plate: aztreonam (30 μg), ofloxacin (10 μg), tobramycin (10 μg), meropenem (10 μg), norfloxacin (30 μg), piperacillin/tazobactam (100/10 μg), and gentamicin (10 μg). Zone-size reading was followed by overnight incubation of lawn-cultured MHA plates for 24 h at 37°C. As the disk diffusion method is not recommended by CLSI so minimum inhibitory breakpoints (MIC < 2 µg/ml) was performed using the colistin disk elution method by placing 10 μg colistin disks into tubes containing the broth to achieve final concentrations of 0, 1, 2, and 4 μg/ml. The colistin was allowed to elute by incubating at room temperature for 30 min. Following this, P. aeruginosa inoculum was added to each tube and incubated at 35°C for 18–20 h. The minimum inhibitory concentration (MIC) was determined as the lowest concentration of colistin that inhibits visible bacterial growth before reporting it susceptible.¹⁴

Case definition

Extensively drug-resistant P. aeruginosa

Extensively drug-resistant P. aeruginosa is defined as resistance to a wide range of antibiotics (at least one agent in all groups) but remains susceptible to two or fewer anti-pseudomonal antimicrobial categories.¹⁵

Criteria for differentiating XDR-PA based on AST interpretation

After the evaluation of the resistance pattern of an applied antibiotic disk, P. aeruginosa was recognized as XDR if the zone-size interpretation of the antibiotic disk indicated resistance to almost one agent of all groups of antibiotics but demonstrated susceptibility to a few (one or two) antipseudomonal antibiotics.¹⁵

Screening for ESBL, AmpC, and MBL

The obtained P. aeruginosa from clinical specimens were first subjected to screening tests for various β-lactamases that were later confirmed by two different phenotypical tests. The isolates were screened with Ceftazidime (30 μg) for ESBL, Cefoxitin (30 μg) for AmpC, and Imipenem/Meropenem (10 μg) for MBL producers. Bacterial isolates that were resistant to the above-mentioned antibiotics were suspected to be multidrug-resistant due to the production of this β-lactamase enzyme. Hence, this was further confirmed using the phenotypic testing method.^16–18

Phenotypical confirmation of ESBL

Combined disk method for ESBL

The ESBL producer P. aeruginosa obtained from the culture of clinical specimens was subjected to Ceftazidime (30 μg) and Ceftazidime-clavulanic acid (30/10 μg) disk in the lawn culture of 0.5 McFarland suspension of a bacterium. The rise of a zone of inhibition ⩾5 mm in Ceftazidime-clavulanic acid (30/10 μg) indicated an ESBL producer when compared with the Ceftazidime (30 μg) disk. In such cases, the isolated bacterium (P. aeruginosa) was identified as an ESBL producer.¹⁶

Phenotypical confirmation of AmpC

Inhibitor-based method for AmpC detection

AmpC detection test was performed following the algorithm of EUCAST Guidelines¹⁷ and procedure used by Fatin Izzati et al.¹⁸ Bacterial suspension standardized to 0.5 McFarland was spread on MHA, and two disks: one with cefoxitin (30 µg) and another with cefoxitin and cloxacillin (230 µg) were placed on the surface of MHA following incubation at 37°C for 24 h. If the zone size is ⩾4 mm in cefoxitin + cloxacillin as compared to cefoxitin alone then the result indicates the presence of AmpC beta-lactamase.

Phenotypical confirmation of MBL

Combined disk diffusion method for Metallo β-lactamase

An EDTA combined disk method (CDT) was performed as described by Panchal et al., 2017. A lawn culture of test isolates was first prepared. After allowing it to dry for 5 min, two imipenem disks, one with 0.5 M EDTA and the other a plain imipenem disk, were placed on the surface of MHA agar plates approximately 30 mm apart. The plates were incubated overnight at 37°C. An increase in zone diameter of ⩾7 mm around the imipenem + EDTA disk in comparison to the imipenem disk alone indicated the production of MBL.¹⁹

Quality control

The sterilization efficiency of the autoclave was assessed using a biological indicator (Geobacillus stearothermophilus) in the sterilization process. Prepared agar plates were tested for sterility by incubating one plate from each batch for 24 h. MHA plates were maintained at a thickness of 4 mm and a pH of 7.2–7.4 for reliable antimicrobial susceptibility testing. The ATCC P. aeruginosa 27853 was used to standardize disk diffusion tests and interpret zones of inhibition.

Statistical analysis

The statistical analysis was conducted using SPSS (Version 16.0, USA, Chicago), employing simple descriptive statistics and chi-square tests to compare antimicrobial susceptibilities of β-lactamase and non-β-lactamase producing isolates. Descriptive statistics summarized the baseline characteristics of the study population, including measures of central tendency (mean, median) and dispersion (standard deviation) for continuous variables. Chi-square tests were used to assess associations between categorical factors, such as age, gender, and risk factors (e.g., clinical conditions, mechanical ventilation, chronic kidney disease, previous antibiotic therapy, and prolonged hospital stays) with the outcomes of XDR-PA and β-lactamase production. Bivariate chi-square analysis explored relationships between dichotomous predictors and the outcomes. To address confounding effects, Pearson’s correlation and standard error of regression coefficients were used to identify multi-collinearity among variables, which were then controlled in multivariate binary logistic regression. Crude and adjusted odds ratios (CORs and AORs), 95% confidence intervals (CI), and p-values were reported, with p-values < 0.05 considered statistically significant.

Results

Patient demographic and clinical characteristics

Our study randomly selected 390 patients following a simple random sampling technique from an initial pool of 427 participants based on the isolation of MDR-PA as a statistical estimation of the sample size needed. Out of 390 participants, male participants yielded 269 (69%) isolates of MDR-PA while female participants yielded 121(31%) MDR-PA isolates. The mean age group of participants was found to be 44.01 ± 21. Previously admitted inpatients were on average older (48 ± 21.7) as compared to infected patients from the outpatient department (41.5 ± 20.1). Altogether 78(20%) out of the 390 admitted patients had prolonged hospital stays in the ICU (>1 month). The number of isolated MDR traits in the P. aeruginosa was significantly greater in number in outpatient department as compared to that of the inpatient department. The results are summarized in Table 1.

Table 1.

Demographic and clinical characteristics of inpatient and outpatient study participants (n = 390) who had been randomly selected from an initial pool of 427 patients who exhibited MDR-PA.

Baseline characteristic	All departments (n = 390)	Inpatient department (n = 147)	Outpatient department (n = 243)
Gender
Male	269 (68.9%)	97 (65.9%)	172 (70.7%)
Female	121 (31.0%)	50 (34.0%)	71 (29.2%)
Age
Mean ± SD	44.01 ± 21.0	48 ± 21.7	41.5 ± 20.1
Clinical conditions
Urinary tract infection	74 (18.9%)	24 (16.3%)	50 (20.5%)
Respiratory infection	121 (31.0%)	19 (12.9%)	102 (41.9%)
Wound or burn infection	49 (12.5%)	10 (6.8%)	39 (16.0%)
Chronic kidney disease	16 (4.1%)	6 (4.08%)	10 (4.1%)
Sepsis	6 (1.5%)	6 (4%)	0
Soft tissue infection	5 (1.2%)	0	5 (2.0%)
Pleural effusion	6 (1.5%)	6 (4.0%)	0
Bacterial peritonitis	5 (1.2%)	5 (3.4%)	0
Mechanical ventilation	38 (9.7%)	38 (25.8%)	0
Previous treatment with immunosuppressive drug	21 (5.3%)	7 (4.7%)	14 (5.7%)
Previous antibiotics therapy	164 (42.05%)	129 (87.7%)	35 (14.4%)
Prolonged stay in ICU (>1 month)	78 (20%)	78 (53%)	0

MDR-PA, multidrug-resistant P. aeruginosa.

Prevalence of XDR-PA among MDR-PA

The drug-resistant pattern isolates of MDR-PA were evaluated to estimate the existence of XDR-PA and PDR-PA. From the total of 390 MDR-PA, altogether the drug-resistant pattern of n = 43 (11.02%) bacterial isolates met the criteria for the presence of XDR characteristics (i.e., resistant to all groups of antibiotics, only a few 1 or 2 antibiotics remain susceptible).

ESBL, MBL, and AmpC β-lactamase producer P. aeruginosa

The 390 MDR-PA isolates were evaluated to estimate the presence of three different β-lactamase enzymes (ESBL, MBL, and AmpC) and multienzyme coproducers. Based on our findings, the total number of β-lactamase producers is as follows: ESBL producers were n = 141 (36.1%); MBL producers were n = 99 (25.3%); AmpC producers were n = 80 (20.5%) out of the total 390 MDR-PA isolates. Apart from producers of ESBL, MBL, and AmpC, there were several coproducers of β-lactamases in our study. There were altogether 41 (10.5%) isolates of multienzyme coproducers (ESBL + MBL, ESBL + AmpC, and MBL + AmpC). The proportion of MDR-PA that resulted in the formation of ESBL, MBL, and AmpC only (excluding coproducers) were 93(23.8%), 53(13.5%), and 14 (3.5%), respectively. Among the two enzyme coproducers, the ESBL + MBL producer was found to have the largest proportion of coproducers (21 or 5.3%), followed by the ESBL + AmpC producer with 11 coproducers (2.8%), and the producer with least coproducers (9 or 2.3%) was MBL + AmpC. Altogether, 16 MDR-PA isolates (4.1%) determine the formation of all enzyme coproducers (ESBL + MBL + AmpC).

Antibiotics-resistant pattern in β-lactamases producers and nonproducers

The evaluation of antibiotic resistance patterns against the various antibiotics is presented in Table 2. Our results show that two antibiotics (aztreonam and piperacillin-tazobactam) were found to be highly resistant in both β-lactamase producers (aztreonam 235 (96.3%), piperacillin-tazobactam 207 (84.8%)) and nonproducers (aztreonam 143 (97.9%), piperacillin-tazobactam 109 (74.6%)), whereas all the MDR-PA was found to be absolute susceptible (100%) to colistin. Interestingly, our results showed that the number of β-lactamase producers was higher than that of nonproducers as well as the resistant rates were significantly greater for β-lactamase producers compared to nonproducers. The major differences in resistant rates were observed for gentamicin, piperacillin-tazobactam, meropenem, and tobramycin among β-lactamase producer and nonproducer strains of MDR-PA, which were found to be statistically significant (p value < 0.05). The computed analysis results are represented in Table 2.

Table 2.

Evaluation of antimicrobial resistance patterns between β-lactamase producers and nonproducers.

Antibiotics	β-Lactamases producers(n = 244)	β-LactamasesNonproducers(n = 146)	p Value
Ofloxacin	110 (45.1%)	57 (39.0%)	0.329
Aztreonam	235 (96.3%)	143 (97.9%)	0.366
Gentamicin	101 (41.3%)	29 (19.8%)	<0.001*
Meropenem	166 (68.0%)	41 (28.1%)	<0.001*
Norfloxacin	53 (21.7%)	39 (26.7%)	0.267
Piperacillin-tazobactam	207 (84.8%)	109 (74.6%)	<0.001*
Tobramycin	99 (40.5%)	31 (21.2%)	<0.001*
Colistin	0	0	—

Statistical analysis was not computed for colistin as all the MDR-P. aeruginosa in 390 participants were susceptible to colistin.

Indicates p value < 0.05.

Assessment of clinical and predisposing risk factors with XDR-PA

The clinical specimens of the 390 randomly selected pool of participants yielded MDR-PA in culture after the evaluation of the antimicrobial resistance patterns. Various clinical conditions and predisposing factors were investigated for their association with the colonization of XDR-PA (Table 3).

Table 3.

Clinical and predisposing factors associated with cases of XDR-PA.

Risk factor	XDR-PA		COR 95% CI	p Value	AOR 95% CI	p Value
Risk factor	Yes (n = 43)	No (n = 347)	COR 95% CI	p Value	AOR 95% CI	p Value
Gender
Female	14	107	1 (ref)
Male	29	240	0.9 (0.4–1.8)	0.810	NA
Age group (in years)
<60	28	272	1 (ref)
⩾60	15	75	1.94 (0.9–3.8)	0.051	NA
Previous treatment with immunosuppressive drug
No	41	328	1 (ref)
Yes	2	19	0.8 (0.1–3.7)	0.821	NA
Mechanical ventilation
No	22	330	1 (ref)
Yes	21	17	18.5 (8.5–40.1)	<0.001*	2.6 (1.0–6.5)	0.041*
Sepsis
Absent	37	347	1 (ref)
Present	6	0	0.09 (0.07–0.131)	0.993	NA
Chronic kidney disease
Absent	42	332	1 (ref)
Present	1	15	0.52 (0.06–4.0)	0.531	NA
Type II diabetes mellitus
Absent	39	333	1 (ref
Present	4	14	2.4 (0.7–7.7)	0.120	NA
Previous antibiotic therapy
No	6	220	1 (ref)
Yes	37	127	10.6 (4.3–26.0)	<0.001*	1.8 (0.5–6.0)	0.310
Prolonged stay in ICU (>1 month)
No	9	303	1 (ref)
Yes	34	44	26.01 (11.6–57.8)	<0.001*	11.2 (3.7–33.8)	<0.001*

Indicates p value < 0.05.

AOR, adjusted odd ratio; CI, confidence interval; COR, crude odd ratio; NA, not applicable; p value, probability value; ref, reference in a dichotomous variable; XDR-PA, extensively drug-resistant P. aeruginosa.

Among the nine risk factors examined, the occurrence of XDR-PA was found to be higher in patients with previously applied antibiotic therapy (n = 37, 86.0%) followed by prolonged hospital stays (n = 34, 79.1%) and mechanical ventilation (n = 21, 48.8%). The bivariate analysis (Table 3) shows a significant statistical association (p < 0.05) was observed for mechanical ventilation, previous antibiotics therapy, and prolonged hospital stays, and these were adjusted in a multivariate regression model to determine their combined effect on XDR-PA. Based on the results of multivariate analysis, patients who had undergone prolonged hospital stays (>1 month) were 11.2 times more likely (OR = 11.2, 95% CI 3.7–33.8) to get infected and become colonized with XDR-PA as compared to patients who had short stays or who were outpatients (p < 0.001). Similarly, patients under mechanical ventilation were 2.6 times more prone to get infected and colonized with XDR-PA (OR = 2.6, 95% CI 1.0–6.5) as compared to patients not under mechanical ventilation (p = 0.041). Therefore, in the presence of two other controlling confounders (mechanical ventilation and previous antibiotic therapy), prolonged hospital stays were determined to be the predominant risk factor (OR = 11.2) for the colonization of XDR-PA.

Assessments of bivariate and multivariate analysis between predisposing factors and the presence of β-lactamases in P. aeruginosa isolated from various clinical specimens

Altogether, nine risk factors incorporated in our study were analyzed in bivariate regression models for predicting the colonization of β-lactamases producers of MDR-PA (Table 4). Among these, the larger proportion of cases of β-lactamases was isolated from patients under previously applied antibiotics therapy (n = 118, 48.5%), followed by prolonged hospital stays (n = 60, 24.5%). In the bivariate analysis, we incorporated one predictor (risk factor) individually to observe the outcome of β-lactamases. From the bivariate analysis, previous treatment with immunosuppressive drugs, mechanical ventilation, previously applied antibiotic therapy, and prolonged stays in the ICU were statistically significant (p < 0.05). These four confounders were applied to predict the exact risk for colonization of β-lactamases using a multivariate regression model. In the multivariate model, immunosuppressive drugs were identified as the potent risk factor in the presence of the other three confounders (previous antibiotic treatment, mechanical ventilation, and prolonged hospital stay). The odds for colonization of β-lactamases in patients who had undergone treatment with immunosuppressive drugs were 6.7 times more likely as compared to patients who had no prior treatment with immunosuppressive drugs (OR = 0.6.7, 95% CI 1.5–29.3), and this was found to be statistically significant (p = 0.012).

Table 4.

Risk factors involved in colonization of β-lactamases in P. aeruginosa.

Risk factor	Total β-lactamases (ESBL/MBL/AmpC)		COR 95% CI	p Value	AOR 95% CI	p Value
Risk factor	Producers (n = 244)	Nonproducers (n = 146)	COR 95% CI	p Value	AOR 95% CI	p Value
Gender
Female	79	42	1 (ref)
Male	165	104	0.8 (0.5–1.3)	0.456	NA
Age group (in years)
<60	186	114	1 (ref)
⩾60	58	32	1.1 (0.6–1.8)	0.674	NA
Previous treatment with immunosuppressive drug
No	225	114	1 (ref)
Yes	19	2	6.0 (1.6–26.4)	0.007*	6.7 (1.5–29.3)	0.012*
Mechanical ventilation
No	212	140	1 (ref)
Yes	32	6	3.5 (1.4–8.6)	0.004*	2.3 (0.7–6.8)	0.132
Sepsis
Absent	238	146	1 (ref
Present	6	0		0.056	NA
Chronic kidney disease
Absent	233	141	1 (ref
Present	11	5	1.3 (0.4–3.9)	0.602	NA
Type II diabetes mellitus
Absent	230	142	1 (ref
Present	14	4	2.1 (0.6–6.6)	0.172	NA
Previous antimicrobial therapy
No	126	100	1 (ref)
Yes	118	46	2.0 (1.3–3.1)	0.001*	1.5 (0.9–2.6)	0.078
Prolonged stay in ICU (>1 month)
No	184	128	1 (ref)
Yes	60	18	2.3 (1.3–4.1)	0.003*	1.2 (0.5–2.7)	0.554

p < 0.05.

AmpC, AmpC-β-lactamases; AOR, adjusted odd ratio; CI, confidence interval; COR, crude odd ratio; ESBL, extended-spectrum β-lactamases; MBL, metallo β-lactamases; NA, not applicable; p value, probability value; ref, reference in a dichotomous variable.

Discussion

MDR-PA and XDR-PA cause severe complications and clinical challenges. Undiagnosed, these infections can result in treatment failures. The growing prevalence of these resistant strains is a global public health concern, linked to high mortality and increased resource use. P. aeruginosa produces many β-lactamases, including AmpC, ESBLs, and MBLs. While techniques for detecting AmpC β-lactamases are not included in current CLSI guidelines, they are crucial for identifying plasmid-produced AmpC β-lactamases.^20–22

Among third-generation cephalosporins, ceftazidime is widely used to treat infections caused by P. aeruginosa. The therapeutic care of patients infected with such isolates leads to clinical complications, accelerating the rate at which ceftazidime resistance is rising. The P. aeruginosa isolates in this investigation showed a significant degree of ceftazidime resistance. A past study from Iran found that 73.4% of P. aeruginosa acquired ceftazidime resistance during 2008.²³ Ceftazidime resistance is mainly mediated by the production of β-lactamases, such as ESBL, MBL, and occasionally AmpC.²⁴ Apart from the production of β-lactamases, other mechanisms confer resistance to applied antibiotics, such as low drug penetration in porins due to mutation in porin channels, outer membrane protein loss, and pump efflux mechanisms.²⁵

The current study used 390 isolated strains of MDR-PA. Most of the isolated strains were found in male participants (269, 68.9%) as compared to female participants (121, 31%). The isolated MDR strains were found to be significantly higher from patients from the outpatient department (p value < 0.05) compared to those from the inpatient department as the number of participants from the outpatient department enrolled in our study was larger than the number from the inpatient department. The mean age of the participants was 44.01, although admitted inpatients were older (48 ± 21.7). A research study conducted in Iran²⁶ also determined that cases of MDR-PA were more frequent in males (72.5%) compared to females (27.5%), which is consistent with our findings. That study also revealed the existence of 15.5% of XDR which was higher than the 11.0% found in our study.

Pseudomonas aeruginosa has been widely known for its potential to cause systemic infections such as respiratory tract infections (RTI), UTI, pleural effusion, bacteremia, sepsis, pneumonia, and burn and wound infections.²⁷ In our current study, MDR-PA was isolated mostly from RTIs (121, 31%) followed by UTIs (74, 18.9%). This finding was found to be concordant with a study conducted by Misset et al. in which the enormous incidence of nosocomial respiratory tract and UTIs was found to be associated with P. aeruginosa.²⁸ This is also consistent with the observation that the majority of P. aeruginosa was isolated from respiratory specimens and urine in our study.

Altogether, out of the 390 MDR-PA, 43 (11.0%) met the criteria for being XDR. The presence of three different β-lactamase enzymes (ESBL, MBL, and AmpC) and multienzyme coproducers were evaluated. ESBL producers were found in 141 (36.1%) bacterial strains, MBL producers in 99 (25.3%), and AmpC in 80 (20.5%), without excluding overlapping enzymes. Comparing these results with previous research, the prevalence of MBL-producing P. aeruginosa in our study is approximately half that reported by Shrestha et al. (50%) and Qureshi et al. (58%),^29,30 but higher than that reported by Malathi et al.³¹ and Kohalpure et al. (5.79%).³² The prevalence of ESBL-producing P. aeruginosa among MDR-PA in our study was nearly equal to that found by Taneja et al. (27.9%).³³

The incidence of ESBL in our study was higher than in the studies conducted by Oberoi (18.75%)³⁴ and by Malathi et al. (13.6%).³¹ Two further studies from India and Brazil had an incidence of ESBL (21%) that was found to be consistent with our value of 23.8% if we consider pure ESBL production, excluding other enzymes.²⁴ The prevalence of AmpC-producing P. aeruginosa in our study was less than that reported by Upadhyay et al. (50%)²⁰ and Parveen et al. (55.5%),³⁵ but significantly greater than the study conducted by Rafiee et al. (19.6%)³⁶ and Kohalpure et al. (11.59%).³²

There were numerous enzyme coproducers P. aeruginosa in our study (ESBL + MBL, ESBL + AmpC, MBL + AmpC, and ESBL + MBL + AmpC indicating the complexity of the resistance mechanisms of P. aeruginosa. Regarding the prevalence of MBL and ESBL coproducers in the same bacterium, altogether 5.38% (MBL + ESBL) were observed in our study which is significantly greater than that reported by Kotwal et al. (0.4%)³⁷ but lower as compared to Chaudhary and Payasi (14%).³⁸ Our study estimated the prevalence of both MBL and AmpC coproducers (2.30%) and ESBL + AmpC coproducers (2.82%) to be greater than those found by the study of Salimi et al.³⁹ but lower than those of Rawal et al.⁴⁰ They determined the coexistence of MBL + AmpC coproducers and ESBL + AmpC coproducers to be 18% and 20%, respectively. Our study estimated that all three β-lactamase coproducers (ESBL + AmpC + MBL) represented 4.1% of the total MDR-P. aeruginosa. This was small compared to a study conducted in Iran,⁴¹ which reported 12.5% for all three coproducers. Numerous studies claim that the existence of ESBL, MBL, and AmpC increases resistance rates to a wide range of both broad-spectrum and narrow-spectrum antimicrobials.^30,34,36 This can explain the greater existence of XDR (34.8%) in P. aeruginosa with all three β-lactamase producers in our study.

Regarding possible risk factors that increase the chances of becoming infected with XDR-PA, our study explored vital factors, including mechanical ventilation, previous treatment with immunosuppressive drugs, previous antibiotic therapy, and prolonged healthcare stays. Similar risk factors were examined in a study conducted in Thailand that found that patients who underwent mechanical ventilation had a 33.9% chance of contracting XDR-PA, while previous empirical therapy resulted in chance of 96.4% to contract XDR-PA. Interestingly, in their study, prolonged hospital stays (19.6%) had a relatively lower proportion of XDR-PA cases compared to our findings (79.1%).⁴¹ However, a study conducted in the USA explained that the prior use of antibiotics and longer hospital stays, particularly in ICU were known to be major causes of MDR-PA/XDR-PA.⁴² Other studies conducted in Nepal on rare non-fermented Gram-negative bacteria have also determined that long hospital stays are a leading risk factor for developing MDR/XDR bacterial infection.⁴³

Our study also analyzed the possible risk factors influencing the evolution of any β-lactamases (ESBL/MBL/AmpC) in bivariate and multivariate regression models. The multivariate model estimated that previous treatment with immunosuppressive drugs (OR~6.7) imposed substantial risk in the presence of other confounding factors. A study conducted in Iran determined that the previous use of immunosuppressive drugs was the highest risk factor (OR~7.3) for colonization by the MBL-Enterobacteriaceae family.⁴⁴ Alternatively, Kumar et al.⁴⁵ designated that an absolute (100%) proportion of β-lactamase was obtained from patients who had a history of mechanical ventilation, prior use of antibiotics, and longer hospital stays. Therefore, to minimize multidrug-resistant bacteria, it is necessary to implement proper antibiotic stewardship. In addition, to combat infections caused by P. aeruginosa, innovative therapeutic approaches are being explored besides antibiotics, such as phage therapy, herbal treatments, and nanoparticles. Phage therapy utilizes bacteriophages to specifically target and kill P. aeruginosa, disrupting biofilms and enhancing antibiotic effectiveness.⁴⁶ Herbal treatments involve natural antimicrobial agents found in herbs such as oregano and thyme oil, which have shown promise in inhibiting P. aeruginosa.⁴⁷ Silver nanoparticle treatments offer a targeted approach by delivering antimicrobial agents directly to the infection site, improving drug penetration and efficacy against MDR and XDR-PA.⁴⁸ There are several limitations and strengths of our study: our study was single-centered; the findings would have been much more precise if the study were multicentered to explore MDR, XDR, and β-lactamases in P. aeruginosa. In addition, our study was conducted in a low-resource country with limited laboratory equipment. Therefore, we were unable to employ molecular methods to explore genes of MDR, XDR, and various β-lactamases in our sample size. To explore every gene in a 390 MDR-PA for ESBL, AmpC, and MBL concerning MDR and XDR are extremely expensive for low-resource settings. Despite these limitations, our study possesses certain strengths, that is, we have an adequate sample size of MDR-PA isolate to observe the prevalence of the occurrence of XDR strains among MDR-PA. We have explored all three β-lactamases (ESBL, MBL, and AmpC) using phenotypical methods following standard procedures that can be followed in a country with low resources. Although the current findings solely focused on MDR-PA, it is the first time such a study has been conducted in Nepal. We evaluated various risk factors that require extensive care that gives insight into the correlation with drug-resistant pathogens in healthcare settings. Our study determined risk factors based on XDR strains, as well as on β-lactamases separately, which provides valuable information to treating clinicians and nurses so that they may understand the risks of colonization in patients by drug-resistant pathogens and they may implement improvement in infection control practices.

Conclusion

The current study highlights the significant production of multiple β-lactamase enzymes by P. aeruginosa, resulting in the development of MDR and XDR. This research underscores the risk factors that contribute to the emergence and colonization of drug-resistant P. aeruginosa. Detecting these β-lactamase producing isolates early on using routine laboratory practice could effectively prevent treatment failures. In addition, it is crucial to implement strict antibiotic policies and measures aimed at reducing the indiscriminate use of antibiotics in hospital settings, to mitigate the emergence of this organism that produces multiple β-lactamases. Thus, microbiologists play a pivotal role in preventing the global spread of this concerning multidrug-resistant pathogen.

Footnotes

Acknowledgements

We also would like to highly acknowledge Dr. Bill Turrel, Marine Biologist, Scotland for English editing and improving scientific terms in our manuscript.

Declarations

ORCID iD

Pragyan Dahal

References

Reynolds

Kollef

The epidemiology and pathogenesis and treatment of Pseudomonas aeruginosa infections: an update. Drugs 2021; 81(18): 2117–2131.

Elfadadny

Ragab

AlHarbi

, et al. Antimicrobial resistance of Pseudomonas aeruginosa: navigating clinical impacts, current resistance trends, and innovations in breaking therapies. Front Microbiol 2024; 15: 1374466.

Moradali

Ghods

Rehm

BH.

Pseudomonas aeruginosa lifestyle: a paradigm for adaptation, survival, and persistence. Front Cellular Infect Microbiol 2017; 7: 39.

Laborda

Sanz-García

Hernando-Amado

, et al. Pseudomonas aeruginosa: an antibiotic resilient pathogen with environmental origin. Curr Opin Microbiol 2021; 64: 125–132.

Sando

Suzuki

Ishida

, et al. Definitive and indeterminate Pseudomonas aeruginosa infection in adults with community-acquired pneumonia: a prospective observational study. Annals Am Thoracic Soc 2021; 18(9): 1475–1481.

Hafiz

Bin Essa

Alharbi

, et al. Epidemiological, microbiological, and clinical characteristics of multi-resistant Pseudomonas aeruginosa isolates in King Fahad Medical City, Riyadh, Saudi Arabia. Trop Med Infect Dis 2023; 8(4): 205.

Pagani

Afshari

Harbarth

Year in review 2010: critical care-infection. Crit Care 2011; 15: 1–7.

Horcajada

Montero

Oliver

, et al. Epidemiology and treatment of multidrug-resistant and extensively drug-resistant Pseudomonas aeruginosa infections. Clin Microbiol Rev 2019; 32(4): 10–128.

Siwakoti

Subedi

Sharma

, et al. Incidence and outcomes of multidrug-resistant gram-negative bacteria infections in intensive care unit from Nepal-a prospective cohort study. Antimicrobial Resist Infect Control 2018; 7: 1–8.

10.

Cheesbrough

District laboratory practice in tropical countries. 2nd ed. Vol. 2. Cambridge: Cambridge University Press, 2006.

11.

Meningitis Lab Manual: Primary culture and presumptive ID, https://www.cdc.gov/meningitis/lab-manual/chpt06-culture-id.html (2020, accessed 20 June 2021).

12.

Wahba

Darrell

. The identification of atypical strains of Pseudomonas aeruginosa. J General Microbiol 1965; 38(3): 329–342.

13.

Goodfellow

Kämpfer

Busse

, et al. Bergey’s manual of systematic bacteriology. New York, NY: Springer New York, 2012.

14.

Clinical and Laboratory Standards Institute. Performance standards for antimicrobial susceptibility testing, 35th ed CLSI supplement M100 Clinical and Laboratory Standards Institute, 2024.

15.

Magiorakos

Srinivasan

Carey

, 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(3): 268–281.

16.

Laudy

Rog

Smolińska-Król

, et al. Prevalence of ESBL-producing Pseudomonas aeruginosa isolates in Warsaw, Poland, detected by various phenotypic and genotypic methods. PloS One 2017; 12(6): e0180121.

17.

EUCAST Guidelines: resistant mechanism [Internet], https://www.eucast.org/resistance_mechanisms (2017, accessed March 2025).

18.

Fatin Izzati

Karunakaran

Roshalina Rosli

, et al. Genotypic and phenotypic detection of AmpC β-lactamases in Enterobacter spp. isolated from a teaching hospital in Malaysia. PLoS One 2016; 11: e0150643.

19.

Panchal

Oza

Mehta

SJ.

Comparison of four phenotypic methods for detection of metallo-β-lactamase-producing Gram-negative bacteria in rural teaching hospital. J Lab Phys 2017; 9(2): 81–83.

20.

Upadhyay

Sen

Bhattacharjee

Presence of different beta-lactamase classes among clinical isolates of Pseudomonas aeruginosa expressing AmpC beta-lactamase enzyme. J Infect Dev Ctries 2010; 4(4): 239–242.

21.

Nicasio

Kuti

Nicolau

DP.

The current state of multidrug-resistant gram-negative bacilli in North America. Pharmacotherapy 2008; 28(2): 235–249.

22.

Zhao

ZQ.

Beta-lactamases identified in clinical isolates of

Pseudomonas aeruginosa. Crit Rev Microbiol 2010; 36(3): 245–258.

23.

Saderi

Karimi

Owlia

, et al. Phenotypic detection of metallo-beta-lactamase producing Pseudomonas aeruginosa strains isolated from burned patients. Iran J Pathol 2008; 3: 20–24.

24.

Picao

Poirel

Gales

, et al. Diversity of beta-lactamases produced by ceftazidime-resistant Pseudomonas aeruginosa isolates causing bloodstream infections in Brazil. Antimicrob Agents Chemotherapy 2009; 53: 3908–3913.

25.

Noyal

Menezes

Harish

, et al. Simple screening tests for detection of carbapenemases in clinical isolates of nonfermentative Gram-negative bacteria. Indian J Med Res 2009; 129: 707–712.

26.

Mirzaei

Bazgir

Goli

, et al. Prevalence of multi-drug resistant (MDR) and extensively drug-resistant (XDR) phenotypes of Pseudomonas aeruginosa and Acinetobacter baumannii isolated in clinical samples from Northeast of Iran. BMC Res Notes 2020; 13: 380.

27.

Golemi-Kotra

. ‘Pseudomonas infections’, xPharm: The Comprehensive Pharmacology Reference, 2008; pp. 1–8. doi:10.1016/b978-008055232-3.63828-0.

28.

Misset

Timsit

Dumay

, et al. A continuous quality-improvement program reduces nosocomial infection rates in the ICU. Intensive Care Med 2003; 30(3): 395–400.

29.

Shrestha

Baral

Shrestha

LB.

Metallo-β lactamase producing non-fermentative gram-negative bacilli from various clinical isolates in a tertiary care hospital: a descriptive cross-sectional study. J Nepal Med Assoc 2021; 59(241): 875–880.

30.

Qureshi

Bhatnagar

RK.

Phenotypic characterization of ESBL, AMPC and MBL producers among the clinical isolates of multidrug resistant

Pseudomonas aeruginosa. Int J Curr Microbiol Appl Sci 2016; 5(10): 749–758.

31.

Murugan

Malathi

Therese

, et al. Antimicrobial susceptibility and prevalence of extended spectrum betalactamase (ESBL) and metallobetalactamase (MBL) and its co-existence among Pseudomonas aeruginosa recovered from ocular infections. Int J Pharm Pharm Sci 2015; 7: 147e51.

32.

Kolhapure

Kumar

Rajkumar

HRV

. Coexpression of ESBL, amp C and MBL in gram negative bacilli. Int J Res Med Sci 2015; 2698–2703.

33.

Taneja

Rao

Arora

, et al. Occurrence of ESBL &Amp-C β-lactamases & susceptibility to newer antimicrobial agents in complicated UTI. Indian J Med Res 2008; 127(1): 85–88.

34.

Oberoi

ESBL, MBL and AMPC lactamases producing superbugs – Havoc in the intensive care units of Punjab India. J Clin Diagnostic Res 2013.

35.

Parveen

Harish

Parija

SC.

AmpC beta lactamases among gram negative clinical isolates from a tertiary hospital, South India. Brazil J Microbiol 2010; 41: 596–602.

36.

Rafiee

Eftekhar

Tabatabaei

, et al. Prevalence of Extended-Spectrum and Metallo β-Lactamase Production in AmpC β-Lactamase Producing Pseudomonas aeruginosa Isolates From Burns. Jundishapur J Microbiol 2014; 7(9): e16436.

37.

Kotwal

Biswas

Kakati

, et al. ESBL and MBL in cefepime resistant Pseudomonas aeruginosa: an update from a rural area in Northern India. J Clin Diagn Res 2016; 10(4): DC09–DC011.

38.

Chaudhary

Payasi

Rising antimicrobial resistance of Pseudomonas aeruginosa isolated from clinical specimens in India. J Proteom Bioinform 2013; 6(1): 005–009.

39.

Salimi

Eftekhar

Coexistence of AMPC and extended-spectrum β-lactamases inmetallo-β-lactamase producing Pseudomonas aeruginosa burn isolates in Tehran. Jundishapur J Microbiol 2013; 6(8): 1–5.

40.

Rawat

Singhai

Verma

PK.

Detection of different β-lactamases and their co-existence by using various discs combination methods in clinical isolates of Enterobacteriaceae and Pseudomonas spp. J Lab Phys 2013; 5: 21–25.

41.

Palavutitotai

Jitmuang

Tongsai

, et al. Epidemiology and risk factors of extensively drug-resistant Pseudomonas aeruginosa infections. PLoS ONE 2018; 13(2): e0193431.

42.

Raman

Avendano

Chan

, et al. Risk factors for hospitalized patients with resistant or multidrug-resistant Pseudomonas aeruginosa infections: a systematic review and meta-analysis. Antimicrob Resistant Infect Control 2018; 7: 79.

43.

Parajuli

Limbu

Chaudhary

, et al. Phenotypical detection of β-lactamases in a multidrug-resistant and extensively drug-resistant Chryseobacteriumindologens: a rare human pathogen with special references to risk factor. MicrobiolInsights 2023; 16: 11786361221150755.

44.

Masaeli

Faraji

Ramazanzadeh

Risk factors associated with resistance in Metallo beta-lactamase producing Enterobacteriaceae isolated from patients in Sanandaj Hospitals. Curr Drug Therapy 2012; 7(3): 179–183.

45.

Kumar

Baveja

, et al. Prevalence and risk factors of Metallo β-lactamase producing Pseudomonas aeruginosa and Acinetobacter species in burns and surgical wards in a tertiary care hospital. J Lab Phys 2012; 4(1): 39–42.

46.

Chegini

Khoshbayan

Taati Moghadam

, et al. Bacteriophage therapy against Pseudomonas aeruginosa biofilms: a review. Annal Clin Microbiol Antimicrob 2020; 19: 1–7.

47.

How to treat Pseudomonas aeruginosa naturally, https://adelaidenaturopathic.com.au/pseudomonas-aeruginosa/ (2025, accessed January 2025).

48.

Kamer

El Maghraby

Shafik

, et al. Silver nanoparticle with potential antimicrobial and antibiofilm efficiency against multiple drug resistant, extensive drug resistant Pseudomonas aeruginosa clinical isolates. BMC Microbiol 2024; 24(1): 277.