Introduction

Pseudomonas aeruginosa is a highly flexible Gram-negative bacterium that is found virtually everywhere, from nature to the delicate environment of healthcare settings. Its ability to thrive in different environments and survive in nutrient-poor conditions demonstrates why it is regarded as an alarming pathogen1,2. This flexibility is shown in how and where it causes infections targeted at the community and within the healthcare settings, where it contributes to infections acquired from the hospital3,4. Its increasing concern is due to its infliction of grave infections like wounds, urinary tract infections (UTI), bloodstream infections (BSI), and ventilator-associated pneumonia (VAP), where it ranks among the leading causes of mortality, especially in critically ill patients5.

However, the issues presented by P. aeruginosa are not limited to its virulence, but also the ever-growing problem of antibiotic resistance. This bacterium has an alarming propensity to utilize and break down diverse antibiotic treatments, which makes most of the therapies futile6,7,8,9. This becomes ever more pressing when a substantial number of isolates show resistance towards carbapenems and several other classes of antimicrobials10,11. As the world faces the burden of multi-drug resistant (MDR) strains of P. aeruginosa, the impact of these infections on global health remains devastating because they have been labelled and categorized as a “critical” pathogen12. The Centre for Disease Control and Prevention (CDC) has identified this burden of MDR-Pseudomonas infections to the healthcare system and patients in particular as a significant concern for a very long time13,14. Indeed, the differences in the patient outcomes between those infected and non-infected with MDR-Pseudomonas respiratory infections tell a compelling tale of the necessity of new treatment techniques to be developed14.

Effective therapy of MDR-Pseudomonas infections depends on determining risk factors. Prior Pseudomonas infection, extended hospitalization or intensive care unit stay, chronic obstructive pulmonary disease (COPD), and the use of invasive medical equipment are all important factors that promote susceptibility15,16. The difficulty is made worse by Pseudomonas’ propensity to produce nosocomial infections by forming biofilms on hospital equipment17,18. MDR strains are particularly dangerous for intensive care unit (ICU) patients, with frightening odds of coming across them19,20.

P. aeruginosa possesses a wide array of virulence factors that contribute to its pathogenicity, persistence, and immune evasion. Among these, exotoxins such as ExoS, ExoT, ExoU, and ExoY, secreted via the Type III secretion system, play a crucial role in disrupting host cell functions, promoting cytotoxicity, and dampening immune responses. ExoU, in particular, is associated with severe tissue damage and poor clinical outcomes21.

Proteolytic enzymes like elastase (LasB) degrade host proteins including elastin, collagen, immunoglobulins, and complement components, aiding in tissue invasion and immune suppression21. Phospholipase C contributes to membrane disruption and haemolysis, enhancing inflammation and bacterial spread. The redox-active pigment pyocyanin generates reactive oxygen species, leading to oxidative damage and interference with host respiratory epithelial function22.

The formation of biofilms, primarily mediated by alginate production, enables P. aeruginosa to persist in chronic infections, especially in cystic fibrosis patients. Biofilms confer protection against antibiotics and immune clearance23. Structural components like flagella and type IV pili are essential for motility, adhesion, and the initial stages of biofilm development. Furthermore, quorum sensing systems such as Las, Rhl, and PQS regulate the expression of many virulence genes in response to cell density, facilitating coordinated behaviours such as biofilm maturation and toxin production23,24.

Recent studies continue to highlight the interplay between these virulence determinants and antibiotic resistance, making P. aeruginosa a challenging pathogen in clinical settings21,24.

Our study aims to investigate the antibiotic resistance landscape of Pseudomonas infections at a tertiary hospital in a developing country in light of these difficulties. Our goal is to empower treatment decision-making by giving doctors comprehensive resistance profiles, which will ultimately lower Pseudomonas-associated death rates. To improve targeted infection control measures and advance worldwide efforts against antimicrobial resistance, our work also aims to further our understanding of the etiological causes underlying antibiotic resistance of Pseudomonas. Given this urgent public health concern, we hope that our endeavour will support the group’s quest for knowledge, creativity, and better patient outcomes.

Materials and methods

Study design and setting

This retrospective observational study analysed data from January 2019 to December 2020 at King Khalid Hospital, Saudi Arabia. It explored the epidemiology of Pseudomonas infections, patient clinical characteristics, and antibiotic susceptibility patterns of isolated strains during the study period.

Ethical consideration

The research was conducted following the Declaration of Helsinki. After obtaining approval from the Ethics Committee, Research Deanship, University of Hail, the study was performed, patients were informed about the research, and informed consent was taken from them.

Study population and data collection

The study included both patients who were admitted with P. aeruginosa-positive cultures (i.e., community-acquired or present on admission) and those who developed P. aeruginosa infections during hospitalization (i.e., hospital-acquired). All inpatients of any age with confirmed P. aeruginosa growth in various hospital departments, including the emergency department, vascular surgery, critical care, paediatrics, cardiology, surgery, ICU, and general medicine, were included in the study. P. aeruginosa was identified through both active surveillance cultures and clinical diagnostic samples. Outpatient samples were excluded due to incomplete clinical information. For patients with growth from multiple anatomical sites, only the initial non-duplicate isolate from each site was analyzed, while noting all additional sites from which the organism was isolated. Data from a total of 817 patients were collected, analyzed, and assessed during the study period.

The hospital’s electronic medical records and microbiological system were the key sources of patient data, including demographic and clinical information. Important details such as age, gender, comorbidities, previous hospitalizations, and antibiotic history were recorded. Furthermore, specifics on the department of culture collection, the presence of intrusive equipment, the period of the commencement of bacterial growth, and the locations of Pseudomonas isolation were all carefully recorded. The study also carefully examined antibiotic susceptibility patterns, treatment approaches, and Pseudomonas species.

Identification and antimicrobial testing of Pseudomonas aeruginosa

For comprehensive identification and sensitivity assessment, isolates underwent confirmation as Pseudomonas spp. utilizing the BD Phoenix automated microbiological system. Antimicrobial sensitivity testing (AST) was conducted for a panel of antibiotics, including ceftazidime, cefepime, ciprofloxacin, piperacillin-tazobactam, amikacin, imipenem, meropenem, colistin, levofloxacin, and aztreonam. Results were interpreted and reported per the CLSI, 2021 guidelines, classifying isolates as susceptible (S), intermediate (I), or resistant (R)25. Classification of P. aeruginosa isolates based on their antibiotic resistance profile adhered to the International Consensus standards.

Phenotypic characterization of virulence factors

  1. 1.

    Hemolysin production

Hemolysin activity was measured by streaking isolates on 5% sheep blood agar plates and then incubating them for 24 h at 37 °C. Red blood cell lysis was suggested by the creation of hemolysin, which was indicated by the development of a translucent halo around the bacterial growth26.

  1. 2.

    Alkaline protease production

In order to test for protease activity, isolates were streaked on skimmed milk agar and incubated for 24 h at 37 °C. The development of a clear halo surrounding the bacterial colonies demonstrated proteolytic activity and validated the production of alkaline protease27.

  1. 3.

    Phospholipase C production

Egg yolk agar plates were used to cultivate clinical isolates for a whole day at 37 °C. The existence of a clear, distinct zone surrounding the bacterial growth served as the basis for the detection of phospholipase C activity28.

  1. 4.

    Biofilm formation

The biofilm production assessment involved inoculating a loopful of the test organisms from overnight cultures into 10 mL of trypticase soy broth (TSB) supplemented with 1% glucose. The inoculated cultures were incubated at 37 °C for 24 h under static conditions. Following incubation, the cultures were diluted 1:100 in fresh TSB medium, and 200 µL of the diluted suspension was dispensed into the wells of a 96-well flat-bottom tissue culture plate. Sterile TSB was used as a blank control, while reference strains underwent the same protocol under identical incubation conditions. After a 24-hour incubation at 37 °C, non-adherent cells and free-floating bacteria were removed by gently tapping the plates. The wells were then washed four times with phosphate-buffered saline (PBS, pH 7.2) to remove any residual debris. The adherent biofilms were fixed using 2% sodium acetate, stained with 0.1% crystal violet, and washed thoroughly with deionized water to eliminate excess stains. The plates were air-dried before further analysis29,30.

To determine the extent of biofilm formation, the optical density (OD) of the stained wells was measured at 570 nm using a micro-ELISA auto-reader. Background noise was accounted for by subtracting the OD values of sterile negative controls from those of the test wells. Each experiment was performed in triplicate, ensuring reproducibility and accuracy. The interpretation of biofilm production followed the criteria outlined by Stepanovic et al., categorizing biofilm-forming capabilities based on OD values31 as shown in Table 1.

Table 1 Interpretation and classification of biofilm production based on optical density (OD) values of the tissue culture plate method.
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Molecular detection of virulence factor genes

To create DNA templates for the procedure, four bacterial colonies from each isolate were suspended in 200 µL of sterile water. The suspension was heated for 30 min at 95 °C, and then it was rapidly frozen for another 30 min at −20 °C to undergo thermal lysis. For further molecular analysis, the samples were thawed and centrifuged for 10 min at 14,000 rpm, and the supernatant was removed and stored at −20 °C32.

The presence of certain virulence genes (algD, lasB, toxA, plcH, plcN, and exoS) was assessed using the polymerase chain reaction (PCR). Previous studies have shown that the test employed already validated primers (ThermoScientific, USA)33 (Table 2).

Table 2 Oligonucleotide primers sequence and amplicon size34.
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PCR findings were examined using Tris-Acetate-EDTA (TAE) buffer (40 mM Tris, 20 mM acetic acid, and 1 mM EDTA, pH 8.5) and 1% agarose gel electrophoresis with a voltage of 100–120 V. We used a UV transilluminator (Entela, USA) to view the gels at 254 nm. The amplified DNA fragments were compared to a DNA ladder loaded with the samples to determine their molecular sizes. This strategy ensured that the target virulence genes were identified precisely.

Statistical analysis

Data were entered into a standardized Microsoft Excel 2019 and analyzed by SPSS software version 26.0 (IBM SPSS, Armonk, NY, USA) was used to code, classify, and enter the data. GraphPad Prism (v9.4.1; GraphPad Software, San Diego, CA, USA) was used to create the visuals. For categorical variables, descriptive statistics were performed using frequencies and percentages, and for continuous variables, medians and interquartile ranges (IQRs). P-values < 0.05 were set as the significance threshold.

Result

A total of 817 patients met the inclusion criteria that were specified for this study. Of this cohort, 296 (36.2%) were female and 521 (63.8%) were male. Regarding comorbidities, 121 (14.8%) patients had cancer, 439 (53.7%) had cardiovascular disease, 297 (36.3%) had diabetes mellitus, and 28 (15.1%) had renal abnormalities. Of the population, 39 (4.7%), were receiving dialysis, as shown in Table 3. Approximately 223 (27.3%) were hospitalised for different infectious causes. Moreover, the primary reason for admission for 24 (3%) patients was COVID-19 infection. In terms of medical devices implanted, 336 (41.1%) had a Foley catheter placed before Pseudomonas was isolated, 366 (44.8%) had a central line, and 187 (22.9%) were intubated for more than 48 h before Pseudomonas grew on culture. Additional details are provided in Table 3.

The data illustrated in Fig. 1 provides an overview of how the 817 patients, all demonstrating Pseudomonas aeruginosa growth, were dispersed throughout different hospital wards. Noteworthy is the prominence of the surgery department, with 211 patients (representing 25.8% of the total), closely followed by the medicine department, with 182 patients (22.3%). Subsequently, the surgical intensive care unit accommodated 103 (12.6%), while the paediatric intensive care unit housed 102 (12.5%) patients. Of the 817 isolates of Pseudomonas, 579 (70.8%) were already present upon admission, defined as a positive culture obtained within the first three days of admission. Additionally, 87 (10.6%) patients had the pathogen isolated from multiple body sites, as depicted in Fig. 2.

Table 3 Demographics and clinical profile of patients with Pseudomonas aeruginosa.
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Fig. 1
figure 1

Wards where cultures that showed Pseudomonas aeruginosa growth were obtained.

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Fig. 2
figure 2

Infectious profile for the Pseudomonas aeruginosa during study design.

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A total of 1,619 samples were processed, comprising 920 (56.8%) clinical specimens and 699 (43.2%) surveillance samples. Among the clinical specimens, sputum constituted the most frequently isolated source with 279 samples (30.3%), followed by wound swabs (n = 197; 21.4%), urine (n = 137; 14.9%), pus (n = 99; 10.8%), and blood (n = 93; 10.1%). Less frequently represented specimens included central line venous catheter (CVC) tips (n = 53; 5.8%), body fluids (n = 41; 4.5%), and miscellaneous sources (n = 21; 2.3%), which included high vaginal swabs, ulcer biopsies, throat swabs, and ear swabs.

Among the 699 surveillance samples, rectal swabs constituted the majority (n = 273; 39.1%), followed by nasal swabs (n = 192; 27.5%), axillary swabs (n = 139; 19.9%), and groin swabs (n = 95; 13.6%). For detailed data, please see Table 4.

Table 4 Body sites from which clinical samples and active surveillance testing cultures of P. aeruginosa were isolated.
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Out of 817 P. aeruginosa isolates tested, the highest sensitivity was observed with colistin, with 690 (84.5%) isolates showing susceptibility. This was followed by amikacin, with 678 (83.0%) isolates, and cefepime, with 598 (73.2%) isolates, demonstrating sensitivity.

Among the carbapenems, meropenem and imipenem exhibited sensitivity in 534 (65.4%) and 497 (60.8%) isolates, respectively. Piperacillin-tazobactam also showed moderate effectiveness, with 575 (70.4%) isolates being sensitive.

In the fluoroquinolone class, ciprofloxacin and levofloxacin showed sensitivity in 519 (63.5%) and 500 (61.2%) isolates, respectively. Aztreonam showed sensitivity in 419 (51.3%) isolates, while ceftazidime had the lowest among the tested agents, with 283 (34.6%) isolates demonstrating susceptibility.

These results indicate that colistin, amikacin, and cefepime remain the most effective agents against P. aeruginosa in this cohort, please shown in Fig. 3.

Fig. 3
figure 3

Antimicrobial resistance pattern of the isolated Pseudomonas aeruginosa.

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Of the 817 patients enrolled in the study, 596 (73%) individuals were identified as having an MDR isolate. Interestingly, the presence of MDR was not found to have any statistically significant correlation with gender or the presence of various comorbidities among the patients. However, it was notably associated with certain medical interventions, particularly tracheal intubation. Specifically, among MDR patients, 156 (26.2%) individuals had a history of tracheal intubation either during the current admission or before the culture collection. In contrast, among non-MDR patients, only 31 (14%) individuals had undergone tracheal intubation. This discrepancy was statistically significant (p = 0.0003, OR 2.17, CI 1.43–3.31), indicating a clear link between tracheal intubation and the presence of MDR isolates. Moreover, a central venous catheter was also found to be significantly associated with MDR isolates (p = 0.032, OR 1.43, CI 1.04–1.96). Table 5 of the study provides further details and specific statistical values.

When considering risk factors associated with the onset of P. aeruginosa acquisition, whether upon admission or during the hospital stay, diabetes mellitus emerged as statistically significant (p = 0.0457, OR 1.37, CI 1.01–1.87) between the two groups. Additionally, the presence of invasive medical devices such as tracheal intubation (OR 27.65 CI 14.38–53.15), central venous catheter (OR 4.75, CI 3.42–6.60), and indwelling catheter (OR 4.83, CI 3.49–6.69), along with undergoing dialysis, were all significantly linked to hospital-onset cases of Pseudomonas (p < 0.001). Furthermore, it’s worth noting that MDR P. aeruginosa was predominantly associated with hospital-onset cases (p < 0.001, OR 2.17 CI 1.48–3.17). For a more comprehensive understanding, please refer to Table 6 for detailed insights.

Figure 4 demonstrates a significant association between phospholipase C production in non-MDR isolates and biofilm formation in MDR isolates, with a p-value of < 0.001. In contrast, other virulence factors, such as haemolysin and alkaline protease production, do not significantly correlate with multidrug resistance (p = 0.084 and p = 0.673), respectively.

Figure 5 illustrates that the toxA and plcH genes were significantly more prevalent in non-MDR isolates than in MDR isolates (p < 0.001). In contrast, other virulence genes, including algD, lasB, exoS, and plcN, did not exhibit statistically significant differences between MDR and non-MDR isolates (p > 0.05).

Among the tested P. aeruginosa isolates, hemolysin production was significantly associated with the presence of five virulence genes: algD, toxA, exoS, plcH, and plcN, except for lasB. Alkaline protease production showed a significant association with lasB, exoS, plcH, and plcN. In contrast, no significant association was observed for phospholipase C production. Notably, biofilm production demonstrated a significant association exclusively with the plcN gene (Fig. 6).

Table 5 Relation between risk factors and multidrug resistance.
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Table 6 Relation between risk factors and Pseudomonas aeruginosa acquisition onset.
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Fig. 4
figure 4

Distribution of virulence factors among MDR and Non-MDR P. aeruginosa.

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Fig. 5
figure 5

Distribution of virulence genes among MDR and Non-MDR isolates.

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Fig. 6
figure 6

Association between the phenotypic detection of virulence factors and the presence of virulence genes among the P. aeruginosa clinical isolates. The p-values indicate significance where p < 0.005.

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Discussion

The rise of P. aeruginosa variants that are resistant to drugs poses a serious threat to global healthcare systems35. Globally, there has been a notable surge in the prevalence of MDR P. aeruginosa, with reports indicating its involvement in approximately 30% of documented P. aeruginosa infections in certain nations. In Saudi Arabia, P. aeruginosa has emerged as a progressively common nosocomial pathogen, contributing to approximately 11% of all hospital-acquired infections (HAIs)36. Its ability to cause serious, potentially fatal infections in people is further worsened by the increasing antimicrobial resistance (AMR) that the world is witnessing. The increasing resistance profile of P. aeruginosa poses a significant threat to public health, requiring the development of comprehensive and detailed control strategies37.

The study involved 817 patients who tested positive for P. aeruginosa, among whom 521 (63.8%) were male and 296 (36.2%) were female. Interestingly, our findings are consistent with a previous study conducted at a tertiary care facility, which also found that men were more likely to have Pseudomonas infections, with percentages of 51.5%, 54%, and 55.6%, respectively36,38,39. Notably, Pseudomonas was found in multiple sites within the same patient in 87 (10.6%) of the clinical samples analysed. Among our study participants, P. aeruginosa was predominantly isolated from sputum samples, accounting for 279 (30.3%), followed by wound swabs with 197 (21.4%), and urine samples with 137 (14.9%). These findings are consistent with previous studies conducted in Makkah, Saudi Arabia, which also indicated a high prevalence of Pseudomonas in sputum samples (38%)40. However, it is worth noting that, contrary to our results, several other studies have reported urine as the most common sample for detecting Pseudomonas38,41,42. These variations may have resulted from various contributing factors, including the study time, patient population and size, ethnicity and geographic location.

Comorbidities may increase the susceptibility of patients to Pseudomonas acquisition. Our investigation revealed that among patients with Pseudomonas isolates, 439 (53.7%) had cardiovascular disease. Additionally, diabetes mellitus, renal diseases, and malignancy were prevalent in 439 (53.7%), 143 (17.5%), and 121 (14.8%) of the population, respectively. Similarly, different studies conducted in Saudi Arabia and Turkey identified various chronic illnesses associated with an increased risk of Pseudomonas infections10,41,43.

Viral respiratory tract infections are frequently complicated by secondary bacterial infections, which greatly worsen symptoms and raise fatality rates. Westblade et al. discovered P. aeruginosa as a bacterial respiratory pathogen in 8% of co-infections in patients with COVID-1944. This result is consistent with the comparatively low prevalence of Pseudomonas (3%), which we found in our analysis of COVID-19 patients. These results, therefore, corroborate the suggestion that routine empirical treatment for P. aeruginosa may not be required unless the patient has a history of infection with this organism or has a persistent lung disease, like bronchiectasis, that is linked to P. aeruginosa pneumonia45.

P. aeruginosa, an opportunistic pathogen, predominantly targets individuals who have been hospitalized for prolonged periods and have undergone various medical procedures37. Additionally, any disruptions in the body’s natural defences, such as surgical incisions, the insertion of urinary or vascular catheters, and endotracheal intubation, can weaken the body’s barriers, thereby increasing susceptibility to P. aeruginosa infections. These factors collectively elevate the risk of acquiring and developing P. aeruginosa infections41. Our research revealed that 366 (44.8%) of the patients had a central venous catheter, 336 (41.1%) had an indwelling urinary catheter, 187 (22.9%) were intubated, and 39 (4.7%) underwent dialysis. Similar observations have been reported in various studies conducted in Middle Eastern countries41,43.

In our study, Pseudomonas aeruginosa was most commonly isolated from the patients admitted to the surgery wards, with a prevalence of (25.8%), a similar trend was seen in various studies globally (Anupurba et al., 32%; Oguntibegri and Nwobu et al., 33.3%; Hani et al., 27.8%; Stephen et al., 18.8%)46,47,48. Following surgery wards, ICUs accounted for (23.5%) of Pseudomonas infections, encompassing medical, surgical, and paediatric units. The location of patients during hospitalization played an important role in our observations, with (23.5%) of ICU admissions experiencing Pseudomonas infections. ICUs are recognized as high-risk settings, predominantly housing immunocompromised patients requiring specialized interventions, diligent care, and continuous monitoring, along with frequent invasive procedures and instrumentation, which collectively elevate the risk of opportunistic infections. Our findings are complemented by an Indian study reporting the ICU department as the second-highest contributor to Pseudomonas isolates42,49,50.

In the present study, we found that P. aeruginosa exhibited a concerning level of resistance to several antibiotics. Aztreonam showed the highest resistance rate, affecting 56.2% of isolates, followed closely by ceftazidime (48.7%), Cefepime (44.5%), imipenem (39.2%), levofloxacin (38.8%), and ciprofloxacin (36.5%). However, amidst this resistance trend, there were notable instances of sensitivity to certain antibiotics. Colistin emerged as the most effective option, with a sensitivity rate of (84.5%), followed by amikacin (83%), cefepime (73.2%), piperacillin/tazobactam (70.4%), meropenem (65.4%), ciprofloxacin (63.5%), levofloxacin (61.2%), and imipenem (60.8%). These findings are consistent with studies conducted by Hafiz et al. and Shbaita et al. at King Fahad Medical City and An-Najah National University Hospital, Saudi Arabia, which reported similar antibiotic susceptibility profiles10,41. Conversely, a study from Palestine demonstrated differing susceptibility patterns, with lower sensitivity to imipenem (51%) and meropenem (54.9%), but higher sensitivity to ciprofloxacin (78.4%)51.

Cefepime is a fourth-generation cephalosporin that continues to be one of the few medications that consistently works against P. aeruginosa. Our analysis revealed significantly higher resistance rates to cefepime of (44.5%) values that were higher than those reported in a few previous Saudi Arabian studies40,52. The origin of this resistance seems closely related to the use of cephalosporins as empirical remedies, which may have encouraged the possible emergence of resistance, which may have been aided by the acquisition of plasmids containing β-lactamases. Furthermore, our analysis identified resistance standards of 39.1% for imipenem and 36% for ciprofloxacin. P. aeruginosa tends to rapidly develop resistance to certain treatment drugs, which has significant implications for both clinical effectiveness and financial constraints. Globally, about 30% of organisms show significant levels of ciprofloxacin resistance, while between 13% and 20% show similar levels of imipenem resistance40. Interestingly, our research revealed a high colistin resistance ratio of 15.5%, which is significantly higher than the lower rates reported elsewhere. These variations could be complex, impacted by differences in the number of isolates examined, the length of observation, and setting-specific preferences for the use of antibiotics and the ensuing selected pressures.

While colistin resistance is rare, it is more common in areas like the Mediterranean and Southeast Asia, where South Korea and Singapore are examples of two such countries53. However, because of its nephrotoxic tendency, colistin is only used as a last-resort antibiotic to treat P. aeruginosa strains that are resistant to multiple drugs. When it comes to treating pseudomonal infections, amikacin is the aminoglycoside that is used the most frequently. Even though resistance to aminoglycosides with antipseudomonal action is common, our results show an encouraging 83% susceptibility rate to amikacin, which is in line with information from previous studies36,40. This highlights the continued effectiveness of amikacin as a reliable empirical treatment option for Pseudomonas infections.

In addition, our investigation clarifies a comparatively low resistance rate of 29% to piperacillin-tazobactam, which deviates from greater rates reported in similar Saudi-based investigations40. Again, these differences are probably complex, based on differences in the entire set of isolates examined, the length of the investigation, and the unique preferences and guidelines for antibiotic use and the resulting selection pressures.

P. aeruginosa is considered MDR when it shows resistance to at least one antipseudomonal class. MDR Pseudomonas isolates made up about 596 (73%) of the isolates in our investigation, which represents a larger percentage in comparison to other studies conducted globally. A study carried out in the Middle East and North Africa region revealed that the prevalence of MDR P. aeruginosa was 47.6%54, 58.4%41, 55%55, 47.8% in Africa, and 56%55 in Palestine. The consistent global and Saudi Arabian observations of an increase in MDR incidence over time highlight the persistent evolution of resistance mechanisms in P. aeruginosa populations. The unique genomic landscape of P. aeruginosa, which has the highest known genome size of any known bacterial species at 6.3 million base pairs, is presumably one factor contributing to this phenomenon55.

It appears that the global literature presents a troubling image of the growing arms race between antimicrobial drugs and the adaptive abilities of P. aeruginosa. This emphasises the need for ongoing watchfulness, creative treatment approaches, and coordinated efforts towards antimicrobial stewardship to lessen the growing threat that MDR P. aeruginosa strains offer. The increased frequency of MDR Pseudomonas isolates in our environment may be due to a complex interaction of factors, such as higher rates of active surveillance testing carried out in compliance with our internal screening guidelines. This scenario does not, however, eliminate the organism’s increased virulence resulting from the non-judicious use of antibiotics, which acts as a catalyst for antibiotic resistance. Interestingly, there were no recorded histories of recent antibiotic use in our sample, which may be a sign of the effectiveness of aggressive awareness efforts and the establishment of a national action plan for antibiotic resistance that runs from 2020 to 202456.

MDR risk factors have attracted a lot of interest among researchers. A study conducted in Colombia examined presumptive risk factors and compared susceptible and MDR Pseudomonas isolates (n = 40) concerning them. 10% of these individuals had diabetes mellitus, 11% had kidney illness, and 8% had cancer. Males accounted for 51.9% of the cases, indicating that they were disproportionately impacted by MDR infections. This pattern is consistent with other studies, such as one reported from Brazil, where a greater frequency of MDR infections was seen among males (55.1%)57. Previous studies have identified specific clinical situations that put people at risk for multidrug resistance (MDR) illnesses. 11 were on mechanical ventilation, 26 had catheterizations, and 22 had central lines installed during the 48 h before admission58.

Similarly, in our study among the MDR-infected patients, 17.9% had kidney problems, 14% had cancer, 52.5% had CVD, and 35.2% had diabetes mellitus. Furthermore, of the 596 patients in the group, 26.2% had had tracheal intubation, 47.2% had central venous catheters, and 41% had indwelling urine catheters. These results highlight the complex interactions between clinical, demographic, and healthcare-related factors that lead to the formation and spread of MDR Pseudomonas strains, emphasizing the need for customized intervention approaches supported by strong epidemiological insights58.

Moreover, the current study reveals significant associations between virulence factors and MDR in P. aeruginosa, highlighting the complex relationship between pathogenicity and antibiotic resistance mechanisms. Biofilm formation was strongly linked to MDR isolates (p < 0.001), suggesting their roles in enhancing bacterial survival and persistence in high-antibiotic environments. Biofilm formation is particularly critical in antimicrobial resistance, as it limits drug penetration and provides a protective niche for bacterial communities59,60. Phospholipase C, a lipolytic enzyme involved in tissue destruction and immune evasion, is generally considered to promote bacterial survival. However, in the present study, its presence was significantly associated with non-MDR P. aeruginosa isolates61, suggesting a possible inverse relationship with multidrug resistance. Conversely, other virulence factors such as hemolysin and alkaline protease did not show a statistically significant association with MDR status (p = 0.084 and p = 0.673, respectively), implying that their roles in antimicrobial resistance may be limited or mediated through indirect mechanisms.

There was a noticeable pattern in the virulence gene prevalence, with non-MDR isolates having considerably higher levels of toxA and plcH (p < 0.001). Two important factors that contribute to acute pathogenicity are plcH, which encodes hemolytic phospholipase C, and ToxA, which encodes exotoxin A. Their greater frequency in non-MDR isolates points to a trade-off between resistance and virulence, where acquiring MDR may result in health risks that lower these genes’ expression or retention62. Other virulence genes, such as algD, lasB, exoS, and plcN, showed no significant differences between MDR and non-MDR isolates, suggesting a baseline prevalence unaffected by resistance profiles63.

Hemolysin production demonstrated significant associations with five virulence genes algD, toxA, exoS, plcH, and plcN except lasB, indicating a coordinated regulatory mechanism that enhances pathogenicity. Alkaline protease production was similarly associated with lasB, exoS, plcH, and plcN, emphasizing its role in tissue degradation and immune system evasion62. However, phospholipase C production did not exhibit significant associations with any specific genes, suggesting distinct regulatory pathways. Biofilm production showed a significant association exclusively with the plcN gene, highlighting its critical role in biofilm formation. Given the importance of biofilms in chronic infections and resistance, plcN may serve as a promising target for anti-biofilm therapies64. These findings emphasize the complexity of virulence and resistance interplay in P. aeruginosa.

MDR isolates are strongly linked with biofilm formation and phospholipase C production, while non-MDR isolates are associated with a higher prevalence of acute virulence genes like toxA and plcH. This difference provides valuable insights for developing targeted therapies, such as anti-virulence approaches, to combat infections caused by MDR strains more effectively.

Conclusion

The increasing incidence of MDR P. aeruginosa strains poses a significant threat to healthcare systems. P. aeruginosa is now a common nosocomial pathogen in Saudi Arabia, accounting for a considerable portion of HAIs. Based on our analysis, it is evident that males are more likely than females to contract pseudomonas infections, with sputum samples serving as the main source of isolation. Comorbid conditions like diabetes, cancer, renal illness, and cardiovascular disease make people more vulnerable to acquiring pseudomonas. Interestingly, ICUs and surgery wards turned out to be hotspots for Pseudomonas infections, highlighting the crucial role that healthcare environments play in its spread. Antibiotic resistance remains a pressing concern, with fourth-generation cephalosporins demonstrating high resistance rates. However, certain antibiotics like tetracycline and colistin retain effectiveness against P. aeruginosa, highlighting the importance of judicious antibiotic use in combating MDR strains. Antimicrobial stewardship collaboration is essential to counter the growing problem of MDR P. aeruginosa.