Distribution, epidemiology, and antimicrobial resistance pattern of gram-negative bacteria isolated from blood: a retrospective study in a tertiary care hospital, Dhaka, Bangladesh

Distribution, epidemiology, and antimicrobial resistance pattern of gram-negative bacteria isolated from blood: a retrospective study in a tertiary care hospital, Dhaka, Bangladesh | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Distribution, epidemiology, and antimicrobial resistance pattern of gram-negative bacteria isolated from blood: a retrospective study in a tertiary care hospital, Dhaka, Bangladesh View ORCID Profile Nusrat Noor Tanni , Maherun Nesa , View ORCID Profile Rubaiya Binte Kabir , Farjana Binte Habib , View ORCID Profile Md. Asaduzzaman , View ORCID Profile Avizit Sarker , Md. Faizur Rahman , Noor E Jannat Tania , Azmeri Haque , Umme Saoda , Kakali Halder , Nadira Akter , Rozina Aktar Zahan , Mahbuba Chowdhury , Sazzad Bin Shahid doi: https://doi.org/10.1101/2025.06.25.25330327 Nusrat Noor Tanni 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nusrat Noor Tanni For correspondence: nusratnoortanni{at}gmail.com Maherun Nesa 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Rubaiya Binte Kabir 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Rubaiya Binte Kabir Farjana Binte Habib 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Md. Asaduzzaman 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Md. Asaduzzaman Avizit Sarker 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Avizit Sarker Md. Faizur Rahman 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Noor E Jannat Tania 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Azmeri Haque 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Umme Saoda 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kakali Halder 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nadira Akter 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Rozina Aktar Zahan 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mahbuba Chowdhury 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sazzad Bin Shahid 1 Department of Microbiology, Dhaka Medical College , Shahbag, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract The effective treatment of bloodstream infections caused by gram-negative bacteria (GNB) poses significant challenges as their distribution and resistance patterns vary across geographic locations and healthcare settings. The objective of this study was to identify the prevalence, distribution, and antimicrobial resistance patterns of commonly isolated GNB from the blood cultures of patients. This retrospective study was conducted between November 2023 to October 2024 in the Department of Microbiology, Dhaka Medical College, Bangladesh. Bacterial blood culture and susceptibility testing records of GNB from both inpatient department (IPD), intensive care units (ICU), and outpatient department (OPD) samples, irrespective of age and sex, were included and analyzed in this study. Total isolated gram-negative bacteria were 87.6%, with a slightly higher prevalence in male patients. Salmonella spp was the most prevalent isolate from the OPD, while Acinetobacter spp was predominant in IPD and ICU. Among the antimicrobial agents, the highest resistance was observed to ceftazidime in all isolated GNB, except Salmonella spp, which were highly resistant to fluoroquinolones. Acinetobacter spp was predominantly multidrug-resistant (MDR) (75.4%), and the lowest was Salmonella spp (40.7%). Among 15% extensively drug-resistant (XDR) isolates, the majority were Acinetobacter spp, followed by Pseudomonas spp and Klebsiella spp. The highest prevalence of both multidrug-resistant (MDR) and XDR organisms were observed in the ICU. The antibiotic resistance trends display restricted effectiveness of commonly used antibiotics, such as cephalosporins and fluoroquinolones, compelling dependence on last-resort antibiotics like colistin. Systematic local surveillance and epidemiological studies of antimicrobial resistance would assist in taking measures to slow down the spread of resistance. Introduction Bloodstream infection (BSI) is one of the most important causes of hospitalization and mortality globally, and its clinical presentation ranges from transient asymptomatic bacteremia to life-threatening septicemia and septic shock [ 1 , 2 ]. Although any age group can be affected, infants and children are at the highest risk of contracting such infections [ 2 ]. Rapid and reliable bacteremia diagnosis entails aseptic blood collection for culture and sensitivity testing before the administration of antimicrobial agents [ 3 ]. Gram-negative bacteria (GNB) were considered the cause of around 25% of nosocomial bacteremia and 45% of community-acquired bacteremia [ 4 ]. Based on the current population, BSI caused by GNB accounts for 279,000 cases and 33,500– 41,900 deaths annually in the USA [ 5 ]. Gram-negative pathogens exhibit a higher case fatality rate in neonates with sepsis than Gram-positive pathogens (59% vs. 33%) [ 6 ]. Most notably isolated GNBs are Escherichia coli, Klebsiella pneumoniae, Enterobacter cloaca, Salmonella typhi, Pseudomonas aeruginosa, and Acinetobacter baumannii [ 7 ]. Bacterial distribution and sensitivity trends vary across geographic locations and healthcare facilities [ 8 ]. Antibiotic-resistant strains, particularly those of Gram-negative bacteria, are emerging at an alarming rate, posing significant challenges to the effective treatment of BSI [ 9 ]. Antimicrobial resistance (AMR) has emerged as a critical global health crisis. Infections caused by multidrug-resistant (MDR) bacteria significantly increase morbidity and mortality, leading to extended hospital stays, consumption of more expensive antibiotics, and the risk of developing antimicrobial resistance. Consequently, MDR infections not only threaten patient outcomes but also result in substantial financial losses for healthcare systems [ 10 ]. AMR surveillance plays a pivotal role in combating and managing this crisis, as emphasized in the World Health Organization’s (WHO) Global Strategy for Containment of Antimicrobial Resistance (2001). Furthermore, adopting the Global Action Plan on Antimicrobial Resistance (GAP) by the 68th World Health Assembly in May 2015 underscores the importance of ensuring the sustained efficacy of antimicrobials for treating and preventing infectious diseases [ 11 ]. Understanding the epidemiology of Gram-negative BSIs and AMR trends is vital for selecting empirical antibiotics and optimizing antibiotic therapy regimens [ 12 ]. Since every geographical area has a unique pattern of resistant organisms, monitoring local resistant patterns consistently can guide the appropriate use of antimicrobial agents and contribute to preventing antimicrobial resistance. Although the mainstream data on bacterial pathogen surveillance and AMR profile comes from high-income nations, it is well acknowledged that AMR is a worldwide concern that mostly affects low-income countries. Scrutiny of microorganism distribution, BSI epidemiology, changing antibiotic resistance rates, and demographics are required to support appropriate therapy. This study aimed to ascertain the prevalence, distribution, and antimicrobial resistance patterns with MDR, and XDR status, of commonly isolated GNB by age, sex, and hospital units through the analysis of the blood cultures of patients at Dhaka Medical College Hospital (DMCH), a tertiary care hospital in Dhaka, Bangladesh. Materials and Methods This was a retrospective study of records for bacterial culture and susceptibility testing results between November 2023 to October 2024 at the Department of Microbiology, Dhaka Medical College, Dhaka, Bangladesh. Among culture-positive blood samples, only gram-negative bacteria culture records were included and analyzed in this study. Both inpatient and outpatient samples, regardless of age or hospital setting, were included. All laboratory data of blood culture samples with contamination and repetitive isolated species of the same patient in the same specimen type were excluded from this present study, only the first isolate was considered. The following variables were included: age, gender, hospital units, name of the organisms, antimicrobial disk used for susceptibility testing, and susceptibility results of each antibiotic tested. Ethical approval for the study was obtained from the Institutional Review Board (IRB) of Dhaka Medical College. Individual participate had unique identification number against each blood sample. However, data confidentiality and the right to privacy were preserved per the Declaration of Helsinki. Blood Collection With strict aseptic technique, 10 ml of venous blood was collected from adult patients, and 3-4 ml from pediatric patients. The blood samples were inoculated immediately into an automated blood culture bottle and analyzed by an automated monitoring system for bacterial detection (BacT/Alert 3D 60, BioMerieux, France), incubated at 37 ° C aerobically until a positive culture was observed or up to a maximum of 7 days [ 13 ]. In some instances, when automated blood culture bottles were not available, a few blood samples were inoculated in conventional blood culture bottles containing Trypticase soy Broth (TSB), incubated at 37 ° C aerobically overnight, and examined daily for turbidity up to 7 days. Microbial identification Subculture was carried out on the MacConkey agar and Blood agar plates, incubated at 35-37 °C overnight, and then examined for visible growth. From the colony, gram-negative bacteria were identified by Gram staining, biochemical tests including the oxidase test, Triple Sugar Iron (TSI), Motility Indole Urea (MIU), and citrate tests. In addition, Gram-positive organisms were identified using the catalase test and coagulase test [ 14 ]. The Antibiotic susceptibility testing was performed by the Kirby-Bauer disk diffusion method, following laboratory protocol, and the interpretation of the zone of inhibition was done according to Clinical and Laboratory Standards Institute (CLSI), 2022 guidelines [ 15 ]. Antibiotic susceptibility was done using following discs-Amoxicillin-clavulanic acid (20/10μg), Piperacillin-Tazobactum (100/10μg), Ceftriaxone (30μg), Ceftazidime (30μg), Cefixime (5μg), Cefepime (30μg), Meropenem (10μg), Ciprofloxacin (5μg), Gentamicin (10μg), Amikacin (30μg), Netilmicin (30μg), Tigecycline (15μg), Doxycycline (30μg), Trimethoprim-Sulphamethoxazole (1.25/23.75μg), and Azithromycin (15μg) disk. Susceptibility to tigecycline was defined according to the Food and Drug Administration (FDA), Identified Interpretive Criteria 2023; isolates were categorized as resistant if the zone diameter was <14 mm and susceptible if the zone diameter was ≥19 mm [ 16 ]. Statistical Analysis Data for categorical variables were presented as numbers and percentages, and mean ± standard deviation (SD) or as the median for continuous data. The test used for a normal distribution was the Shapiro–Wilk test. The Pearson Chi-square test and Fisher’s exact test were used to define statistical significance. All tests with p-value < 0.05 were considered significant with a 95% confidence interval. The data were statistically evaluated with Statistical Package for the Social Sciences (SPSS) version 23.0 (IBM Corp., Armonk, NY). Operational definition of multidrug-resistant (MDR) and extensively drug-resistant (XDR) Bacteria: [ 17 ] MDR is defined as non-susceptibility to at least one agent in three or more antimicrobial categories. XDR is defined as non-susceptibility to at least one agent in all but two or fewer antimicrobial categories (i.e., bacterial isolates remain susceptible to only one or two categories). Results Bacterial blood culture yielded 427 isolates during the study period. Gram-positive organisms were 53 (12.4%), among them S. aureus was 90.6%, Coagulase Negative Staphylococcus 7.5%, and Enterococcus spp. was 1.9%. The total number of isolated gram-negative bacteria was 374 (87.6%). Isolation of GNB was slightly higher in male patients 214 (57.2%) compared to female 160 (42.8%), the male-female ratio was 1.33:1. The most common isolated GNB were Salmonella spp. 189 (50.6%), followed by Acinetobacter spp 69 (18.5%), Pseudomonas spp 46 (12.3%), Klebsiella spp 33 (8.8%), Escherichia coli ( E. coli ) 21 (5.6%), Enterobacter spp 12 (3.2%), Citrobacter spp 2 (0.5%), and Proteus spp 2 (0.5%). The relationship between organisms isolated in the blood sample and the gender of patients is presented in Table 1 . Notably, no significant association between males and females in terms of isolates was observed (p = 0.177). Among the isolates, Salmonella spp was the most prevalent bacteria, followed by Acinetobacter spp in both female and male groups. View this table: View inline View popup Download powerpoint Table 1: Distribution of GNB according to gender (N=374) The age of patients ranged from <1 year to 82 years with a mean age of 27.10 years and a standard deviation of 19.003 years. Between the females and males, the mean age ± SD was 27.53±20.35, and 26.78±17.98 years, and the median was 22.00 and 23.00 years respectively. Shapiro–Wilk test for normal distribution was done, which rejects normality ( p -value < 0.05). The age range was distributed into six intervals to individualize the possible relationship between isolates and age ( Table 2 ). In age interval analysis, Acinetobacter spp, Klebsiella spp, and Pseudomonas spp were more prevalent in the ≤ 18 years. Among 19-30 years age group more Salmonella spp were isolated. View this table: View inline View popup Download powerpoint Table 2: Isolated Gram-negative bacteria stratified by age intervals (N=374) The association between the isolates and hospital settings were analyzed ( Table 3 ); Hospital units were assigned into Outpatient departments (OPD), Inpatient Departments (IPD), and Intensive Care Units (ICU). View this table: View inline View popup Download powerpoint Table 3: Distribution of Gram-negative bacteria in different hospital settings There was a significant association between hospital units and isolated organisms ( p < 0.001). Salmonella spp (76.8%) was the most frequent isolate in the OPD, while Acinetobacter spp (45.0%, 33.1%) followed by Pseudomonas spp (15.0%, 21.8%), were most frequent in ICU and IPD accordingly. Antimicrobial resistance patterns for various gram-negative bacterial species against different categories of antimicrobials were presented in Table 4 . E. coli showed the highest resistance to ciprofloxacin (95.2%), followed by amoxicillin-clavulanic acid, piperacillin-tazobactam, ceftriaxone, and ceftazidime (90.5% each). Klebsiella spp exhibited 100% resistance to ceftazidime, followed by ceftriaxone and piperacillin-tazobactam (97%), with low resistance to netilmicin (54.5%), and tigecycline (60.6%). Acinetobacter spp and Pseudomonas spp demonstrated frequent resistance to third-generation cephalosporins. For Salmonella spp, most isolates were resistant to ciprofloxacin (95.2%). View this table: View inline View popup Table 4: Antimicrobial resistance pattern of isolated Gram-Negative Bacteria Distribution of isolated organisms and hospital units according to drug resistance status were evaluated in Table 5 , which lists the number of resistant isolates per total tested. Total MDR was 53.7%, the highest MDR positive rate observed for Citrobacter spp (100.0%), though the sample size was very small (only two isolates). The lowest MDR-positive organisms were Salmonella spp (40.7%). There is a statistically significant association (p <0.000) between the type of organisms and MDR status. About 15% of all isolated GNBs were identified as XDR as per the definition. Among the Acinetobacter spp, 42.5% were XDR, followed by Pseudomonas spp (26.1%) and Klebsiella spp (21.1%). Notably, no XDR isolates were detected among Salmonella spp in this current study. When associating resistance across hospital settings, the highest prevalence of both MDR and XDR was observed in the intensive care unit (ICU), with rates of 80.0% and 50.0%, respectively. In contrast, the OPD recorded the lowest prevalence, with 42.9% MDR and 5.2% XDR isolates. View this table: View inline View popup Download powerpoint Table 5: Distribution of isolated organisms and hospital settings according to their drug resistance status (N=374) Discussion The distribution and resistance patterns of BSI-causing pathogens vary according to time, geographical location, environment, population, and healthcare expenditure [ 18 ]. Knowledge of the baseline microbial resistance profile concerned with the hospital prevents irrational use of antibiotics in that hospital, thus helping progress a step forward in limiting the spread of antibiotic resistance. Globally, antimicrobial-resistant bacteria (ARB) have been recognized as a threat to public health. Though detection of the causing microbial by using molecular techniques has been proven suboptimal, blood culture remains the gold standard and first-line tool in the pathogen diagnostics of BSIs and provides clinically relevant information concerning the identity and analysis of microorganisms with their susceptibility to antibiotics [ 19 ]. The present study was a retrospective cross-sectional study from November 2023 to October 2024, conducted in the Department of Microbiology, Dhaka Medical College, to analyze the positive blood culture isolates from patients with BSI. In this study, 12.4% of the isolated organisms were gram-positive, and GNB were 87.6%; these observations were comparable to those studies conducted by Prakash et al in Nepal, Mia et al in Bangladesh, and Alhumaid et al in Saudi Arabia [ 20 , 4 , 21 ]. In this current study, Salmonella spp accounted for 50.5% of GNB isolates from blood. Nasrin et al. also reported Salmonella as the prominent organism causing BSI in Bangladesh [ 22 ]. The isolation rate of GNB was slightly higher in male patients (57.2%) compared to females 42.8% which coincides with the outcome of Ejaz et al in Pakistan [ 13 ]. Although the present study does not show any significant differences (p-value 0.177) based on gender in Gram-negative isolates from blood, E. coli bacteremia was more frequent in women. The female anatomy and vaginal colonization by E. coli can be a risk factor for E. coli bacteremia from a urinary tract infection (UTI). In this observation, Salmonella spp was more prevalent in males, which agrees with the study conducted by Bhumbla et al. [ 23 ]. The variation in male-female proportion in this study could be attributed to factors such as the male population being more involved in outdoor activities in our context, exposing them to infection. The age-specific prevalence of different bacterial pathogens reflects variations in infection patterns among distinct demographic groups. In age interval analysis, Acinetobacter spp was more prevalent in the <18 years age group, suggesting higher vulnerability in these age groups due to factors such as immature immune systems, reduced antimicrobial activity by neutrophils and macrophages, reduced antigen presentation by dendritic cells, decreased NK cell killing, and compromised adaptive lymphocyte responses in younger individuals [ 24 ]. Similarly, Klebsiella spp and Pseudomonas spp were most frequent in the <18 years age group, likely due to increased susceptibility to hospital-acquired infections among pediatric patients due to their immature immunity, exposure to invasive procedures, and the multidrug-resistant organisms in the hospital environment. [ 9 , 25 ]. In contrast, Salmonella spp were more occurred (49.2%) in the 19-30 years age group, Prakash et al . from India also found the highest Salmonella spp isolation rate in the age group between 16-30 years (54.10%) [ 20 ]. The relationship between the distribution of bacterial isolates and hospital wards reveals a significant association, as indicated by the Chi-Square test (p < 0.001). Salmonella spp was predominantly isolated from OPD (76.8%), likely reflecting community-acquired infections. A study from Pakistan reflected similar trends, with Salmonella causing a significant proportion of bloodstream infections in outpatient settings [ 26 ]. In the ICU predominant organism was Acinetobacter spp, this is consistent with the findings of Saharman et al ., where a significant burden of Acinetobacter , was observed in the intensive care unit setting [ 27 ]. Hospital-associated infections were dominated by Acinetobacter spp and Pseudomonas spp, particularly in ICUs. In contrast, a study by Mathur et al . reported Klebsiella spp as the most frequently identified pathogens among bloodstream infections in the ICU in India [ 28 ]. Upon exploring collective antimicrobial resistance pattern in GNB except Salmonella spp, the highest resistance were observed to ceftazidime (94.1%), followed by piperacillin-tazobactam (89.2%), and ciprofloxacin (87.7%), which were concordant to that reported by Parajuli et al. in Nepal [ 29 ]. In the current study, Acinetobacter spp and Pseudomonas spp demonstrated frequent resistance to third-generation cephalosporins, which were in agreement with the study by Nesa et al. and Sharmin et al. from Bangladesh, reported that 93.5% to 100.0% Acinetobacter baumannii were resistant to the extended spectrum of cephalosporins [ 30 , 31 ]. Saha et al . reported similar finding that Pseudomonas spp were highly resistant to ceftazidime (82.3%) [ 32 ]. On the contrary, Pseudomonas spp showed 60.9% carbapenem resistance in this study, whereas AlBahrani et al. found only 9% resistance in Saudi Arabia. These variations in the susceptibility rates may be associated with differences in antibiotic use in different geographical areas and hospital settings [ 33 ]. E. coli showed high resistance to ciprofloxacin, piperacillin-tazobactam, and third generatin cephalosporin group of drugs. Additionally, Klebsiella spp. exhibited high resistance to ceftazidime, followed by ceftriaxone and piperacillin-tazobactam; those findings have similarities with a study conducted in Bangladesh by Akter et al . [ 34 ]. Overall carbapenem resistance rate was 63.2 %, which is slightly higher than Aminul et al. reported from Bangladesh [ 35 ]. Carbapenem resistance in Enterobacterales has been particularly worrisome in South Asian settings, attributed to the widespread dissemination of carbapenemase-producing strains [ 36 ]. In this current study, among the total 374 isolated organisms, 201 (53.7%) were identified as MDR and 58 (15.5%) as XDR. Salmonella spp (40.7%) demonstrated the lowest MDR rate, with no isolates classified as XDR. This was supported by previous studies conducted by Mina et al ., where Salmonella spp has shown variable susceptibility to ciprofloxacin but limited resistance to other groups of antibiotics [ 37 ]. Acinetobacter spp exhibited the highest MDR (75.4%) and XDR (42%) rates, which were consistent with study reports by Banerjee et al. and Sharmin et al., where Acinetobacter spp has shown a high resistance rate to multiple antibiotic classes, including carbapenems [ 38 , 31 ]. These findings highlight the alarming prevalence of antimicrobial resistance (AMR) in hospital settings, which poses a grave threat to public health, particularly in low-income countries in South Asia, including Bangladesh. The present study also revealed significant disparities in MDR and XDR prevalence across hospital units. The ICU had the highest proportion of MDR and XDR isolates, followed by the inpatient department (IPD); this trend is consistent with studies conducted by Van An et al. in Vietnam [ 39 ]. ICU settings are a hotspot for nosocomial infection with AMR pathogens, due to the high usage of broad-spectrum antibiotics, invasive procedures, and prolonged hospital stays. The lowest MDR prevalence was observed in the outpatient department (OPD), likely reflecting reduced exposure to hospital-acquired infections and limited prior antibiotic use. The rise of antimicrobial resistance (AMR) and bloodstream infections (BSIs) in Bangladesh underscores the urgent need for effective Antimicrobial Stewardship Programs (ASP) and infection control practices. Effective diagnostics, infection prevention, and responsible antibiotic use are critical to combating this growing threat. Overall, this study was a single institution-based retrospective observational study with some limitations. CLSI 2022 breakpoints were used to interpret the antibiotic susceptibility testing, whereas some changes in zone diameters were adopted by CLSI afterwards, which were not considered in this study. Patient outcome, mortality, morbidity rates, and other risk factors were not measured in this study due to a lack of data. Advanced molecular methods can provide deep insight into the isolation and resistance profile, which were not considered in this study. Therefore, the findings must be interpreted with caution, and further studies should be conducted on a larger sample involving several hospitals from different geographical areas. Conclusion GNB isolated from the blood sample had a slight predominance of male gender. Salmonella spp. were prominent isolates in OPD, whereas Acinetobacter spp and Pseudomonas spp were more prevalent in ICU and IPD settings. Most of the isolates show high resistance to cephalosporin, piperacillin-tazobactam, and ciprofloxacin. This current study also highlights the high prevalence of MDR and XDR Gram-negative pathogens in bloodstream infections. The ICU remains the most affected setting, and Acinetobacter spp emerges as a key pathogen of concern. Regular updates on the epidemiology of BSIs, including geographic and climate-driven variations in antibiotic resistance patterns, are essential for antibiotic stewardship that ensures timely and effective treatment. Data Availability All the data related to this manuscript have been uploaded as Supporting Information files. Acknowledgments We acknowledged the staff of the Microbiology Department, Dhaka Medical College, for their contributions. References 1. ↵ Zenebe T , Kannan S , Yilma D , Beyene G . Invasive bacterial pathogens and their antibiotic susceptibility patterns in Jimma University specialized hospital, Jimma, Southwest Ethiopia . 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