Antimicrobial resistance (AMR) is a critical public health issue in Bangladesh, where antibiotic use is widespread but often unregulated. This nationwide cross-sectional study (2017–2020) analyzed data from 26 public and private laboratories across all divisions of the country. Standardized data on antimicrobial susceptibility testing (AST) were collected, curated, and analyzed using WHONET, QAAPT, and R software to assess resistance patterns in 232,329 bacterial isolates from various clinical specimens. Escherichia coli was the most common pathogen (32.5%), followed by Klebsiella sp. (15.5%) and Pseudomonas sp. (10.6%). Urine specimens comprised 50.3% of the tested samples, while blood and soft tissue/body fluids accounted for 12.1% and 24.8%, respectively. Patients aged 55 years and older represented the largest group (36.3%), highlighting their vulnerability to drug-resistant infections. Resistance to third-generation cephalosporins was alarmingly high in Escherichia coli (62.9% resistant to ceftriaxone), whereas carbapenem resistance remained relatively low (5.3% and 6.8% to imipenem and meropenem, respectively). Klebsiella sp. showed widespread resistance, though carbapenems remained relatively effective (imipenem resistance 20.3%, meropenem 21.7%). In contrast, Salmonella sp. remained largely sensitive to third-generation cephalosporins. However, 42% of Staphylococcus aureus isolates were methicillin-resistant (MRSA). This study underscores the urgent need for improved antibiotic stewardship, enhanced diagnostic capacity, and strengthened AMR surveillance to preserve treatment options in Bangladesh.

The analysis and visualisation of antimicrobial resistance (AMR) surveillance data is a crucial challenge, especially in high-burden, low-middle-income countries. We describe the design, development, integration, and implementation of the Quick Analysis of Antimicrobial Patterns and Trends (QAAPT) tool for AMR data analysis and visualisation. The QAAPT tool was created by the Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia project, led by the International Vaccine Institute (IVI). This open-source web-based tool/application generates statistical and visual outputs of AMR data, offers data curation options, and can be integrated with laboratory information management systems. The QAAPT tool is user-friendly and is operable by someone with limited expertise in software or programming. As a part of the project, the tool was used to analyse data from 72 laboratories across 7 Asian countries. In this study, we present the technical aspects of tool development and highlight implementation outcomes for analysing and generating visual reports from more than 2.37 million highly heterogeneous antimicrobial susceptibility test data points.

Introduction: Antimicrobial resistance (AMR) is a global public health issue, particularly in resource-limited, low- to middle-income countries like Bangladesh. In this study, we analyze and present four years of data on AMR from a tertiary care hospital in Bangladesh to inform policymakers and the wider community. Methods: In a retrospective cross-sectional study, we collected data for 4403 bacterial isolates reported between January 2017 and February 2020 at Mymensingh Medical College Hospital (MMCH), Bangladesh. All data were entered, cleaned, and analyzed using the software Stata Version-16.0, WHONET, a microbiology laboratory data management solution, and Quick Analysis of Antimicrobial Patterns and Trends (QAAPT), an AMR data visualization platform. Results: The bacteria were most commonly isolated from urine (71.66%, n = 3155), followed by pus (11.63%, n = 512), sputum (6.70%, n = 295), wound swabs (6.70%, n = 295), stool (1.91%, n = 84), endotracheal aspirate (1.20%, n = 53), and blood (0.20%, n = 9). Gram-negative bacteria predominated in all samples. Escherichia coli was the most common Gram-negative bacterium (31.30%, n = 1378), while Staphylococcus aureus was the most common Gram-positive bacterium (4.38%, n = 193). Antimicrobial susceptibility testing (AST) showed that multidrug resistance in Gram-negative bacteria such as E. coli, Klebsiella sp., and Acinetobacter sp. was common. S. aureus exhibited high resistance rates for beta-lactams, macrolides, and quinolones. In the urine samples, E. coli demonstrated high resistance to antibiotics like amoxicillin/clavulanic acid, ciprofloxacin, ceftriaxone, and cefuroxime (60–100%). Critical and high-priority pathogens as listed by the WHO constituted approximately 60% of the isolates. The AMR trends over three months showed increased resistance to amoxicillin/clavulanic acid for E. coli and to cefuroxime for Klebsiella sp. For S. aureus, the resistance to ciprofloxacin increased over three years, while the resistance to azithromycin decreased. Conclusions: There is a rise in bacterial resistance to the available antibiotics, with a significant prevalence of critical and high-priority pathogens in Bangladesh. We recommend vigilant AMR surveillance and stewardship programs to control the AMR in this country.

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.

Background: It is essential to monitor causative agents of infections and antimicrobial resistance patterns to inform treatment and policy at the local level. In this study, we investigated the microbiological profile and antibiotic susceptibility pattern records in a tertiary care hospital. Materials and Method: This cross-sectional study was performed in a tertiary care hospital in Dhaka city, Bangladesh. The study utilized a retrospective descriptive research approach conducted between January 2018 and February 2021 in which culture results of blood, stool, urine, body fluid, genital, respiratory and soft tissue specimens were retrieved and analyzed. Results: A total of 26,825 samples were ana-lyzed; of which 3,779 records for microbial growth from clinical specimens were identi-fied, yielding a 14.09% isolation rate. Escherichia coli (E. coli), Klebsiella sp., Staphylo-coccus aureus, Pseudomonas sp., coagulase negative Staphylococcus, Salmonella Typhi and Enterococcus sp. were the most frequently isolated organisms among all specimens. E. coli, the most common causative organism of urinary tract infection (UTI) and genital infection, showed high resistance to co-trimoxazole (48%), ciprofloxacin (79%), and cephalosporins (63-65%) while the resistance rate to nitrofurantoin (7%), mecillinam (16%), aminoglycosides (7-18%), meropenem (8%) and colistin (0%) was low. In bloodstream infection, the most common microorganism found was S. Typhi. High sensitivity towards amoxicillin (100%), chloramphenicol (78%), co-trimoxazole (76%), cefixime (100%) and ceftriaxone (100%) were seen in S. typhi whereas almost all isolates were resistant to nalidixic acid (97%) and ciprofloxacin (96%). S. aureus, the predominant cause of soft tissue infection, was highly sensitive to co-trimoxazole (70%), doxycycline (86%), and linezolid (97%). Methicillin-resistant Staphylococcus aureus (MRSA) was 54%. The most common cause of respiratory infection was Klebsiella sp. The rate of resistance of Klebsiella sp. to third and fourth generation cephalosporins was approximately 65% and to ciprofloxacin and meropenem was 74% and 42% respectively. Pseudomonas sp., found commonly in urine, soft tissue, body fluids, and respiratory infections, were susceptible to ceftazidime, piperacillin/tazobactam and ciprofloxacin with resistance rate of 27%, 18% and 34% re-spectively. High resistance to meropenem was recorded for Pseudomonas sp. (30%) and Acinetobacter sp. (64%). Acinetobacter sp. showed low sensitivity (< 45%) to all of the tested antibiotics except colistin and tigecycline. Conclusion: This study highlights the high potential for infections associated with resistant microorganisms in the tertiary care hospital where samples for this study were collected. It is therefore recommended that judicious treatment following drug-susceptibility testing of isolates, regular surveillance programs, and strict infection control measures be put into place to address this increasing drug resistance problem.

Introduction: Antimicrobial resistance (AMR) is an urgent global public health problem. It threatens effective treatment of infections and leads to prolonged duration of illness, higher morbidity and mortality rates, and an increased cost of health care. The effectiveness of currently available antibiotics is decreasing as a result of increasing resistant strains among clinical isolates. Objective: The aim of this study was to determine the bacterial profile and AMR patterns of bacterial isolates from different clinical specimens at Uttara Adhunik Medical College Hospital (UAMCH), Dhaka. Material and methods: This retrospective study was carried out at UAMCH in Bangladesh from January 2017 to December 2019. In total 32,187 clinical specimens such as urine, blood, stool, wound swab/pus, and sputum were collected and processed at the Microbiology laboratory. Among these, 4232 were positive culture samples. Standard bacteriological methods were employed to identify the bacteria, and Kirby-Bauer disc diffusion methods were used in accordance with CLSI guidelines to assess the bacteria's susceptibility to various antibiotics. Data were entered, cleaned, and analyzed using the WHONET software developed by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance and the Quick Analysis of Antimicrobial Patterns and Trends (QAAPT) web application. Result: Urine had the highest percentage of positive cultures (47.5%, n=2009), followed by blood (35%, n=1500), wound swab/pus (10.1%, n=426) and sputum (5.3%, n=225). Among positive samples, E. coli was the most frequent isolate accounting for 37.19% (1574) of specimens, followed by Salmonella typhi (25.73%, n=1089), Klebsiella sp. (11.51%, n=487), Salmonella paratyphi A (6.38%, n=270), Staphylococcus aureus (4.21%, n=178), and Enterobacter sp. (3.59%, n=152). Overall, the Gram-negative isolates exhibited a high level of resistance to commonly used antibiotics such as amoxicillin/clavulanic acid, cefixime, and ceftriaxone. The resistance rate was lower in case of gentamicin, amikacin, and meropenem; however, Acinetobacter sp. showed a higher and alarming resistance rate against all antibiotics. Conclusion: This study exposes the antibiotic resistance patterns of bacterial isolates to routinely used antibiotics. The outcomes of this study will assist healthcare professionals in Bangladesh and the area in making informed decisions and providing better care to their patients. Therefore, resistance surveillance studies should be conducted to develop local antibiogram data, which will help to choose the best antibiotic for empirical therapy.