Prevalence and Antimicrobial Susceptibility Patterns of Wound and Pus Bacterial Pathogens at a Tertiary Care Hospital in Central Riyadh, Saudi Arabia

Abstract

The long history and extensive use of antibiotics have caused resistant bacterial pathogens to emerge, increasing mortality and morbidity. The current study was designed to see the prevalence of aerobic bacterial isolates with their antimicrobial resistance pattern from out- and inpatients requested for wound or pus culture. Retrospective study conducted at a tertiary care hospital in central Riyadh from January 2023 to December 2023. Samples were collected and inoculated onto the appropriate media following standard guidelines. Bacterial pathogens were identified by the Vitek2 compact system. Antimicrobial susceptibility was tested using the Kirby–Bauer disk diffusion method as well as by MIC determination through the Vitek2 compact. A total of 1186 subjects were included in the study with a bacterial isolation rate of 691 (58.3%). Out of these, 155 positive cultures had incomplete information or anaerobic or fungal growth and were excluded from the study. With a slight female predominance (54.9%), the majority of subjects (72.2%) were outpatients, and over half of the isolates (55.2%) were Gram-positive. The most common isolate was Staphylococcus spp. (44.4%), followed by E. coli (13.6%) and P. aeruginosa (12.9%). The highest resistance was reported against penicillin followed by fusidic acid against Gram-positive bacteria. Methicillin-resistant Staphylococcus aureus (MRSA) was detected in 40.5% of Staphylococcus aureus (S. aureus) isolates. Amikacin was the most susceptible antibiotic against all Gram-negative isolates. MDR Gram-negative bacteria accounted for 51.9% of wound infection isolates (95% CI: 45.95 to 58.33) while 6.3% (95% CI: 4.39 to 8.86) were XDR (nonsusceptibility to at least one agent in all but two or fewer antimicrobial categories). A high prevalence of bacterial isolates, with S. aureus as the predominant pathogen, showed high rates of multidrug resistance. This highlights the importance of monitoring antibiotic choices for prophylaxis and treatment in the study area.

1. Introduction

Skin is the body’s largest organ that plays a crucial role in safeguarding internal organs and harboring colonizing microbiota. This normal flora prevents pathogenic bacteria from attaching to the healthy skin surface but, on the other hand, can become pathogenic if they gain entry into the body in the form of cuts or injuries [1]. Wounds create a favorable environment for microbial colonization and infection due to their moist, warm, and nutritive nature. While the human body has defense mechanisms that prevent many harmless bacteria from causing disease, any breach in the skin, such as trauma or surgery, can lead to bacterial infections [2]. The occurrence of pus within the wound site represents a classic sign of infection, along with systemic symptoms like fever, localized tenderness, and swelling [3]. Patients with high-risk wounds, often associated with factors like old age or poor nutritional status, are more susceptible to pathogenic bacterial infiltration and infection [4]. Bacterial infections in wounds can significantly impede the healing process by prolonging inflammation and producing virulence factors that promote bacterial growth and tissue destruction [5].

Wounds can be classified into various types based on different criteria such as etiology, morphology, and healing process. Common types of wounds include diabetic foot ulcers, pressure sores, surgical site infections, and burns [6,7,8]. Trauma, whether accidental or intentional, is the main cause of wounds. Hospital-acquired wounds, including surgical and device-related ones, are a distinct subgroup and pressure sores from immobility are another concern [9]. Wound infection evolution is a complex process influenced by multiple factors. These factors include skin conditions, bacterial load and virulence, the nature of the surgical procedures, prior exposure to antibiotics, and the immune status of the affected individual [10]. Infections in wounds can stem from a wide array of pathogens, including bacteria, fungi, protozoa, and viruses. Among the common bacterial culprits associated with wound infections are notorious species such as Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli, Klebsiella pneumoniae, Proteus species, as well as different Enterococcus and Streptococcus species [11].

Annually, a significant number of individuals around the globe endure the pain and trauma of wounds, struggle with wounds that are slow to heal, or face the challenge of acute wounds that are further complicated due to infections. Significant progress has been made in infection control strategies, yet eradicating drug-resistant pathogens remains a challenge due to the overuse of antibiotics. These resistant strains contribute to higher morbidity and mortality, especially in wound infections. Healthcare settings are sources of these antibiotic-resistant pathogens like MRSA and VRE, leading to difficult-to-treat hospital-acquired wound infections [12].

Wound infections are a significant concern in healthcare settings, including hospitals in Saudi Arabia. They pose a significant concern for healthcare practitioners due to the potential for escalating trauma to the patient, as well as the considerable impact they can have on both financial resources and the overall efficiency of the healthcare system [13]. The prevalence of wound infections in the country is influenced by various factors such as the complexity of intensive care unit (ICU) environments, the increased number of patients with serious diseases, widespread gastrointestinal colonization, and extensive use of antimicrobial drugs [14]. Effectively managing wound infections is essential not only for the well-being of the patient but also for the sustainability of healthcare services. Understanding the various causative agents responsible for wound infections plays a crucial role in guiding treatment decisions, implementing infection control protocols in healthcare facilities, and establishing effective antibiotic policies.

The high prevalence of multidrug-resistant bacteria accounts for a significant health issue in the region as inadequately managed wounds contribute significantly to heightened rates of patient suffering and prolonged hospitalization [15]. This survey was conducted in central Riyadh at a tertiary care hospital to identify aerobic bacterial isolates from a group of patients with different types of wound infections. Furthermore, the study was designed to detect antimicrobial and MDR profiles of various bacterial isolates.

Consistent monitoring of evolving wound infection trends, including sensitivity and multidrug resistance profiles, is essential for effective treatment. Health providers can adapt therapies to combat antimicrobial resistance, improving patient care. This approach helps manage infections by adjusting treatments promptly and minimizing risks.

2. Material and Methods

2.1. Study Design and Setting

The current study was designed as a retrospective design carried out from January 2023 to December 2023. All culture requests under the label of wound or pus culture received during the defined study period were included. The data were collected for a tertiary care hospital of 450 beds in central Riyadh, Saudi Arabia.

2.2. Demographic Data of Study Participants and Sample Size

A wound culture is requested if there is a suspected infection when the wound is not healing or exudating pus. The study included both males and females of all age groups who attended the hospital as outpatients or inpatients during the study period. A total of 1186 specimens were requested for wound culture from various types of wounds like surgical wounds, diabetic wounds, and deep and superficial wounds. Patient data were taken from the medical health records of the hospital and microbial growth and antimicrobial susceptibility reports were taken from the microbiology lab of the hospital. Patients with inadequate demography or missing antimicrobial susceptibility data were excluded from the study.

2.3. Identification of Bacterial Isolates

Upon the physician’s request, the specimen was collected from the patient by a nurse or doctor inside the clinic or ward following the standard protocol for wound culture. The samples were transported immediately to the microbiology lab for processing. The wound culture was inoculated and incubated aerobically and anaerobically according to the standard guidelines of the hospital on different enriched and selective media. Primary identification was made by colony morphology and growth characteristics on different media and by Gram stain. Final identification was made by the Vitek2 compact system following the manufacturer’s guidelines.

2.4. Antimicrobial Susceptibility Testing

Antimicrobial susceptibility testing was performed by both Kirby–Bauer disk diffusion and micro broth dilution methods for minimal inhibitory concentration (MIC) determination by the Vitek2 compact system. Interpretation of disk zone sizes and MIC values was made according to Clinical Laboratory Standard Institute (CLSI) 2023 guidelines. Antimicrobial agents were selected as per CLSI guidelines for various bacterial species.

2.5. Statistical Analysis

Statistical analysis was performed by SPSS (IBM Co., Armonk, NY, USA). Categorical data were presented as the frequency and percentage and analyzed using the chi-square test or exact test, as appropriate. Univariate logistic regression analysis was performed to assess the association between the gender of patients and the probability of testing positive for each isolate. A two-tailed p value < 0.05 was considered statistically significant.

2.6. Ethical Consideration

The study was approved by the Research Committee of Dr. Sulaiman Al Habib Medical Group Research Center, Riyadh, Kingdom of Saudi Arabia (IRB study number RC24.05.15).

3. Results

3.1. Demographic Characteristics of the Study Participants

A total of 1186 specimens were requested during the study period under pus and wound culture. Microbial growth was obvious in 691 (58.3%) of the samples, whereas 495 cultures (41.7%) were sterile. The total number of positive cultures included in the study was 536, while the remaining 155 positive cultures had incomplete information or anaerobic or fungal growth. Among the total of 536 patients with infected wounds, 42.4% and 28.9% were respectively in the 12 to 40 years age group and the older than 60 years group, with a slight female predominance (54.9%). The majority of subjects (72.2%) were outpatients as shown in

Table 1. Characteristics of patients with wound cultures included in the study.

Characteristic	Frequency (n)	Percentage (%)
Age group (in years)
<12	58	10.8
12 to 40	227	42.4
41 to 60	96	17.9
>60	155	28.9
Gender
Male	242	45.1
Female	294	54.9
Patient setting
Inpatient	149	27.8
Outpatient	387	72.2

n = number.

.

3.2. Prevalence of Bacterial Isolates among Different Types of Wound Infections

Out of 536 samples, monomicrobial infection was evident in 285 (53%) cases, while the remaining 251 (47%) cases were reported as polymicrobial infections. Over half of the isolates (55.2%) were Gram-positive and overall the most common isolate was Staphylococcus spp. (44.4%), followed by E. coli (13.6%), P. aeruginosa (12.9%), E. faecalis (10.8%), K. pneumonia (8.4%), Proteus spp. (3.7%), Enterobacter spp. (3%), Serratia spp. (1.3%), Citrobacter spp. (1.1%), and Acinetobacter spp. (0.7%). The frequencies of bacterial isolates from different types of wound infection are shown in Figure 1.

Table 2. Characteristics of bacterial isolates of wound infection among inpatients and outpatients.

Characteristic	Inpatient n (%)	Outpatient n (%)	Total n (%)
Gram reaction
Negative	85 (35.4)	155 (64.6)	240 (44.8)
Positive	64 (21.6)	232 (78.4)	296 (55.2)
Type of infection
Monomicrobial	59 (20.7)	226 (79.3)	285 (53.2)
Polymicrobial	90 (35.9)	161 (64.1)	251 (46.8)
Type of bacteria
Staphylococcus	35 (14.7)	203 (85.3)	238 (44.4)
S. aureus	33 (16.1)	172 (83.9)	205 (38.2)
S. epidermidis	0 (0)	1 (100)	1 (0.2)
S. lugdunensis	2 (6.3)	30 (93.7)	32 (6)
E. faecalis	29 (50)	29 (50)	58 (10.8)
E. coli	18 (24.7)	55 (75.3)	73 (13.6)
K. pneumoniae	20 (44.4)	25 (55.6)	45 (8.4)
P. aeruginosa	24 (34.8)	45 (65.2)	69 (12.9)
E. cloacae	4 (25)	12 (75)	16 (3)
Proteus spp.	11 (55)	9 (45)	20 (3.7)
S. marcescens	4 (57.1)	3 (42.9)	7 (1.3)
Citrobacter spp.	1 (16.7)	5 (83.3)	6 (1.1)
Acinetobacter spp.	3 (75)	1 (25)	4 (0.7)

n = number.

shows the characteristics of bacterial isolates from inpatients and outpatients.

3.3. Antimicrobial Susceptibility of Gram-Positive Isolates

The highest resistance was reported against penicillin followed by fusidic acid in both S. aureus and CoNS. MRSA was detected in 40.5% of S. aureus isolates. The detailed percentage of resistance of these isolates is shown in Figure 2.

E. faecalis isolates showed the highest resistance against tetracycline, followed by ampicillin and penicillin. Vancomycin resistance was reported in four E. faecalis isolates (8.6%); however, no resistance was seen against linezolid. The detail is given in Figure 3.

3.4. Antimicrobial Susceptibility of Gram-Negative Isolates

Data in Figure 4 and Figure 5 represent the antimicrobial resistance to various tested antibiotics against Enterobacteriaceae and P. aeruginosa, respectively. More than 50% of the Enterobacteriaceae isolates were found resistant to augmentin, cefalothin, cefuroxime, cefixime, and cefpodoxime. Amikacin was the most susceptible antibiotic as 99.4% of Enterobacteriaceae isolates were susceptible to it. P. aeruginosa also showed the highest susceptibility to amikacin (98.6%), followed by gentamicin, ceftazidime, and cefepime (97.1% each). Carbapenem resistance was noticed in 8.7% of P. aeruginosa isolates.

3.5. Antimicrobial Resistance Profile Correlation with Gender

A statistically significant relation was detected between the gender of patients and resistance of Gram-positive isolates to ampicillin (p = 0.022), showing a significantly higher proportion of resistant isolates among males than females (

Table 3. Comparison between males and females of antimicrobial-resistant patterns of Gram-positive isolates.

Antibiotic	Susceptibility Profile		p Value
	Sensitive	Resistant
Gentamicin
Male	117 (94.4%)	7 (6.1%)	0.871
Female	107 (93.9%)	7 (5.6%)
Co-trimoxazole
Male	106 (85.5%)	18 (14.5%)	0.647
Female	95 (83.3%)	19 (16.7%)
Ciprofloxacin
Male	106 (85.5%)	18 (14.5%)	0.169
Female	104 (91.2%)	10 (8.8%)
Levofloxacin
Male	105 (84.7%)	19 (15.3%)	0.123
Female	104 (91.2%)	10 (8.8%)
Oxacillin
Male	81 (65.3%)	43 (34.7%)	0.366
Female	68 (59.6%)	46 (40.4%)
Fusidic acid
Male	56 (45.2%)	68 (54.8%)	0.454
Female	46 (40.4%)	68 (59.6%)
Clindamycin
Male	108 (87.1%)	16 (12.9%)	0.413
Female	95 (83.3%)	19 (16.7%)
Ampicillin
Male	16 (61.5%)	10 (38.5%)	0.022
Female	28 (87.5%)	4 (12.5%)
Penicillin
Male	23 (15.3%)	127 (84.7%)	0.110
Female	33 (22.6%)	113 (77.4%)
Vancomycin
Male	146 (97.3%)	4 (2.7%)	0.371
Female	145 (99.3%)	1 (0.7%)
Linezolid
Male	150 (100%)	0 (0%)	---
Female	146 (100%)	0 (0%)
Erythromycin
Male	88 (59.5%)	60 (40.5%)	0.250
Female	76 (52.8%)	68 (47.2%)
Tetracycline
Male	126 (84%)	24 (16%)	0.659
Female	119 (82.1%)	26 (17.9%)

Data are presented as frequency (%), statistical significance at p value < 0.0003 (after Bonferroni correction).

).

There was a significant relation between gender of patients and resistance of Gram-negative isolates to imipenem (p = 0.010), meropenem (p < 0.001), levofloxacin (p = 0.014), ofloxacin (p = 0.020), gentamicin (p = 0.047), and piperacillin/tazobactam (p = 0.006), with significantly higher proportions of resistant isolates among males than females (

Table 4. Comparison between males and females of antimicrobial-resistant patterns of Gram-negative isolates.

Antibiotic	Susceptibility Profile		p Value
	Sensitive	Resistant
Ampicillin–sulbactam
Male	0 (0%)	2 (100%)	0.333
Female	2 (100%)	0 (0%)
Colistin
Male	1 (50%)	1 (50%)	>0.999
Female	0 (0%)	2 (100%)
Tigecycline
Male	2 (100%)	0 (0%)	---
Female	2 (100%)	0 (0%)
Amikacin
Male	92 (100%)	0 (0%)	0.288
Female	145 (98%)	3 (2%)
Cefepime
Male	75 (81.5%)	17 (18.5%)	0.734
Female	118 (79.7%)	30 (20.3%)
Imipenem
Male	77 (83.7%)	15 (16.3%)	0.010
Female	139 (93.9%)	9 (6.1%)
Meropenem
Male	81 (88%)	11 (12%)	<0.001
Female	148 (100%)	0 (0%)
Ciprofloxacin
Male	59 (64.1%)	33 (35.9%)	0.380
Female	103 (69.6%)	45 (30.4%)
Levofloxacin
Male	61 (66.3%)	31 (33.7%)	0.014
Female	119 (80.4%)	29 (19.6%)
Ofloxacin
Male	61 (66.3%)	31 (33.7%)	0.020
Female	118 (79.7%)	30 (20.3%)
Gentamicin
Male	85 (92.4%)	7 (7.6%)	0.047
Female	145 (98%)	3 (2%)
Ceftriaxone
Male	35 (61.4%)	22 (38.6%)	>0.999
Female	70 (61.4%)	44 (38.6%)
Co-trimoxazole
Male	39 (68.4%)	18 (31.6%)	0.723
Female	81 (71.1%)	33 (28.9%)
Ceftazidime
Male	34 (91.9%)	3 (8.1%)	0.240
Female	36 (100%)	0 (0%)
Piperacillin/tazobactam
Male	80 (88.9%)	10 (11.1%)	0.006
Female	143 (97.9%)	3 (2.1%)
Ampicillin
Male	6 (26.1%)	17 (73.9%)	0.188
Female	29 (41.4%)	41 (58.6%)
Amoxicillin/clavulanic acid
Male	16 (29.1%)	39 (70.9%)	0.197
Female	44 (39.3%)	68 (60.7%)
Cephalothin
Male	14 (25.5%)	41 (74.5%)	0.078
Female	44 (39.3%)	68 (60.7%)
Cefuroxime
Male	19 (34.5%)	36 (65.5%)	0.303
Female	48 (42.9%)	64 (57.1%)
Cefixime
Male	22 (40%)	33 (60%)	0.498
Female	51 (45.5%)	61 (54.5%)
Cefpodoxime
Male	22 (40%)	33 (60%)	0.371
Female	53 (47.3%)	59 (52.7%)
Aztreonam
Male	28 (80%)	7 (20%)	0.307
Female	30 (90.9%)	3 (9.1%)

Data are presented as frequency (%), statistical significance at p value < 0.002 (after Bonferroni correction).

).

3.6. Antimicrobial Resistance Profile Correlation with Different Age Groups

There was a statistically significant relation between the age of patients and resistance of Gram-positive isolates to ampicillin (p = 0.006), penicillin (p < 0.001), erythromycin (p = 0.013), and tetracycline (p < 0.001) (

Table 5. Comparison of age groups in antimicrobial-resistant patterns of Gram-positive isolates.

Antibiotic	Age Group				p Value
	<12 yrs	12–40 yrs	41–60 yrs	>60 yrs
Gentamicin
Sensitive	49 (94.2%)	95 (95%)	43 (89.6%)	37 (97.4%)	0.466
Resistant	3 (5.8%)	5 (5%)	5 (10.4%)	1 (2.6%)
Co-trimoxazole
Sensitive	40 (76.9%)	88 (88%)	42 (87.5%)	31 (81.6%)	0.286
Resistant	12 (23.1%)	12 (12%)	6 (12.5%)	7 (18.4%)
Ciprofloxacin
Sensitive	43 (82.7%)	87 (87%)	45 (93.8%)	35 (92.1%)	0.303
Resistant	9 (17.3%)	13 (13%)	3 (6.3%)	3 (7.9%)
Levofloxacin
Sensitive	43 (82.7%)	86 (86%)	45 (93.8%)	35 (92.1%)	0.282
Resistant	9 (17.3%)	14 (14%)	3 (6.3%)	3 (7.9%)
Oxacillin
Sensitive	29 (55.8%)	60 (60%)	32 (66.7%)	28 (73.7%)	0.301
Resistant	23 (44.2%)	40 (40%)	16 (33.3%)	10 (26.3%)
Fusidic acid
Sensitive	22 (42.3%)	47 (47%)	16 (33.3%)	17 (44.7%)	0.468
Resistant	30 (57.7%)	53 (53%)	32 (66.7%)	21 (55.3%)
Clindamycin
Sensitive	45 (86.5%)	87 (87%)	38 (79.2%)	33 (86.8%)	0.614
Resistant	7 (13.5%)	13 (13%)	10 (20.8%)	5 (13.2%)
Ampicillin
Sensitive	---	23 (92%)	5 (100%)	16 (57.1%)	0.006
Resistant	---	2 (8%)	0 (0%)	12 (42.9%)
Penicillin
Sensitive	0 (0%)	29 (23.2%)	8 (15.1%)	19 (28.8%)	<0.001
Resistant	52 (100%)	96 (76.8%)	45 (84.9%)	47 (71.2%)
Vancomycin
Sensitive	52 (100%)	124 (99.2%)	52 (98.1%)	63 (95.5%)	0.176
Resistant	0 (0%)	1 (0.8%)	1 (1.9%)	3 (4.5%)
Linezolid
Sensitive	52 (100%)	125 (100%)	53 (100%)	66 (100%)	---
Resistant	0 (0%)	0 (0%)	0 (0%)	0 (0%)
Erythromycin
Sensitive	34 (65.4%)	69 (55.6%)	35 (67.3%)	26 (40.6%)	0.013
Resistant	18 (34.6%)	55 (44.4%)	17 (32.7%)	38 (59.4%)
Tetracycline
Sensitive	47 (90.4%)	107 (85.6%)	49 (94.2%)	42 (63.6%)	<0.001
Resistant	5 (9.6%)	18 (14.4%)	3 (5.8%)	24 (36.4%)

Data are presented as frequency (%), statistical significance at p value < 0.0003 (after Bonferroni correction).

).

Age of patients was significantly associated with the resistance of Gram-negative isolates to imipenem (p = 0.003), meropenem (p = 0.006), ciprofloxacin (p = 0.020), levofloxacin (p = 0.003), ofloxacin (p = 0.006), gentamicin (p = 0.029), piperacillin/tazobactam (p = 0.006), cefpodoxime (p = 0.034), and aztreonam (p = 0.029) (

Table 6. Comparison of age groups in antimicrobial-resistant patterns of Gram-negative isolates.

Antibiotic	Age Group				p Value
	<12 yrs	12–40 yrs	41–60 yrs	>60 yrs
Ampicillin–sulbactam
Sensitive	---	---	1 (33.3%)	1 (100%)	>0.999
Resistant	---	---	2 (66.7%)	0 (0%)
Colistin
Sensitive	---	---	1 (33.3%)	0 (0%)	>0.999
Resistant	---	---	2 (66.7%)	1 (100%)
Tigecycline
Sensitive	---	---	3 (100%)	1 (100%)	---
Resistant	---	---	0 (0%)	0 (0%)
Amikacin
Sensitive	6 (100%)	102 (100%)	42 (97.7%)	87 (97.8%)	0.354
Resistant	0 (0%)	0 (0%)	1 (2.3%)	2 (2.2%)
Cefepime
Sensitive	5 (83.3%)	82 (80.4%)	38 (88.4%)	68 (76.4%)	0.449
Resistant	1 (16.7%)	20 (19.6%)	5 (11.6%)	21 (23.6%)
Imipenem
Sensitive	6 (100%)	100 (98%)	34 (79.1%)	76 (85.4%)	0.003
Resistant	0 (0%)	2 (2%)	9 (20.9%)	13 (14.6%)
Meropenem
Sensitive	6 (100%)	102 (100%)	42 (97.7%)	79 (88.8%)	0.006
Resistant	0 (0%)	0 (0%)	1 (2.3%)	10 (11.2%)
Ciprofloxacin
Sensitive	6 (100%)	77 (75.5%)	27 (62.8%)	52 (58.4%)	0.020
Resistant	0 (0%)	25 (24.5%)	16 (37.2%)	37 (41.6%)
Levofloxacin
Sensitive	6 (100%)	86 (84.3%)	32 (74.4%)	56 (62.9%)	0.003
Resistant	0 (0%)	16 (15.7%)	11 (25.6%)	33 (37.1%)
Ofloxacin
Sensitive	6 (100%)	85 (83.3%)	32 (74.4%)	56 (62.9%)	0.006
Resistant	0 (0%)	17 (16.7%)	11 (25.6%)	33 (37.1%)
Gentamicin
Sensitive	5 (83.3%)	102 (100%)	39 (90.7%)	84 (94.4%)	0.029
Resistant	1 (16.7%)	0 (0%)	4 (9.3%)	5 (5.6%)
Ceftriaxone
Sensitive	1 (50%)	54 (67.5%)	23 (67.6%)	27 (49.1%)	0.135
Resistant	1 (50%)	26 (32.5%)	11 (32.4%)	28 (50.9%)
Co-trimoxazole
Sensitive	2 (100%)	61 (76.3%)	23 (67.6%)	34 (61.8%)	0.239
Resistant	0 (0%)	19 (23.8%)	11 (32.4%)	21 (38.2%)
Ceftazidime
Sensitive	4 (100%)	22 (100%)	11 (91.7%)	33 (94.3%)	0.641
Resistant	0 (0%)	0 (0%)	1 (8.3%)	2 (5.7%)
Piperacillin/ tazobactam
Sensitive	6 (100%)	101 (99%)	41 (97.6%)	75 (87.2%)	0.006
Resistant	0 (0%)	1 (1%)	1 (2.4%)	11 (12.8%)
Ampicillin
Sensitive	0 (0%)	21 (44.7%)	9 (45%)	5 (20%)	0.127
Resistant	1 (100%)	26 (55.3%)	11 (55%)	20 (80%)
Amoxicillin/clavulanic acid
Sensitive	0 (0%)	32 (40%)	15 (48.4%)	13 (24.1%)	0.057
Resistant	2 (100%)	48 (60%)	16 (51.6%)	41 (75.9%)
Cephalothin
Sensitive	0 (0%)	33 (41.3%)	13 (41.9%)	12 (22.2%)	0.064
Resistant	2 (100%)	47 (58.8%)	18 (58.1%)	42 (77.8%)
Cefuroxime
Sensitive	0 (0%)	36 (45%)	16 (51.6%)	15 (27.8%)	0.051
Resistant	2 (100%)	44 (55%)	15 (48.4%)	39 (72.2%)
Cefixime
Sensitive	0 (0%)	39 (48.8%)	17 (54.8%)	17 (31.5%)	0.052
Resistant	2 (100%)	41 (51.3%)	14 (45.2%)	37 (68.5%)
Cefpodoxime
Sensitive	0 (0%)	41 (51.3%)	17 (54.8%)	17 (31.5%)	0.034
Resistant	2 (100%)	39 (48.8%)	14 (45.2%)	37 (68.5%)
Aztreonam
Sensitive	4 (100%)	22 (100%)	8 (88.9%)	24 (72.7%)	0.029
Resistant	0 (0%)	0 (0%)	1 (11.1%)	9 (27.3%)

Data are presented as frequency (%), statistical significance at p value < 0.002 (after Bonferroni correction).

).

3.7. Antimicrobial Resistance Profile Correlation with the Patient Settings

Among bacterial isolates from wound swab cultures, the proportions of those obtained from inpatients that showed resistance to imipenem (p = 0.006), meropenem (p = 0.040), ceftriaxone (p = 0.011), piperacillin/tazobactam (p = 0.028), ampicillin (p = 0.025), vancomycin (p = 0.004), and erythromycin (p = 0.041) were significantly higher than those obtained from outpatients (

Table 7. Comparison between inpatients and outpatients of antimicrobial resistance of bacterial isolates from wound swab cultures.

Antibiotic	Inpatient	Outpatient	p Value
Ampicillin–sulbactam
Sensitive	2 (66.7%)	---	---
Resistant	1 (33.3%)	---
Colistin
Sensitive	1 (33.3%)	---	---
Resistant	2 (66.7%)	---
Tigecycline
Sensitive	3 (100%)	---	---
Resistant	0 (0%)	---
Amikacin
Sensitive	63 (96.9%)	109 (99.1%)	0.556
Resistant	2 (3.1%)	1 (0.9%)
Cefepime
Sensitive	48 (73.8%)	91 (82.7%)	0.160
Resistant	17 (26.2%)	19 (17.3%)
Imipenem
Sensitive	52 (80%)	103 (93.6%)	0.006
Resistant	13 (20%)	7 (6.4%)
Meropenem
Sensitive	58 (89.2%)	107 (97.3%)	0.040
Resistant	7 (10.8%)	3 (2.7%)
Ofloxacin
Sensitive	43 (66.2%)	84 (76.4%)	0.144
Resistant	22 (33.8%)	26 (23.6%)
Gentamicin
Sensitive	83 (94.3%)	176 (97.8%)	0.159
Resistant	5 (5.7%)	4 (2.2%)
Ciprofloxacin
Sensitive	62 (70.5%)	136 (75.6%)	0.372
Resistant	26 (29.5%)	44 (24.4%)
Levofloxacin
Sensitive	64 (72.7%)	144 (80%)	0.180
Resistant	24 (27.3%)	36 (20%)
Ceftriaxone
Sensitive	20 (44.4%)	53 (67.9%)	0.011
Resistant	25 (55.6%)	25 (32.1%)
Ceftazidime
Sensitive	20 (87%)	32 (100%)	0.068
Resistant	3 (13%)	0 (0%)
Co-trimoxazole
Sensitive	50 (73.5%)	115 (77.7%)	0.502
Resistant	18 (26.5%)	33 (22.3%)
Piperacillin/tazobactam
Sensitive	53 (86.9%)	106 (96.4%)	0.028
Resistant	8 (13.1%)	4 (3.6%)
Ampicillin
Sensitive	17 (39.5%)	44 (61.1%)	0.025
Resistant	26 (60.5%)	28 (38.9%)
Amoxicillin/clavulanic acid
Sensitive	13 (31%)	32 (41%)	0.277
Resistant	29 (69%)	46 (59%)
Cephalothin
Sensitive	11 (26.2%)	31 (39.7%)	0.138
Resistant	31 (73.8%)	47 (60.3%)
Cefuroxime
Sensitive	13 (31%)	36 (46.2%)	0.106
Resistant	29 (69%)	42 (53.8%)
Cefixime
Sensitive	14 (33.3%)	38 (48.7%)	0.105
Resistant	28 (66.7%)	40 (51.3%)
Cefpodoxime
Sensitive	14 (33.3%)	38 (48.7%)	0.105
Resistant	28 (66.7%)	40 (51.3%)
Aztreonam
Sensitive	14 (70%)	27 (87.1%)	0.163
Resistant	6 (30%)	4 (12.9%)
Penicillin
Sensitive	17 (36.2%)	23 (25.6%)	0.195
Resistant	30 (63.8%)	67 (74.4%)
Tetracycline
Sensitive	30 (63.8%)	71 (78.9%)	0.057
Resistant	17 (36.2%)	19 (21.1%)
Vancomycin
Sensitive	42 (89.4%)	90 (100%)	0.004
Resistant	5 (10.6%)	0 (0%)
Linezolid
Sensitive	47 (100%)	90 (100%)	---
Resistant	0 (0%)	0 (0%)
Oxacillin
Sensitive	16 (69.6%)	53 (75.7%)	0.559
Resistant	7 (30.4%)	17 (24.3%)
Clindamycin
Sensitive	21 (91.3%)	55 (78.6%)	0.224
Resistant	2 (8.7%)	15 (21.4%)
Fusidic acid
Sensitive	7 (30.4%)	28 (40%)	0.411
Resistant	16 (69.6%)	42 (60%)
Erythromycin
Sensitive	15 (32.6%)	45 (51.1%)	0.041
Resistant	31 (67.4%)	43 (48.9%)

Data are presented as frequency (%), statistical significance at p value < 0.001 (after Bonferroni correction).

).

3.8. Frequency of Multidrug and Other Resistant Profiles

Among the total infected wound cultures, 9.5% (n = 51) of cases were because of ESBL-producing Enterobacteriaceae, whereas 0.9% (n = 5) of cases were due to carbapenemase-producing bacteria. As depicted in

Table 8. MDR, XDR, and PDR profile of wound infection isolates (n = 536).

Phenotype	Frequency (n)	Percentage (%)
MDR	278	51.9
XDR	34	6.3
PDR	0	0.0
CAR	5	0.9
ESBL	51	9.5
MRSA	84	15.7
VRE	4	0.7

MDR: Multidrug-resistant, XDR: Extensively drug-resistant, PDR: Pan drug-resistant, CAR: Carbapenamase producer, ESBL: Extended-spectrum beta-lactamase producer, MRSA: Methicillin-resistant Staphylococcus aureus, VRE: Vancomycin-resistant enterococci.

, MDR bacteria accounted for 51.9% of wound infection isolates (95% CI: 45.95 to 58.33) while 6.3% (95% CI: 4.39 to 8.86) were XDR.

4. Discussion

This study evaluates the prevalence of different bacteria isolated from various types of wound infections among patients from a tertiary care hospital in central Riyadh. Out of 1186 specimens requested during the study period under pus and wound culture, 691 were positive for microbial growth with an isolation rate of 58.3%. This prevalence rate was similar to the findings of Alharbi, who reported a 56.1% isolation rate of bacterial growth from wound infections in Jeddah [16].

The slight predominance of monomicrobial infection was evident in our study (53%) whereas 47% were polymicrobial infections. These findings were in line with those of Hassan et al., who reported 60% monomicrobial wound infection [17]. Likewise, Alharbi also found a predominance of monomicrobial infections of 90.6% [16]. The ratio of polymicrobial wound infections in this study is much higher as compared to those of Alharbi and Maharjan et al., who reported 9.4% and 2.5% of wound cultures yielding more than one type of bacteria, respectively [16,18]. This difference could be due to many factors, including wound characteristics and environmental conditions, that interact in complex ways to shape bacterial communities in wounds, impacting their composition, behavior, evolution, and response to treatment [19].

Our survey revealed a slight predominance of Gram-positive bacteria (55.2%) over Gram-negative bacteria (44.8%). These findings are in contrast to other studies where Gram-negative predominance was reported [16,17,19,20]. Variations in participants’ demographic traits, reflecting diverse age, gender, and cultural backgrounds, could lead to these contrasting outcomes.

S. aureus was the most commonly isolated wound pathogen, followed by E. coli and P. aeruginosa. This was in parallel with the findings of El-Saed et al. [21]. Another report by Puca et al. also supports our findings [20]. Various studies confirm the predominance of S. aureus in wound cultures, up to 65% reported by Mulu et al. [22]. This predominance is not surprising as S. aureus is normally present on human skin. Among Gram-negative isolates, E. coli (13.6%) was the predominant isolate in our setting followed by P. aeruginosa (12.9%). Various studies performed previously on wound infections reported E. coli and P. aeruginosa as the second most common cause of wound infection after S. aureus [16,18,22,23].

Staphylococci showed the highest resistance to penicillin with the resistance rate reaching up to 96.6%. Our results showed 40.5% MRSA strains among all S. aureus isolates. The prevalence of MRSA in Saudi Arabia has been the subject of several studies. A review of the literature reveals varying prevalence rates across different regions and periods. El Amin et al. conducted a retrospective survey on 186 S. aureus isolates and reported almost the same rate (39.5%) of MRSA isolation [24]. However, a remarkable increase in the prevalence of MRSA was revealed in our findings compared to a recent survey that was conducted by Alharbi et al. who reported a 29% resistance rate to oxacillin against S. aureus [16]. MRSA prevalence was reported to be 83% by Saba et al. [25]. Reduced susceptibility to vancomycin has been reported in Saudi Arabia in previous studies by Al-Obeid et al. and Alzolibani et al. [26,27], although we found S. aureus 100% susceptible to vancomycin and linezolid in our setting. However, vancomycin-resistant enterococci were observed at 8.6% in our study. This rate of resistance is also remarkably high in comparison to that of Somily et al., who reported vancomycin-resistant enterococci at 4.5% [28]. These variations could be associated with the different patient settings and bacterial identification methods.

Regarding Enterobacteriaceae in Gram-negative sensitivity, amikacin was the most effective antibiotic tested with a resistance rate of 0.6%. High rates of resistance were noticed in all Enterobacteriaceae isolates against beta-lactam antibiotics except for carbapenems, imipenem (10.8%), and meropenem (3%). Resistance to meropenem was due to carbapenem-resistant K. pneumoniae (3%). However, Proteus spp. showed a resistance to imipenem but all these isolates were susceptible to meropenem. The rest of the Enterobacteriaceae members were 100% susceptible to these tested carbapenems in our survey. In the past decade, carbapenem-resistant Enterobacteriaceae (CRE), particularly carbapenem-resistant K. pneumoniae with the New Delhi metallo-β-lactamase gene, has emerged as a global threat, spreading in regions like Asia, Europe, the UK, and the Arab countries [29]. An abrupt increase in the prevalence of CRE was reported in a recent study from western Saudi Arabia from 8% in 2017 to 61% in 2019 [30]. However, our low percentage could be due to the site of infection included in our study in comparison to the surveillance study for screening CRE only.

Likewise, amikacin was the most effective antibiotic against P. aeruginosa as well. The highest resistance was noticed against aztreonam (15.9%), followed by quinolones (13–14.5%). Carbapenem-resistant P. aeruginosa was found at 8.7% in our survey. Our results are not in agreement with those of Momenah et al., who reported a high resistance to cefepime (42.7%), followed by ciprofloxacin (34.3%), imipenem (30.5%), ceftazidime (29.2%), gentamicin (26%), and piperacillin/tazobactam (24.2%) [31]. These variations in antibiotic susceptibility patterns stem from factors like number of isolates included in the study, screening duration, antibiotic use, selective pressure, and study conditions, reflecting diverse settings and environmental influences [32].

Antimicrobial resistance is a significant global health concern affected by demographic changes, especially the increasing elderly population. Understanding the impact of demographic changes is crucial due to a lack of knowledge in this area. The relationship between age, gender, infections, and antibiotic resistance is complex, requiring a nuanced understanding to develop effective strategies against drug-resistant infections. In our study, the overall sample of male patients showed higher levels of antimicrobial resistance with statistically significant differences noticed in ampicillin, carbapenem, quinolones, and piperacillin/tazobactam. This male predominance for antimicrobial resistance was supported by Akhavizadegan et al. [33]. Overall, antimicrobial resistance predominance was noticed in the age group of more than 60 years. Older patients with multiple comorbidities receive care in various healthcare settings and are more vulnerable to antibiotic-resistant pathogens, making careful antibiotic use crucial for effective infection management. The significance of age as a factor influencing the variation in antimicrobial resistance has not only been visually delineated for Europe in previous studies [34] but has also been thoroughly investigated in studies focused on specific regions [35,36]. However, to our knowledge, this is the first report from the region highlighting the impact of gender and age on antimicrobial resistance from wound infections.

Our study highlights the urgent need for better infection control in healthcare settings due to high antibiotic resistance among inpatients, emphasizing monitoring, targeted interventions, and collaboration to combat resistance effectively. All five cases of vancomycin-resistant enterococci were inpatient. Two cases of colistin resistance were also isolated from inpatient samples. Carbapenem resistance was also significantly high among inpatients, indicating the overuse of these life-saving, last-resort drugs in our hospital setting. The prevalence of MDR Gram-negative bacteria was 51.9% in our study, which is supported by various other surveys [37,38]. However, our MDR prevalence is remarkably high as compared to that of Alharbi et al., who recorded a 22% isolation rate of MDR bacteria from wound infections [16]. Variations in isolated pathogens, study population, medication access, treatment adherence, infection control, and antimicrobial use may contribute to these discrepancies.

As a retrospective study, in-depth details about patient profiles were not available, which was one of our study limitations. Missing data on pathologies (missing wound site, etc.) and limited numbers of bacterial isolates in this single-center study were other constraints. We could not retrieve data for anaerobic bacterial isolates and streptococci were also excluded from our survey as we were unable to have their antimicrobial susceptibility pattern recorded by the laboratory.

In conclusion, analysis of wound samples showed prevalent monomicrobial infections, with S. aureus, E. coli, and P. aeruginosa as the main pathogens. High MRSA incidence among S. aureus emphasized antibiotic resistance challenges. Vancomycin and linezolid were effective against S. aureus, while amikacin worked best against Gram-negative isolates. Many isolates were multidrug-resistant, escalating antibiotic resistance concerns and hindering treatment options. Urgent action is needed to develop new treatments and improve antimicrobial practices in healthcare settings. This knowledge enables local healthcare professionals to make informed choices regarding empirical therapy, enhances the effectiveness of infection prevention strategies within medical settings, and contributes to the development of rational approaches toward antibiotic usage. By staying abreast of the causative factors behind wound infections, healthcare providers can optimize patient care, minimize the risks associated with infections, and work towards achieving cost-effective and sustainable healthcare management strategies in our setting.