https://orcid.org/0000-0001-7461-859X
Figures
Abstract
Background
Managing bloodstream infections in resource-constrained regions like Ethiopia is challenging due to scarce blood culture surveillance data. To guide empirical therapy, this study determines the bacterial profiles and antimicrobial resistance patterns among patients with suspected bloodstream infections at the Amhara Public Health Institute.
Methods
This retrospective study analyzed blood culture records from the Amhara Public Health Institute spanning January 1, 2020, to December 30, 2023. Blood samples were processed using standardized manual culture techniques in accordance with World Health Organization (WHO) protocols. Antimicrobial susceptibility testing was performed using the Kirby-Bauer disk diffusion method following Clinical and Laboratory Standards Institute (CLSI) guidelines. Statistical analysis was conducted using SPSS version 20, employing descriptive statistics and regression models, with statistical significance defined as p < 0.05.
Results
True bacterial pathogens were isolated from 50.3% (N = 340) of the 676 patients, with Gram-negative bacteria predominating (61.2%, N = 208) over Gram-positive bacteria (38.8%, N = 132). Notably, ESKAPEE pathogens accounted for 96.5% (N = 328) of all isolates, led by Klebsiella spp. (25.9%, N = 88), Enterococcus spp. (20.9%, N = 71), and S. aureus (15.6%, N = 53). Among Gram-positive isolates, high resistance was observed against oxacillin (74.5%, N = 41), penicillin (72%, N = 36), and vancomycin (51.1%, N = 24). Gram-negative isolates exhibited critical resistance to national frontline therapeutics, including ampicillin (100%, N = 24), ceftriaxone (92.4%, N = 157), and trimethoprim-sulfamethoxazole (89.4%, N = 126). Overall, multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR) profiles were detected in 43.8% (N = 149), 30.5% (N = 104) and 5.3% (N = 18) of isolates with similar distributions observed among ESKAPEE strains. Sex and age were the only independent predictors of culture positivity, with female sex reducing bloodstream infection odds by 44% (p = 0.002). Conversely, neonates (≤ 28 days) and young adults (15–24 years) had 4.7 times (p = 0.001) and 9.5-times (p = 0.001) higher odds compared to elderly patients.
Conclusions
This study reveals a severe 50.3% (N = 340) bloodstream infection rate dominated by highly resistant Gram-negative and ESKAPEE pathogens, disproportionately affecting males, neonates, and young adults. Combating this threat requires immediate antibiotic stewardship, updated guidelines, and advanced laboratory testing (anaerobic culture, minimum inhibitory concentration, and molecular sequencing) to track and manage resistance.
Citation: Getie M, Tafere W, Tsega A, Gebreyesus T, Belay G, Getachew H, et al. (2026) Bacterial profile and antimicrobial resistance patterns of bloodstream infections at Amhara Public Health Institute, Bahir Dar, Ethiopia. PLoS One 21(7): e0354710. https://doi.org/10.1371/journal.pone.0354710
Editor: Mengistu Hailemariam Zenebe, Hawassa University College of Medicine and Health Sciences, ETHIOPIA
Received: April 10, 2025; Accepted: July 10, 2026; Published: July 27, 2026
Copyright: © 2026 Getie et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are fully available without restriction and are included within the submitted paper and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: AOR, adjusted odds ratio; APHI, Amhara public health institute; BSI, blood stream infection; CLSI, clinical laboratory standards institute; CoNS, coagulase-negative staphylococci; ESKAPEE, Enterococcus spp., S. aureus, K. Pneumoniae, A. baumannii, P. aeruginosa, Enterobacter spp. and E. coli; MRSA, methicillin resistant S. aureus
Background
Bloodstream infections (BSIs) are severe, life-threatening conditions primarily caused by bacteria, fungi, viruses, and protozoa can also invade the bloodstream [1]. Globally, they are associated with high morbidity, prolonged hospital stays, increased intensive care needs, and significant mortality rates ranging from 20% to 50%. In 2020, the World Health Organization (WHO) reported that sepsis a common complication of BSIs affects 49 million people and causes 11 million deaths annually, disproportionately affecting children [2,3]. Symptoms range from fever, chills, and altered mental status to severe complications like septic shock and multi-organ failure.
The prevalence of BSIs varies across geographic regions and healthcare settings, influenced by factors such as patient demographics, medical practices, antibiotic usage, and antimicrobial resistance (AMR) patterns [4]. Globally, bacteria are the most frequently isolated pathogens. In low- and middle-income countries (LMICs), the most common isolates belong to the ESKAPEE group (Enterococcus spp., S. aureus, K. pneumoniae, A. baumannii, P. aeruginosa, Enterobacter spp. and E. coli). These are recognized by the WHO as critical and high-priority pathogens due to their high virulence and ability to cause severe, costly complications [5]. Other common isolates include S. viridans, S. pneumoniae, S. pyogenes and Coagulase-negative staphylococci (CoNS), with fungal isolates being rarer.
Antimicrobial resistance (AMR) in bloodstream infections poses a severe and rapidly escalating threat to global public health. In 2019, drug-resistant infections contributed to an estimated 4.95 million deaths worldwide. Projections indicate that without immediate, coordinated intervention, annual AMR-related mortality could reach 10 million by 2050 [5]. Resource-limited regions, including Ethiopia, bear the brunt of this crisis, accounting for the vast majority of these AMR-associated deaths. WHO reports highlight critically high levels of resistance in BSI-causing pathogens, including Methicillin-Resistant S. aureus (MRSA), and 3rd-generation cephalosporin and carbapenem-resistant K. pneumoniae, A. baumannii and E. coli [6]. Infections caused by these multidrug-resistant (MDR) organisms severely limit therapeutic options, require expensive medications, and increase both hospital stays and mortality [6].
Managing BSIs in developing countries such as Ethiopia remains largely empirical, heavily relying on clinical judgment in the absence of routine bacterial culture and susceptibility testing. Studies indicate that BSI prevalence among suspected septicemia cases in Ethiopia is 30.66% [7], fluctuating between 4.0% and 41.5% depending on patient risk factors [8]. The mortality rate for BSIs is approximately 50% [9]. Since bacterial pathogens and their resistance profiles are geographically variable and change rapidly, ongoing blood culture surveillance is vital for effective clinical management [10]. Therefore, this study determines the bacterial profiles and antimicrobial resistance patterns among patients with suspected BSIs at the Amhara Public Health Institute.
Materials and methods
Study design, period, and study area
This four-year retrospective study analyzed 676 blood culture and antimicrobial susceptibility records from the Amhara Public Health Institute (APHI) bacteriology reference laboratory between January 1, 2020 and December 30, 2023. The institute’s fully accredited laboratory plays a vital role in managing infectious diseases for a population of over 28.54 million in north-western and north-central Ethiopia [11].
Data collection
Laboratory blood culture records were accessed on January 6, 2025, and data were retrieved using a standardized data collection form. The extracted variables encompassed patient sex, age, bacterial growth status, isolated microbial species, and antimicrobial susceptibility profiles. For stratified analysis, patients were categorized into three age groups: (≤ 28 days), pediatrics (>28 days to 14 years), and adults (≥ 15 years). Records with missing or illegible data, as well as those identified as blood culture contaminants, were excluded from the final analysis.
Blood samples collection.
Blood samples were collected according to standardized manual blood culture methods following WHO recommendations [12]. The pre-analytical phase of blood culture procedures have a significant impact on the sensitivity, interpretation, and clinical relevance of blood cultures. The positivity of a blood culture depends on the volume of blood, number of blood culture sets and timing of blood cultures [13]. The site of venipuncture was properly disinfected with 70% alcohol followed by 2% tincture of iodine to avoid contamination of the blood culture with skin flora. Depending on institute manual blood culture collection standard operating procedure (SOP) adults, 10 ml per bottle (two aerobic bottles), pediatrics a maximum of 5 ml per bottle (two aerobic bottles) and for neonates 1 ml per bottle (two aerobic bottles) of blood sample was drawn within a 24-hour period via separate peripheral venipuncture prior to antibiotic administration [14].
Blood culture.
Following collection, blood samples were immediately transferred into blood culture bottles containing tryptone soy broth (TSB) at a standard 1:10 blood-to-broth ratio. Inoculated bottles were transported at room temperature to the laboratory within 30 minutes of collection. The bottles were then incubated at 35–37°C for up to seven days and inspected daily for macroscopic signs of microbial growth. Cultures displaying evidence of growth were sub cultured using manual blood culture systems [12].
Sub-culture of primary blood culture.
Positive blood cultures were sub cultured onto blood agar plates (BAP), MacConkey agar plates (MAP), and chocolate agar plates (CAP). The BAP and CAP media were incubated under microaerophilic conditions using a candle jar at 35–37°C for 48 hours, whereas MAP media were incubated aerobically at the same temperature for 24 hours. Bacterial identification was subsequently performed based on colony morphology, hemolysis patterns, Gram staining, and standard biochemical tests.
Bacteria identification.
Following the isolation of pure cultures from subculture plates, bacterial identification was guided by Gram stain results. Gram-negative bacilli were characterized using a panel of conventional biochemical assays, including triple sugar iron (TSI) agar fermentation, indole production, citrate utilization, urease activity, motility, lysine decarboxylase (LDC) and oxidase testing [15]. Gram-positive bacteria were identified using conventional biochemical assays, including catalase, coagulase, bile esculin agar and mannitol fermentation, in accordance with the Clinical and Laboratory Standards Institute (CLSI) 2024 guidelines [16,17]. Candida spp. were identified based on macroscopic features, including colony morphology, growth rate, and surface texture, and further confirmed via microscopic examination and the germ tube test [7].
Antimicrobial susceptibility testing
Antimicrobial susceptibility testing (AST) was performed for each isolate on Mueller–Hinton agar using the standardized Kirby–Bauer disk diffusion method, in accordance with the Clinical and Laboratory Standards Institute (CLSI) 2024 (M100) guidelines [16]. Bacterial suspensions were prepared, adjusted, and inoculated onto the agar surface. Gram-positive isolates were tested against chloramphenicol (30 μg), cefoxitin (30 μg), penicillin (10 units), gentamicin (10 μg) and vancomycin (30 µg). Gram-negative isolates were evaluated using ampicillin (10 µg), amoxicillin-clavulanic acid (30 μg), ceftriaxone (30 μg), ceftazidime (30 μg), chloramphenicol (30 μg), ciprofloxacin (5 μg), gentamicin (10 μg), imipenem (10 μg), meropenem (10 μg), trimethoprim-sulfamethoxazole (1.25/23.75 μg), tobramycin (10 μg) and piperacillin-tazobactam (100/10 μg). These specific antimicrobial agents were selected based on their local availability and high prescription frequency for managing bloodstream infections in Ethiopia, particularly within the study area. Following overnight incubation, zones of inhibition were measured to categorize the isolates as susceptible, intermediate, or resistant. All antibiotic disks were sourced from Oxoid Ltd. (Basingstoke, Hampshire, UK).
Definitions
Bacterial isolates were classified as multidrug-resistant (MDR), extensively drug-resistant (XDR), or pandrug-resistant (PDR) according to the criteria defined by Magiorakos et al [9].
- Multi-drug resistance: defined as non-susceptibility to at least one agent in three or more antimicrobial classes [9].
- Extensive-drug resistance: defined as non-susceptibility to at least one agent in all but two or fewer antimicrobial categories tested for a particular microorganism [9].
- Pan-drug resistance was defined as non-susceptibility all to agents in all antimicrobial classes for each bacterium in this study [9].
- Blood culture contamination: defined as the growth of common skin commensals in only a single blood culture set out of a series [18,19].
- Contaminant species: included Diphtheroids (excluding Corynebacterium diphtheriae), Bacillus spp. (excluding Bacillus anthracis), coagulase-negative staphylococci (CoNS), Propionibacterium spp, Aerococcus spp, Micrococcus spp. and Streptococci viridans regardless of the number of positive blood culture bottles [18,19].
Quality control
Standard operating procedures (SOPs) for blood culture processing were strictly followed across all phases including sample collection, transportation, inoculation, incubation, and biochemical identification to ensure data accuracy and reliability. Media quality control was performed by randomly selecting 5% of each prepared batch and incubating it aerobically at 35–37°C for 24 hours to confirm sterility. Media performance was further validated using standard control strains prior to inoculation and susceptibility testing. Antibiotic disks were selected based on local availability in accordance with CLSI guidelines [16]. Quality control for organism identification and susceptibility testing was maintained using reference strains, including E. coli ATCC 25922, S. aureus ATCC 25923 and P. aeruginosa ATCC 27853. Finally, senior microbiologists verified the accuracy of all inoculation techniques, colony characterizations, zone measurements, and AST interpretations.
Data analysis and interpretation
Statistical analysis was performed using SPSS version 20 for data entry, cleaning, coding, and modeling. Descriptive statistics, including frequencies and percentages, were calculated to summarize the study variables. To assess the strength of association between independent and dependent variables, binary logistic regression models were utilized. Variables demonstrating a p-value < 0.20 in the bivariate analysis were entered into the multivariate logistic regression model to control for confounding and identify independent associations. Statistical significance was evaluated using adjusted odds ratios (AOR) with corresponding 95% confidence intervals (CI). Finally, the data analyzed was presented using text, tables, and graphs.
Ethical consideration
Ethical approval for this study was granted by the regional public health research Ethical Review Committee (ERC) (Ref: NOH/R/T/D/07/74). Furthermore, permission was obtained from the institute’s laboratory director and the head of the bacteriology reference laboratory. Because the study utilized secondary, routinely collected laboratory culture data, the requirement for patient informed consent was waived by the ERC. To ensure patient confidentiality, all personal identifiers were removed, and the dataset was analyzed entirely anonymously. All relevant data was included within the manuscript and supporting information files without restriction. The study was conducted in full compliance with the ethical principles of the Declaration of Helsinki.
Results
Socio- demographic and clinical characteristics of study participants
Between 2020 and 2023, a total of 817 blood culture records were retrieved; 141 were excluded as contaminants, leaving 676 records for the final analysis. The mean age of the participants was 15.86 years (SD ± 20.8 years; range: 1 day to 90 years). More than half of the participants were male (58.9%, N = 398). The most represented age groups were infants aged 29 days to 5 years (27.8%, N = 188), followed by neonates (≤ 28 days) (23.8%, N = 161). Regarding clinical management settings, most of the study participants were treated in inpatient department (89.1%, N = 602) (Table 1).
Regarding clinical indications, many participants were investigated for suspected community-acquired bloodstream infections (75.0%, N = 507), followed by hospital-acquired infections (11.7%, N = 79) and surgical site infections (3.6%, N = 24). Notably, a high proportion of the study population (78.4%, N = 530) reported a history of prior antimicrobial use. In terms of temporal distribution, the highest sample volume was recorded in 2021, accounting for 38.3% (N = 259) of the total study population (Table 1).
Bacteriological profiles of bloodstream infection suspected patients
Out of 817 blood culture records retrieved, 58.9% (N = 481) yielded growth, while 41.1% (N = 336) showed no growth. Among the positive cultures, 29.3% (N = 141) were identified as contaminants and excluded from further analysis. These included Coagulase-negative staphylococci (CoNS) (27%, N = 130), Bacillus spp. (1.2%, N = 6) and Candida spp. (1%, N = 5). The remaining 676 blood culture records were included in the final analysis, of which 50.3% (N = 340) yielded true bacterial pathogens (Fig 1).
Among the 340 true bacterial pathogens, Gram-negative bacteria were the most frequent isolates at 61.2% (N = 208), while Gram-positive bacteria accounted for the remaining 38.8% (N = 132) (Fig 2).
Among true bloodstream infections, ESKAPEE pathogens accounted for 96.4% (N = 328) of isolates, driven primarily by Klebsiella spp. 25.9% (n = 88), Enterococcus spp. 20.9% (N = 71), and S. aureus 15.6% (N = 53) (Fig 3).
Non-ESKAPEE pathogens were infrequently isolated, accounting for only 3.5% (N = 12) of the true pathogens. Among these, Citrobacter spp. and true CoNS represented 1.2% (N = 4) and 0.6% (N = 2) respectively (Fig 4).
Antimicrobial susceptibility patterns of bacterial isolates
Analysis of the antimicrobial resistance patterns among Gram-positive isolates revealed high resistance rates to oxacillin were 74.5% (N = 41), penicillin was 72% (N = 36), and vancomycin was 51.1% (N = 24). Resistance profiles varied significantly across species. While Enterococcus spp. demonstrated high susceptibility to chloramphenicol 77.8% (N = 42), they exhibited substantial resistance to penicillin 71.1% (N = 32) and vancomycin 57.1% (N = 24). Among S. aureus isolates, susceptibility to gentamicin was 56.7% (N = 21), but resistance to oxacillin and penicillin reached 75.5% (N = 40) and 80% (N = 4) respectively. In contrast, S. pneumoniae and S. viridans isolates displayed complete susceptibility to gentamicin, vancomycin, and chloramphenicol. Overall, gentamicin and chloramphenicol demonstrated the highest cumulative efficacy against the Gram-positive pathogens in this study (Table 2).
In this study, Gram-negative bacteria were resistant to commonly used antimicrobials include ampicillin 100% (N = 24), ceftriaxone 92.4% (N = 157), trimethoprim-sulphamethoxazole 89.4% (N = 126), amoxicillin-clavulanic acid 81.1% (N = 103), ceftazidime 80.9% (N = 93), gentamicin 118 76.6% (N = 118), tobramycin 70.3% (N = 109), ciprofloxacin 66.5% (N = 127), and piperacillin-tazobactam 66.7% (N = 14) respectively.
Klebsiella species exhibited severe resistance profiles, with K. oxytoca reaching 100% resistance to ceftriaxone, ceftazidime, and tobramycin and K. pneumoniae demonstrating up to 96.3% (N = 26) resistance to ceftazidime and ceftriaxone 95.5% (N = 63), trimethoprim-sulphamethoxazole 89.6% (N = 60), gentamicin 83.8% (N = 57), amoxicillin-clavulanic acid 80% (N = 48), piperacillin-tazobactam 80% (N = 4), tobramycin 76.1% (N = 35), and ciprofloxacin 69.6% (N = 48) respectively. Chloramphenicol 53.3% (N = 8), imipenem 57.1% (N = 4), and meropenem 87.5% (N = 7) were more effective against K. pneumoniae.
A. baumannii showed high levels of resistance to ceftriaxone 87.1% (N = 27), ceftazidime 78.1% (N = 25), tobramycin 61.5% (N = 24), and ciprofloxacin 58.1% (N = 25). It was found that A. baumannii was susceptible to imipenem 60% (N = 6) and meropenem 50% (N = 6). The isolates of E. coli showed high resistance to ciprofloxacin 75% (N = 15), ampicillin 100% (N = 12), ceftriaxone 90% (N = 18), tobramycin 88.9% (N = 16), and amoxicillin-clavulanic acid 76.2% (N = 16). Chloramphenicol 50% (N = 4), imipenem 60% (N = 3), and meropenem 83.3% (N = 5) were more effective against E. coli. Additional, E. cloacae showed high resistance to the following antimicrobials: ampicillin 100% (N = 11), trimethoprim-sulphamethoxazole 95% (N = 19), amoxicillin-clavulanic acid 94.4% (N = 17), ceftriaxone 90.9% (N = 20), ceftazidime 90% (N = 9), chloramphenicol 88.9% (N = 8), gentamicin 77.3% (N = 17), ciprofloxacin 76.2% (N = 16), and tobramycin 70.6% (N = 12). E. cloacae were susceptible to meropenem 80% (N = 4) and imipenem 57.1% (N = 4). Notably, P. aeruginosa presented a reversal of typical trends, displaying 100% (N = 1) resistance to imipenem but remaining highly sensitive to tobramycin 71.4% (N = 10) and ceftazidime 61.5% (N = 8) resistance (Table 3 and Fig 5).
Prevalence of MDR, XDR and PDR bacterial isolations
This study analyzed antimicrobial susceptibility test for 50.3% (N = 340) of true pathogenic bacterial isolates. Multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR) strains were identified; MDR accounted for 43.8% (N = 149), XDR for 30.5% (N = 104), and PDR for 5.3% (N = 18) of the isolates. In ESKAPEE pathogens, MDR, XDR, and PDR were 44.2% (N = 145), 31.4% (N = 103), and 5.1% (N = 17). The non-ESKAPEE pathogens were also 28.6% (N = 4), 7.1% (N = 1), 7.1% (N = 1) MDR, XDR, and PDR, respectively. The following Gram-negative bacteria in particular notable MDR, XDR, and PDR frequencies: Klebsiella spp. 81.8% (N = 88), 9.1% (N = 8), 6.8% (N = 6), Enterobacter spp.70.6% (n = 24), 14.7% (N = 5), 14.7% (N = 5), E. coli 77.3% (N = 17), 13.6% (N = 3) and 9.1% (N = 2) respectively (Table 4).
Factors associated with bloodstream infections
Both bivariable and multivariable logistic regression analyses demonstrated that sex and age were the only independent predictors of a positive culture result, whereas clinical setting and prior antimicrobial use had no statistically significant impact. While males comprised the majority of the study population 58.8% (N = 398), female sex was associated with a significantly lower likelihood of culture positivity (AOR = 0.56; 95% CI: 0.39–0.81; p = 0.002), representing a 44% reduction in odds compared to males. Age-stratified analysis revealed substantially elevated risks of positive cultures in two specific independent predictors relative to elderly patients (≥ 65 years). Specifically, neonates (≤ 28 days) were 4.7 times more likely to test positive (AOR = 4.70; 95% CI: 1.83–12.03; p = 0.001), while young adults aged 15–24 years exhibited the highest risk, with nearly 9.5-fold higher odds of a positive culture (AOR = 9.46; 95% CI: 3.08–29.03; p = 0.001). No statistically significant differences in culture outcomes were observed for the remaining age brackets when compared to the elderly patients (Table 5).
Discussion
Bloodstream infections (BSIs) remain a primary global driver of severe morbidity and mortality. Because pathogen distribution and antimicrobial resistance trends vary significantly by geographic region, localized surveillance data are vital for optimizing empirical antimicrobial therapy and guiding effective public health strategies.
In the present study, the overall prevalence of true bacterial isolates among patients suspected of bloodstream infections was 50.3% (N = 340). This finding is consistent with previous studies conducted in California (49.5%) [20], China (55.1%, 42.9%) [21,22], and Saudi Arabia (46.6%) [23], Tanzania (45.5%) [24,25], Nigeria (42.8%) [26], Malawi (48.9%) [27], Egypt (50.4%) [28], Ethiopia (56%) [29,30]. These findings reveal a substantial burden of bacterial pathogens within the study population, underscoring a critical regional public health concern that demands targeted intervention. Conversely, the prevalence noted in our study falls below the rates previously documented in other Ethiopian healthcare facility (76.8%) [31]. This variation may be from differences in clinical sample collection protocols, prior empirical antibiotic exposure, or regional variations in patient demographics. Conversely, the positivity rate in our study was higher than the finding from a study conducted in Italy (20.0%) [32], Baghdad (20.8%) [33], Bangladesh (18.8% [34], Maldives (4.9%) [35], Nepal (7.2 % and 7%) [36,37], Tanzania (5.2%) [38], China (7.9%) [39], India (25.3%, 29.8% and 14.2%) [40–42], Asmara (35.5%) [43] and Ethiopia (9.8%, 28.06%, 25.5%) [44–47]. This disparity may be attributed to geographic variations, distinct study periods, and differences in patient demographic profiles, sampling techniques and microbiological methodologies.
In this study, Gram-negative bacteria were identified as the primary cause of bloodstream infections (BSIs), accounting for 61.2% (N = 208) of isolates, while Gram-positive bacteria were responsible for 38.8% (N = 132) of isolates. This clear predominance of Gram-negative pathogens aligns with recent studies conducted in Italy (62.0% vs 37.3%) [48,49], Vietnam (64.12% vs 28.73%, 67.9% vs 31%, 65.7% vs 34.3%) [14,50–52], Nepal (78.7% vs 21.31%, 65% vs 35%) [36,53,54], India 70·0% vs 30%, (56.7% vs 36.7%) [55–57], Saudi Arabia (71.9% vs 28.1%) [58], South Africa (57% vs 36%, 60% vs 33%) [29,18], Zambia (64.8% vs 35.2%) [19], Ethiopia (54.5% vs 45.43%, 60% vs 30.8%, 58% vs 40.4%) [30,31,45]. In contrast to our findings, Gram-positive bacteria are consistently reported as the predominant etiology of bloodstream infections (BSIs) in studies conducted in Bangladesh (68.9% vs 31.1%) [59]), Nepal (64.6% vs 35.4%) [60], China (61.84% vs 38.26%) [61], Ghana (67% vs 33%) [62] and Ethiopia (59.1% vs 40.9%, 77.4% vs 22.6%) [44,47]. This notable predominance may be attributed to the intrinsic resistance characteristic of Gram-negative pathogens, alongside their capacity for prolonged survival and persistence within healthcare environments.
In this study, a substantial proportion of bloodstream infections 96.5% (N = 328), were caused by the emerging ESKAPEE group of pathogens. Among these, Klebsiella spp. were the most frequently isolated organisms at 25.8% (N = 88), followed by Enterococcus spp. at 20.8% (N = 71), S. aureus at 15.5% (N = 53), A. baumannii at 13.2% (N = 45), Enterobacter spp. at 10% (N = 34), E. coli at 6.4% (N = 22) and P. aeruginosa at 4.4% (N = 15) respectively. This pathogen distribution aligns closely with studies done from Perugia (78.9%) [63], Romania (75.6%, 97%) [64,65], Italy (38.7%) [66], India (77.6%) [67], Turkey (73.2%) [68], China (73.1%) [69], Zambia (25.7%) [70] and Ethiopia (67%, 65.3%) [31,71]. This pattern is largely due to the widespread resistance of these pathogens to common first-line antibiotics, creating significant therapeutic challenges in clinical management.
In our study, resistance among Gram-positive pathogens was critically high for oxacillin 74.6% (N = 41), penicillin 72% (N = 36), and vancomycin 51.1% (N = 24). Similar escalating resistance profiles have been documented in blood culture studies from other parts of the countries, Turkey (penicillin 93.8%, oxacillin 44.3%) [72], Bangladesh (penicillin 92%) [59], India (oxacillin 40.6% and vancomycin 11.9%, oxacillin 70.6% and vancomycin 21.6%) [73,74], Saudi Arabia (oxacillin 12.3%) [75], Macedonia (penicillin 100% and vancomycin 33,3%) [76], Asmara (oxacillin 80.4%) [43], Ethiopia (penicillin 60%, oxacillin 66.7%) [77], (oxacillin 63%), (oxacillin 62.5% and penicillin 81%), (penicillin 92.4%), (penicillin 85%, oxacillin 38% and vancomycin 94%) [46,78–82] have also reported comparable finding on this regards. This may be due to several mechanisms, including enzymatic degradation of antimicrobials, alterations in drug targets, reduced drug uptake, and the formation of biofilms. While some studies in Colombia report lower resistance rates to oxacillin (40.8%) and penicillin (51%) [83]. This variation may be attributed to differences in study population, variations in diagnostic methodologies, and the continuous evolution of antimicrobial resistance profiles over time.
The present study indicates a high level of antimicrobial resistance in Enterococcus spp. to penicillin 71.1% (N = 32) and vancomycin 57.1% (N = 24). This alarming resistance profile aligns with reports from China, where Enterococcus spp. demonstrated a penicillin resistance rate of 94.1% and a vancomycin resistance rate of 31.1% [84,85]. These high levels of antimicrobial resistance may be driven by several factors, including intrinsic resistance, acquired resistance mechanisms, and the selective pressure of antimicrobial use.
In the present study, S. aureus isolates demonstrated substantial resistance to penicillin 80% (N = 4) and oxacillin 75.5% (N = 40). These findings are consistent with surveillance data from Turkey, where oxacillin resistance rates among S. aureus isolates ranged from 50.8% to 66.0% [86,87], Italy (oxacillin 36.4%) [49], Iran (penicillin 91.8%) [88], Vietnam (oxacillin 77.2%), Bangladesh (penicillin 87.5%) [89], Saudi Arabia (penicillin 98%) [75], Nigeria (37.5%) [90], Asmera (oxacillin 80.4%) [43], Ethiopia penicillin resistance rates ranging from 83.5% to 86.7%, and oxacillin resistance from 24.5% to 88.9% [8,31,46,79,80,91–93]. This is might be due to the presence of the mecA gene, which encodes for the altered penicillin-binding protein PBP2a, leading to resistance to beta-lactam antimicrobials like penicillin and oxacillin. The current study’s findings may deviate from Bangladesh oxacillin (7.40%) [89] and Ethiopia (penicillin 29.4%) [94].This might be due to variations in bacterial strains, genetic makeup, and the presence of other resistance mechanisms beyond the standard mecA-mediated resistance.
The Gram-negative bacterial isolates exhibit a high level of resistance to ampicillin 100% (N = 24), ceftriaxone 92.4% (n = 157), trimethoprim-sulphamethoxazole 89.4% (n = 126), amoxicillin-clavulanic acid 81.1% (N = 103), ceftazidime 80.9% (N = 93), gentamicin 118 76.6% (N = 118), tobramycin 70.3% (N = 109), piperacillin-tazobactam 66.7% (N = 14) and ciprofloxacin 66.5% (N = 127) respectively. These resistance profiles closely align with the findings reported in Palestinian resistance to ampicillin (87.2%) [95]. Similarly, multiple studies from Ethiopia have documented comparable trends, with ampicillin resistance ranging from 66.0% to 93.0%, amoxicillin-clavulanic acid from 83.9% to 88.7%, cotrimoxazole from 64.1% to 75.5%, and ceftriaxone at 82.6% [8,77,80,82,96–99] respectively. This pervasive increase in antimicrobial resistance is likely driven by inherent bacterial defense mechanisms, the horizontal acquisition of resistance genes, and the selective pressure exerted by widespread antimicrobial utilization. Conversely, resistance rates in the present study were notably higher than those reported in Nepal, where gentamicin and ampicillin resistance were limited to 7.4% and 66.6% [100] respectively. These discrepancies are most likely attributable to regional variations in antibiotic prescribing behaviors, local healthcare infrastructure, and the distinct geographical distribution of resistant bacterial strains.
In the present study, K. pneumoniae isolates demonstrated high resistance rates to ceftazidime 96.3% (N = 26), ceftriaxone 95.5% (N = 63), trimethoprim-sulphamethoxazole 89.6% (N = 60), gentamicin 83.8% (N = 57), amoxicillin-clavulanic acid 80% (N = 48), piperacillin-tazobactam 80% (N = 4), tobramycin 76.1% (N = 35), and ciprofloxacin 69.6% (N = 48) respectively. Similar high resistance profiles have been documented across sub-Saharan Africa. For instance, studies in Zambia reported substantial resistance to gentamicin (81%) and fluoroquinolones (80.8%) [101]. In Cameroon, notable resistance was observed against beta-lactams (72%), phenolics (62.30%), and quinolones (60.41%) [102]. Furthermore, data from Ethiopia highlighted significant resistance to ampicillin (75%), amoxicillin-clavulanic acid (62.5%), ceftriaxone (62.5%), and trimethoprim-sulfamethoxazole (50%) [94]. The elevated resistance rates observed in K. pneumoniae are typically driven by inherent bacterial defense mechanisms, selective pressure from widespread antimicrobial misuse, and the horizontal transfer of resistance genes between bacterial populations. Conversely, certain strains demonstrated continued susceptibility to specific reserve antibiotics. In the present study, K. pneumoniae displayed the highest susceptibility to meropenem 87.5% (N = 7), followed by imipenem at 57.1% (N = 4) and chloramphenicol at 53.3% (N = 8). These susceptibility trends align closely with previous findings from Cameroon, which similarly recorded high susceptibility rates for imipenem (91.7%), co-trimoxazole (78.1%), tobramycin (71.8%), and gentamicin (56.2%) [102,103].
In this study, A. baumannii isolates demonstrated notable resistance to several common antimicrobials, including ceftriaxone 87.1% (N = 27), ceftazidime 78.1% (N = 25), tobramycin 61.5% (N = 24) and ciprofloxacin 58.1% (N = 25). These resistance profiles are comparable with findings reported in previous studies in Greece (80% to 100%) [104], though notably higher than those observed in Nepal 26.8% [42]. Conversely, the isolates in this cohort retained moderate sensitivity to carbapenem reserve antibiotics, specifically imipenem at 60% (N = 6) and meropenem at 50% (N = 6). Generally, A. baumannii develops resistance to these beta-lactam agents through four primary mechanisms: enzymatic inactivation by hydrolysis, increased drug efflux, decreased membrane influx, or structural protection of the antimicrobial target site.
In the present study, the overall prevalence of multidrug-resistant (MDR) isolates was 43.6% (N = 149). This rate is slightly lower than previous findings reported in West Africa (59%), and various regions in Ethiopia (47.1% to 61.6%) [130–133]. Considerably higher MDR resistance rates have been documented elsewhere, such as in Bangladesh (83.4%) [59], Zambia (90%) [87], and in other Ethiopian studies where rates ranged from 68.2% to 84.4% [44,57,95,97,99,134]. Conversely, markedly lower MDR prevalence were reported in New Zealand (3.4%) [135], Italy (6%) [136], South Korea (24.7%) [137], and a specific localized study in Ethiopia (19.7%) [138].
In the present study, the overall prevalence of multidrug-resistant (MDR) isolates was 43.6% (N = 149). This rate is slightly lower than previous findings reported in West Africa (59%) [105], Nigeria (57.4%) [106], and various regions across Ethiopia (47.1% to 61.6%) [107–110] . However, more elevated resistance rates have been reported in Bangladesh (83.4%) [59], Zambia (90%) [87], and other studies in Ethiopia (ranging from 68.2% to 84.4%) [44,57,95,97,99]. Conversely, lower MDR rates were documented in New Zealand (3.4%) [111], Italy (6%) [112], South Korea (24.7%) [113], and a specific study in Ethiopia (19.7%) [114]. Among the ESKAPEE pathogens, 44.2% (N = 145) of the isolates exhibited multidrug resistance. This aligns with previous regional and international data showing high resistance profiles, such as in Greece (P. aeruginosa at 30% and A. baumannii at 97%)[115], Turkey (50.86%) [15], and Ethiopia (A. baumannii at 100%, MRSA at 90%, and K. pneumoniae at 67%) [44,88]. Because the highest rates of MDR were predominantly observed among Gram-negative bacterial isolates, conducting routine antimicrobial susceptibility testing is essential to guide effective treatment and manage the spread of bacterial infections. In the present study, the prevalence rates of extensive drug-resistant (XDR) and pandrug-resistant (PDR) bacterial isolates were 30.4% (N = 104) and 5.3% (N = 18) of bacterial isolated. These findings are consistent with those reported from Greece (22%) [104], Nigeria XDR (11.9%) and PDR (4.0%) [116], Addis Ababa XDR (22.4%) and (4%) [117] respectively. Our study finding were higher than others studies, in Canada XDR (2.6%) [118], Saudi Arabia (3.5%) and no PDR were isolated [119], India (5.4%) [120]. However lower than studies conducted in Iran 96.4% were XDR and 76.4% were PDR [121], Pakistan XDR (51%), (54.7%) [122,123], Saudi Arabia XDR (10%) and PDR (6%), [124], Addis Ababa XDR, and PDR were 32.2% and 7.3% [45], Gondar XDR (24.8%) and PDR (4.8%) [125], Bahir Dar XDR, and PDR were 53%, 43% and 2% [71] respectively. This may be due to increased selection pressure caused by self-medication, misuse and overuse of antimicrobials and absence of an appropriate antibiotic policy.
In the present study, both bivariable and multivariable logistic regression analyses revealed that female sex was associated with a significantly lower likelihood of culture positivity (AOR = 0.56; 95% CI: 0.39–0.81; p = 0.002), representing a 44% reduction in odds compared to males. This finding is strongly supported by previous studies in Norway that females had lower risk of BSI compared to males (AOR) = 1.4, 95% CI = 1.32–1.59) [126], Ireland (AOR)=1.3, 95% CI = 1.31–1.46) [127], Maldives (59%) [35], Brazil (AOR) = 2.9, 95% CI = 1.18–7.47, P = 0.02) [128] and Minnesota BSIs were less common in females than males (23.8% vs 13.9%; P = 002) [129]. This might be due to differences in biological immunity, anatomical differences and behavioral factors. While others studies in Tanzania indicated that female (AOR) =2.2, 95% CI = 1.01, 4.80; p = 0.048) were associated with increased odds of BSI [130]. In contrary a study in Iran reported that no significant association was found between BSIs and gender (P = 0.70) [131].
According to our data, neonates (≤ 28 days) were 4.7 times more likely to test positive (AOR = 4.70; 95% CI: 1.83–12.03; p = 0.001), while young adults aged 15–24 years exhibited the highest risk, with nearly 9.4-fold higher odds of a positive culture (AOR = 9.46; 95% CI: 3.08–29.03; p = 0.001). This finding is consistent with other studies reported in Malaysia significantly associated with 28-day with increased BSI (AOR) =1.0: 95% CI = 1.03–1.09; p < 0.001) [132], South Korea (AOR) =2.1, 95% Cl = 1.18–3.77, P = 0.005) [133], Sweden (AOR) = 5.5, 95% CI = 2.8–11.0) [134], Ethiopia (AOR) = 3.4, 95% CI = 1.63–7.11, p = 0.001) [135]. This result was different from studies conducted China [136] showed that older adults are more prone to bloodstream infection due to aging organ function, low immunity and underlying disease.
This study has several limitations. Its retrospective design introduces inherent data constraints, and resource limitations precluded anaerobic blood cultures, potentially lowering the overall diagnostic yield. Additionally, antimicrobial susceptibility testing was restricted to disk diffusion without determining minimum inhibitory concentration (MIC) values. Lastly, because molecular characterization was not performed, specific resistance genes could not be identified.
Conclusion and recommendations
This study highlights a critical public health crisis with a 50.3% bacterial bloodstream infection rate, dominated by Gram-negative and ESKAPEE pathogens. Resistance is alarmingly high, with over 43% multidrug-resistant strains and extensive failure of first-line drugs like ampicillin and ceftriaxone, particularly risking males, neonates, and young adults. To combat this, healthcare facilities must immediately restrict antibiotic misuse through strict stewardship, update empirical guidelines, and upgrade routine lab testing. Additionally, future research must implement anaerobic culturing, quantitative MIC testing, and molecular sequencing to accurately track and manage these drug-resistant strains.
Acknowledgments
The authors express their gratitude to the staff at the Amhara Public Health Institute bacteriology reference laboratory for their technical assistance and support throughout this study.
References
- 1. Holmes CL, Albin OR, Mobley HLT, Bachman MA. Bloodstream infections: mechanisms of pathogenesis and opportunities for intervention. Nat Rev Microbiol. 2025;23(4):210–24. pmid:39420097
- 2. Rudd KE, et al. Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study. Lancet. 2020;395(10219):200–11.
- 3.
World Health Organization. Global report on the epidemiology and burden of sepsis: current evidence, identifying gaps and future directions. World Health Organization; 2020.
- 4. Lafuente Cabrero E, Terradas Robledo R, Civit Cuñado A, García Sardelli D, Hidalgo López C, Giro Formatger D, et al. Risk factors of catheter- associated bloodstream infection: Systematic review and meta-analysis. PLoS One. 2023;18(3):e0282290. pmid:36952393
- 5. Abdallah EM, Alhudhaibi AM, Dahab M, Al Noman A, Sharma PD, Taha TH, et al. The WHO priority list of antibiotic-resistant bacteria: challenges and opportunities for next-generation antimicrobial development. Front Pharmacol. 2026;17:1699987. pmid:42038316
- 6. Allel K, Stone J, Undurraga EA, Day L, Moore CE, Lin L, et al. The impact of inpatient bloodstream infections caused by antibiotic-resistant bacteria in low- and middle-income countries: A systematic review and meta-analysis. PLoS Med. 2023;20(6):e1004199. pmid:37347726
- 7. Chiang SJF, Chien M-K, Tsai C-Y, Hsiao J-C, Koo F-H, Yen Y-F, et al. A Simple, Fast, and Reliable Method for the Identification of Candida albicans. Environ Health Insights. 2024;18:11786302241272398. pmid:39290369
- 8. Belew H, Tamir W, Dilnessa T, Mengist A. Phenotypic Bacterial Isolates, Antimicrobial Susceptibility pattern and Associated factors among Septicemia Suspected Patients at a hospital, in Northwest Ethiopia: Prospective cross-sectional study. Ann Clin Microbiol Antimicrob. 2023;22(1):47. pmid:37349767
- 9. Magiorakos A-P, Srinivasan A, Carey RB, Carmeli Y, Falagas ME, Giske CG, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect. 2012;18(3):268–81. pmid:21793988
- 10. Li K, Li L, Wang J. Distribution and Antibiotic Resistance Analysis of Blood Culture Pathogens in a Tertiary Care Hospital in China in the Past Four Years. Infect Drug Resist. 2023;16:5463–71. pmid:37638064
- 11. Shiferaw MB, Sisay Misganaw A. Evaluation of continuous quality improvement of tuberculosis and HIV diagnostic services in Amhara Public Health Institute, Ethiopia. PLoS One. 2020;15(3):e0230532. pmid:32191762
- 12.
Organization WHO. WHO guidelines on drawing blood: best practices in phlebotomy, in WHO guidelines on drawing blood: best practices in phlebotomy. 2010. 130 p.
- 13. Snyder JW. Blood Cultures: the Importance of Meeting Pre-Analytical Requirements in Reducing Contamination, Optimizing Sensitivity of Detection, and Clinical Relevance. Clin Microbiol Newsl. 2015;37(7):53–7.
- 14. Quang H-V, Nhung L-TK, Thuy P-TT, Quyen PC, Huy LB, Dung HS. Blood-Stream Infections: Causative Agents, Antibiotic Resistance and Associated Factors in Older Patients. Mater Sociomed. 2024;36(1):82–9. pmid:38590604
- 15. Shume T, Tesfa T, Mekonnen S, Asmerom H, Tebeje F, Weldegebreal F. Aerobic Bacterial Profile and Their Antibiotic Susceptibility Patterns of Sterile Body Fluids Among Patients at Hiwot Fana Specialized University Hospital, Harar, Eastern Ethiopia. Infect Drug Resist. 2022;15:581–93. pmid:35228808
- 16.
Lewis I, James S. Performance standards for antimicrobial susceptibility testing. 2024.
- 17. Humphries R, Bobenchik AM, Hindler JA, Schuetz AN. Overview of Changes to the Clinical and Laboratory Standards Institute Performance Standards for Antimicrobial Susceptibility Testing, M100, 31st Edition. J Clin Microbiol. 2021;59(12):e0021321. pmid:34550809
- 18. Mashau RC, et al. Culture-confirmed neonatal bloodstream infections and meningitis in South Africa, 2014–19: a cross-sectional study. Lancet Glob Health. 2022;10(8):e1170–8.
- 19. Shawa M, Paudel A, Chambaro H, Kamboyi H, Nakazwe R, Alutuli L, et al. Trends, patterns and relationship of antimicrobial use and resistance in bacterial isolates tested between 2015-2020 in a national referral hospital of Zambia. PLoS One. 2024;19(4):e0302053. pmid:38625961
- 20. Nava GR, et al. Inpatient hospice impact on blood culture practices near the time of death, tertiary center, Northern California, 2019–2023. Antimicrob Steward Healthc Epidemiol. 2024;4(S1):s85–6.
- 21. Zhou Y, et al. Bacterial distribution and drug resistance in blood samples of children in Jiangxi region, 2017–2021. Front Cell Infect Microbiol. 2023;13:1163312.
- 22. Ren J, Duan S, Wu Y, Wen M, Zhang J, Liu Y, et al. Multidrug-resistant bacterial infection in adult patients following cardiac surgery: clinical characteristics and risk factors. BMC Cardiovasc Disord. 2023;23(1):472. pmid:37735348
- 23.
Al-Shukri RNK. Prevalence, Predictors and Outcomes of ICU-Acquired Central Line-Associated Bloodstream Infections in Oman. Oman: Sultan Qaboos University; 2021.
- 24. Kumburu HH, Sonda T, Mmbaga BT, Alifrangis M, Lund O, Kibiki G, et al. Patterns of infections, aetiological agents and antimicrobial resistance at a tertiary care hospital in northern Tanzania. Trop Med Int Health. 2017;22(4):454–64. pmid:28072493
- 25. Moorthy GS, et al. Clinical characteristics, antimicrobial resistance, and mortality of neonatal bloodstream infections in Northern Tanzania, 2022–2023. PLoS One. 2025;20(3):e0319816.
- 26. Isaac EW, Jalo I, Manga MM, Difa AJ, Poksireni MR, Christianah O, et al. Trends in Bacterial Blood Culture Isolates and Resistance in Children in Two Microbiologic Eras from a Tertiary Health Facility in North East Nigeria. OJMM. 2023;13(02):159–82.
- 27. Kumwenda P, Adukwu EC, Tabe ES, Ujor VC, Kamudumuli PS, Ngwira M, et al. Prevalence, distribution and antimicrobial susceptibility pattern of bacterial isolates from a tertiary Hospital in Malawi. BMC Infect Dis. 2021;21(1):34. pmid:33413184
- 28. El-Sokkary RH, Ramadan RA, El-Shabrawy M, El-Korashi LA, Elhawary A, Embarak S, et al. Community acquired pneumonia among adult patients at an Egyptian university hospital: bacterial etiology, susceptibility profile and evaluation of the response to initial empiric antibiotic therapy. Infect Drug Resist. 2018;11:2141–50. pmid:30464557
- 29. Dramowski A, Cotton MF, Rabie H, Whitelaw A. Trends in paediatric bloodstream infections at a South African referral hospital. BMC Pediatr. 2015;15:33. pmid:25884449
- 30. Tsegaye EA, Teklu DS, Bonger ZT, Negeri AA, Bedada TL, Bitew A. Bacterial and fungal profile, drug resistance pattern and associated factors of isolates recovered from blood samples of patients referred to Ethiopian Public Health Institute: cross-sectional study. BMC Infect Dis. 2021;21(1):1201. pmid:34844570
- 31. Seid M, Bayou B, Aklilu A, Tadesse D, Manilal A, Zakir A, et al. Antimicrobial resistance patterns of WHO priority pathogens at general hospital in Southern Ethiopia during the COVID-19 pandemic, with particular reference to ESKAPE-group isolates of surgical site infections. BMC Microbiol. 2025;25(1):84. pmid:39987036
- 32. Capsoni N, Azin GM, Scarnera M, Bettina M, Breviario R, Ferrari L, et al. Bloodstream infections due to multi-drug resistant bacteria in the emergency department: prevalence, risk factors and outcomes-a retrospective observational study. Intern Emerg Med. 2025;20(2):573–83. pmid:39001978
- 33. Al-shattrawi HJG. Evaluation Of Bacterial Pathogens And Antimicrobial Resistance In Blood Isolates From Febrile Cases At Medical City Hospital In Baghdad. Acad Open. 2025;10(1):10497.
- 34. Talha KA, Patwary MI, Fatema K, Ahmad H, Selina F, Bhuiyan MS, et al. Bacteriological Profile and Antibiogram of Blood Stream Infection in a Tertiary Teaching Hospital of Bangladesh. Mymensingh Med J. 2025;34(1):186–91. pmid:39739488
- 35. Maharath A, Ahmed MS. Bacterial Etiology of Bloodstream Infections and Antimicrobial Resistance Patterns from a Tertiary Care Hospital in Malé, Maldives. Int J Microbiol. 2021;2021:3088202. pmid:34707660
- 36. Simkhada S, Prakash S. Bacteriological profile and antibiotic susceptibility pattern of blood culture isolates from patients visiting tertiary care hospital. Glob J Med Res Microbiol Pathol. 2016;16(1).
- 37. Adhikhari A, Mishra VP, Parajuli P. Burden of Antibiotic Resistance in Bloodstream Infections. SXC J. 2025;2(1):96–108.
- 38. Kortz TB, et al. Prospective genomic surveillance of severe febrile illness in Tanzanian children identifies high mortality and resistance to first-line antibiotics in bloodstream infections. medRxiv. 2025;2025.05.25.25328306.
- 39. Li C, Tang F, Xi L, Wang X. Influence of meteorological and environmental factors on pediatric urinary tract infections: insights from a 6-year retrospective study in Central China. Front Public Health. 2025;13:1512403. pmid:40017552
- 40. 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. J Lab Physicians. 2018;10(4):426–31. pmid:30498316
- 41. Kumar S, Nalage DN, Aslam M, Singh S, Kumar U. Evaluation of Bloodstream Infections Associated with Carbapenem-Resistant Enterobacteriaceae in Paediatric and Adult Patients. Egypt J Vet Sci. 2025;0(0):1–8.
- 42. Khanal B, Shrestha LB, Sharma A, Siwakoti S. Bloodstream infections: trends in etiology and antimicrobial resistance in 10 years in Eastern Nepal. BMC Infect Dis. 2025;25(1):1001. pmid:40781612
- 43. Andemichael YG, Habtetsion ET, Gulbet HH, Eman MH, Achila OO, Mengistu ST, et al. Major blood stream infection-causing bacterial pathogens, antimicrobial resistance patterns and trends: a multisite retrospective study in Asmara, Eritrea (2014-2022). Ann Clin Microbiol Antimicrob. 2025;24(1):15. pmid:39984936
- 44. Birru M, Woldemariam M, Manilal A, Aklilu A, Tsalla T, Mitiku A, et al. Bacterial profile, antimicrobial susceptibility patterns, and associated factors among bloodstream infection suspected patients attending Arba Minch General Hospital, Ethiopia. Sci Rep. 2021;11(1):15882. pmid:34354138
- 45. Beshah D, Desta A, Belay G, Abebe T, Gebreselasie S, Sisay Tessema T. Antimicrobial Resistance and Associated Risk Factors of Gram-Negative Bacterial Bloodstream Infections in Tikur Anbessa Specialized Hospital, Addis Ababa. Infect Drug Resist. 2022;15:5043–59. pmid:36068835
- 46. Birhanu A, Gebre G, Getaneh E, Yohannes H, Baye N, Mersha GB, et al. Investigation of methicillin, beta lactam, carbapenem, and multidrug resistant bacteria from blood cultures of septicemia suspected patients in Northwest Ethiopia. Sci Rep. 2025;15(1):5769. pmid:39962179
- 47. Kitila KT, et al. Assessment of bacterial profile and antimicrobial resistance pattern of bacterial isolates from blood culture in Addis Ababa regional laboratory, Addis Ababa, Ethiopia. Clin Microbiol. 2018;7(312):2.
- 48. Trecarichi EM, Pagano L, Candoni A, Pastore D, Cattaneo C, Fanci R, et al. Current epidemiology and antimicrobial resistance data for bacterial bloodstream infections in patients with hematologic malignancies: an Italian multicentre prospective survey. Clin Microbiol Infect. 2015;21(4):337–43. pmid:25595706
- 49. Cento V, Carloni S, Sarti R, Bussini L, Asif Z, Morelli P, et al. Epidemiology and Resistance Profiles of Bacteria Isolated From Blood Samples in Septic Patients at Emergency Department Admission: A 6-Year Single Centre Retrospective Analysis From Northern Italy. J Glob Antimicrob Resist. 2025;41:202–10. pmid:39805348
- 50. Van An N, et al. Distribution and antibiotic resistance characteristics of bacteria isolated from blood culture in a teaching hospital in Vietnam during 2014–2021. Infection and Drug Resistance. 2023. p. 1677–92.
- 51. Dat VQ, Vu HN, Nguyen The H, Nguyen HT, Hoang LB, Vu Tien Viet D, et al. Bacterial bloodstream infections in a tertiary infectious diseases hospital in Northern Vietnam: aetiology, drug resistance, and treatment outcome. BMC Infect Dis. 2017;17(1):493. pmid:28701159
- 52. Nguyen Thi KT, Le Nguyen MH, Pham NT, Nguyen Vu T. Pathogens associated with bacterial bloodstream infections at the facility 2 of national hospital for tropical diseases in dong anh district (2018 - 2020). VJID. 2021;4(36):23–8.
- 53. Siwakoti S, et al. Bloodstream infections in a Nepalese tertiary hospital-aetiology, drug resistance and clinical outcome. Diabetes. 2024;57:12.
- 54. Yadav NS, Sharma S, Chaudhary DK, Panthi P, Pokhrel P, Shrestha A, et al. Bacteriological profile of neonatal sepsis and antibiotic susceptibility pattern of isolates admitted at Kanti Children’s Hospital, Kathmandu, Nepal. BMC Res Notes. 2018;11(1):301. pmid:29764503
- 55. Kumhar GD, Ramachandran VG, Gupta P. Bacteriological analysis of blood culture isolates from neonates in a tertiary care hospital in India. J Health Popul Nutr. 2002;20(4):343–7. pmid:12659415
- 56. Jain K, Kumar V, Plakkal N, Chawla D, Jindal A, Bora R, et al. Multidrug-resistant sepsis in special newborn care units in five district hospitals in India: a prospective cohort study. Lancet Glob Health. 2025;13(5):e870–8. pmid:40023188
- 57. Phukan C, et al. Comparative patterns of antimicrobial susceptibility testing by direct susceptibility and conventional susceptibility testing of blood culture isolates from a tertiary care centre from Dibrugarh, Assam. Res J Med Sci. 2025;19:168–73.
- 58. Alhumaid S, Al Mutair A, Al Alawi Z, Alzahrani AJ, Tobaiqy M, Alresasi AM, et al. Antimicrobial susceptibility of gram-positive and gram-negative bacteria: a 5-year retrospective analysis at a multi-hospital healthcare system in Saudi Arabia. Ann Clin Microbiol Antimicrob. 2021;20(1):43. pmid:34118930
- 59. Kamruzzaman M, et al. Antimicrobial susceptibility patterns of pathogens isolated from clinical specimens at a tertiary care hospital in Bangladesh, 2020-2023. The Microbe. 2025. 100244 p.
- 60. Jha BK, Mahaseth S, Sanjana R. Facultative Anaerobic Bacterial Profile of Bacteremia and Septicemia among ICU Patients and its Antibiotic Susceptibility Pattern in Central Nepal. J Coll Med Sci-Nepal. 2022;18(3):275–87.
- 61. Peng Z, Wang Y, Jia L, Jiang Y, Li X. A 12-Year Retrospective Analysis of Blood Culture Isolates in the Intensive Care Unit of a Tertiary Hospital in China. Clin Lab. 2023;69(1). pmid:36649502
- 62. Aidoo NB, Ramirez-Arcos S, Gillard L, Azumah DE, Adatsi A. Preliminary determination of bacterial contamination of whole blood units in a Ghanaian blood bank: Providing evidence to improve transfusion safety. Vox Sang. 2025;120(5):503–8. pmid:39930642
- 63. De Socio GV, Rubbioni P, Botta D, Cenci E, Belati A, Paggi R, et al. Measurement and prediction of antimicrobial resistance in bloodstream infections by ESKAPE pathogens and Escherichia coli. J Glob Antimicrob Resist. 2019;19:154–60. pmid:31112804
- 64. Bereanu A-S, Bereanu R, Mohor C, Vintilă BI, Codru IR, Olteanu C, et al. Prevalence of Infections and Antimicrobial Resistance of ESKAPE Group Bacteria Isolated from Patients Admitted to the Intensive Care Unit of a County Emergency Hospital in Romania. Antibiotics (Basel). 2024;13(5):400. pmid:38786129
- 65. Arbune M, et al. Prevalence of antibiotic resistance of ESKAPE pathogens over five years in an infectious diseases hospital from South-East of Romania. Infect Drug Resist. 2021;:2369–78.
- 66. De Prisco M, Manente R, Santella B, Serretiello E, Dell’Annunziata F, Santoro E, et al. Impact of ESKAPE Pathogens on Bacteremia: A Three-Year Surveillance Study at a Major Hospital in Southern Italy. Antibiotics (Basel). 2024;13(9):901. pmid:39335074
- 67. Gupta M, Gupta V, Gupta R, Chaudhary J. Current trends in antimicrobial resistance of ESKAPEEc pathogens from bloodstream infections - Experience of a tertiary care centre in North India. Indian J Med Microbiol. 2024;50:100647. pmid:38871082
- 68. Salim MA, et al. Analysis of epidemiology and drug resistance patterns of ESKAPE and non-ESKAPE pathogens at Nigde Hospital in Turkey: A retrospective study (2022–2024). medRxiv. 2024;2024.12.19.24318901.
- 69. Wei D-D, Gao J, Yang R-L, Bai C-Y, Lin X-H. Antimicrobial resistance profiles of ESKAPE and Escherichia coli isolated from blood at a tertiary hospital in China. Chin Med J (Engl). 2020;133(18):2250–2. pmid:32804738
- 70.
Namukonda S, et al. Prevalence and antibiotic resistance profile of ESKAPE pathogens in the neonatal intensive care unit of the women and newborn hospital in Lusaka, Zambia. 2024.
- 71. Erkihun M, Assefa A, Legese B, Almaw A, Berhan A, Getie B, et al. Epidemiology and Antimicrobial Resistance Profiles of Bacterial Isolates from Clinical Specimens at Felege Hiwot Comprehensive Specialized Hospital in Ethiopia: Retrospective Study. Bacteria. 2024;3(4):405–21.
- 72. GÜMÜŞ HH. Prevalence and resistance trends of Gram positive cocci Staphylococcus aereus and Enterococcus spp. in a tertiary care hospital. Cukurova Med J. 2023;48(3):1177–86.
- 73. Moolchandani K, Sastry AS, Deepashree R, Sistla S, Harish BN, Mandal J. Antimicrobial Resistance Surveillance among Intensive Care Units of a Tertiary Care Hospital in Southern India. J Clin Diagn Res. 2017;11(2):DC01–7. pmid:28384858
- 74. Gohel K, et al. Bacteriological profile and drug resistance patterns of blood culture isolates in a tertiary care nephrourology teaching institute. BioMed Res Int. 2014;2014(1):153747.
- 75. Abdulmanea AA, Alharbi NS, Somily AM, Khojah OT, Farrag MA, Alobaidi AS, et al. Prevalence and antibiogram pattern of multidrug-resistant Staphylococcus aureus infections in individuals with sickle cell disease. A retrospective study, hematological and genetic analysis. J King Saud Univ Sci. 2024;36(11):103542.
- 76. Jovchevski R, Cekovska Z, Kovacheva-Trpkovska D, Kostovski M, Labachevska Gjatovska L, Krsteva N, et al. Antimicrobial resistance in gram-postivie bacteria isolated from blood culture. JMS. 2024;7(2):37–44.
- 77. Kebede D, Shiferaw Y, Kebede E, Demsiss W. Antimicrobial susceptibility and risk factors of uropathogens in symptomatic urinary tract infection cases at Dessie Referral Hospital, Ethiopia. BMC Microbiol. 2025;25(1):126. pmid:40057723
- 78. Hailemariam M, Alemayehu T, Tadesse B, Nigussie N, Agegnehu A, Habtemariam T, et al. Major bacterial isolate and antibiotic resistance from routine clinical samples in Southern Ethiopia. Sci Rep. 2021;11(1):19710. pmid:34611232
- 79. Muleta D, et al. Bacterial profile and their antimicrobial resistance pattern among adult patients with suspected bloodstream infection at Jimma University Medical Center, Ethiopia. Sciences. 2022;11(6):104–16.
- 80. Tadesse S, Erkihun M, Ayalew W, Fissiha P, Tefera MM. Common bacterial isolates and their antibiotic susceptibility profile from different clinical specimens at Felege Hiwot compressive specialized Hospital, North west Ethiopia; A three year retrospective cross-sectional study. Glob Health Netw Collect. 2023.
- 81. Gebremariam NM, Bitew A, Tsige E, Woldesenbet D, Tola MA. A High Level of Antimicrobial Resistance in Gram-Positive Cocci Isolates from Different Clinical Samples Among Patients Referred to Arsho Advanced Medical Laboratory, Addis Ababa, Ethiopia. Infect Drug Resist. 2022;15:4203–12. pmid:35946034
- 82. Hailu D, et al. Bacterial blood stream infections and antibiogram among febrile patients at Bahir Dar Regional Health Research Laboratory Center, Ethiopia. Ethiop J Sci Technol. 2016;9(2):103–12.
- 83. Saavedra JC, et al. Bloodstream infections and antibiotic resistance at a regional hospital, Colombia, 2019–2021. Rev Panam Salud Publica. 2023;47:e18.
- 84. Shen H, Zhang Q, Li S, Huang T, Ma W, Wang D, et al. Surveillance and characteristics of vancomycin-resistant Enterococcus isolates in a Chinese tertiary hospital in Shenzhen, 2018 to 2024. J Glob Antimicrob Resist. 2025;40:29–33. pmid:39577832
- 85. Luo Q, Lu P, Chen Y, Shen P, Zheng B, Ji J, et al. ESKAPE in China: epidemiology and characteristics of antibiotic resistance. Emerg Microbes Infect. 2024;13(1):2317915. pmid:38356197
- 86. Zeki C, Murat K, Osman A. Prevalence and antimicrobial-resistance of Staphylococcus aureus isolated from blood culture in university hospital, Turkey. Glob J Infect Dis Clin Res. 2015;1(1):010–3.
- 87. Mutlu M, Aslan Y, Aktürk Acar F, Kader Ş, Bayramoğlu G, Yılmaz G. Changing trend of microbiologic profile and antibiotic susceptibility of the microorganisms isolated in the neonatal nosocomial sepsis: a 14 years analysis. J Matern Fetal Neonatal Med. 2020;33(21):3658–65. pmid:30760078
- 88. Salehi Rad S, Pourmoshtagh H, Sabour S, Nazari S, Sohrabizadeh S, Azimi T. A 12-year surveillance study on distribution and antimicrobial resistance of gram-positive bacteria in Iran. AMB Express. 2025;15(1):30. pmid:39945925
- 89. Rahman MM, Amin KB, Rahman SMM, Khair A, Rahman M, Hossain A, et al. Investigation of methicillin-resistant Staphylococcus aureus among clinical isolates from humans and animals by culture methods and multiplex PCR. BMC Vet Res. 2018;14(1):300. pmid:30285752
- 90. Agbo MC, Ezeonu IM, Onodagu BO, Ezeh CC, Ozioko CA, Emencheta SC. Antimicrobial resistance markers distribution in Staphylococcus aureus from Nsukka, Nigeria. BMC Infect Dis. 2024;24(1):320. pmid:38491352
- 91. Wasihun AG, Wlekidan LN, Gebremariam SA, Dejene TA, Welderufael AL, Haile TD, et al. Bacteriological profile and antimicrobial susceptibility patterns of blood culture isolates among febrile patients in Mekelle Hospital, Northern Ethiopia. Springerplus. 2015;4:314. pmid:26155453
- 92.
Eshetu S. Bacterial profile and antimicrobial susceptibility pattern of blood culture isolates at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. Addis Ababa University; 2017.
- 93. Tolera M, et al. Bacterial nosocomial infections and antimicrobial susceptibility pattern among patients admitted at Hiwot Fana Specialized University Hospital, Eastern Ethiopia. Adv Med. 2018;2018(1):2127814.
- 94. Dagnew M, Yismaw G, Gizachew M, Gadisa A, Abebe T, Tadesse T, et al. Bacterial profile and antimicrobial susceptibility pattern in septicemia suspected patients attending Gondar University Hospital, Northwest Ethiopia. BMC Res Notes. 2013;6:283. pmid:23875886
- 95. Bader RS, Allabadi H, Ihsoun JM, Atout H, Khreishi RH, Bzour AM, et al. Identification of bacterial pathogens and antimicrobial susceptibility of early-onset sepsis (EOS) among neonates in Palestinian hospitals: a retrospective observational study. BMC Pediatr. 2025;25(1):118. pmid:39955515
- 96. Abebaw A, et al. The bacterial profile and antibiotic susceptibility pattern among patients with suspected bloodstream infections. Pathology and Laboratory Medicine International. 2018. p. 1–7.
- 97. Tilahun M, Sharew B, Shibabaw A. Antimicrobial resistance profile and associated factors of hospital-acquired gram-negative bacterial pathogens among hospitalized patients in northeast Ethiopia. BMC Microbiology. 2024;24(1):339.
- 98. Weledegebriel MG, et al. Prevalence of antibacterial resistance among hospitalized patients in Tigray, Ethiopia, 2021: A cross-sectional design. IJID Regions. 2024;13:100477.
- 99. Sisay A, Seid A, Tadesse S, Abebe W, Shibabaw A. Assessment of bacterial profile, antimicrobial susceptibility status, and associated factors of isolates among hospitalized patients at Dessie Comprehensive Specialized Hospital, Northeast Ethiopia. BMC Microbiol. 2024;24(1):116. pmid:38575901
- 100. Thapa RB, Shrestha S, Adhikari P, Shrestha R. Antibiotic resistance patterns in uropathogens: insights from a Nepalese tertiary care setting. Ther Adv Infect Dis. 2025;12:20499361251339383. pmid:40385975
- 101. Egbe FN, Cowden C, Mwananyanda L, Pierre C, Mwansa J, Lukwesa Musyani C, et al. Etiology of Bacterial Sepsis and Isolate Resistance Patterns in Hospitalized Neonates in Zambia. Pediatr Infect Dis J. 2023;42(10):921–6. pmid:37364138
- 102. Chafa AB, et al. Evolution of the resistance profile of Klebsiella species to antibiotics over ten years at the Yaoundé University Teaching Hospital, Cameroon. N/A. 2023;N/A(N/A):N/A.
- 103. Cannella MML, Serge AOD, Gueguim C, Akono L, Biwole MS, Dieudonné A. Distribution and Resistance Profile of Klebsiella pneumoniae Strains at the Yaound Central Hospital: Analysis and Implications. AiM. 2025;15(01):19–29.
- 104. Kritsotakis EI, Lagoutari D, Michailellis E, Georgakakis I, Gikas A. Burden of multidrug and extensively drug-resistant ESKAPEE pathogens in a secondary hospital care setting in Greece. Epidemiol Infect. 2022;150:e170. pmid:36148865
- 105. Diop M, Bassoum O, Ndong A, Wone F, Ghogomu Tamouh A, Ndoye M, et al. Prevalence of multidrug-resistant bacteria in healthcare and community settings in West Africa: systematic review and meta-analysis. BMC Infect Dis. 2025;25(1):292. pmid:40022011
- 106. Ojewuyi OO, Bamikefa TA, Alesinloye AR, Shittu Ikimat P, Akinfolarin SS, Abe EO. Multidrug-Resistant Clinical Infections; Results from a PointPrevalence Study in a Tertiary Resource-Limited Hospital, South-West Nigeria. West J Med Biomed Sci. 2025;6(1).
- 107. Azerefegne EF, Tasamma AT, Demass TB, Tessema AG, Degu WA. Prevalence of multidrug resistant gram-negative bacteria and associated factors among gram-negative blood culture isolates at Tikur Anbessa Specialized Hospital: a retrospective study. BMC Infect Dis. 2025;25(1):1006. pmid:40781593
- 108. Mekonnen S, Tesfa T, Shume T, Tebeje F, Urgesa K, Weldegebreal F. Bacterial profile, their antibiotic susceptibility pattern, and associated factors of urinary tract infections in children at Hiwot Fana Specialized University Hospital, Eastern Ethiopia. Plos one. 2023 Apr 5;18(4):e0283637.
- 109. Getie M, Tafere W, Tsega A, Gebreyesus T, Belay G, Abate A, et al. Antimicrobial resistance profiles of bacteria from clinical specimens at Amhara Public Health Institute, Bahir Dar, Ethiopia: A retrospective study. PLoS One. 2025;20(12):e0337332. pmid:41348728
- 110. Deress T, Belay G, Ayenew G, Ferede W, Worku M, Feleke T, et al. Bacterial etiology and antimicrobial resistance in bloodstream infections at the University of Gondar Comprehensive Specialized Hospital: a cross-sectional study. Front Microbiol. 2025;16:1518051. pmid:40182289
- 111. Cleland H, Stewardson A, Padiglione A, Tracy L. Bloodstream infections and multidrug resistant bacteria acquisition among burns patients in Australia and New Zealand: a registry-based study. Burns. 2024;50(6):1544–54.
- 112. Montalti M, Soldà G, Capodici A, Di Valerio Z, Gribaudo G, La Fauci G, Salussolia A, Scognamiglio F, Zannoner A, Gori D. Antimicrobial Resistance (AMR) in Italy over the past five years: a systematic review. Biologics. 2022;2(2):151–64.
- 113. Sung YH, Park SM, Lee HJ, Yoon YK. Molecular characteristics and antimicrobial susceptibility profiling of carbapenem-resistant Pseudomonas aeruginosa clinical isolates in Korea: Implications for novel β-lactam therapy. J Glob Antimicrob Resist. 2026. pmid:42419643
- 114.
Erkihun M. Three years Retrospective Analysis of Distribution and Antimicrobial Resistance Profiles of Isolates from Culture-positive Clinical Specimens at Felege Hiwot Comprehensive Specialized Hospital in northwestern Ethiopia. Research Square (Research Square). 2024.
- 115. Kritsotakis EI, Lagoutari D, Michailellis E, Georgakakis I, Gikas A. Burden of multidrug and extensively drug-resistant ESKAPEE pathogens in a secondary hospital care setting in Greece. Epidemiol Infect. 2022;150:e170. pmid:36148865
- 116.
Jibril A, et al. Multi drug resistance, extensive drug resistance, and pan drug resistance Enterobacterales from clinical samples in Usmanu Danfodiyo University Teaching Hospital Sokoto. 2025.
- 117. Addis T, Mekonnen Y, Ayenew Z, Fentaw S, Biazin H. Bacterial uropathogens and burden of antimicrobial resistance pattern in urine specimens referred to Ethiopian Public Health Institute. PLoS One. 2021;16(11):e0259602. pmid:34767605
- 118. Adam HJ, Golden AR, Martin I, Baxter MR, Davidson RJ, Karlowsky JA, et al. Comparison of antimicrobial resistance and serotype patterns in Streptococcus pneumoniae from blood cultures and respiratory specimens in Canadian hospitals from the CANWARD study (2007-23). J Antimicrob Chemother. 2025;80(Supplement_2):ii35–44. pmid:40873029
- 119. Alkofide H, Alhammad AM, Alruwaili A, Aldemerdash A, Almangour TA, Alsuwayegh A, et al. Multidrug-Resistant and Extensively Drug-Resistant Enterobacteriaceae: Prevalence, Treatments, and Outcomes - A Retrospective Cohort Study. Infect Drug Resist. 2020;13:4653–62. pmid:33380815
- 120. Dawaiwala I, Awaghade S, Kolhatkar P, Pawar S, Barsode S. Microbiological Pattern, Antimicrobial Resistance and Prevalence of MDR/XDR Organisms in Patients With Diabetic Foot Infection in an Indian Tertiary Care Hospital. Int J Low Extrem Wounds. 2023;22(4):695–703. pmid:34382450
- 121. Kadivarian S, Rostamian M, Dashtbin S, Kooti S, Zangeneh Z, Abiri R, et al. High burden of MDR, XDR, PDR, and MBL producing Gram negative bacteria causing infections in Kermanshah health centers during 2019-2020. Iran J Microbiol. 2023;15(3):359–72. pmid:37448672
- 122. Cheema KH, et al. Assessment of bacterial profile and antimicrobial susceptibility pattern of blood culture isolates. J Islam Int Med Coll. 2022;17(1):9–13.
- 123. Alam H. Antibiotic susceptibility pattern of bacterial strains isolated from different clinical samples in Multan, Pakistan. PAB. 2020;9(4).
- 124. Almakrami M, Salmen M, Aldashel YA, Alyami MH, Alquraishah N, AlZureea M, et al. Prevalence of multidrug-, extensively drug-, and pandrug-resistant bacteria in clinical isolates from King Khaled Hospital, Najran, Saudi Arabia. Discov Med. 2024;1(1).
- 125. Bitew G, Dagnew M, Dereje M, Birhanu A, Gashaw Y, Ambachew A, et al. Burden of multi-drug resistant bacterial isolates and its associated risk factors among UTI-confirmed geriatrics in Gondar town. Sci Rep. 2025;15(1):14270. pmid:40274838
- 126. Mohus RM, Gustad LT, Furberg A-S, Moen MK, Liyanarachi KV, Askim Å, et al. Explaining sex differences in risk of bloodstream infections using mediation analysis in the population-based HUNT study in Norway. Sci Rep. 2022;12(1):8436. pmid:35589812
- 127. Humphreys H, Fitzpatick F, Harvey BJ. Gender differences in rates of carriage and bloodstream infection caused by methicillin-resistant Staphylococcus aureus: are they real, do they matter and why? Clin Infect Dis. 2015;61(11):1708–14. pmid:26202769
- 128. Leal HF, Azevedo J, Silva GEO, Amorim AML, de Roma LRC, Arraes ACP, et al. Bloodstream infections caused by multidrug-resistant gram-negative bacteria: epidemiological, clinical and microbiological features. BMC Infect Dis. 2019;19(1):609. pmid:31296179
- 129. Uslan DZ, Crane SJ, Steckelberg JM, Cockerill FR 3rd, St Sauver JL, Wilson WR, et al. Age- and sex-associated trends in bloodstream infection: a population-based study in Olmsted County, Minnesota. Arch Intern Med. 2007;167(8):834–9. pmid:17452548
- 130. Madut DB, Rubach MP, Kalengo N, Carugati M, Maze MJ, Morrissey AB, et al. A prospective study of Escherichia coli bloodstream infection among adolescents and adults in northern Tanzania. Trans R Soc Trop Med Hyg. 2020;114(5):378–84. pmid:31820810
- 131. Rajabi MM, Gharib B, Mirzaaghayan MR. The Incidence of Nosocomial Bloodstream Infections in Children With Congenital Heart Disease Undergoing Cardiac Surgery: A Retrospective Study. ACTA. 2024.
- 132. Mohamed Shukri NRI, Hassan SK, Md Noor SS, Ab Hamid SA, Nik Mohamad NA, Wan Muhd Shukeri WF, et al. The Outcome of Hospital-Acquired Bloodstream Infection and Its Associated Factors in Critical Care Unit. Malays J Med Sci. 2024;31(6):160–77. pmid:39830098
- 133. Kim YE, Choi HJ, Lee H-J, Oh HJ, Ahn MK, Oh SH, et al. Assessment of pathogens and risk factors associated with bloodstream infection in the year after pediatric liver transplantation. World J Gastroenterol. 2022;28(11):1159–71. pmid:35431506
- 134. Isendahl J, Giske CG, Tegmark Wisell K, Ternhag A, Nauclér P. Risk factors for community-onset bloodstream infection with extended-spectrum β-lactamase-producing Enterobacteriaceae: national population-based case-control study. Clin Microbiol Infect. 2019;25(11):1408–14. pmid:30986557
- 135. Worku M, Molla T, Kasew D, Assefa M, Geteneh A, Aynalem M, et al. Antibiogram of Bacteria Isolated from Bloodstream Infection-Suspected Patients at the University of Gondar Comprehensive Specialized Hospital in Northwest Ethiopia: A Retrospective Study. Int J Microbiol. 2024;2024:7624416. pmid:39015246
- 136. Cui J, Li Y, Du Q, Wei Y, Liu J, Liang Z. Species Distribution, Typical Clinical Features and Risk Factors for Poor Prognosis of Super-Elderly Patients with Bloodstream Infection in China. Infect Drug Resist. 2024;17:779–90. pmid:38444771