Skip to main content
Download PDF

Emergence of microbial infections in some hospitals of Cairo, Egypt: studying their corresponding antimicrobial resistance profiles

BMC Infectious Diseases volume 23, Article number: 424 (2023) Cite this article

Abstract

Background

Antimicrobial resistance is one of the ten major public health threats facing humanity, especially in developing countries. Identification of the pathogens responsible for different microbial infections and antimicrobial resistance patterns are important to help clinicians to choose the correct empirical drugs and provide optimal patient care.

Methods

During the period from November 2020 to January 2021, one hundred microbial isolates were collected randomly from different specimens from some hospitals in Cairo, Egypt. Sputum and chest specimens were from COVID-19 patients. Antimicrobial susceptibility testing was performed according to CLSI guidelines.

Results

Most microbial infections were more common in males and in elderly people over 45 years of age. They were caused by Gram-negative, Gram-positive bacteria, and yeast isolates that represented 69%, 15%, and 16%, respectively. Uropathogenic Escherichia coli (35%) were the most prevalent microbial isolates and showed high resistance rates towards penicillin, ampicillin, and cefixime, followed by Klebsiella spp. (13%) and Candida spp. (16%). Of all microbial isolates, Acinetobacter spp., Serratia spp., Hafnia alvei, and Klebsiella ozaenae were extremely multidrug-resistant (MDR) and have resisted all antibiotic classes used, except for glycylcycline, in varying degrees. Acinetobacter spp., Serratia spp., and Candida spp. were secondary microbial infections in COVID-19 patients, while H. alvei was a bloodstream infection isolate and K. ozaenae was recorded in most infections. Moreover, about half of Staphylococcus aureus strains were MRSA isolates and reported low rates of resistance to glycylcycline and linezolid. In comparison, Candida spp. showed high resistance rates between 77 and 100% to azole drugs and terbinafine, while no resistance rate towards nystatin was reported. Indeed, glycylcycline, linezolid, and nystatin were considered the drugs of choice for the treatment of MDR infections.

Conclusion

The prevalence of antimicrobial resistance in some Egyptian hospitals was high among Gram-negative, Gram-positive bacteria, and candida spp. The high resistance pattern —especially in secondary microbial infections in COVID-19 patients— to most antibiotics used is a matter of great concern, portends an inevitable catastrophe, and requires continuous monitoring to avoid the evolution of new generations.

Peer Review reports

Introduction

Nosocomial or healthcare-associated infections caused by antimicrobial-resistant pathogens represent a serious burden and ongoing threat to patients’ health and safety [1]. The prevalence of nosocomial infection varies from one setting to another depending on the level of development of the health system, since it is more prevalent in developing countries compared to developed ones and is associated with different risk factors [2]. During the coronavirus disease 2019 (COVID-19) pandemic, changes in hospital infection prevention and control and antibiotic stewardship strategies have had implications for nosocomial infection rates and antimicrobial resistance [3].

Antimicrobial resistance is a growing problem that causes over 700,000 deaths every year around the world [4] and is expected to cause the deaths of 10 million people by 2050 [5]. The excessive use of antibiotics or antifungals, empirical treatment without antimicrobial susceptibility testing and self-treatment lead to mutation and increased drug resistance [6]. Reporting of susceptibility testing results is a key reference to choose the correct antimicrobial and avoiding the emergence of new antimicrobial resistance. In Egypt, the most common nosocomial infections are urinary tract, wound, respiratory tract, and bloodstream infections [7]. Nosocomial infections were caused by microbes, which includ bacteria, viruses, and fungi [7, 8]. The most common bacterial pathogens included E. coli, P. aeruginosa, Klebsiella spp., Enterobacter spp., Proteus spp., Serratia spp., Acinetobacter spp., S. aureus, Coagulase Negative Staphylococci (CoNS), and Streptococcus spp. [9]. Acinetobacter baumanii is linked to a high mortality rate in the intensive care units because of its inherent MDR properties [8]. Fungal pathogens are most commonly found in immune-compromised patients and those who have indwelling devices, such as urinary catheters and central lines. Candida species, such as C. albicans, C. glabrata, and C. parapsilosis as well as Aspergillus species, are the most prevalent causes of fungal infection [8, 10]. Therefore, the present study is a trail to give a broad picture of pathogens responsible for different infections and the antimicrobial resistance of many bacterial and yeast isolates.

Methods

Study design

The data of microbial isolates from different clinical specimens were collected from the Clinical Microbiology Department at some hospitals in Cairo, Egypt, during the period from November 2020 to January 2021. Patient samples in this study were included and analyzed by sex and age.

Isolation and identification of the microbial isolates

Microbial isolates were collected randomly and in aseptic conditions from different clinical specimens, including urine, blood, wound swab, abscess swab, liver pus, ascites swab, pelvic aspiration, pleural effusion, vaginal swab, as well as sputum swab and chest aspirations from COVID-19 patients.

The clinical specimens were cultured immediately after collection on Blood and MacConkey agar, except urine specimens, which were cultured on Blood and CLED agar medium according to the standard method and incubated for 18–24 h under standard conditions at 37 °C [11]. After the incubation period, the different colonies of bacteria on Blood, CLED, and MacConkey agar were sub-cultured on nutrient agar medium in order to purify the isolated pathogens, while yeast-like isolates were sub-cultured on CHROM agar medium [12]. All media used in the present study were from Oxoid, UK. Pure isolates of bacteria and yeast were subjected to the Gram-staining technique, examined microscopically, and finally identified by VITEK 2 system [13].

Antimicrobial susceptibility testing

Antibiotic sensitivity testing of bacterial isolates was performed for commonly used antibiotics by the standard disc diffusion technique on Muller-Hinton agar according to the Kirby-Bauer method [14]. After the incubation period at 37°C, the zone of inhibition was measured, and results were interpreted according to the Clinical and Laboratory Standards Institute [15]. Due to the lack of established CLSI breakpoints for tigecycline at this time FDA breakpoints were: (susceptible at MIC ≤ 2 mg/l, with zone diameter ≥ 19 mm; intermediate at MIC ≥ 4 mg/l, with zone diameter resistant 15–18 mm; resistant at MIC ≥ 8 mg/l, with zone diameter ≥ 14 mm.” https://www.accessdata.fda.gov/drugsatfda_docs/label/2013/021821s026s031lbl.pdf.

Twenty-four antibiotics were used against Gram-negative bacterial isolates and twenty-eight antibiotics were tested against Gram-positive bacterial isolates. The antibiotics used in this respect were the following classes: (I) Penicillins: penicillin (P 10), ampicillin (AMP 10), amoxicillin-clavulanic acid (AMC 30) and sulbactam/ampicillin (SAM 20), (II) Cephalosporins: ceftazidime (CAZ 30), cefixime (CFM 5), cefoperazone (CFP 75), ceftriaxone (CRO 30), cefotaxime (CTX 30) and cefepime (FEP 30), (III) DNA synthesis inhibitors (fluoroquinolones): ciprofloxacin (CIP 5), norfloxacin (NOR 10) and ofloxacin (OFX 5), (IV) Protein Synthesis Inhibitors: amikacin (AK 30), gentamicin (CN 10), tigecycline (TGC 15) and chloramphenicol (CL 30), (V) Carbapenems: ertapenem (ETP 10) and meropenem (MEM 10), (VI) Others: ceftazidime-avibactam (CZA 50), ceftolozane/tazobactam (C/T), cefoperazone/sulbactam (SCF 105), sulphamethoxazole/trimethoprim (SXT 25), piperacillin/tazobactam (TZP 110), (VII) Gram-positive antibiotics: clindamycin (DA 2), erythromycin (E 15), linezolid (LZD 30), and oxacillin (OX 1).

Various commonly used antifungals were tested on yeast isolates on 2% glucose-supplemented Mueller-Hinton agar [16]. The antifungal discs used in this test were the following: nystatin (100 U), clotrimazole (10 µg), fluconazole (25 µg), itraconazole (10 µg) and terbinafine (1 µg). The results were explained using the standard zone sizes of the Clinical and Laboratory Standards Institute guidelines [17].

Data analysis

Data were entered and analyzed using Statistical Package for Social Science version 27 (IBM Corp released 2020.IBM SPSS statistics. Armonk, NY: IBM Corp). A Chi-square test was used for the comparison between groups, and a P value lower than 0.05 was regarded as statistically significant.

Results

Percentage of microbial isolates in relation to the source of microbial infection

One hundred (100) clinical pathogens were isolated from different patients from different specimens, as illustrated in Fig. 1. The most common source of microbial infection was in urine specimens with a percentage of 44%, followed by 20% COVID-19 patients’ isolates (13% sputum and 7% chest isolates), 13% blood, and 10% wound isolates.

Fig. 1
figure 1

Percentage of the microbial isolates in relation to the isolation source

Full size image

Prevalence of microbial Infections in relation to patients’ gender

From the results displayed in Table 1; Fig. 2, the distribution of microbial infections among patients increased in males (51%) than females (49%) (P value = 0.054 > 0.05), although the differences were not statistically significant. Urinary infections were more common in females than males, however none statistically significant difference was found (P = 0.166 > 0.050) as well as abscess, chest, and sputum infection showed none statistically significant difference. On the other hand, blood infection was more prevalent in males (P value = 0.045 < 0.050), and wound infection was more prevalent in females (P value = 0.039 < 0.050), so both results were statistically significant.

Table 1 The prevalence of microbial infections among patients’ gender
Full size table
Fig. 2
figure 2

The prevalence of microbial infections among patients’ gender

Full size image

Prevalence of microbial Infections among patients’ age groups

Patients in this study were separated into 4 age groups from infants to old patients (1 − 93 years). Most microbial infections were found in the age group over 45 years and represented about 54% of microbial infections (P = 0.055), so P > 0.05 and a non-significant difference was found as shown in Table 2; Fig. 3.

Table 2 Distribution of microbial infections in relation to patients’ age groups
Full size table
Fig. 3
figure 3

Distribution of microbial infections in relation to patients’ age groups

Full size image

Characterization and identification of the microbial isolates

The microbial isolates were subjected to microscopic examination, with cell shape and arrangement being bacilli, cocci, coccobacilli, coccoid cluster, and ovoid in shape. Additionally, the Gram-staining technique was performed and reported 15% Gram-positive bacterial isolates, 69% Gram-negative bacterial isolates and 16% Gram-positive staining yeast isolates that appeared in an oval shape under the microscope, as shown in Fig. 4.

Fig. 4
figure 4

Prevalence of microbial isolates according to gram staining and domain

Full size image

The microbial isolates were identified according to phenotypic and biochemical characteristics by VITEK 2 system. In view of the presented data from Fig. 5, it was observed that E. coli was the most frequently identified Gram-negative bacteria (35%), followed by Klebsiella spp. (13%) (Klebsiella pneumoniae 9% and Klebsiella ozaenae 4%), Pseudomonas aeruginosa (8%), Acinetobacter spp. (5%) (Acinetobacter baumannii 4% and Acinetobacter lwoffii 1%), Proteus mirabilis (3%), Enterobacter gergoviae (2%), Serratia spp. (2%) (Serratia rubidaea 1% and Serratia liquefaciens 1%), and Hafnia alvei (1%). Moreover, among the Gram-positive bacterial isolates, Staphylococcus aureus and CON Staphylococcus spp. were most frequently identified, representing 6% for each, followed by Streptococcus pyogenes (2%) and Streptococcus agalactiae (1%). On the other hand, the non-bacterial growth isolates were Candida spp., including Candida albicans, Candida glabrata, Candida krusei, and Candida tropicalis, which represented 13, 1, 1, and 1%, respectively, of all microbial isolates.

Fig. 5
figure 5

Percentage of the identified microbial isolates

Full size image

Distribution of the identified microbial isolates among different specimens

The data in Table 3 indicated that urine specimens were the most common source of microbial infections, accounting for 44% of microbial infections. Uropathogenic E. coli 27% was the most frequently identified Gram-negative bacteria in urine specimens, followed by Klebsiella spp. (5%), P. aeruginosa (2%), and P. mirabilis (2%) as well as CON S. agalactiae (1%), the only identified Gram-positive bacteria. Additionally, C. albicans (6%) and C. krusei (1%) were the identified yeast isolates.

On the other hand, sputum and chest swabs microbial isolates were secondary infection in COVID-19 patients and accounted for 20% of microbial infections. Gram-negative bacteria (Acinetobacter spp., P. aeruginosa, Klebsiella spp., and Serratia spp.) were the most prevalent sputum and chest isolates, followed by Candida spp., while Gram-positive bacteria represented by S. aureus were the least prevalent.

Blood infections accounted for 13% of microbial isolates and were caused by both Gram-positive and Gram-negative bacteria as well as by certain yeast (C. albicans). The most commonly encountered bacteria were Gram-positive, represented by S. aureus and CON Staphylococcus spp., followed by Gram-negative bacteria that included E. gergoviae, E. coli, H. alvei, and K. ozaenae.

Moreover, wound infections from wound swab specimens represented 10% of microbial infections and were caused by both Gram-positive (S. aureus, CONS epidermidis, and S. pyogenes) and Gram-negative bacteria (E. coli and P. aeruginosa), while yeast were not identified in our study.

Table 3 Distribution of the identified microbial isolates on basis of the source of microbial isolates
Full size table

Antimicrobial resistance pattern

Resistance pattern in Gram-negative bacterial isolates

Twenty-four antibiotics were tested against Gram-negative bacterial isolates. Data in Table 4 revealed the resistance percentage of different Gram-negative bacterial isolates to different antibiotics used.

Different microbial infection isolates of Acinetobacter spp., S. rubidaea, and S. liquefaciens were secondary microbial infection from COVID-19 patients and showed high resistance rates between 80% and 100% towards different classes of antibiotics, including penicillins, cephalosporins, fluoroquinolones, protein synthesis inhibitors (amikacin, gentamicin, and chloramphenicol), carbapenems, and others combined antibiotics (ceftolozane/tazobactam, sulphamethoxazole/trimethoprim, and piperacillin/tazobactam). Additionally, they showed complete sensitivity towards glycylcycline.

H. alvei (blood isolate) and K. ozaenae from different specimens (urine, sputum, blood, and abscess isolates) have also complete resistance rates of 100% to most classes of antibiotics used, except for glycylcycline in K. ozaenae that was completely sensitive.

The majority of K. pneumoniae were urine and sputum clinical isolates. They reported complete resistance of 100% to penicillin, ampicillin, cefixime, and sulphamethoxazole/trimethoprim antibiotics as well as complete sensitivity of 100% to glycylcycline. In addition, resistance rates over 65% have been reported in sulbactam/ampicillin, cephalosporins (cefoperazone, ceftriaxone, cefotaxime, and cefepime), fluoroquinolones (ciprofloxacin, norfloxacin, and ofloxacin), and chloramphenicol. In comparison, low rates of resistance to carbapenems and combined antibiotics have been reported.

Indeed, E. coli showed resistance to penicillin, ampicillin, cefixime, and chloramphenicol at different rates of 100, 97, 89, and 46%, respectively. Furthermore, about third of isolates were resistant to amoxicillin-clavulanic acid, sulphamethoxazole/trimethoprim, cephalosporins (except for cefixime), and fluoroquinolones. In contrast, low resistance rates were reported towards carbapenems group, chloramphenicol, glycylcycline, and combined antibiotics.

Among the isolates, E. gergoviae were blood isolates and showed sensitivity to most of the used antibiotics, with the exception of penicillin, ampicillin, cefixime, and chloramphenicol. Moreover, half of the isolates were resistant to gentamicin and sulphamethoxazole/trimethoprim.

Additionally, P. mirabilis isolates were found in urine and abscesses specimens. They showed resistance rates between 67% and 100% to penicillin, ampicillin, sulphamethoxazole/trimethoprim, norfloxacin, ofloxacin, and gentamicin, while they had a resistance rate of 33% towards amoxicillin-clavulanic acid, sulbactam/ampicillin, cefixime, ciprofloxacin, chloramphenicol, ertapenem, and meropenem. On the other hand, P. mirabilis isolates were completely sensitive to cephalosporins.

The microbial isolates of P. aeruginosa were found in most specimens that included urine, blood, chest, and sputum isolates. All isolates were resistant to penicillins group, cefixime, chloramphenicol, and sulphamethoxazole/trimethoprim, while showing resistance rates between 50% and 75% towards cefoperazone, ceftriaxone, cefotaxime, cefepime, norfloxacin, ofloxacin, glycylcycline, ertapenem, and meropenem. In comparison, P. aeruginosa isolates showed a low resistance rate of 25% towards ceftazidime, ceftazidime-avibactam, and ceftolozane/tazobactam.

Table 4 Resistance degree of Gram-negative bacterial isolates to each antibiotic used
Full size table

Resistance pattern in Gram-positive bacterial isolates

Twenty-eight antibiotics were tested against Gram-positive bacterial isolates. Data in Table 5 revealed the resistance percentage of different Gram-positive bacterial isolates to different antibiotics used.

Most of S. aureus strains were blood and wound microbial isolates, with about half of the isolates being methicillin-resistant S. aureus (MRSA) strains. The microbial isolates of S. aureus showed a high resistance rate of 83.0% towards penicillin, ampicillin, and cefixime, while they showed moderate resistance (50%) to oxacillin, amoxicillin-clavulanic acid, ceftazidime, cefotaxime, fluoroquinolones (ciprofloxacin, norfloxacin, and ofloxacin), chloramphenicol, carbapenems (ertapenem and meropenem), ceftolozane/tazobactam, and sulphamethoxazole/trimethoprim.

The CON Staphylococcus spp. detected in our study were blood, wound, and abscess infection isolates, namely, S. epidermidis and S. saprophyticus. They showed high resistance rates of 100% to penicillin, 83% to ampicillin and cefixime both, and 50% to clindamycin, erythromycin, and oxacillin, while low rates of resistance were reported towards amoxicillin-clavulanic acid, sulbactam/ampicillin, cephalosporins (ceftazidime, cefoperazone, ceftriaxone, cefotaxime, and cefepime), fluoroquinolones, carbapenems, sulphamethoxazole/trimethoprim, and linezolid.

Streptococcus spp. microbial isolates in the present study included S. agalactiae (group B streptococcus) urine isolates and S. pyogenes (group A streptococcus) wound infection isolates. They showed complete sensitivity to most classes of antibiotics used, with the exception of penicillin, ampicillin, cefixime, amikacin, gentamicin, and sulphamethoxazole/trimethoprim, which recorded low resistant rates of 33%.

Table 5 Resistance degree of Gram-positive bacterial isolates to each antibiotic used
Full size table

Resistance pattern in Candida spp. microbial isolates

Five antifungals were tested against Candida spp. isolates on 2% glucose enriched Mueller-Hinton agar. Candida spp. showed a high resistance rate to azole drugs (fluconazole 88%, itraconazole 81%, and clotrimazole 75%) and terbinafine 81%. On the other hand, they were completely sensitive to polyene antifungal medication (nystatin) as indicated in Table 6.

Table 6 Resistance degree of Candida spp. isolates to different antifungals used
Full size table

Discussion

Healthcare-associated infection is a major problem in healthcare facilities and is associated with increased morbidity, mortality, prolonged hospital stays, and increased antimicrobial resistance [7, 18]. Over recent years, extensive exposure to antimicrobials has led to the emergence and widespread of MDR pathogens with developed mechanisms of resistance against β-lactams, cotrimoxazole, sulfamethoxazole/trimethoprim, nitrofurantoin, carbapenems, and fluoroquinolones [2, 4, 6].

In the current study, urine specimens were the most prevalent source of microbial infections, followed by COVID-19 patients’ specimens from sputum and chest swabs, blood, and wound infections. Urinary tract infection (UTI) is among the most common community- and hospital-associated microbial infections, affecting about 150 million people worldwide each year [19]. Chest and bloodstream infections are common conditions causing death and morbidity in humans of all ages, with a high burden on public health. These infections are frequent and present life-threatening conditions in hospital settings [8, 20]. Additionally, other studies reported the prevalence of microbial respiratory infections as secondary infections in patients with COVID-19 [21].

Most microbial infections were more prevalent in males and the elderly over 45-years of age. This is partly explained by an attenuation of the inflammatory response by sex hormones in females [22]. Bereshchenko et al. [23] declared that infectious disease incidence is often male-biased due to differences in sex hormones and genetic architecture. The differences in the distribution of infections among different patients’ ages could be related to the strength of the immune system response, which would be expected to decrease in elderly patients [24]. On the other hand, the majority of studies concluded the predominance of female UTI, as compared to male UTI, as in this study, in which UTI is known as the disease of females. The main reason might be an anatomical predisposition compared to males, which allow bacteria access to the bladder as well as poor personal hygiene [25, 26].

Analysis of the data from the current study revealed that uropathogenic E. coli was the most frequently identified in urine specimens. In line with our study, Seifu and Gebissa [27] reported Gram-negative bacteria as the predominant species in patients with UTIs. Moreover, other studies found that K. pneumoniae, P. mirabilis, S. saprophyticus, E. faecalis, group B Streptococcus (GBS), P. aeruginosa, S. aureus, and Candida spp. are particularly relevant as hospital-acquired and catheter-associated infectious agents [28].

Our findings also showed that Acinetobacter spp., P. aeruginosa, Klebsiella spp., and Serratia spp. were the most predominant sputum and chest COVID-19 patient isolates. Previous studies by Sharifipour et al. [29] focused on secondary infection in COVID-19 respiratory patients and found that A. baumannii was the most common pathogen, followed by S. aureus. On the other hand, other studies in 2014 and 2018 on non-COVID-19 patients reported A. baumannii in respiratory patients and were associated with other bacteria, including P. aeruginosa, Stenotrophomonas maltophilia, S. aureus, Enterococcus spp., and K. pneumonia [30]. In line with our results, Candida spp. was the most prevalent yeast isolate in respiratory samples and colonized the lower respiratory tract of mechanically ventilated patients [31].

In blood specimens, S. aureus and CON Staphylococcus spp. were the most commonly encountered Gram-positive bacteria, as in the study of Deku et al. [32], followed by Gram-negative bacteria and Candida spp. These findings were supported by Haddadin et al. [33] study, which found that C. albicans was the most common fungus involved in blood infections. In contrast to the present study, Khurana et al. [34] found that Acinetobacter spp. and Klebsiella spp. were the most common pathogens in bloodstream infections.

In wound infection, S. aureus, CON S. epidermidis, and S. pyogenes were the most frequently identified Gram-positive bacteria in the present study. Likewise, a prior study reported that S. aureus was the leading cause of wound infections, followed by P. aeruginosa, Bacillus spp., E. coli, Candida spp., and CON Staphylococcus spp. [35]. In comparison, other investigations found Gram-negative bacteria were the dominant in wound infection [36].

Considering the resistance pattern in Gram-negative bacterial isolates, Acinetobacter spp. from COVID-19 patients were extreme MDR isolates and showed complete resistance to most antibiotics, including β-lactams, cephalosporins, fluoroquinolones, and carbapenems, as reported in Sharifipour et al. [29] study, with the exception of glycylcycline (no resistance rate reported). However, lower rates of resistance to ceftazidime of 52.2% were recorded in a prior study [37]. In line with our study, a previous study by Namiganda et al. [38] reported that A. baumannii pulmonary strains were completely resistant to amikacin, ciprofloxacin, cotrimoxazole, ceftazidime, and piperacillin antibiotics, while 19% of isolates were sensitive to imipenem. Likewise, S. rubidaea and S. liquefaciens from COVID-19 patients were also extreme MDR isolates, and these were supported by the study of Namiganda et al. [38]. Serratia spp. isolates in our study showed high antimicrobial resistance levels when compared to Agyepong et al. [39] study. Early reports from Wuhan, China, indicated that half of the patients who died from COVID-19 developed secondary bacterial infections due to the high consumption of antibiotics during this viral pandemic [40, 41].

On the other hand, H. alvei and K. ozaenae were also extreme MDR strains and resisted all classes of antibiotics used, except for glycylcycline in K. ozaenae. However, Abbott et al. [42] reported different results and revealed H. alvei was susceptible at different rates to aminoglycosides, cephalosporins, monobactams, quinolones, and carbapenems. Moreover, another study reported H. alvei was resistant at different rates to amoxicillin (35%), cefoxitin (35%), ceftazidime (50%), and amikacin (40%), while it showed complete sensitivity to chloramphenicol [43]. In line with our study, Ghenea et al. [44] isolated K. ozaenae that was completely resistant to amoxicillin, ceftazidime, cefotoxime, amikacin, tetracycline, naldixic acid, erythromycin, and trimethoprim but sensitive only to imipenem and gentamicin, which contrasts our results.

K. pneumoniae clinical isolates in our study were extended spectrum β-lactam (ESBL) isolates, and these results were supported by the study conducted by Nirwati et al. [45] who found that K. pneumoniae was resistant to various antibiotics, including ampicillin, cefazolin, and cefuroxime, while amikacin, carbapenems, and piperacillin-tazobactam were the most favorable profile for treatment. The majority of the E. coli in our study was uropathogenic and showed resistance to penicillin, ampicillin, cefixime, and chloramphenicol antibiotics with different rates of 100, 97, 89, and 46%, respectively, which were consistent with previous studies [46, 47]. Additionally, E. coli showed good sensitivity to amikacin, glycylcycline, carbapenems (ertapenem and meropenem), ceftazidime-avibactam, ceftolozane/tazobactam, cefoperazone/sulbactam, and piperacillin/tazobactam, as reported by Scudeller et al. [48] study.

E. gergoviae isolates in our study were susceptible to most antibiotics, which contrasts with a previous study conducted by Friedrich et al. [49], who isolated E. gergoviae from bloodstream infections that were resistant to cefepime, carbapenems, piperacillin-tazobactam, aztreonam, and trimethoprim-sulfamethoxazole.

The high resistance rates of P. mirabilis isolates in the present study towards penicillin, ampicillin, sulphamethoxazole/trimethoprim, norfloxacin, ofloxacin, and gentamicin were reported to be at higher rates than in the Mirzaei et al. [50] study. On the other hand, P. mirabilis were completely sensitive to cephalosporins in our study; however, different resistance rates towards third-generation cephalosporins were reported in a previous study [51].

P. aeruginosa clinical isolates in the present study showed resistance rates of 100% towards penicillins, cefixime, chloramphenicol, and sulphamethoxazole/trimethoprim, and this was consistent with Motbainor et al. [52] findings. On the other hand, a low resistance rate to ceftazidime was reported in other studies in Ethiopia and Qatar, which were consistent with our results [53, 54]. The rates of P. aeruginosa resistance towards carbapenems (meropenem 50%) in the present study were coherent with other studies that documented resistance rates of 54, 45.5, and 41.7 in Bhatt et al. [55], Motbainor et al. [52], and Solomon et al. [53], respectively.

Considering the resistance pattern in Gram-positive bacterial isolates, about half of S. aureus were MRSA strains; these results were consistent with Taylor and Unakal [56] study. On the other hand, S. aureus reported a lower resistance rate of 13.4% towards oxacillin in Yılmaz and Aslantaş [57] reports that contrast our results. The ampicillin resistance rate (83.0%) in our study was consistent with the resistance rate findings of Yılmaz and Aslantaş [57] and Li et al. [58] studies but inconsistent with Gu et al. [59] study, which reported 49.2% resistance rates towards ampicillin and 17% towards gentamicin.

The resistance rate results of CON Staphylococcus in our study were supported by the study conducted by Xu et al. [60], who found that CON Staphylococcus isolates had high resistance rates to penicillin (94.7%), moderate resistance to oxacillin (52.6%), and low resistance to sulphamethoxazole-trimethoprim (33.9%). Furthermore, a low resistance rate of CON Staphylococcus towards linezolid has been reported in other studies that support our results [61]. On the other hand, high resistance rates to ciprofloxacin and amikacin were recorded in Adamus-Białek et al. [62] study, while low resistance rates towards clindamycin were found in Yılmaz and Aslantaş [57] study, which contrast our findings.

Streptococcus resistance rates of 33% towards penicillin and ampicillin in our study were relatively high compared to Rerambiah et al. [9] study. Penicillins are considered the first choice for the treatment of streptococcal infections [9]. More than 10% of patients reported an allergy to penicillin, leading to the use of macrolides as an alternative drug. Thus, the rates of macrolide resistance among Streptococcus spp. increased in North America [63].

Regarding the resistance pattern in Candida spp. clinical isolates, they showed high resistance rates to azole drugs. This resistance to azole drugs may be increased due to their general and long-term use in the treatment of Candida spp. [64]. The increase in Candida resistance to fluconazole is a matter of great concern, as it is the most commonly used azole for the treatment of candiduria [65]. On the other hand, all Candida isolates in our study were completely sensitive to polyene antifungal medication (nystatin), as reported in a previous study [66]. These results suggested nystatin could be used as an alternative drug for the treatment of azole-resistant Candida infections [67].

Finally, the high rates of resistance to azole drugs and most of the antibiotics used could be due to indiscriminate use, while the low rates of resistance to glycylcycline and nystatin antimicrobials could also be due to low prescription by physicians or low availability in different countries. The variation in results may be a result of the type and frequency of antibiotics used in different countries.

Conclusions

There is an increase in the proportion of resistant Gram-negative, Gram-positive, and Candida spp. microbial isolates to most commonly prescribed antimicrobials. The high resistance rates of Acinetobacter spp., Serratia spp. (secondary microbial infection from COVID-19 patients), H. alvei, and K. ozaenae to all used antibiotic classes except glycylcycline are a major concern that portends an inevitable catastrophe. Guided prescriptions of antimicrobial agents should be implemented and controlled in hospitals to avoid the development of new generations of highly resistant microbial infections. Glycylcycline has been recommended for the treatment of MDR Gram-negative and Gram-positive bacteria, while nystatin has been recommended for the treatment of candida infections. Finally, recording the pathogens responsible for different infections and their antimicrobial resistance profiles, conducting an annual count of them, and continuous monitoring of antibiotic usage are vital to curbing existing microbial infections and identifying antimicrobial resistance patterns.

Data Availability

All information created or analyzed during the present study are included in the manuscript.

Abbreviations

CON:

Coagulase Negative

CONS:

Coagulase Negative Staphylococci

ESBL:

Extended spectrum β-lactam antibiotic

MDR:

Multidrug resistant

MRSA:

Methicillin-resistant Staphylococcus aureus

UTIs:

Urinary tract infections

References

  1. Gidey K, Gidey MT, Hailu BY, Gebreamlak ZB, Niriayo YL. Clinical and economic burden of healthcare-associated infections: A prospective cohort study. Plos one. 2023;18(2):e0282141. https://doi.org/10.1371/journal.pone.0282141.

  2. Hassan R, El-Gilany AH, El-Mashad N, Azim DA. An overview of healthcare-associated infections in a tertiary care hospital in Egypt. Infection Prevention in Practice. 2020;2(3):100059. https://doi.org/10.1016/j.infpip.2020.100059.

  3. Stevens MP, Doll M, Pryor R, Godbout E, Cooper K, Bearman G. Impact of COVID-19 on traditional healthcare-associated infection prevention efforts. Infect Control Hosp Epidemiol. 2020;41(8):946–7. https://doi.org/10.1017/ice.2020.141.

  4. Dadgostar P. Antimicrobial resistance: implications and costs. Infection and drug resistance. 2019;20:3903–10. https://doi.org/10.2147/IDR.S234610.

    Article  Google Scholar 

  5. de Kraker ME, Stewardson AJ, Harbarth S. Will 10 million people die a year due to antimicrobial resistance by 2050?. PLoS Med 2016;13(11):e1002184. https://doi.org/10.1371/journal.pmed.1002184.

  6. Prestinaci F, Pezzotti P, Pantosti A. Antimicrobial resistance: a global multifaceted phenomenon. Pathogens and global health. 2015;109(7):309 – 18. https://doi.org/10.1179/2047773215Y.0000000030.

  7. Moustafa AA, Raouf MM, El-Dawy MS. Bacterial healthcare-associated infection rates among children admitted to Pediatric Intensive Care Unit of a Tertiary Care Hospital, Egypt. Alexandria Journal of Pediatrics. 2017;30(3):100. https://doi.org/10.4103/AJOP.AJOP_2_18.

  8. Sikora A, Zahra F. Nosocomial infections. InStatPearls [Internet] 2022 Feb 28. StatPearls Publishing. Available from: https://www.ncbi.nlm.nih.gov/books/NBK559312/.

  9. Rerambiah LK, Ndong JC, Massoua PM, Medzegue S, Elisee-Ndam M, Mintsa-Ndong A, Siawaya JF. Antimicrobial profiles of bacterial clinical isolates from the Gabonese National Laboratory of Public Health: data from routine activity. International Journal of Infectious Diseases. 2014;29:48–53. Available from: https://pubmed.ncbi.nlm.nih.gov/25449235/.

  10. Faksri K, Kaewkes W, Chaicumpar K, Chaimanee P, Wongwajana S. Epidemiology and identification of potential fungal pathogens causing invasive fungal infections in a tertiary care hospital in northeast Thailand. Medical Mycology. 2014;52(8):810-8. Available from: https://pubmed.ncbi.nlm.nih.gov/25231771/.

  11. Mishra MP, Debata NK, Padhy RN. Surveillance of multidrug resistant uropathogenic bacteria in hospitalized patients in Indian. Asian Pacific journal of tropical biomedicine. 2013;3(4):315 – 24. https://doi.org/10.1016/S2221-1691(13)60071-4.

  12. Tan GL, Peterson EM. CHROMagar Candida medium for direct susceptibility testing of yeast from blood cultures. Journal of clinical microbiology. 2005;43(4):1727-31. Available from: https://pubmed.ncbi.nlm.nih.gov/15814992/.

  13. Spanu T, Sanguinetti M, Ciccaglione D, D’Inzeo T, Romano L, Leone F, Fadda G. Use of the VITEK 2 system for rapid identification of clinical isolates of staphylococci from bloodstream infections. J Clin Microbiol. 2003;41(9):4259–63. https://doi.org/10.1128/JCM.41.9.4259-4263.2003.

  14. Nassar MS, Hazzah WA, Bakr WM. Evaluation of antibiotic susceptibility test results: how guilty a laboratory could be?. Journal of the Egyptian Public Health Association. 2019;94(1):1–5. Available from: https://jepha.springeropen.com/articles/https://doi.org/10.1186/s42506-018-0006-1.

  15. Clinical and Laboratory Standards Institute. Performance standards for antimicrobial susceptibility testing. 30th ed. CLSI supplement M100. Wayne, PA: CLSI. 2020. Available from: https://www.nih.org.pk/wp-content/uploads/2021/02/CLSI-2020.pdf.

  16. Khadka S, Sherchand JB, Pokhrel BM, Parajuli K, Mishra SK, Sharma S, Shah N, Kattel HP, Dhital S, Khatiwada S, Parajuli N. Isolation, speciation and antifungal susceptibility testing of Candida isolates from various clinical specimens at a tertiary care hospital, Nepal. BMC research notes. 2017;10(1):1–5. Available from: https://bmcresnotes.biomedcentral.com/articles/https://doi.org/10.1186/s13104-017-2547-3.

  17. Weinstein MP, Patel JB, Bobenchik AM, Campeau S, Cullen SK, Galas MF, Gold H, Humphries RM, Kirn TJ, Lewis Ii JS, Limbago B. M100 Performance Standards for Antimicrobial Susceptibility Testing A CLSI supplement for global application. Performance standards for antimicrobial susceptibility testing performance standards for antimicrobial susceptibility testing. 2020. Available from: https://clsi.org/media/3481/m100ed30_sample.pdf.

  18. World Health Organization (WHO). Antibiotic Resistance. 2020. Available online at: https://www.who.int/news-room/fact-sheets/detail/antibiotic-resistance.

  19. Fordyce CB, Katz JN, Alviar CL, Arslanian-Engoren C, Bohula EA, Geller BJ, Hollenberg SM, Jentzer JC, Sims DB, Washam JB, van Diepen S. Prevention of complications in the cardiac intensive care unit: a scientific statement from the American Heart Association. Circulation. 2020;142(22):e379-406. Available from: https://www.ahajournals.org/doi/suppl/10.1161/CIR.0000000000000909.

  20. Dat VQ, Vu HN, Nguyen The H, Nguyen HT, Hoang LB, Vu Tien Viet D, Bui CL, Van Nguyen K, Nguyen TV, Trinh DT, Torre A. Bacterial bloodstream infections in a tertiary infectious diseases hospital in Northern Vietnam: aetiology, drug resistance, and treatment outcome. BMC infectious diseases. 2017;17:1–1. Available from: https://link.springer.com/articles/https://doi.org/10.1186/s12879-017-2582-7.

  21. Langford BJ, So M, Raybardhan S, Leung V, Westwood D, MacFadden DR, Soucy JP, Daneman N. Bacterial co-infection and secondary infection in patients with COVID-19: a living rapid review and meta-analysis. Clinical microbiology and infection. 2020;26(12):1622-9. https://doi.org/10.1016/j.cmi.2020.07.016.

  22. Mege JL, Bretelle F, Leone M. Sex and bacterial infectious diseases. New microbes and new infections. 2018;26:S100-3. https://doi.org/10.1016/J.NMNI.2018.05.010.

  23. Bereshchenko O, Bruscoli S, Riccardi C. Glucocorticoids, sex hormones, and immunity. Frontiers in immunology. 2018;9:1332. https://doi.org/10.3389/FIMMU.2018.01332/BIBTEX.

  24. Lawton G. You’re only as young as your immune system. New Scientist. 2020;245(3275):44 – 8. https://doi.org/10.1016/S0262-4079(20)30646-1.

  25. Vasudevan R. Urinary tract infection: an overview of the infection and the associated risk factors. J Microbiol Exp. 2014;1(2):00008. Available from: https://medcraveonline.com/JMEN/JMEN-01-00008.php.

  26. Storme O, Tirán Saucedo J, Garcia-Mora A, Dehesa-Dávila M, Naber KG. Risk factors and predisposing conditions for urinary tract infection. Therapeutic advances in urology. 2019;11:1756287218814382. https://doi.org/10.1177/1756287218814382.

  27. Seifu WD, Gebissa AD. Prevalence and antibiotic susceptibility of Uropathogens from cases of urinary tract infections (UTI) in Shashemene referral hospital, Ethiopia. BMC infectious diseases. 2018;18:1–9. Available from: https://bmcinfectdis.biomedcentral.com/articles/https://doi.org/10.1186/s12879-017-2911-x.

  28. Kline KA, Lewis AL. Gram-positive uropathogens, polymicrobial urinary tract infection, and the emerging microbiota of the urinary tract. Urinary tract infections: molecular pathogenesis and clinical management. 2017:459–502. https://doi.org/10.1128/MICROBIOLSPEC.UTI-0012-2012.

  29. Sharifipour E, Shams S, Esmkhani M, Khodadadi J, Fotouhi-Ardakani R, Koohpaei A, Doosti Z, Ej Golzari S. Evaluation of bacterial co-infections of the respiratory tract in COVID-19 patients admitted to ICU. BMC infectious diseases. 2020;20(1):1–7. Available from: https://bmcinfectdis.biomedcentral.com/articles/https://doi.org/10.1186/s12879-020-05374-z.

  30. Mahendra M, Jayaraj BS, Lokesh KS, Chaya SK, Veerapaneni VV, Limaye S, Dhar R, Swarnakar R, Ambalkar S, Mahesh PA, Indian Society of Critical Care Medicine. Antibiotic prescription, organisms and its resistance pattern in patients admitted to respiratory ICU with respiratory infection in Mysuru. Indian Journal of Critical Care Medicine: Peer-reviewed, Official Publication of. 2018;22(4):223. Available from: https://pubmed.ncbi.nlm.nih.gov/29743760/.

  31. Timsit JF, Schwebel C, Styfalova L, Cornet M, Poirier P, Forrestier C, Ruckly S, Jacob MC, Souweine B. Impact of bronchial colonization with Candida spp. on the risk of bacterial ventilator-associated pneumonia in the ICU: the FUNGIBACT prospective cohort study. Intensive care medicine. 2019;45:834 – 43. https://doi.org/10.1007/S00134-019-05622-0.

  32. Deku JG, Dakorah MP, Lokpo SY, Orish VN, Ussher FA, Kpene GE, Angmorkie Eshun V, Agyei E, Attivor W, Osei-Yeboah J. The epidemiology of bloodstream infections and antimicrobial susceptibility patterns: A nine-year retrospective study at St. Dominic Hospital, Akwatia, Ghana. Journal of tropical medicine. 2019;2019. Available from: https://pubmed.ncbi.nlm.nih.gov/31641359/.

  33. Haddadin Y, Annamaraju P, Regunath H. Central line associated blood stream infections. 2017. Available from: https://www.ncbi.nlm.nih.gov/books/NBK430891/.

  34. Khurana S, Bhardwaj N, Kumari M, Malhotra R, Mathur P. Prevalence, etiology, and antibiotic resistance profiles of bacterial bloodstream infections in a tertiary care hospital in Northern India: a 4-year study. Journal of laboratory physicians. 2018;10(04):426 – 31. Available from: http://www.thieme-connect.de/DOI/DOI?10.4103/JLP.JLP_78_1.

  35. Akinkunmi EO, Adesunkanmi AR, Lamikanra A. Pattern of pathogens from surgical wound infections in a Nigerian hospital and their antimicrobial susceptibility profiles. African health sciences. 2014;14(4):802-9. Available from: http://www.thieme-connect.de/DOI/DOI?10.4103/JLP.JLP_78_18.

  36. Hassan MA, Abd El-Aziz S, Elbadry HM, Samy A, Tamer TM. Prevalence, antimicrobial resistance profile, and characterization of multi-drug resistant bacteria from various infected wounds in North Egypt. Saudi Journal of Biological Sciences. 2022;29(4):2978-88. https://doi.org/10.1016/j.sjbs.2022.01.015.

  37. Bahrami S, Shafiee F, Hakamifard A, Fazeli H, Soltani R. Antimicrobial susceptibility pattern of carbapenemase-producing Gram-negative nosocomial bacteria at Al Zahra hospital, Isfahan, Iran. Iran J Microbiol 2021;13(1):50. https://doi.org/10.18502/IJM.V13I1.5492.

  38. Namiganda V, Mina Y, Meklat A, Touati D, Bouras N, Barakate M, Sabaou N. Antibiotic Resistance Pattern of Acinetobacter baumannii strains isolated from different clinical specimens and their sensibility against bioactive molecules produced by Actinobacteria. Arabian Journal for Science and Engineering. 2019;44:6267-75. Available from: https://link.springer.com/article/https://doi.org/10.1007/s13369-019-03893-9.

  39. Agyepong N, Govinden U, Owusu-Ofori A, Essack SY. Multidrug-resistant gram-negative bacterial infections in a teaching hospital in Ghana. Antimicrob Resist Infect Control 2018;7(1):1–8. https://doi.org/10.1186/S13756-018-0324-2.

  40. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, Xiang J, Wang Y, Song B, Gu X, Guan L. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. The lancet. 2020;395(10229):1054-62. https://doi.org/10.1016/S0140-6736(20)30566-3.

  41. Nag VL, Kaur N. Superinfections in COVID-19 patients: role of antimicrobials. Dubai Medical Journal. 2021;4(2):117 – 26. Available from: https://www.karger.com/Article/FullText/515067.

  42. Abbott SL, Moler S, Green N, Tran RK, Wainwright K, Janda JM. Clinical and laboratory diagnostic characteristics and cytotoxigenic potential of Hafnia alvei and Hafnia paralvei strains. J Clin Microbiol. 2011;49(9):3122–6. https://doi.org/10.1128/JCM.00866-11.

  43. Singh AK, Das S, Kumar S, Gajamer VR, Najar IN, Lepcha YD, Tiwari HK, Singh S. Distribution of antibiotic-resistant Enterobacteriaceae pathogens in potable spring water of eastern Indian Himalayas: emphasis on virulence gene and antibiotic resistance genes in Escherichia coli. Frontiers in Microbiology. 2020;11:581072. Available from: https://doi.org/10.3389/FMICB.2020.581072/FULL.

  44. Ghenea AE, Cioboată R, Drocaş AI, Țieranu EN, Vasile CM, Moroşanu A, Țieranu CG, Salan AI, Popescu M, Turculeanu A, Padureanu V. Prevalence and antimicrobial resistance of Klebsiella strains isolated from a county hospital in Romania. Antibiot 2021;10(7):868. https://doi.org/10.3390/ANTIBIOTICS10070868.

  45. Nirwati H, Sinanjung K, Fahrunissa F, Wijaya F, Napitupulu S, Hati VP, Hakim MS, Meliala A, Aman AT, Nuryastuti T. Biofilm formation and antibiotic resistance of Klebsiella pneumoniae isolated from clinical samples in a tertiary care hospital, Klaten, Indonesia. InBMC proceedings 2019; 13(11):1–8. BioMed Central. https://doi.org/10.1186/S12919-019-0176-7.

  46. Raeispour M, Ranjbar R. Antibiotic resistance, virulence factors and genotyping of Uropathogenic Escherichia coli strains. Antimicrobial Resistance & Infection Control. 2018;7(1):1–9. Available from: https://pubmed.ncbi.nlm.nih.gov/30305891/.

  47. Aabed K, Moubayed N, Alzahrani S. Antimicrobial resistance patterns among different Escherichia coli isolates in the Kingdom of Saudi Arabia. Saudi journal of biological sciences. 2021;28(7):3776-82. Available from: https://doi.org/10.1016/j.sjbs.2021.03.047.

  48. Scudeller L, Righi E, Chiamenti M, Bragantini D, Menchinelli G, Cattaneo P, Giske CG, Lodise T, Sanguinetti M, Piddock LJ, Franceschi F. Systematic review and meta-analysis of in vitro efficacy of antibiotic combination therapy against carbapenem-resistant Gram-negative bacilli. International journal of antimicrobial agents. 2021;57(5):106344. https://doi.org/10.1016/J.IJANTIMICAG.2021.106344.

  49. Friedrich R, Rappold E, Bogdan C, Held J. Comparative analysis of the Wako β-glucan test and the Fungitell assay for diagnosis of candidemia and Pneumocystis jirovecii pneumonia. Journal of Clinical Microbiology. 2018;56(9):e00464-18. Available from: https://pubmed.ncbi.nlm.nih.gov/29899003/.

  50. Mirzaei A, Habibi M, Bouzari S, Asadi Karam MR. Characterization of antibiotic-susceptibility patterns, virulence factor profiles and clonal relatedness in Proteus mirabilis isolates from patients with urinary tract infection in Iran. Infection and drug resistance. 2019:3967–79. https://doi.org/10.2147/IDR.S230303.

  51. Moremi N, Claus H, Mshana SE. Antimicrobial resistance pattern: a report of microbiological cultures at a tertiary hospital in Tanzania. BMC Infect Dis. 2016;16(1):1–7. https://doi.org/10.1186/s12879-016-2082-1.

  52. Motbainor H, Bereded F, Mulu W. Multi-drug resistance of blood stream, urinary tract and surgical site nosocomial infections of Acinetobacter baumannii and Pseudomonas aeruginosa among patients hospitalized at Felegehiwot referral hospital, Northwest Ethiopia: a cross-sectional study. BMC infectious diseases. 2020;20:1–1. Available from: https://pubmed.ncbi.nlm.nih.gov/32000693/.

  53. Solomon FB, Wadilo F, Tufa EG, Mitiku M. Extended spectrum and metalo beta-lactamase producing airborne Pseudomonas aeruginosa and Acinetobacter baumanii in restricted settings of a referral hospital: a neglected condition. Antimicrob Resist Infect Control. 2017;6:1–7. https://doi.org/10.1186/s13756-017-0266.

  54. Sid Ahmed MA, Abdel Hadi H, Hassan AA, Abu Jarir S, Al-Maslamani MA, Eltai NO, Dousa KM, Hujer AM, Sultan AA, Soderquist B, Bonomo RA. Evaluation of in vitro activity of ceftazidime/avibactam and ceftolozane/tazobactam against MDR Pseudomonas aeruginosa isolates from Qatar. Journal of Antimicrobial Chemotherapy. 2019;74(12):3497 – 504. Available from: https://pubmed.ncbi.nlm.nih.gov/31504587/.

  55. Bhatt P, Rathi KR, Hazra S, Sharma A, Shete V. Prevalence of multidrug resistant Pseudomonas aeruginosa infection in burn patients at a tertiary care centre. Indian Journal of Burns. 2015;23(1):56. https://doi.org/10.4103/0971-653X.171656.

  56. Taylor TA, Unakal CG. Staphylococcus aureus. In StatPearls [Internet]. StatPearls Publishing. 2022. Available from: https://www.ncbi.nlm.nih.gov/books/NBK441868/.

  57. Yılmaz E, Aslantaş Ö. Antimicrobial resistance and underlying mechanisms in Staphylococcus aureus isolates. Asian Pacific journal of tropical medicine. 2017;10(11):1059-64. https://doi.org/10.1016/J.APJTM.2017.10.003.

  58. Li L, Dai JX, Xu L, Chen ZH, Li XY, Liu M, Wen YQ, Chen XD. Antimicrobial resistance and pathogen distribution in hospitalized burn patients: a multicenter study in Southeast China. Medicine. 2018;97(34). https://doi.org/10.1097/MD.0000000000011977.

  59. Gu F, He W, Xiao S, Wang S, Li X, Zeng Q, Ni Y, Han L. Antimicrobial resistance and molecular epidemiology of Staphylococcus aureus causing bloodstream infections at Ruijin Hospital in Shanghai from 2013 to 2018. Scientific reports. 2020;10(1):1–8. Available from: https://pubmed.ncbi.nlm.nih.gov/32265473/.

  60. Xu Z, Shah HN, Misra R, Chen J, Zhang W, Liu Y, Cutler RR, Mkrtchyan HV. The prevalence, antibiotic resistance and mecA characterization of coagulase negative staphylococci recovered from non-healthcare settings in London, UK. Antimicrobial Resistance & Infection Control. 2018;7:1 – 0. Available from: https://aricjournal.biomedcentral.com/articles/https://doi.org/10.1186/s13756-018-0367-4.

  61. Xu Y, Wang B, Zhao H, Wang X, Rao L, Ai W, Yu J, Guo Y, Wu X, Yu F, Chen S. In vitro activity of vancomycin, teicoplanin, linezolid and daptomycin against methicillin-resistant Staphylococcus aureus isolates collected from chinese hospitals in 2018–2020. Infection and drug resistance. 2021:5449–56. https://doi.org/10.2147/IDR.S340623.

  62. Adamus-Białek W, Wawszczak M, Arabski M, Majchrzak M, Gulba M, Jarych D, Parniewski P, Głuszek S. Ciprofloxacin, amoxicillin, and aminoglycosides stimulate genetic and phenotypic changes in uropathogenic Escherichia coli strains. Virulence. 2019;10(1):260 – 76. https://doi.org/10.1080/21505594.2019.1596507.

  63. Biedenbach DJ, Toleman MA, Walsh TR, Jones RN. Characterization of fluoroquinolone-resistant β-hemolytic Streptococcus spp. isolated in North America and Europe including the first report of fluoroquinolone-resistant Streptococcus dysgalactiae subspecies equisimilis: report from the SENTRY Antimicrobial Surveillance Program (1997–2004). Diagnostic microbiology and infectious disease. 2006;55(2):119 – 27. https://doi.org/10.1016/J.DIAGMICROBIO.2005.12.006.

  64. Bhattacharya S, Sae-Tia S, Fries BC. Candidiasis and mechanisms of antifungal resistance. Antibiotics. 2020;9(6):312. https://doi.org/10.3390/ANTIBIOTICS9060312.

  65. Yashavanth R, Shiju MP, Bhaskar UA, Ronald R, Anita KB. Candiduria: prevalence and trends in antifungal susceptibility in a tertiary care hospital of Mangalore. J Clin Diagn Research: JCDR. 2013;7(11):2459. https://doi.org/10.7860/JCDR/2013/6298.3578.

  66. Shaban S, Patel M, Ahmad A. Improved efficacy of antifungal drugs in combination with monoterpene phenols against Candida auris. Scientific reports. 2020;10(1):1162. Available from: https://www.nature.com/articles/s41598-020-58203-3.

  67. Quindós G, Gil-Alonso S, Marcos-Arias C, Sevillano E, Mateo E, Jauregizar N, Eraso E. Therapeutic tools for oral candidiasis: current and new antifungal drugs. Medicina oral, patologia oral y cirugia bucal. 2019;24(2):e172. https://doi.org/10.4317/MEDORAL.22978.

Download references

Acknowledgements

None.

Funding

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB). This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Botany and Microbiology Department, Faculty of Science for Girls, Al-Azhar University, Cairo, Egypt

    Asmaa K. Helmy & Nagwa M. Sidkey

  2. Medical lab specialist, Cleopatra hospital, Cairo, Egypt

    Ramy E. El-Badawy

  3. Zoonotic Diseases Department, National Research Centre, Dokki, Giza, Egypt

    Ahmed G. Hegazi

Authors
  1. Asmaa K. Helmy
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nagwa M. Sidkey
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ramy E. El-Badawy
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ahmed G. Hegazi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

NMS and AGH developed and supervised the work. NMS, AGH, AKH and REE designed the study. AKH and REE collected, analyzed and interpreted the data. AKH wrote the first draft of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Asmaa K. Helmy.

Ethics declarations

Competing interests

The authors have declared that no competing interest exists.

Ethics approval and consent to participate

Not applicable. This manuscript does not refer to or imply the use of any animal or human data or tissues. The research is based on the analysis of the data extracted from the laboratory information systems. Data were analyzed nameless, and results could not be traced back to individual patients.

Consent for publication

Not applicable.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Helmy, A.K., Sidkey, N.M., El-Badawy, R.E. et al. Emergence of microbial infections in some hospitals of Cairo, Egypt: studying their corresponding antimicrobial resistance profiles. BMC Infect Dis 23, 424 (2023). https://doi.org/10.1186/s12879-023-08397-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12879-023-08397-4

Keywords

BMC Infectious Diseases

ISSN: 1471-2334

Contact us