A Multicenter Surveillance of Antimicrobial Resistance Among Pseudomonas aeruginosa in Hospitals of the Greater Accra Region of Ghana

Abstract

Background:

Carbapenem-resistant Pseudomonas aeruginosa (CRPA) and multidrug-resistant (MDR) P. aeruginosa limit therapeutic options but have been sparsely documented in Ghana.

Methods:

From November 2023 to December 2024, we conducted a prospective cross-sectional study of P. aeruginosa isolates from acute-care hospitals in Greater Accra, Ghana. Isolates were identified by matrix-assisted laser desorption ionization–time of flight, and antimicrobial susceptibility was assessed by disk diffusion as per Clinical Laboratory Standard Institute guidelines. Meropenem-resistant isolates with positive carbapenemase phenotype were subjected to whole-genome sequencing. Multivariable logistic regression models identified risk factors for infections caused by MDR and carbapenemase-producing Pseudomonas aeruginosa (CRPA).

Results:

P. aeruginosa accounted for 0.32% (n = 267/83,589) of all bacterial infections identified from submitted clinical specimens and 2.82% (n = 267/12,236) of culture-positive infections. Of the 267 P. aeruginosa isolates, 20.2% (n = 54/267) were MDR and 13.5% (n = 36/267) were CRPA. Amikacin retained the highest activity against P. aeruginosa. The mean multiple antibiotic resistance index among MDR isolates (0.51 ± 0.26) was significantly higher than that among non-MDR P.aeruginosa isolates (0.02 ± 0.07; p < 0.001), with a large between-group difference (Hedges’ g = 3.70). Only one isolate (2.7%) harbored a single carbapenemase gene, blaNDM-1. The remaining 35 carried a blaOXA-50-type backbone that co-occurred with either class A carbapenemases (blaKPC [n = 7], blaSME-1 [n = 4], blaGES-5 [n = 1]) or class B metallo-β-lactamases (blaNDM-1 [n = 19], blaVIM-5 [n = 3], blaIMP-15 [n = 1]). blaNDM-1 was the most dominant carbapenemase gene (n = 20/36) . Wound infection was the strongest predictor of MDR infections (adjusted odds ratio [aOR] = 3.01; 95% confidence interval (CI) = 1.43–4.47; p = 0.001], whereas inpatient status was the strongest predictor of CRPA infection (aOR = 3.32; 95% CI = 0.98–4.09; p = 0.001).

Conclusions:

MDR P. aeruginosa and carbapenem Resistant P.aeruginosa (CRPA), mostly blaNDM-1 producers, are major causes of infection in our setting. Restricting carbapenem use through stewardship and strengthening infection control is essential to limit CRPA spread.

Keywords

antibiotics isolates nosocomial infections microbial drug resistance

Introduction

Pseudomonas aeruginosa is a major cause of healthcare-associated infections, particularly in critically ill and immunocompromised patients.^1,2 It is frequently implicated in ventilator-associated pneumonia, bloodstream infections, urinary tract infections, and surgical site infections (SSI), with outcomes often marked by substantial morbidity and mortality.² Clinical management is challenged by the organism’s intrinsic resistance, mediated by efflux pumps, low outer-membrane permeability, and chromosomally encoded β-lactamases, as well as its capacity to acquire additional determinants through horizontal gene transfer and mutational adaptation. Consequently, therapeutic options for severe P. aeruginosa infections remain limited, especially in high-risk populations.³

Globally, antimicrobial resistance is a pressing public health threat, with nearly 4.95 million deaths in 2019 linked to bacterial resistance.³ Carbapenem-resistant P. aeruginosa (CRPA) is of particular concern and has been designated by the World Health Organization as a critical priority pathogen, reflecting the paucity of therapeutic alternatives once resistance emerges.^4–6 Among CRPA, carbapenemase-producing isolates (CRPA) represent a clinically important subset, as resistance is frequently mediated by carbapenem-hydrolyzing enzymes, including metallo-β-lactamases (MBLs; e.g., blaNDM, blaVIM, blaIMP) and class D oxacillinases (e.g., blaOXA variants), which may act alone or in combination.⁷ These determinants often coexist with genes conferring resistance to aminoglycosides, fluoroquinolones, and extended-spectrum cephalosporins, driving the spread of multidrug-resistant (MDR) and extensively drug-resistant phenotypes.⁸

In sub-Saharan Africa, the burden of MDR and CRPA is likely underestimated, owing to unregulated antibiotic use, underdeveloped stewardship programs, and limited diagnostic capacity.⁹ In Ghana, systematic multicenter surveillance of P. aeruginosa is lacking, despite increasing reports of MDR among other Gram-negative pathogens. This evidence gap is worrying given the increasing reliance on carbapenems as last-line agents for Gram-negative infections across the region.^10,11 Accordingly, the present study determined the prevalence and antimicrobial susceptibility profiles of clinical P. aeruginosa isolates, characterized CRPA using phenotypic and genomic approaches, and identified patient- and hospital-level risk factors associated with MDR and CRPA infections.

Materials and Methods

Study settings

This multicenter, cross-sectional study was conducted from November 2023 to December 2024 in eight government-supported acute care hospitals in Accra, the business center of the Greater Accra Region and the national capital of Ghana. Among the 31 government-supported acute care hospitals in the region, nine offer microbiological services, including culture and antimicrobial susceptibility testing (AST). Eight of these nine hospitals consented to participate. The study sites included three teaching hospitals (University of Ghana Medical Center [1,000 beds], Korle-Bu Teaching Hospital [2,000 beds], and Greater Accra Regional Hospital [420 beds]), three secondary hospitals (Ledzokuku-Krowor Municipal Assembly Hospital [100 beds], Tema General Hospital [400 beds]), and two (Maamobi Government Hospital [70 beds], and two primary hospitals, Ga North Municipal Hospital [100 beds], and Dodowa Government Hospital [244 beds]).

Sampling design

During the study period, all P. aeruginosa isolates cultured from clinical specimens and identified as causative agents of infection following physician-prescribed bacteriological investigations at the participating hospitals were prospectively included as study isolates. P. aeruginosa isolates received from study sites were purified on MacConkey agar and speciated using matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) (Bruker Daltonics, Germany) using Biotyper^™ system 2.0 software at the genus [log(score) 1.7–2.0] and species [log(score) ≥ 2.0] levels.¹² Non-P. aeruginosa isolates were discarded. Study isolates were stocked in trypticase soy broth (TSB) supplemented with 10% glycerol and stored at −20°C until further analysis. Complete medical records for review were available for inpatient and outpatient and accessed through the Lightwave Health Information Management System. Other data were collected by reviewing microbiology laboratory reports and logbooks. A data extraction form was used to collect information on each patient, including the admission duration (more than 2 weeks), type of sample (clinical specimen submitted to the laboratory), previous antibiotic use (the use of antibiotic in the past 3 months), comorbidity (underlying medical condition), biographic data, hospitalization status (inpatient or outpatient), and invasive procedures (any procedure that involves entry of the vein).

Antimicrobial susceptibility testing

The P. aeruginosa isolates were subjected to Kirby–Bauer-based (AST) on Mueller–Hinton agar (MHA), (BioMerieux, France) following the Clinical Laboratory Standard Institute (CLSI) M02^TM13(2023) Performance standards for antimicrobial disk susceptibility tests.¹⁴ A 0.5 McFarland standard P. aeruginosa inoculum loopful was evenly swabbed on the surface of an MHA plate for semiconfluent growth after incubation. Antibiotic discs—piperacillin/tazobactam (TZP) (100/10 µg), ceftazidime (CAZ; 30 µg), cefepime (FEP; 30 µg), amikacin (AMK) (30 µg), ciprofloxacin (CIP; 5 µg), meropenem (MEM; 10 µg), and aztreonam (ATM; 30 µg) (Oxoid, Basingstoke, UK)—were firmly applied to the agar plate surface and incubated aerobically at 35–37°C for 18–24 hours. The zones of inhibition for the various antibiotics were interpreted according to CLSI M100^TM (2023) breakpoints.¹⁴ Antibiotics were selected based on the CLSI M100¹⁴ (2023), a tiered recommendation system for antimicrobial agents that should be considered for routine primary testing and cascade reporting by clinical microbiology laboratories.

Carbapenemase phenotype detection

All P. aeruginosa isolates that were not susceptible to meropenem based on AST results were tested for carbapenemase production using the modified carbapenem inactivation method (mCIM).¹⁴ Briefly, 10-µL loopful from an overnight blood agar culture of each P. aeruginosa isolate was emulsified in 2 mL TSB and vortexed for 10–15 seconds. A 10-µg meropenem disk was completely immersed in each culture suspension using sterile forceps. Tubes were incubated at 35°C ± 2°C for 4 ± 0.25 hours. Concurrently, a 0.5 McFarland colony suspension of Escherichia coli ATCC^® 25922 was prepared in saline and used to inoculate MHA plates according to CLSI M100 (2023) performance standards.¹⁵ meropenem disks were retrieved from the test culture suspensions, drained of excess fluid, and aseptically transferred onto MHA plates previously inoculated with E. coli ATCC^® 25922 and allowed to dry for 3–10 minutes. Plates were incubated at 35°C ± 2°C in ambient air for 18–24 hours, and inhibition zone diameters were interpreted in accordance with CLSI M100 (2023) breakpoints.¹⁴ Quality control for mCIM was performed using Klebsiella pneumoniae ATCC^® BAA-1705^™ as the positive control and K. pneumoniae ATCC^® BAA-1706^™ as the carbapenemase-negative control strain.¹⁴

Whole genome sequencing

Forty isolates were selected for whole genome sequencing (WGS) based on MEM resistance and/or positive mCIM results to identify resistance-associated genetic determinants. Briefly, DNA from overnight cultures on nutrient agar incubated aerobically at 35–37°C for 18–24 hours was extracted using the QIAamp Mini Spin Kit (Qiagen), following the manufacturer’s protocol. DNA concentration was measured with a Qubit 4.0 Fluorometer and Qubit HS dsDNA Kit (Invitrogen, MA, USA), and extracts were stored at −20°C. DNA was diluted to 100–500 ng/µL (30 µL volume) for library preparation using the Illumina DNA Prep (M) Tagmentation Kit (Illumina Inc., San Diego, CA). Libraries were normalized to 2 ng/µL, pooled, and sequenced on the Illumina NextSeq 2000 using NextSeq 2000 P2 300-cycle reagents (Illumina Inc., San Diego, CA; Catalog no. 20046813), generating 2 × 150 bp paired-end reads. Raw FastQ reads were retrieved from the platform after 3 days. Raw Illumina sequencing reads were assessed for quality using FastQC and trimmed with Trimmomatic to remove low-quality bases and adapters. High-quality reads were then assembled de novo using Unicycler, and assembly quality metrics were evaluated with QUAST. Species confirmation of P. aeruginosa isolates, initially identified by MALDI-TOF MS, was performed through genomic analysis using KmerFinder (http://cge.food.dtu.dk/service/KmerFinder/). Antimicrobial resistance genes conferring non-susceptibility to third-generation cephalosporins and meropenem were identified using ResFinder and interpreted according to their structural and functional information provided by the Beta-Lactamase DataBase.¹⁶ Final sequence data were deposited in the GenBank database with a bio project number PRJNA1293373.

Data analysis

Data from laboratory investigations and patient interviews were entered into a Microsoft Excel database and imported into IBM SPSS Statistics (Version 28.0) for data cleaning and analysis. Descriptive analyses were performed to summarize characteristics of the study population, using frequencies and percentages. Categorical variables were expressed as counts and proportions (n, %) and compared across groups using chi-square or Fisher’s exact tests, depending on cell sizes. The prevalence of each outcome was determined by calculating its proportion relative to the total number of participants. A multiple antibiotic resistance (MAR) index was calculated for each isolate as the ratio of the number of antibiotics to which an isolate was resistant to the total number of antibiotics tested, using the formula.¹⁷ An MAR index greater than 0.2 was considered indicative of high-risk contamination sources, typically associated with frequent antibiotic use and elevated selective pressure, which may promote the emergence and dissemination of MDR organisms. For this study, MDR was technically defined as resistance to at least one agent in three or more antimicrobial classes using CLSI breakpoints.¹⁸ For CRPA, resistance was defined as isolates demonstrating resistance to meropenem by disk diffusion. The, CRPA isolates were further required to test positive by the mCIM and harbor a carbapenemase-encoding gene identified by WGS. Associations between infection with MDR and CRPA and their potential predictor variables were initially assessed using univariate analysis, with odds ratios (ORs) and corresponding 95% confidence intervals (CIs) to quantify the strength of associations. Variables with a p value less than 0.05 in univariate analyses were subsequently included in multivariate logistic regression models to identify independent risk factors by adjusted ORs (aORs). The predictive performance of each model was evaluated using the Hosmer–Lemeshow goodness-of-fit test, where a p value greater than 0.05 indicated an adequate fit. Discriminatory ability was assessed using the area under the receiver operating characteristic curve, with values above 0.7 indicating acceptable model discrimination between infected patients and controls.

Results

Between November 2023 and December 2023, a total of 83,589 clinical cases were referred from all 8 participating hospitals to their various microbiology laboratories for investigations of bacterial infections. Out of these cases, 84,660 clinical specimens were received at the laboratories for analysis (some patients submitted more than one specimen for the investigation). Among these specimens, 12,236 were culture-positive, yielding isolates considered to be the causative agents of the infections under investigation. Overall, 299 non-duplicate isolates initially identified as P. aeruginosa—one per specimen—were prospectively collected from various laboratories, where they had been reported as causative agents of infections. Of these, 267 were subsequently confirmed as P. aeruginosa, corresponding to an infection prevalence of 0.319% (n = 267/83,589) (Fig. 1 below). Of the 267 confirmed P. aeruginosa isolates, the majority originated from urine samples (43.8%, n = 117), followed by SSI (25.8%, n = 69), blood cultures (14.2%, n = 38), and soft skin tissue infection (11.6%, n = 31) (Table 1).

FIG. 1.

Geographic distribution and prevalence of Pseudomonas aeruginosa infections in eight acute-care hospitals across the Greater Accra Region, Ghana. Each hospital site is shown with the proportion of P. aeruginosa isolates among (□) all patients submitting clinical specimens for bacteriological investigation and (▧) all culture-positive bacterial infections. The inset map highlights the Greater Accra Region within Ghana. Site 1, Greater Accra Regional Hospital; Site 2, Tema General Hospital; Site 3, Dodowa Government Hospital; Site 4, Ga North Municipal Hospital; Site 5, Korle-Bu Teaching Hospital; Site 6, University of Ghana Medical Center; Site 7, Maamobi Government Hospital; Site 8, Ledzokuku-Krowor Municipal Assembly Hospital.

Table 1.

Distribution of Pseudomonas aeruginosa Isolates Across Clinical Syndromes and Specimen Types^a

Presumptive diagnosis		Specimens submitted		Cultures positive for infections^b	Cultures positive with P. aeruginosa only
Type	Num	Type	Num		Number	Prevalence (%)
						Diagnosis	Specimens	Positive cultures
				Bloodstream infections		19,039	Blood	20,108	2,640	38	0.002	0.002	1.402
Urinary tract Infections	53,708	Urine	53,708	7,183	117	0.002	0.002	1.629
Lower RT	1,721	Sputum	1,721	606	5	0.003	0.003	0.825
Upper RT	164	Throat swabs	164	59	1	0.061	0.061	1.694
SST Infection^c	2,641	Wound swabs	2,643	642	31	1.173	1.172	4.829
Surgical site Infections	3,590	Surgical site specimens, including aspirates of pus and fluids	3,590	1,041	69	1.92	1.92	6.578
GT Infection	2,151	Urethral swab	610	4	1	<0.001	0.002	25.0
		Semen culture	730	3	1		0.001	33.33
		Endocervical swab	811	8	1		0.004	12.5
Otitis media	142	Ear swab	142	10	1	0.007	0.007	10.0
Conjunctivitis	132	Eye swab	132	8	1	0.008	0.008	12.5
CNS	301	CSF	301	32	1	0.003	0.003	3.1
Total	83,589	All specimens	84,660	12,236	267	0.319	0.315	2.182

^aOnly specimens that yielded P. aeruginosa are included.

Culture-positive results refer to growth of any clinically relevant bacteria organism deemed etiologic of the suspected infection.

SST Infections, nonsurgery related Soft Skin and Tissue infections.

Lower RT, lower respiratory tract infection; Upper RT, upper respiratory tract infection; SST, soft skin and tissue; GT, genital tract; CNS, central nervous system infections; Num, number; ID, pathogen identity.

Susceptibility profiles of P. aeruginosa isolates

Table 2 shows the susceptibility of P. aeruginosa isolates from various clinical samples against commonly tested antibiotics. The highest susceptibility rate was observed for AMK (94.38%, n = 252/267), followed by FEP (93.26%, n = 249/267), piperacillin/TZP (88.01%, n = 235/267), MEM (85.09%, n = 227/267), CAZ (84.64%, n = 226/267), ATM (82.77%, n = 221/267), and CIP (81.65%, n = 2,186/267). About 20% (n = 54/267) of the P. aeruginosa isolates were classified as MDR. Overall, MDR isolates exhibited markedly lower susceptibility rates (ranging from 22.22% to 74.07%) compared with non-MDR isolates (susceptibility range: 96.71–76.71%). The MDR strains were predominantly recovered from urinary (22.2%, n = 26/117) and SSI (21.7%, n = 15/69). A MAR index ranging from 0.21 to 0.75 was observed among all MDR isolates, whereas non-MDR isolates had MAR index values ranging from 0.02 to 0.07. The mean MAR index among MDR isolates (0.51 ± 0.26) was significantly higher than that among non-MDR isolates (0.02 ± 0.07; p < 0.001), with a large between-group difference (Hedges’ g = 3.70).

Table 2.

Antibiotic Susceptibility Profile and Resistance Indices of Pseudomonas aeruginosa Clinical Isolates Across Infection Types

Infections (n)	AMK	CAZ	FEP	ATM MER		TZP	CIP	MARI ± SD	MDR (%)
SSI (n = 69)	100.00%	46.37%	76.81%	76.81%	76.81%	23.18%	46.37%	0.29 ± 0.40	15 (21.7)
BSI (n = 38)	100.00%	86.21%	100.00%	82.76%	86.21%	86.21%	86.21%	0.1 ± 0.18	5 (13.2)
UTI (n = 117)	91.11%	80.00%	88.89%	80.00%	86.67%	83.33%	73.33%	0.17 ± 0.29	26 (22.2)
^*SST (n = 31)	94.44%	83.33%	93.33%	81.11%	91.11%	88.89%	83.33%	0.12 ± 0.23	6 (19.4)
Others (n = 12)	95.83%	91.67%	95.83%	91.67%	100.00%	100.00%	95.83%	0.21 ± 0.30	2 (16.6)
Total (n = 267)	94.38%	84.64%	93.26%	82.77%	85.09%	88.01%	81.65%	0.12 ± 0.24	54 (20.2)
Multidrug susceptibility
MDR (20.22%, n = 54)	74.07%	48.15%	68.52%	37.04%	33.33%	40.74%	22.22%	0.51 ± 0.26 (range, 0.21–0.75)
Non-MDR (79.78, n = 213)	94.80%	90.30%	86.10%	92.50%	98.10%	91.80%	96.71%	0.12 ± 0.07 (range, 0.02–0.09)

SST infections, nonsurgery related soft skin and tissue infections; SSI, surgical site infections; BSI, bloodstream infections; UTI, urinary tract infections; others, include lower and upper respiratory tract infection; genital tract infections, central nervous system infections, otitis media, and conjunctivitis; n, number; AMK, Amikacin; CAZ, Ceftazidime; FEP, Cefepime; ATM, Aztreonam; MEM, Meropenem; TZP, Tazobactam; CIP, Ciprofloxacin; %, Percentage; MDR, multidrug-resistant; MARI, multiple antibiotic resistance index; SD, standard deviation.

Carbapenem resistance genotype

Of the 40 carbapenem-resistant P. aeruginosa isolates, 36 tested positive for carbapenemase production by the mCIM assay. WGS confirmed carbapenemase genes in all 36 mCIM-positive isolates, corresponding to a CRPA prevalence of 13.5% (n = 36/267) among all P. aeruginosa infections. The remaining four carbapenem-resistant isolates that tested negative by mCIM carried only the blaOXA-50 gene, which is associated with weak carbapenem hydrolysis; these isolates were therefore not classified as carbapenemase producers. Among the 36 CRPA, one isolate (2.8%) harbored a Class B MBL gene alone (blaNDM-1) (Table 3). The remaining 35 isolates carried class D blaOXA carbapenemase genes in combination with class A or class B genes, with or without the extended-spectrum beta-lactamase (ESBL) gene. Class B MBL genes were identified in 24 isolates (66.7%), including blaNDM-1 in 20 isolates, blaVIM-5 in 3, and blaIMP-15 in 1. Class D oxacillinases co-occurring with MBLs constituted the most common profile (n = 21), predominantly blaOXA-395/blaNDM-1 (n = 15), followed by blaOXA-396/blaVIM-5 (n = 2) and blaOXA-488/blaNDM-1 (n = 2). Two isolates harbored more complex combinations involving two oxacillinase genes and an MBL (blaOXA-396/blaOXA-10/blaVIM-5, n = 1; blaOXA-395/blaOXA-10/blaIMP-15, n = 1). In addition, two isolates carried a combination of a Class D oxacillinase, a Class B MBL, and an ESBL gene (blaOXA-488/blaNDM-1/blaCTX-M-15, n = 2). Class A carbapenemases were observed in 12 isolates, all co-occurring with class D oxacillinases (blaOXA-395/blaKPC, n = 7; blaOXA-396/blaSME-1, n = 4; and blaOXA-488/blaGES-5, n = 1). The most predominant carbapenemase gene was blaOXA-395 (n = 23), followed by blaNDM-1 (n = 20). The blaNDM-1 was frequently recovered from urine samples (n = 11, 55.0%), adult patients (n = 18, 90.0%), and hospital-acquired infections (n = 16/20, 80.0%).

Table 3.

Distribution of Carbapenemases Gene Types in Pseudomonas aeruginosa Isolates by Patient Group, Infection Type, and Source

	Patient group (%)			Infection type (%)					Source (%)
Descriptions	Neonates	Pediatrics	Adults	BSI	UTI	SST	SSI	Others	Hospital	Community
No. of isolates cultured (n = 267)	18	18	231	38	117	31	69	12	127	140
CR phenotype (n = 40)	3	1	36	4	23	4	8	1	32	8
mCIM+ (n = 36)	3	0	33	2	21	4	8	1	29	7
Carbapenemase gene+ (n = 36, 13.5%)	3 (16.7)	0	33 (14.3)	2 (5.2)	21 (17.9)	4 (12.9)	8 (11.6)	1 (8.3)	29 (22.8)	7 (5.0)
Class B metallo-beta-lactamases alone (n = 1)
blaNDM-1 (n = 1)	0	0	1	0	1	0	0	0	1	0
Class D Oxacillinases plus Class A carbapenemases (n = 12)
blaOXA-395/KPC (n = 7)	0	0	7	0	4	1	1	1	7	0
blaOXA-396/SME-1 (n = 4)	0	0	4	0	4	0		0	3	1
blaOXA-488/GES-5 (n = 1)	0	0	1	0	0	0	1	0	0	1
Class D Oxacillinases plus Class B metallo-beta-lactamase (n = 21)
blaOXA-395/NDM-1 (n = 15)	1	0	14	2	6	2	5	0	11	4
blaOXA-396/VIM-5 (n = 2)	0	0	2	0	1	0	1	0	2	0
blaOXA-488/NDM-1 (n = 2)	1	0	1	0	2	0	0	0	2	0
blaOXA-396/OXA-10/VIM-5 (n = 1)	0	0	1	0	1	0	0	0	1	0
blaOXA-395/OXA-10/IMP-15 (n = 1)	0	0	1	0	0	1	0	0	0	1
Class D Oxacillinases plus Class B MBL with ESBLs (n = 2)
blaOXA-488/NDM-1/CTX-M-15 (n = 2)	1	0	1	0	2	0	0	0	2	0
^aGenes conferring weak carbapenem-resistance phenotype (n = 4)
blaOXA-50 (n = 4)	0	1	3	2	2	0	0	0	3	1

^aFour isolates exhibited weak meropenem resistance (inhibition zone size: 16–19 mm). These isolates carried only the blaOXA-50 gene and were not classified as harboring carbapenemases genes. The weak carbapenem-resistant phenotype is likely a result of the synergistic effect of the poorly hydrolyzing OXA-50 enzyme combined with other resistance mechanisms, such as porin loss or the overexpression of efflux pumps.

SST infections, non-surgery related soft skin and tissue infections; SSI, surgical site infections; BSI, bloodstream infections; UTI, urinary tract infections; Others, include lower and upper respiratory tract infection; genital tract infections, central nervous system infections, otitis media, and conjunctivitis; mCIM, modified carbapenem inactivation method; MBL, metallo-β-lactamase; ESBLs, extended spectrum beta-lactamases.

Risk factors for infections with carbapenemase-producing P. aeruginosa

In univariate analysis (Table 4 below), several patient and clinical characteristics were found to be significantly associated with CRPA. Inpatient status (OR = 4.67; 95% CI: 2.03–10.68; p < 0.001), hospitalization within the previous 3 months (OR = 4.00; 95% CI: 1.80–8.89; p < 0.001), prior invasive procedures, and recent antibiotic use (OR = 3.37; 95% CI: 1.61–7.09; p < 0.001) were all linked to increased odds of CRPA infection. Wound infections (OR = 4.64; 95% CI: 1.99–10.80; p < 0.001) and isolates from tertiary care facilities were also more frequently carbapenemase-producing. For P. aeruginosa infections, inpatient status (OR = 4.66; 95% CI: 2.35–9.21; p < 0.001), wound specimens (OR = 5.55; 95% CI: 2.53–12.19; p < 0.001), and specimens classified as “Others” (OR = 9.09; 95% CI: 2.62–31.46; p < 0.001) were significantly associated with multidrug resistance. SSI specimens were less likely to yield MDR isolates (OR = 0.04; 95% CI: 0.01–0.29; p < 0.001), whereas previous hospitalization within 3 months increased the odds of MDR infections (OR = 3.77; 95% CI: 1.95–7.25; p < 0.001).

Table 4.

Univariate Analysis of Factors Associated with Infections by Pseudomonas aeruginosa

Patient characteristics	MDR				CRPA
Patient characteristics	Yes (n = 54)	No (n = 213)	OR (CI)	p Value	Yes (n = 36)	No (n = 231)	OR (CI)	p Value
Gender
Male (n = 114)	27	87	1.32 (0.73–2.39)	0.348	18	96	1.41 (0.65–2.84)	0.340
Female (n = 153)	29	124			18	135
Patients’ age category
Pediatrics (n = 18)	6	12	2.09 (0.75–5.86)	0.218	3	15	1.31 (0.35–4.76)	0.718
Neonates (n = 18)	0	18	—	0.028	1	17	0.36 (0.05–2.79)	0.482
Adults (n = 167)	35	132	1.13 (0.61–2.11)	0.699	21	146	0.82 (0.39–1.67)	0.572
Elderly (n = 64)	13	51	1.01 (0.50–2.03)	1.000	11	53	1.48 (0.68–3.20)	0.319
Mean age in years (±SD)	49 (27)	46 (37)	—	0.503	51 (41)	46 (41)		0.499
Patient status
Inpatients (n = 127)	41	86	4.66 (2.35–9.21)	<0.001	28	99	4.67 (2.03–10.68)	<0.001
Outpatients (n = 140)	13	127			8	132
Study sites
DGH (n = 3)	2	1	8.15 (0.73–91.65)	0.105	0	3	—	1.00
GMH (n = 11)	3	8	1.50 (0.37–5.88)	0.700	0	11	—	0.369
GARH (n = 74)	20	54	1.73 (0.92–3.26)	0.086	7	67	0.59 (0.25–1.41)	0.233
KBTH (n = 15)	3	12	0.98 (0.27–3.62)	1.00	3	12	1.66 (0.44–6.19)	0.701
LEKMA (n = 57)	5	52	0.32 (0.12–0.83)	0.015	3	54	0.29 (0.09–1.01)	0.040
MGH (n = 1)	0	1	—	1.00	0	1	—	1.00
TGH (n = 24)	6	18	1.35 (0.51–3.59)	0.593	3	21	0.91 (0.26–3.22)	1.00
UGMC (n = 82)	15	67	0.83 (0.43–1.62)	0.603	20	62	3.41 (1.66–6.99)	<0.001
Type of hospital
Tertiary (n = 171)	38	133	1.43 (0.75–2.73)	0.277	30	141	3.19 (1.28–7.92)	0.001
Secondary (n = 81)	11	70	0.52 (0.25–1.08)	0.075	6	75	0.42 (0.17–1.04)	0.055
Primary (n = 15)	5	10	2.07 (0.68–6.34)	0.318	0	15	—	0.143
Specimen types
SSI (n = 69)	1	68	0.04 (0.01–0.29)	<0.001	0	69	—	<0.001
Wound (n = 31)	16	15	5.55 (2.53–12.19)	<0.001	11	20	4.64 (1.99–10.80)	<0.001
Blood (n = 38)	6	32	0.71 (0.28–1.78)	0.462	4	34	0.72 (0.24–2.18)	0.752
Urine (n = 117)	23	97	0.89 (0.49–1.62)	0.699	18	99	1.33 (0.66–2.69)	0.420
Others (n = 12)	8	4	9.09 (2.62–31.46)	<0.001	3	9	2.24 (0.58–8.71)	0.379
Comorbidity
Yes (n = 72)	24	48	2.75 (1.47–5.14)	0.001	13	59	1.64 (0.78–3.46)	0.183
No (n = 195)	30	165			23	172
Invasive procedures in past 3 months
Yes (n = 110)	40	70	5.83 (2.97–11.43)	<0.00	24	86	3.37(1.61–7.09)	<0.001
No (n = 157)	14	143			12	145
Recent hospitalization in past 3 months
Yes (n = 126)	39	87	3.77 (1.95–7.25)	<0.001	27	99	4.0 (1.80–8.89)	<0.001
No (n = 141)	15	126			9	132
Surgery in past year
Yes (n = 85)	16	69	0.87 (0.46–1.68)	0.698	11	74	0.934 (0.44–1.99)	0.862
No (n = 182)	38	144			25	157
Recent antibiotic use in past 3 months
Yes (n = 69)	14	55	1.01 (0.51–1.99)	1.00	4	65	0.32 (0.11–0.94)	0.029
No (n = 198)	40	158			32	166

SD, standard deviation; y, years; d, days; n, number; MDR, multidrug resistance; cCRPA, carbapenemase-producing CRPA; CRPA, carbapenem-resistant Pseudomonas aeruginosa; DGH, Dodowa Government Hospital; GMH, Ga-North Municipal hospital; GARH, Greater Accra Regional Hospital; KBTH, Korle-Bu Teaching Hospital; LEKMA, Ledzekoku Municipal Assembly Hospital; MGH, Maamobi Government Hospital; TGH, Tema General Hospital; UGMC, University of Ghana Medical Hospital; OR, odds ratio; CI, confidence interval; SSI, surgical site infections; Others, include lower and upper respiratory tract Infection; genital tract infections, central nervous system infections, otitis media, and conjunctivitis.

In the adjusted multivariable logistic regression model for CRPA (Table 5 below), inpatient status remained independently associated with a nearly threefold increase in the odds of infection (aOR = 3.32; 95% CI: 1.98–4.09; p = 0.001). Isolates from tertiary hospitals had nearly twice the odds of being carbapenemase-producing compared with those from secondary or primary care facilities (aOR = 1.87; 95% CI: 1.10–2.91; p = 0.023). A history of invasive procedures within the preceding 3 months was also a significant predictor (aOR = 2.03; 95% CI: 1.14–3.21; p = 0.020). For infections with MDR isolates, inpatient status was likewise an independent risk factor, with more than twice the odds of infection compared with outpatients (aOR = 2.55; 95% CI: 1.78–3.96; p = 0.002). Isolates from wound specimens were three times more likely to be MDR than those from other specimen types (aOR = 3.01; 95% CI: 1.43–4.47; p = 0.001). Previous invasive procedures within the past 3 months also significantly increased the odds of MDR infection (aOR = 1.54; 95% CI: 1.09–2.34; p = 0.011).

Table 5.

Multivariable Logistic Regression Analysis of Factors Associated with Infections by Pseudomonas aeruginosa

Variables	Level	aOR	95%CI	p Value
MDR
Inpatient	Yes/No	2.55	1.78–3.96	0.002
Wound	Yes/No	3.01	1.43–4.47	0.001
Invasive procedures	Yes/No	1.54	1.09–2.34	0.011
CRPA
Inpatient	Yes/No	3.32	1.98–4.09	0.001
Tertiary hospital	Yes/No	1.87	1.1–2.91	0.023
Invasive procedures	Yes/No	2.03	0.14–0.21	0.021

Only variables with p value <0.05 are shown.

MDR, multidrug-resistant; CRPA, carbapenemase-producing CRPA; CRPA, carbapenem-resistant Pseudomonas aeruginosa; aOR, adjusted odds ratio; CI, confidence interval.

Discussion

P. aeruginosa infections are a growing challenge in hospitals worldwide, especially among severely ill patients, due to widespread multidrug resistance.¹⁹ Region-specific multicenter epidemiological surveys on MDR and carbapenemase genes in P. aeruginosa remain scarce, and the available data from resource-limited settings, such as sub-Saharan Africa, are limited and fragmented.²⁰ This study examined the multicenter prevalence of P. aeruginosa, the occurrence of MDR and associated carbapenem resistance genes, and the risk factors for carbapenem-resistant and MDR infections in the Greater Accra Region, Ghana.

In this study, we show that across the Greater Accra Region of Ghana, among all acute-care government hospitals, P. aeruginosa accounted for 2.1% (95% CI: 1.94–2.46) of all laboratory-confirmed bacterial infections, with prevalence ranging from 0.83% in lower respiratory tract infections to 33.3% in genitourinary tract infections, the latter likely inflated by very small specimen numbers. While comparable regional studies are scarce, available data indicate notable variation in prevalence across Ghana, largely due to differences in study design and specimen focus. Most existing reports come from single-center studies, rely on random or otherwise unsystematic rather than prospective, isolate sampling, and are often limited to specific patient groups or specimen types, making it difficult to reliably assess the overall disease burden. For example, Newman et al. (2006) reported P. aeruginosa prevalence of 6.5% among clinical isolates from Korle-Bu Teaching Hospital.²¹ Codjoe and Donkor (2017) described P. aeruginosa as a key MDR pathogen in Ghana, with prevalence estimates ranging from 4.5% to 8.0% depending on the specimen type.²¹ Similarly, Sampene-Donkor et al. (2023) documented P. aeruginosa in 7.2% of isolates from bloodstream infections in a tertiary-care setting.²² The most comparable findings to ours come from Odoi et al. (2021), who found that P. aeruginosa represented 2.06% (95% CI: 0.64–7.18) of all bacterial isolates across diverse specimens in Ghana using a diagnostic framework similar to ours.²³

Our report highlights key resistance patterns in P. aeruginosa that warrant attention. The overall MAR index of 0.12 ± 0.24 suggests moderate antibiotic pressure across the study population, but values >0.2 in SSI indicate localized hotspots of selective pressure within specific infection syndromes that may be driving resistance.²⁴ A Stark difference in susceptibility was also seen between non-MDR and MDR isolates. While non-MDR strains remained >90% susceptible to most agents, susceptibility among MDR isolates dropped to 22–74%, with only 33.3% for MEM and 22.2% for CIP. This observation implies that if we can reduce the emergence of MDRs, then the utility of a broad repertoire of antibiotics, to which pathogenic organisms remain susceptible, may be preserved.

amikacin was the most reliable agent, with >90% activity overall and 100% susceptibility in bloodstream and surgical site isolates, surpassing meropenem, a drug often reserved as a last resort. This finding likely reflects the restricted use of aminoglycosides compared to carbapenems in Ghana, where extensive reliance on meropenem for empirical therapy may be accelerating resistance. Carbapenem resistance in P. aeruginosa is multifactorial, involving both chromosomal and plasmid-mediated mechanisms. Chromosomal-based resistance is typically disseminated through vertical gene transfer and includes loss of the OprD porin, overexpression of efflux pumps, and hyperproduction of AmpC β-lactamase. These alterations collectively reduce drug penetration and limit carbapenem access to its targets, such as penicillin-binding proteins. However, analysis of our isolate collection highlighted plasmid-borne carbapenemase production as the predominant resistance mechanism, accounting for 90% (n = 36/40) of the observed carbapenem-resistant phenotype. Unlike chromosomal mechanisms, plasmid-mediated resistance spreads rapidly via horizontal gene transfer, which appears to be the principal driver of carbapenem resistance dissemination in our local context.

The blaNDM-1 was the most frequent carbapenemase gene in our isolates, consistent with Ghanaian reports identifying NDM-type enzymes, particularly blaNDM-1, as the dominant carbapenemases among non-fermenters.²⁵ Nearly all P. aeruginosa in our study carried chromosomally encoded blaOXA-50 family variants (OXA-395, OXA-396, and OXA-488), which exhibit weak carbapenem-hydrolyzing activity and are not clinically significant carbapenemases on their own. In our collection, blaOXA-50 variants consistently co-occurred with acquired carbapenemases, including MBLs (NDM-1, VIM-5, IMP-15) and Class A enzymes (GES-2, GES-5), suggesting that the carbapenemase phenotype in our isolates is primarily driven by these acquired enzymes.²⁵ It is noteworthy that, because blaOXA-50 variants are ubiquitous in our Ghanaian isolates, studies of carbapenemase production should interpret phenotypic results cautiously to avoid false positives from blaOXA-50 derivatives and structural cell modifications.

In our multivariable analysis, inpatient status and invasive procedures within the prior 3 months independently increased the odds of both CRPA and MDR P. aeruginosa infection. Hospitalization increases exposure to antibiotic pressure and contaminated clinical environments, whereas procedures and device use create portals for colonization and biofilm formation—conditions repeatedly linked to CRPA acquisition in meta-analyses and cohort studies.²⁶ Notably, prior carbapenem exposure and the presence of indwelling devices are among the strongest risk factors reported internationally, alongside ICU stay and recent broad-spectrum antibiotics.^27–29 From a clinical and public health perspective, the shared risk factors for CRPA and MDR P. aeruginosa point to common preventive priorities. These include stricter carbapenem stewardship, rigorous implementation of infection-prevention (IPC) bundles, and, where feasible, unit-level surveillance (e.g., in ICUs) to identify transmission points and assess intervention impact over time.³⁰

This study has several limitations. The sample size of 267 isolates from a few hospital sites may not represent the full diversity of P. aeruginosa strains and infection types, a common limitation noted in similar multicenter studies with a regional focus. Our focus on hospital-based isolates means the results may not apply to community settings. Our findings may have limited generalizability to other geographical areas. Due to resource constraints, the use of a limited panel of tests may have missed uncommon resistance mechanisms. While we adjusted for several key clinical factors, detailed data on prior antibiotic exposure and specific comorbidities were not collected. This lack of granular data means that residual confounding cannot be entirely ruled out. Although WGS was performed, analyses were limited to carbapenemase genes. Broader resistome and phylogenomic analyses were beyond the scope of this study and will be reported separately. Despite inherent limitations, the survey offers multicenter evidence on the occurrence of P. aeruginosa infections across varied clinical specimens and hospital settings. Our findings highlight the urgent need for judicious antibiotic stewardship to minimize carbapenem use and underscore the importance of rigorous device care and IPC practices to limit the spread of carbapenem resistance in P. aeruginosa.

Authors’ Contributions

Conceptualization: N.O.-N., E.S.-D., and F.D.; Methodology: F.D., E.S.-D., and N.O.-N.; Software: F.D. and N.O.-N.: Validation: N.O.-N., E.S.-D., A.D., J.O., B.E., and F.D.; Formal analysis: F.D. and N.O.-N.; Investigation: F.D.; Resources: F.D., M.B.-A., and A.D.; Data curation: F.D. and M.B.-A.; Writing—original draft preparation: F.D.; Writing—review and editing: F.D., E.S.-D., and N.O.-N.; Visualization: N.O.-N., E.S.-D., J.O., and B.E.; Supervision: N.O.-N., E.S.-D., J.O., and B.E.; Project administration: N.O.-N. and B.E.; Funding acquisition: F.D., A.D., and B.E.; and investigation, resources, review, and editing: M.-M.O., W.B., and M.B.-A. All authors have read and agreed to the published version of the article.

Footnotes

Informed Consent Statement

Patients’ interviewees provided written consent before enrolment into this study. On receipt of any isolate or patients’ data, we re-identified all accompanying data to ensure complete obscurity from laboratory archives. Arbitrary numbers were allotted to all isolates assigned to the study. This work received ethical clearance from the Institutional Review Board of Ghana Health Service (Ethics identification number: GHS-ERC:009/11/22).

Ethical Considerations

A cross-sectional study was conducted between November 2022 and December 2023 and following ethical approval from the Institutional Review Board (IRB) or Ethics Committee of Ghana Health Service (Ethics identification number: GHS-ERC:009/11/22), Scientific and Technical Institutional Review Board of the Korle-Bu Teaching Hospital (Ethics identification number: KBTH-STC-IRB/000193/2022), and the University of Ghana Medical Center (Ethics identification number: UGMC-IRB/MSRC/032/2023); each study participant was enrolled in the study once informed consent was obtained.

Data Availability

The data analyzed can be made available by the corresponding authors on request, but all relevant documents for the peer-review process are attached as supplementary files.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This is research received no external funding.

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