Bacterial Profile and Antimicrobial Resistance Pattern from Different Clinical Specimens at Uttara Adhunik Medical College Hospital, Dhaka

Abstract

Introduction: Antimicrobial resistance (AMR) is a critical global public health issue, leading to prolonged illness, increased morbidity and mortality, and rising healthcare costs. The effectiveness of antibiotics is diminishing due to the emergence of resistant bacterial strains. This study aimed to determine the bacterial profile and AMR patterns of clinical isolates at Uttara Adhunik Medical College Hospital (UAMCH), Dhaka. Methods: A retrospective study was conducted at UAMCH from January 2017 to December 2019. A total of 32,187 clinical specimens (urine, blood, stool, wound swabs/pus, and sputum) were processed, of which 4232 yielded positive cultures. Bacterial identification followed standard bacteriological methods, and antibiotic susceptibility was assessed using the Kirby–Bauer disc diffusion method per CLSI guidelines. Data analysis was conducted using WHONET and QAAPT. Results: The highest proportion of positive cultures was from urine (47.5%), followed by blood (35.0%) and wound swabs/pus (10.1%). The most common isolates were Escherichia coli (37.2%), Salmonella typhi (25.7%), and Klebsiella sp. (11.5%). Gram-negative bacteria showed high resistance to commonly used antibiotics such as amoxicillin/clavulanic acid, cefixime, and ceftriaxone, while the resistance rates were lower for gentamicin, amikacin, and meropenem. However, Acinetobacter sp. exhibited alarming resistance to all tested antibiotics. Conclusions: This study highlights concerning resistance patterns among bacterial isolates, emphasizing the need for ongoing AMR surveillance to inform treatment strategies and improve patient care in Bangladesh.

1. Introduction

Antimicrobials are medicines used to treat infections or diseases, which are essential in both human and animal health. Antimicrobial resistance (AMR) occurs when microorganisms change over time and no longer respond to medicines, making infections harder to treat and increasing the risk of severe illness and death [1]. The development of resistance among microorganisms or ‘superbugs’ is a natural phenomenon that will inevitably occur when antimicrobials are used to treat disease [1]. Antimicrobial resistance, especially resistance to antibiotics, has emerged as one of the leading public health threats of the 21st century [1]. Infections caused by resistant bacteria adversely affect treatment outcomes, costs, disease spread and duration of illnesses, posing a serious challenge to future chemotherapies [2].

The AMR problem is challenging in developing countries because of the widespread misuse of antibiotics, non-human antibiotic use, poor quality of drugs, inadequate surveillance, and factors associated with individual and national poverty indicators [3]. The lack of clinical microbiology laboratories to identify the specific etiologic agents and their antimicrobial susceptibility testing has increased empirical therapy, leading to the emergence of AMR.

The World Health Organization (WHO) declared antimicrobial resistance as one of the serious health threats at the global level. Globally, AMR is believed to cause approximately 700,000 deaths per year [4]. In 2019, a total of 4.95 million casualties were associated with AMR, of which 1.27 million deaths occurred due to bacterial AMR in the world, and the six leading pathogens for deaths associated with resistance were Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa [5]. It is estimated that failing to tackle AMR could cause 10 million deaths every year by 2050 [4].

Bangladesh, a developing country of Southeast Asia with a high prevalence of antibiotic resistance, poses a regional and global threat. Up-to-date information about the bacterial profile, monitoring AMR patterns, and the leading pathogen–drug combinations contributing to bacterial AMR burden is crucial to guide empiric antibiotic treatment strategies, rational use of the existing antimicrobials, and infection control programs. In this study, retrospective data were utilized to analyze a large number of samples over an extended period to provide an accurate understanding of the patterns and extent of AMR. Therefore, the present study aimed to determine the bacterial profile and antimicrobial resistance patterns of bacterial isolates from different clinical specimens at Uttara Adhunik Medical College Hospital (UAMCH), Dhaka.

2. Materials and Methods

2.1. Study Design and Setting

A retrospective study was carried out at UAMCH in Bangladesh to analyze pre-recorded data from the period of January 2017 to December 2019. The Capturing data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project funded by the Fleming Fund (a regional grant) supported the digitization of the data [6]. Patients’ data were obtained from the Microbiology laboratory at UAMCH for all specimens collected from both inpatients and outpatients. During the study period from September 2020 to December 2022, a total of 32,187 clinical specimens from the infection site were received. All clinical samples were collected following standard microbiological techniques.

2.2. Isolation and Identification of Bacteria

Clinical specimens (urine, blood, stool, wound swab/pus, and sputum) were transported to the microbiology lab within 2 h. Based on sample type, the specimens were plated onto appropriate media: MacConkey, Blood, and Chocolate agar for blood, wound swab/pus, and sputum; MacConkey and TCBS agar for stool; and CLED agar for urine. The plates were incubated aerobically at 35 °C for 18–24 h.

Blood samples were inoculated into blood culture bottles immediately after collection and processed using the BD BACTEC FX40 automated system (Becton Dickinson, Franklin Lakes, NJ, USA). Positive cultures were sub-cultured on MacConkey, Blood, and Chocolate agar, with Chocolate agar incubated in a candle jar (5–10% CO₂). Bacterial species were identified using standard morphological, Gram staining, and biochemical tests, including indole, urease, oxidase, triple sugar iron agar, citrate utilization, and motility tests for Gram-negative bacteria, while Gram-positive bacteria were identified by Gram reaction, hemolysis, catalase, and coagulase tests.

2.3. Antimicrobial Susceptibility Testing

Following bacterial identification, antimicrobial susceptibility testing (AST) was performed using the Kirby–Bauer disk diffusion method on Mueller–Hinton agar, following the Clinical & Laboratory Standards Institute (CLSI) 2019 guidelines. Mueller–Hinton agar and antimicrobial discs were obtained from Oxoid Ltd., Basingstoke, Hampshire, UK.

2.4. Data Collection Tools

During the specified period (2017–2019), the laboratory maintained manual registers containing patient identifiers, demographic information, and laboratory test results. The WHONET software version 23.17.30 [7], developed by the WHO Collaboration Center for AMR Surveillance, was installed and configured in this laboratory. Training was also provided to the laboratory technologists to enable them to collect Antimicrobial Susceptibility Testing (AST) data using the software.

2.5. Data Management and Statistical Analysis

Data were entered and curated, and demographic characteristics were analyzed by using the WHONET software. The patterns and trends were analyzed using the Quick Analysis of Antimicrobial Patterns and Trends (QAAPT) web application [8]. For calculating the resistance percentage, only the first isolate per patient was considered, following CLSI 39 guidelines.

2.6. Sampling Technique and Sample Size

A convenient sampling technique was employed, resulting in 5602 individual records in different categories such as growth, mixed bacterial species, normal flora, no pathogen detected, and no Salmonella found (n = 1370). After excluding the contaminated samples, we identified 4232 culture-positive isolates and 26,585 culture-negative cases (Figure 1).

2.7. Inclusion and Exclusion Criteria

All isolates from the inpatients and outpatients of the hospital over the study period were included in this study. Incomplete and missing records (age and sex), and specimens other than the aforementioned six were excluded (Figure 1).

2.8. Quality Control

To control the quality of culture and drug susceptibility testing, the American Type Culture Collection (ATCC) isolates of E. coli (ATCC25922), S. aureus (ATCC-25923) and Pseudomonas aeruginosa (ATCC 27853) were used as reference strains. The data were thoroughly reviewed by experienced microbiologists and data management specialists using WHONET standard reports.

3. Results

3.1. Profile of Patients, Clinical Specimens, and Bacterial Isolates

Clinical specimens were collected from 4232 patients; females accounted for 54.2% (n = 2295). Most of the patients were in the age category of 15–24 years old (19.4%, n = 820). Most of the isolates were from medicine wards (78.3%, n = 3315), followed by surgery (8.7%, n = 369), intensive care unit (ICU) (4.9%, n = 210) and pediatrics (3.6%, n = 153). Among the 4232 patients, a total of 1063 (25.1%) samples were collected in 2017, 1620 (38.3%) in 2018 and 1549 (36.6%) in 2019. Their mean age ± standard deviation was 34 years, nearly 76.8% of them were adults, and the majority, 54.2%, were female (

Table 1. Characteristics of the study participants (only positive, n = 4232).

Characteristics	Frequency n = 4232	Percentage (%)
Gender
Male	1937	45.77
Female	2295	54.22
Age group
<1	68	1.60
1–4 Years	157	3.71
5–14 Years	452	10.68
15–24 Years	820	19.37
25–34 Years	603	14.25
35–44 Years	403	9.52
45–54 Years	442	10.44
55–69 Years	768	18.15
70+ Years	519	12.26
Age category
Adult	3253	76.86
Pediatric	979	23.13
Yearly AST
2017	1063	25.12
2018	1620	38.28
2019	1549	36.60
Location type
Inpatient	1971	46.57
Outpatient	2261	53.43
Department
Medicine	3315	78.33
Surgery	369	8.72
Intensive Care Unit	210	4.96
Pediatrics	153	3.62
Obstetrics/Gynecology	73	1.72
Neonatal	67	1.58
Coronary Care Unit	33	0.78
Orthopedic	10	0.24
Neonatal Intensive Care Unit	2	0.04
Specimen type
Urine	2009	47.47
Blood	1500	35.44
Wound swab/pus	426	10.06
Sputum	225	2.36
Stool	44	1.04
Genital	22	0.52
Other	6	0.14

).

Urine samples made up the majority of specimens (50.8%, n = 16,363). Similarly, Figure 2b shows that urine samples had the highest percentage of positive cultures (47.5%, n = 2009), followed by blood (35.0%, n = 1500), wound swab/pus (10.1%, n = 426) and sputum (5.3%, n = 225).

3.2. Bacterial Isolates and Frequency of Organisms

Figure 3 demonstrates that E. coli was the most frequent isolate, accounting for 37.2% (n = 1574), followed by Salmonella Typhi (25.7%, n = 1089), Klebsiella sp. (11.5%, n = 487), Salmonella Paratyphi A (6.38%, n = 270), Staphylococcus aureus (4.2%, n = 178), and Enterobacter sp. (3.6%, n = 152).

Figure 4 shows that E. coli, Salmonella typhi, Staphylococcus aureus, Klebsiella pneumoniae were the top four organisms found in urine, blood, wound swab and sputum, respectively.

3.3. Antibiotic Resistance Patterns of Bacterial Isolates

Table 2. Antimicrobial resistance patterns.

Antibiotics/Organisms	Gram-Negative Organism					Gram-Positive Organism
	E. coli (%)	Klebsiella sp. (%)	Enterobacterus sp. (%)	Pseudomonas sp. (%)	Acinetobacter sp. (%)	Salmonella sp. (%)	S. aureus (%)	Enterococcus sp. (%)
Amikacin	5.06 (76/1501)	19.79 (94/475)	22.92 (33/144)	33.33 (34/102)	53.73 (36/67)	-	-	-
Amoxicillin/Clavulanic acid	71.49 (1096/1533)	65.91 (319/484)				-	-	-
Ampicillin	-	-	-	-	-	26.77 (166/620)	-	-
Azithromycin	-	-	-	-	-	85.21 (1158/1359)	69.01 (118/171)	-
Aztreonam	62.11 (900/1449)	56.37 (261/463)	62.24 (89/143)	60.40 (61/101)		-	-	-
Cefepime	58.06 (72/124)	61.47 (67/109)	46.15 (18/39)	18.03 (11/61)	75.76 (25/33)	-	-	-
Cefixime	65.08 (1014/1558)	58.59 (283/483)	64.90 (98/151)		90.77 (59/65)	-	-	-
Cloxacillin			-	-	-	-	5.93 (8/135)	-
Ceftazidime	-		57.82 (85/147)	52.04 (51/98)	74.24 (49/66)	-	-	-
Ceftriaxone	60.25 (929/1542)	55.46 (264/476)	54.97 (83/151)		80.30 (53/66)	0.29 (4/1361)	-	-
Cefuroxime	64.17 (908/1415)	60.26 (282/468)	63.89 (92/144)		81.54 (53/65)		-	-
Chloramphenicol	-	-	-	-	-	17.2 (232/1349)	-	-
Ciprofloxacin	54.37 (846/1556)	40.75 (196/481)	44.74 (68/152)	39.42 (41/104)	57.58 (38/66)	26.59 (360/1354)	50.87 (88/173)	49.29 (69/140)
Gentamicin	17.87 (272/1522)	24.90 (119/478)	33.11 (50/151)	37.00 (37/100)	56.06 (37/66)	-	2.98 (5/168)	58.91 (76/129)
Levofloxacin	52.86 (803/1519)	34.86 (167/479)	32.88 (48/146)	38.61 (39/101)	51.56 (33/64)	-	-	-
Mecillinam (Amdinocillin)	21.92 (294/1341)	-	39.71 (27/68)	-	-	-	-	-
Meropenem	1.47 (22/1497)	15.43 (73/473)	9.03 (13/144)	21.36 (22/103)	46.15 (30/65)	-	-	-
Netilmicin	7.92 (118/1490)	22.80 (106/465)	24.49 (36/147)	29.00 (29/100)	38.81 (26/67)	-	-	-
Nitrofurantoin	12.76 (168/1317)	34.01 (100/294)	41.18 (28/68)	-	-	-	-	10.37 (14/135)
Penicillin		-	-	-	-	-	78.79 (104/132)	-
Piperacillin/Tazobactam	56.13 (142/253)	70.09 (75/107)	37.14 (13/35)	4.35 (4/92)	-	-	-	-
Trimethoprim/Sulfamethoxazole	50.80 761/1498	54.76 253/462	42.96 58/135		60.94 39/64	18.88 (253/1340)	20.47 (35/171)	42.96 (58/135)
Vancomycin	-	-	-	-	-		1.18 (2/169)	-

reveals the antimicrobial resistance rate of Gram-negative bacteria. In this study, the overall resistance pattern of E. coli isolates from various clinical specimens showed high resistance rates to amoxicillin/clavulanic acid (71.5%), cefuroxime (64.2%), cefixime (65.1%), ceftriaxone (60.3%) and ciprofloxacin (54.4%). A lower rate (12.7%, 5.1% and 1.5%) of resistance was observed in the case of nitrofurantoin, amikacin, and meropenem, respectively. Klebsiella sp. was resistant to amoxicillin/clavulanic acid (65.9%), followed by cefixime (58.6%) and ceftriaxone (55.5%). The resistance rate was lower in the case of gentamicin (24.9%), amikacin (19.8%) and meropenem (15.4%). Enterobacter sp. showed a higher percentage of resistance to the cephalosporine group of drugs. Pseudomonas aeruginosa was found to be 60.4%, 52.1%, 33.3%, 21.4%, 18.1% and 4.4% resistant to aztreonam, ceftazidime, amikacin, meropenem, cefepime and piperacillin/tazobactam, respectively. A higher percentage of resistance was seen in the case of Acinetobacter sp. against ceftriaxone (80.3%), ceftazidime (74.3%), amikacin (53.7%) and meropenem (46.2%), respectively.

Likewise, a higher percentage of strains of Salmonella typhi (85.4%) was found to be resistant to azithromycin. Resistance to ampicillin, chloramphenicol, and cotrimoxazole was 26.9%, 17.1% and 18.8%, respectively, indicating that the resistance trend might have started reversing. Moreover, the resistance rate of S. aureus was 78.8% to penicillin, 69.1% to azithromycin, and 50.8% to ciprofloxacin. In addition, 5.9% resistance was observed to cloxacillin and 2.9% to gentamycin in S. aureus. In the case of Enterococcus sp., 58.9%, 49.3%, and 42.9% resistance was found against gentamicin, ciprofloxacin, and trimethoprim/sulfamethoxazole.

4. Discussion

Drug-resistant bacterial infections have become a real threat in developing countries, including Bangladesh. But the extent of this antimicrobial resistance is not clear due to a lack of adequate data. In a study performed in Dhaka, Salmonella typhi and Salmonella paratyphi had reduced susceptibility against ciprofloxacin and a high percentage of strains were multidrug-resistant (MDR) [9]. Another study examining a three-year antimicrobial susceptibility trend among bacterial isolates from a tertiary healthcare facility in Dhaka conducted from 2016 to 2018 found that the resistance pattern of E. coli, Klebsiella pneumonia, Acinetobacter baumannii and Pseudomonas aeruginosa against meropenem, amikacin, ceftazidime, and cefepime fluctuated in a year-to-year pattern, highlighting an increase in resistance among Gram-negative bacteria to commonly used antibiotics [10]. Uropathogenic E. coli and Klebsiella sp. were found to be very highly resistant to first-line drugs in a study conducted in 2018 at a hospital of Bangladesh [11]. The small-scale study on blood culture isolates conducted in this medical college in 2015 revealed 84% and 77% of isolates of Salmonella typhi and Salmonella paratyphi were resistant to azithromycin [12]. Another study conducted in this medical college focused on wound infection showed a high resistance pattern to commonly used antibiotics in the case of Pseudomonas aeruginosa and E. coli [13].

In this study, a total of 32,187 specimens were processed, among which 4232 (13.0%) were culture-positive. The bacteria isolation rate in this study was 13.0%, which is comparable with the results from India (11.2%) [14], Tanzania (14.8% [15], but it was lower than reports from Ethiopia (28%) [16]. The majority of cases required antibiotic treatment prior to hospital admission, which may be the reason. Since antibiotics are frequently sold over the counter, self-medication is also fairly widespread in Bangladesh.

The difference in the pattern of bacterial isolate among different clinical specimens might be due to differences in study subjects, study design, identification method, geographic variation and variation over time within a study population [17].

Among all specimens, E. coli was the most frequent isolate, accounting for 37.2% (1574), followed by Salmonella typhi (25.7%, n = 1089), Klebsiella sp. (11.5%, n = 487), Salmonella paratyphi A (6.4%, n = 270), S. aureus (4.2%, n = 178), Enterobacter sp. (3.6%, n = 152), and the least frequent was Enterococci sp., which accounted for 3.4% (n = 142) of the isolates. The distribution and frequency of bacteria isolated in different clinical specimens were different. In urine, the predominant bacterial isolates were E. coli, in agreement with different studies [11,16]. In the case of blood specimens, the predominant organism was Salmonella typhi. Several studies from Bangladesh have identified Salmonella typhi as a common cause of BSI in this region and reported Salmonella sp. to be responsible for almost half of the disease burden associated with BSI in Dhaka [9]. Although the proportion and prevalence of the bacterial agents differed, more or less the same observations were made in cases of bacteremia in several countries [18,19]. As the only source of Salmonella sp. infection in diseased humans is fecal contamination of drinking water and food supplies, the highest percentage of salmonella isolates in this study highlight the importance of adequate waste management and infection control practices [20]. In this study, S. aureus and Klebsiella pneumoniae were the top two organisms found in wound swab and sputum, respectively.

The overall resistance patterns of E. coli isolates from various clinical specimens showed high resistance rates to amoxicillin/clavulanic acid (71.5%), cefixime (65.1%), ceftriaxone (60.3%) and ciprofloxacin (54.4%), and lower rates (12.7%, 5.1% and 1.5%) of resistance were observed in the case of nitrofurantoin, amikacin, meropenem, respectively. In addition, the antimicrobial resistance patterns of Klebsiella sp. showed 65.9% resistance to amoxicillin/clavulanic acid, followed by cefuroxime (60.3%), cefixime (58.6%) and ceftriaxone (55.5%). The resistance rate was lower in the case of gentamicin (24.9%), amikacin (19.8%) and meropenem (15.4%). The lower sensitivity of amikacin and meropenem may be due to these drugs being used as an alternate treatment option when first-line drugs are ineffective [21].

This study found that the highest overall resistance was against amoxicillin/clavulanic acid; the reason for high resistance in our study could be due to recurrent empirical therapy with these combinations prior to sampling.

In addition, the high resistance percentages against some of the cephalosporin antibiotics, cefuroxime (60.3%), cefixime (58.0%) and ceftriaxone (55.0%), are an indication of the irrational use of antibiotics for simple infectious or even viral diseases that leads to widespread bacterial resistance to these antibiotics. A different study in Bangladesh on antibiotic-prescribing practice and antibiotic use showed that cephalosporin was a commonly prescribed antibiotic group and third-generation cephalosporins were documented as highly used antibiotics [22,23]. E. coli and Klebsiella pneumoniae showed a lower rate of resistance to gentamicin, amikacin and meropenem, which was comparable to the results of other studies carried out in Bangladesh [11,24]. These findings contrast with those of previous studies in Yemen and India, which found greater rates of gentamycin resistance in E. coli and Klebsiella sp. [25,26].

The majority of bacteria resistant to sulfamethoxazole/trimethoprim and ciprofloxacin were Gram-negative species, such as E. coli, Klebsiella sp., and Enterobacter sp. Ciprofloxacin is a first-line treatment for a variety of diseases, including urinary tract infection (UTI), gastrointestinal infections (GITs), and typhoid. The wide empirical use, and excessive and injudicious use of these drugs may have contributed to the high levels of observed resistance. According to the site of the bacterial infection and geographical aspect, the percentages of ciprofloxacin resistance differed. In this study, E. coli showed 54.4%, Klebsiella pneumoniae showed 40.7% and Enterobacter sp. showed 44.7% resistance to ciprofloxacin, which was close to results of the study from Iran and lower than that in the study from Bangladesh [24,27]. Possible reasons for the disparity in drug resistance at different sites could be attributed to the differences in the rational use of antibiotics in the study areas.

E. coli isolates in our study showed low resistance (12.7%) against nitrofurantoin, which was close to a study conducted by Haque et al. in Bangladesh [28]. Although a slightly higher value was observed in the other study [11], it remains the most sensitive drug, and similar results were also reported in other studies [29,30]. The reason behind this might be due to less use of this drug for a long period considering its toxicity and side effects. Nitrofurantoin might be the only useful oral antibiotic in the treatment of uncomplicated UTI and prophylaxis in the context of gradually decreasing susceptibility of most of the comparatively cheaper anti-UTI drugs.

In our setting, we found higher resistant rates (15.4%, 21.4 and 44.3%) of meropenem in the case of Klebsiella pneumoniae, Pseudomonas sp. and Acinetobacter sp., respectively. Our results were comparable to those obtained in Saudi Arabia, India, and Iran [30,31,32]. Carbapenems were used to treat life-threatening infections caused by multidrug resistance (MDR) bacterial pathogens, and antibiotics in this class represent the last line of therapy in treatment options against very serious infections, such as those caused by extended spectrum beta-lactamases.

Pseudomonas aeruginosa was found to be 60.0%, 52.0% and 33.0% resistant to aztreonam, ceftazidime and amikacin, respectively, which suggests that P. aeruginosa was increasingly becoming resistant to antibiotics. Acinetobacter sp. showed 80.3%, 74.0% and 53.7% resistance against ceftriaxone, ceftazidime and amikacin, respectively. Another review study in Iran (2009 to 2015) revealed the emergence of Acinetobacter baumannii in clinical specimens with high resistance to different classes of antibiotics [31]. Acinetobacter sp. and Pseudomonas sp. are well known for their high degree of resistance against all classes of antibiotics, and the emergence of MDR strains makes it very difficult to treat them.

Salmonella sp. showed a lower resistance rate to ampicillin, chloramphenicol and cotrimoxazole in this study, which is consistent with studies carried out in Nepal and Pakistan [33,34]. A higher percentage of strains of Salmonella typhi was found to be resistant to azithromycin. Several clinical studies have demonstrated good efficacy of azithromycin for the treatment of common enteric fever in clinical and in vitro studies. In a study in India, 93.2% of Salmonella typhi was found susceptible to azithromycin [35]. In our study, we only used a disc diffusion method for azithromycin, and MIC was not carried out, which was one of this study’s limitations. In summary, the study results revealed that first-line anti-typhoidal drugs are becoming less effective against Salmonella, whereas azithromycin resistance is noticeably rising. The use of ceftriaxone should be restricted to patients of enteric fever that are MDR and extensively drug resistant (XDR). However, understanding the significance of microbiology for accurate reporting, evaluation, and monitoring of antimicrobial therapy is essential [34].

Similarly, among the Gram-positive bacteria, high rates of resistance were observed against azithromycin and ciprofloxacin. In contrast to past research, where a higher proportion of Methicillin-resistant Staphylococcus aureus (MRSA) was observed, this study found that S. aureus had a lower rate of cloxacillin resistance [15,36,37].

5. Conclusions

Bacterial AMR is a major global health problem. AMR has increased over the years in Bangladesh owing to the country’s poor healthcare standards, along with the misuse and overuse of antimicrobials, which poses a regional and global threat. This study reveals the bacterial isolates and their antibiotic resistance patterns for commonly used antibiotics. The outcomes of this study will help healthcare professionals in Bangladesh and the region to make informed decisions and provide better care for their patients. The rise in antibiotic resistance in different clinical isolates emphasizes the importance of sound hospital infection control, proper waste management, rational prescribing policies, and the need for new antimicrobial drugs and vaccines. Also, there is a need for continuous evaluation of the local antibiotic resistance patterns for the formulation of a rational antibiotic policy.