Antibacterial-Resistant Genes (ABRG) Associated With Bloodstream Infections In Patients Receiving Treatment: A Case Study Of Nigeria Airforce Medical Center Onikan, Lagos State

Antibacterial-Resistant Genes (ABRG) Associated With Bloodstream Infections In Patients Receiving Treatment: A Case Study Of Nigeria Airforce Medical Center Onikan, Lagos State | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (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],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Antibacterial-Resistant Genes (ABRG) Associated With Bloodstream Infections In Patients Receiving Treatment: A Case Study Of Nigeria Airforce Medical Center Onikan, Lagos State Uzochukwu Godswill Ekeleme This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5784386/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction : The antibacterial-resistant genes (ABRG) associated with bloodstream infections in patients (BSI-PAP) receiving treatment at the Nigerian Air Force Medical Centre, Onikan, Lagos State, were studied from October 2023 to June 2024. BSI-PAP was defined as BSI diagnosed within 48 hours of hospitalization. Methods : Hospital waste samples were analyzed for bacterial contamination and antibiotic resistance adhering to microbiological standards. Results : The prevalence of BSI-PAP was 30 out of 315 discharges (9.5%). The likelihood of being admitted with BSI-PAP was greatest in patients with diabetes mellitus, previous hospitalization, renal failure, and chronic dermatitis. The odds ratios with 95% confidence intervals (CI) were 4.96 (95% CI = 1.37-7.32), 2.59 (95% CI = 0.29-4.9), 2.39 (95% CI = −0.17-4.89), and 1.32 (95% CI = 0.37-4.29). Among the patients admitted with BSI-PAP who were tested with culture media with one of the seven organisms examined (n = 30), the largest proportion had S. scurissp Lentus (n = 6, 35.3%), followed by S. gallinarum (n = 3, 17.6%), S. eqourum (n = 3, 17.6%), E. cloacae SSP (n = 5, 11.8%), B. capacia complex (n = 7, 5.9%), S. xylulosus (n = 1, 5.9%), and C. freundi (n = 5, 5.9%). Approximately 76% (13) of BSI-PAP cases with these organisms had antibiotic-resistant. In general, 86% of individuals examined with SSA culture media had antibiotic-resistant strains, while 78% had EMB and 75% MAC strains (p = 0.0001). Gram-negative bacteria were more frequently involved in BSI in this study (56.7%) than gram-positive bacteria (43.3%). The most frequently isolated bacterium was B. cepacia complex (23.3%); others in descending order were as follows: S. scuri ssp. lentus (20%), E. cloacae ssp., and C. freundi (16.7%). S. gallinarum and S. equourum (10%) and S. xylulosus (3.3%). The drug resistance pattern of gram-positive isolates; Gentamicin Erythromycin and Erythromycin Sulfamethoxazole Tetracycline resistance phenotypes were most common in patients aged 18 to 29 years (54%), while among the gram-negative isolates. Erythromycin, sulfamethoxazole, ciprofloxacin and ampicillin resistance phenotypes were most common in the 30-year-old age group. Erythromycin (85%), gentamicin (55%), sulfamethoxazole (54%), and tetracycline (24%) were commonly used to treat BSI in younger adults, while erythromycin (96%), ciprofloxacin (72%), tetracycline (66%), and ampicillin (60%) were mainly used by middle-aged patients and are easily available without medical authorization. The high antimicrobial resistance has been demonstrated in clinical bacterial isolates ( S. scuri ssp. lentus, S. gallinarum, S. eqourum, and S. xylulosus ) of BSI-PAP to commonly prescribed antibiotics, particularly gentamicin, erythromycin, sulfamethoxazole, and tetracycline. There was a high prevalence of resistant genes of TEM, CTX-M, SHV, and VEB types. General Microbiology Infectious Diseases Bloodstream infections bacteria prevalence susceptibility resistant gene Figures Figure 1 1 Introduction The effectiveness of antimicrobial agents in fighting bloodstream infectious diseases is limited by antimicrobial resistance (AMR) (Zhanget al. 2022 ), a growing global health concern (Silveira et al. 2021 ). The World Health Organization (2021) ranks AMR among the top ten global public health threats. Overuse and misuse of antibiotics in healthcare and other industries have led to the emergence and spread of antimicrobial-resistant pathogens. In 2019, antimicrobial resistance directly caused about 1 in 27 million of the 495 million deaths linked to the disease. Sub-Saharan Africa and South Asia had the highest rates of antimicrobial resistance-related deaths, with 23.5 deaths per 100,000 and 21.5 deaths per 100,000 population, respectively, according to the Global Burden of Disease analysis (Murray et al. 2022 ). Bloodstream infections (BSIs) remain a significant global public health threat, despite significant advancements in management and therapy (Donkor et al. 2023 ). In the United States, they have a high mortality rate, resulting in an estimated 200,000 deaths annually (Sautter et al. 2024 ). Early treatment of significant bacteremia and sepsis is crucial for achieving good clinical outcomes (Spellberg 2020 ). The prevalence of antimicrobial-resistant pattern-related bloodstream infections in admitted patients (BSI-PAP) has increased recently, and it is a potentially fatal illness that consumes substantial resources and incurs significant costs (Sogaard et al. 2011 ). The overall population-based incidence of BSI-PAP in Canada, Europe, and the US ranges from 81.6 to 189 per 100,000 person-years, with a reported incidence of 18.6 per 1000 discharges in 2013 (Laupland et al. 2021 ). Concerns have been raised about the increasing incidence of BSI-PAP, particularly concerning multiple-resistant organisms (Orsini et al. 2012 ). Although BSI has been the subject of several population-based studies (Artero et al. 2010 ), the rise of antimicrobial resistance jeopardizes the effectiveness of healthcare systems, highlighting the urgent need for comprehensive research and interventions (WHO 2015). Of particular concern are bloodstream infections caused by antimicrobial-resistant patterns in patients receiving medical care in hospitals. Treating these infections can be challenging due to the limited availability of effective antimicrobial agents that target antimicrobial-resistant strains. This study aims to identify the antibacterial-resistant genes associated with bloodstream infections in patients receiving treatment at the Nigeria Airforce Medical Center Onikan, Lagos State. 2 Materials and methods 2.1 Study design This study adopted the use of a hospital-based prospective cross-sectional study design approach. 2.2 Study area The study was conducted at the Nigerian Air Force Medical Centre, Onikan. The medical centre is a military health care organisation located in Lagos Island. The medical centre attends to the medical needs of residents of Lagos Island and its surroundings. 2.3 Study population The population of this study was made up of patients receiving treatment from October 2023 to June 2024 at the Nigerian Air Force Medical Centre, Onikan. 2.4 Sample size and sampling method 2.4.1 Determination of sample size The sample size was determined using the formula (n= (Z/2) 2 P (1-P)/d 2 ), as was reviewed in similar studies reported by Ekeng et al. ( 2021 ). The maximum sample size was obtained from a study conducted in southern Nigeria where the prevalence/proportion of bloodstream infections was 28.09% (0.281) (Ekeng et al. 2021 ). As a result, n= (Z/2) 2 P (1- P) /d 2 with a margin of error (d = 0.05) and a 95% confidence interval. p = 0.281, d = 0.05, Z = 0.05 = Z/2 = 0.025 = 1.96. As a result, n= (1.96) 2 x 0.281(1-0.281)/ (0.05) 2 =310. Then, adjusting for a 5% non-response rate, the minimum sample size was 315. 2.4.2 Inclusion and exclusion criteria This study included patients of both sexes and all ages with suspected and proven bloodstream infections. Patients who were critically ill and unable to provide a blood sample during the data collection period were excluded from the study. The study also excluded patients who were released from the hospital and then readmitted with a BSI within 30 days (Horan et al. 2008 ). 2.4.3 Sampling method A convenience sampling technique was used. This was achieved when the physician attending to the patients suspects bloodstream infection in any of the hospital wards. 2.5 Method of data collection, culture and identification of antibacterial-resistant Genes 2.5.1 Data collection using a semi-structured questionnaire The sociodemographic data, and information on risk factors such as recent invasive procedures, immunosuppression, and underlying health conditions were collected from the hospitalized patients and/or their caregivers using a semi-structured questionnaire with the assistance of trained nursing staff and laboratory personnel of the hospital. Also, some of the patient information was collected from the health records, including age, gender, comorbidities, length of hospital stay, and any prior antibiotic exposure. 2.5.2 Blood samples collection and culture Based on the National Healthcare Safety Network (NHSN) definitions, as provided by the Centre for Disease Control and Prevention (CDC) in 2016. Patients with BSI-PAP were defined as those who had a BSI within 48 hours of admission. The patient's blood collection was performed aseptically, ensuring strict adherence to sterile techniques to avoid contamination. The venipuncture site was properly disinfected with 70% alcohol and 2% iodine tincture. Within a 30-minute interval, two bottles of blood for each patient (5 ml of blood for patients over five years of age and 2 ml of blood for patients under five years of age) were aseptically collected from any of the hands as described by Wyss et al. ( 2020 ). The collected sample was inoculated into a blood culture bottle containing Brain Heart Infusion (BHI) broth as a suitable growth medium. The culture flask was incubated at 37°C for 24 to 48 hours to promote microbial growth. The culture was monitored regularly to detect signs of microbial proliferation by looking for turbidity and or colour changes in the medium. When microbial growth was observed, the sample was sub-cultured on solid agar media including MacConkey agar, blood agar, and chocolate agar for isolation and identification of the bacteria. 2.5.3 Identification of the bacterial isolates Gram staining was used to identify the gram reaction of the bacterial isolates that showed positive blood cultures. Traditional biochemical assays and other various methods including, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), and molecular techniques such as polymerase chain reaction (PCR) were used to further identify the bacterial isolates (Clark et al. 2013 ). 2.5.4 Antimicrobial Susceptibility Testing (AST) The disk diffusion method as described by Khan et al. ( 2019 ) was used to perform the AST. The antimicrobial susceptibility of each of the blood culture isolates was assessed following the guidelines of the Clinical and Laboratory Standards Institute (CLSI) 2021 . On nutrient agar, a new subculture of every isolate was initially created. Each isolate was incubated overnight at 37ºC after five colonies were touched with a sterile straight wire and suspended in a sterile Bijou bottle with five millilitres of peptone water (Lab M). Using sterile saline, the overnight broth cultures were diluted to 106 colony-forming units per millilitre by comparing the inoculum's turbidity to the 0.5 McFarland turbidity standards. Mueller-Hinton agar (Oxoid, England) plates were dried and inoculated using a sterile cotton-tipped applicator mixed with a standardized inoculum. Each plate had sterile antibiotic discs, which were then incubated aerobically at 37ºC for 24 hours. Following the standardized CLSI 2021 guidelines, the zone diameter of inhibition of each isolate to the disc was measured using a calibrated ruler (Humphries et al. 2021 ). On Mueller-Hinton agar supplemented with 2 per cent NaCl, staphylococcal isolates exhibiting gentamicin resistance were identified, as previously reported (Taiwo et al. ( 2004 ). Gentamicin 10µg (Gen), erythromycin 10µg (Er), sulfamethoxazole 10µg (Sxt), ciprofloxacin 10µg (Cip), ampicillin 10µg (Amp), tetracycline 10µg (Tet), and cefotaxime 10µg (Ctx) were the antibiotics used for Gram-positive isolates, whereas erythromycin 10µg (Er), sulfamethoxazole 10µg (Sxt), ciprofloxacin 10µg (Cip), ampicillin 10µg (Amp), ampicillin 10µg (Cip), ampicillin 10µg (Amp), tetracycline 10µg (Tet), cefotaxime 5µg (Ctx), and ampicillin-subitan 30µg (Sam) were the antibiotics for Gram-negative isolates. To identify infections and patterns of antimicrobial susceptibility, the algorithms used microbiology results and ICD-9-CM billing codes for the following seven organisms: Citrobacter freundi, Burkholderia cepacia-komplex, Staphylococcus eqourum, Staphylococcus gallinarum, Staphylococcus Scurissp lentus, Staphylococcus Xylulosus, Enterobacter cloacae ssp , and Staphylococcus eqourum. These organisms were chosen because they were among the most common causes of BSI and frequently develop resistance to one or more antimicrobials (World Health Organization 2015). 2.5.5 Extended-Spectrum βeta-Lactamase (ESBL) Screening The isolates were screened by one of these drugs (30 µg of erythromycin, sulfamethoxazole, ciprofloxacin or gentamicin, tetracycline or ampicillin-subitan) on a standard disk diffusion procedure. The zones 29 mm for erythromycin, 20 mm for tetracycline or 10 mm for ampicillin-subitan, 24 mm for gentamicin, or 30 mm for ciprofloxacin were considered as probable ESBL producers which were further confirmed by double disk diffusion testing. Extended-Spectrum β Lactamase Confirmation by Double Disk Diffusion Testing The disks containing erythromycin with and without absolute ethanol (8ml) were placed 20mm apart on the surface of a Kigler’s Iron Agar (KIA) plate previously inoculated with the test organism and incubated at 56°C for 10 minutes. A test result was considered positive if there was an increase of 5mm or higher in the zone diameter for the combination of antimicrobial agent and absolute ethanol compared with the antibiotic alone. The test was done in cognisance with the Clinical and Laboratory Standards Institute (CLSI) document M100-S21 (Cockerill et al. 2013 ). Staphylococcus scurissp lentus was used as the ESBL-positive control, and Barkholderia cepacia-komplex was used as the negative control. 2.5.6 The genomic DNA extraction The specimen (100 µl) was added into a micro-centrifuge tube, followed by the addition of 500 µl of Lysis Buffer. The mixture was then vortexed and incubated at 56ºC for 10 minutes. After incubation, it was centrifuged at 10,000 rpm for 1 minute. Subsequently, 200 µl of absolute ethanol was added to the tube, and the mixture was transferred into a spin column. The spin column was centrifuged at 10,000 rpm for 30 seconds, after which the flow-through was discarded, and the collection tube was blotted on tissue paper. Next, 500 µl of Wash Buffer 1 was added to the spin column, followed by centrifugation at 10,000 rpm for 1 minute. The flow-through was discarded again, and the collection tube was blotted on tissue paper. This was repeated with 500 µl of Wash Buffer 2, centrifuged at 10,000 rpm for 1 minute, and the flow-through was discarded as before. All traces of ethanol were removed, and the spin column was centrifuged once more at 12,000 to 14,000 rpm for 3 minutes. The spin column was then placed into another micro-centrifuge tube, and 50 µl of Elution Buffer or nuclease-free water was added to the centre of the column. The setup was incubated at room temperature for 1 to 2 minutes and centrifuged at 10,000 rpm for 1 minute to elute the DNA. Finally, the DNA was stored at -20ºC or -80ºC. 2.5.7 Detection of Antibacterial Resistance Genes The genotypic analysis for erythromycin ribosome methylation gene F (ermF), erythromycin ribosome methylation gene X (ermX), erythromycin ribosome methylation gene A (ereA), beta-lactamase methicillin-resistance Staphylococcus scurissp lentus (blaMsrS), vietnamese extended-spectrum beta-lactamase (VEB), cefotaximase-type extended-spectrum beta-lactamase (CTX-M), betal-lactamase Klebsiella pneumonia (blaSHV), and beta-lactamase and enzyme (blaTEM), were performed to confirm the resistant isolates. The antimicrobial-resistant pathogens as described by Zhang et al. ( 2021 ) were determined by selecting specific genes associated with antimicrobial resistance, and amplifying them through a series of temperature changes using DNA primers and DNA polymerase. The amplified DNA was then analyzed for the presence of antimicrobial resistance genes using techniques such as gel electrophoresis. Finally, the results were compared to known resistance gene sequences to confirm the presence of specific resistance genes. The primers of the genes used are described in Table 1 . Table 1 Primer Sequence used for Resistance Gene Detection Targets Forward Sequence Reverse Sequence Band size ermF CGA CAC AGC TTT GGT TGA AC QQA CCT ACC TCA TAG ACA AG 309 ermX GAG ATC GGR CCA GGA AGC GTG TGC ACC ATC GCC TGA 488 ereA GCC GGT GCT CAT CAT GAA CTT GAG CGA CTC TAT TCG ATC AGA GGC 420 MsrS GCA CTT ATT GGG GGT AAT GG GTC TAT AAG TGC TCT ATC GTG 384 VEB GAT GGT GTT TGG TCG CAT ATC GCA AC CAT CGC TGT TGG GGT TGC CCA ATT TT 391 TEM TCG CCG CAT ACA CTA TTC TCA AGA ATGAC CAG CAA TAA ACC AGC CAG CCG GAA G 422 CTX-M ATG TGC AGY ACC AGT AAR GTK ATGGC GGT RAA RTA RGT SACC AGA AYC AGC GG 590 SHV TGT ATT ATCTC(C/T) CTG TTA GCC(A/G) CCCTG GCT CTG CTT TGT TAT TCG GGC CAA GC 739 2.5.8 Method of Data Analysis After coding and properly sorting the data in a Microsoft Excel spreadsheet, we transferred it to SPSS version 25 software for analysis. To ensure the data's consistency and completeness, we used a cross-tabulation of all variables. We then calculated the descriptive statistics, including percentages, frequencies, means, and standard deviations (SD), for all variables. Next, we performed bivariate analyses to determine the relationships between BSI-PAP and potential predictor variables, such as source of admission, age, gender, previous hospitalization, renal failure, diabetes mellitus, malignancy, and chronic dermatitis. We used chi-square tests for categorical variables and the Wilcoxon rank sum test for confidence class interval (CCI). Multiple logistic regression was then used to include the variables significantly associated with BSI-HOA in the bivariate analyses (P < 0.05). Due to the small sample size (n = 2), we excluded malignancies from the multivariable analysis. Additionally, we excluded CCI from the multivariable analysis since some of the predictors in our model were included in the CCI composite score. 3 Results 3.1 Socio-Demographic Information of the Study Participants A total of 315 patients were sampled in this study on antibacterial-resistant genes associated with bloodstream infections present in admitted patients at Nigeria Air Force Medical Centre, Onikan Lagos State. All patients had received at least one antimicrobial agent during the study period. Out of these, 30 patients (10%) had bloodstream infections. Among these 30 patients, 21 (71%) were male and 9 (29%) were female. Their ages ranged from 18 to 44 years, with the following distribution: 18-24 years (35%), 25-29 years (29%), 30-34 years (18%), 35-39 years (6%), and 40-44 years (12%). The average age was 29.29 years, with a standard deviation of 7.447, as shown in table 2. The participants' educational backgrounds were as follows: 14 (47%) had a secondary school certificate, 4 (24%) had technical/vocational training, and 9 (29%) had a Bachelor's degree. All participants had chronic medical conditions, including urinary tract infection (35%), renal failure (29%), chronic dermatitis (18%), Diabetes mellitus (12%), and malignancies (6%). They were all taking antibiotics, with 29% having taken them within the past 3 months, 53% within the past 6 months, and 18% within the past year. None of the patients with bloodstream infections had undergone surgery in the past 6 months. The lifestyle and habits of the participants were as follows: 26 (88%) did not smoke, while 4 (12%) admitted to smoking. In terms of alcohol consumption, 35% had never consumed any, 49% consumed occasionally, and 18% consumed regularly. Only 15% of the patients exercised regularly, while 85% did not. Table 2: Socio-demographic information of the study participants Variables Frequency Percentage (%) Age (years) 18- 24 25 – 29 30 – 34 35 - 39 40 – 44 Total Mean Standard Deviation 11 9 5 1 4 17 29.29 7.447 35 29 18 6 12 Gender Male Female Mean Standard Deviation 21 9 1.29 0.469 71 29 Educational Background Secondary Technical/Vocational Training Bachelor’s Degree Mean Standard Deviation 14 7 9 3.79 0.893 47 24 29 Health History Diagnosed with Chronic Medical Condition YES NO Mean Standard Deviation Specify the Chronic Disease Diabetes Mellitus Malignancies Renal Failure Chronic Dermatitis Urinary tract infection Currently Taking Antibiotics YES NO Mean Standard Deviation Antibiotics Intake Within the last 3 months Within the last 6 months Within a year Mean Standard Deviation Surgeries for last 6 Months YES NO 30 0 2.00 0.000 4 2 9 5 11 30 0 2.00 0.000 9 16 5 4.00 0.679 0 30 100 0 12 6 29 18 35 100 0 29 53 18 0 100 Lifestyle and Habits Smoking YES NO Mean Standard Deviation Consume Alcoholic Beverages Never Occasionally Regularly Mean Standard Deviation Do you engage in regular exercise? YES NO Mean Standard Deviation 4 26 1.93 0.267 12 14 4 1.71 0.726 5 25 1.79 0.426 12 88 35 47 18 15 85 Figure 1 below revealed the ages of the participants with ages of 18 to 24 years having the highest frequency. The mean was 29.29 and the SD was 7.447 which indicates less variability. 3. 2 Prevalence and co-morbid conditions of bloodstream infections among the admitted patients (BSI-PAP) The patients were 315, out of which 30 (9.5%) cases were of bloodstream infection admitted. The male patients were the most admitted with a BSI (71%) than the female (29%). The urinary tract infection, diabetes mellitus, renal failure, chronic dermatitis and malignancies were significantly associated with BSI-PAP in bivariate analyses. The mean score (mean = 3.8 ± SD = 3.5) of patients with BSI-PAP was significantly higher, compared with those patients without BSI-PAP (mean = 2.8 ± SD = 3.3), P < 0.001 (Table 3). Table 3: Prevalence and co-morbid conditions of bloodstream infections among the admitted patients (BSI-PAP) BSI-PAP (n = 30) (%) Non- BSI-PAP (n = 285) (%) P-value Laboratory Culture Media Source Eosin Methylene Blue (EMB) Salmonell-Shigella Agar (SSA) MacConkey Agar (MAC) 14 (47) 12 (41) 4 (12) 137 (48) 131 (46) 17 (6) < 0.001 Age Category (years) 18 – 24 25 – 29 30 – 34 35 – 39 40 – 44 11 (35) 9 (29) 5 (18) 1 (6) 4 (12) 66 (23) 51 (18) 100 (35) 23 (8) 46 (16) < 0.001 Gender Male Female 21 (71) 9 (29) 202 (71) 83 (29) < 0.001 Co-Morbid Conditions Urinary tract infection Diabetes mellitus Renal failure Chronic Dermatitis Malignancies CCI Scores: Mean [ Standard Deviation] 11 (53) 4 (29) 9 (35) 5 (18) 2 (12) 3.8 [ 3.5] 94 (33) 51 (18) 68 (24) 48 (17) 26 (9) 2.8 [ 3.3] < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 3.3 The Risk Factors and Predictors contributing to the Development of AMRP-Associated Bloodstream Infections present in Admitted Patients (BSI-PAP). Table 4 shows the multivariable analysis of the association between Patients’ characteristics and BSI-PAP, the odds of being admitted with BSI-PAP were greatest among patients admitted with diabetes mellitus, urinary tract infection, renal failure and chronic dermatitis. The odds ratios 95% confidence interval (CI) were 4.96 (95% CI = 1.37-7.32), 2.59 (95% CI = 0.29-4.9), 2.39 (95% CI = -0.17-4.89) and 1.32 (95% CI = 0.37-4.29) and, respectively. There was no association between ages from 30 to 44 years, female gender and EMB culture media. Table 4: Association between patients’ features and BSI-PAP in multivariable logistic regression analysis. Predictors Odds Ratio (OR) 95% Confidence Interval (C.I) Lower Upper Co-Morbid Conditions Urinary tract infections Diabetes Mellitus Renal Failure Chronic Dermatitis Age (In years) 18 – 24 25 – 29 30 – 34 35 – 39 40 – 44 Gender Male Female Laboratory Culture Media Source Eosin Methylene Blue (EMB) Salmonell-Shigella Agar (SSA) MacConkey Agaar (MAC) 2.5899 4.9566 2.3855 1.3193 1.8777 1.8613 0.3137 0.8341 0.8536 1.0213 0.9792 0.6192 1.2158 2.0354 0.2868 1.3728 -0.1677 0.3668 0.6950 0.6274 0.0718 0.1073 0.1949 0.4257 0.1273 0.2296 0.5003 0.4612 4.9367 7.3295 4.8943 4.2941 5.0723 5.5220 1.3698 6.4851 3.7393 2.4500 2.4213 1.6698 2.9547 8.9836 3.4 Bacterial isolates associated with BSI-PAP Table 5 shows the isolates associated with BSI-PAP among the patients admitted with BSI-PAP (n = 30), the largest proportion presented with S. scurissp Lentus (n = 6, 35.3%), followed by S. gallinarum (n = 3, 17.6%), S. eqourum (n = 3, 17.6%), E.cloacae SSP (n = 5, 11.8%), B. capacia-komplex (n = 7, 5.9%), S. xylulosus (n = 1, 5.9%), and C. freundi (n = 5, 5.9%). About 76% (13) of the BSI-PAP cases with these organisms were antibiotic-resistant. Table 5: Bacterial isolates associated with BSI-PAP among the patients admitted with BSI-PAP Isolates Total EMB Resistant (n, %) SSA Resistant (n, %) MAC Resistant (n, %) P-Value S.gallinarum S.scuri SSP lentus S.xylulosus S.eqourum E. cloacae SSP B.cepacia-konplex C.freundi 3 6 1 3 5 7 5 1(95) 3 (78) 0 (0) 2 (62) 0 (0) 0 (0) 0 (0) 1 (92) 2 (79) 1 (95) 1 (78) 0 (0) 0 (0) 0 (0) 1 (100) 1( 49) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0.545* 0.001* 0.720f 0.003f 0.842* 0.725* 0.360f Total 30 6 (78) 5 (86) 2 (75) 0.001* *-chi-square, f-Fisher’s exact test 3.5 The AMRP of Bacterial Isolates from BSI-PAP among Commonly Prescribed Antibiotics Out of which 30 (34.7%) documented BSI, gram-negative bacteria had the highest frequency (56.7%), which are E. cloacae ssp, B. cepacia-komplex , and C. freundi. The gram-positive bacteria had 43.3% in BSI, which S. scuri ssp lentus, S. gallinarum. S. eqourum and S.xylulosus were present. The most frequently isolated bacterium was B. cepacia-komplex (23.3%) and others occurred in descending order as follows: S. scuri ssp lentus (20%), E. cloacae ssp and C. freundi (16.7%), S. gallinarum and S. eqourum (10%) and S. xylulosus (3.3%). A high level of resistance was obtained among both the gram-positive (4–100%) and gram-negative bacterial isolates (3–100%) (Table 6). Table 6: The Bacterial Isolates of bloodstream infection (BSI) Bacterial isolates No of Isolates (%) Gram Positive S.scurissp.lentus S.gallinarum S.xylulosus S.eqourum Gram Negative E.cloacae ssp B.cepacia-komplex C.freundi Total Isolates 13 (43.3) 6 (20) GENRSS = 5 (83%) 3 (10) GENRSG = 3 (100%) 1 (3.3) 3 (10) ERSE = 3 (100%) 17 (56.7) 5 (16.7) 7 (23.3) 5 (16.7) 30 GENRSS = Gentamicin-resistant Staphylococcus scuri ssp lentus GENRSG = Gentamicin resistant gallinarum ERSE = Erythromicin resistant Streptococcus eqourum 3.6 The Efficacy of the Antibiotic Combination used as first-line Empirical Treatment of BSI-PAP Table 7 displayed the pattern of the drug resistance for both gram-positive and gram-negative isolates, this revealed single and multiple drug resistance patterns with the number of antibiotics ranging from 2 to 5 and from 2 to 6 for Gram positive and Gram negative respectively. For the drug resistance pattern for Gram-positive isolates; gentamicin erythromycin and erythromycin sulfamethoxazole tetracycline resistance phenotypes occurred most frequently among the patients aged 18-29 years (54%), while for the gram-negative isolates, the resistance phenotypes erythromycin sulfamethoxazole and erythromycin sulfamethoxazole ciprofloxacin ampicillin occurred most frequently in the age group of 30–44 years (72%). Erythromycin (85%), Gentamicin (55%), Sulfamethoxazole (54%) and Tetracycline (24%) are widely used for the treatment of BSI by younger adults, while Erythromycin (96%), Ciprofloxacin (72%), Tetracycline (66%) and Ampicillin (60%) are mostly used by middle-aged patients. Table 7: The Antibiotics Resistance Pattern of Gram Positive and Gram-Negative Isolates Gram Positive Isolates No of Antibiotics Resistance (R) Pattern No of Isolates Bacteria % 1 2 3 4 5 Gentamicin Gentamicin Erythromycin Erythromicin Sulfamethoxazole Erythromicin Sulfamethoxazole Tetracycline Gentamicin Erythromycin Sulfamethoxazole Ciprofloxacin Sulfamethoxazole Ciprofloxacin Ampicillin Cefotoxine Gentamicin Erythromycin Sulfamethoxazole Ciprofloxacin Ampicillin 1 4 2 3 1 1 1 S.scuri ssp S.xylulosus; S.equorum; S.gallinarum ; S.scuri ssp S.gallinarum ; S.scuri ssp S.xylulosus ; S.equorum ; S.gallinarum S.scuri ssp S.scuri ssp S.scuri ssp 8 31 15 23 8 8 8 13 Gram Negative Isolates 1 2 3 4 5 6 7 Erythromicin Erythromicin Sulfamethoxazole Erythromicin Sulfamethoxazole Ciprofloxacin Erythromicin Sulfamethoxazole Ciprofloxacin Ampicillin Erythromicin Sulfamethoxazole Ciprofloxacin Ampicillin Tetracycline Erythromicin Sulfamethoxazole Ciprofloxacin Ampicillin Tetracycline Cefotoxime Erythromicin Sulfamethoxazole Ciprofloxacin Ampicillin Tetracycline Cefotoxime Ampicillin-Subitan 3 3 1 3 3 1 3 B.cepacia-komplex , E.cleacole ssp C.freuodii B.cepacia-komplex , E.cleacole ssp C.freuodii B.cepacia-komplex B.cepacia-komplex , E.cleacole ssp C.freuodii B.cepacia-komplex , E.cleacole ssp C.freuodii B.cepacia-komplex B.cepacia-komplex , E.cleacole ssp C.freuodii 18 18 6 18 18 6 18 17 3.7 Extended-Spectrum Beta-Lactamase (ESBL) Screening and Confirmatory Testing In this study, 7 bacterial isolates of E. coli (B. cepacia-komplex) and 5 bacterial isolates of K.pnemonia (E. cloacae ssp) were recovered from the hospitalized patients. Generally, 29% (2 out of 7) isolates of E. coli (B. cepacia-komplex) and 20% (1 out of 5) K. pneumonia (E. cloacae ssp) isolates showed resistance to the third-generation cephalosporin by phenotypic screening tests. 100% (7 out of 7) of ESBL was detected among isolates of E. coli (B. cepacia-komplex) and 100% (5 out of 5) isolates of K. pneumonia (E.cloacae ssp) by confirmatory testing. it was observed that age was significantly associated with the incidence of both E. coli (B. cepacia-komplex) and K. pneumonia (E. cloacae ssp) infection (p < 0.05) (Table 8). Table 8 : Phenotypic Detection of ESBL Isolates. Bacterial Isolates ESBL Screening by the disk diffusion method ESBL confirmed by double disk diffusion testing. Erythromycin 30(µg) N (%) Tetracycline 30(µg) N (%) Sulfamethoxazole 30(µg) N (%) Ciproflaxin 30(µg) N (%) Erythromycin (30µg) with absolute ethanol (10 µg) N (%) E.coli.(B. cepacia-komplex) (7) 7 (100) 3 (43) 6 (86) 5 (71) 7 (100) K.pneumonia (E.cloacae ssp) (5) 5 (100) 2 (40) 4 (80) 3 (60) 5 (100) Total (12) 12 (100) 5 (42) 10 (83) 8 (67) 12 (100) 3.8: Molecular detection of resistant genes The overall incidence of βeta-lactamase genes was found to be 30.7% (12 out of 39) which included 100% (7 out of 7) of Escherichia coli ( B. cepacia-komplex ) and 100% (5 of 5) of Klebsiella pneumonia ( E. cloacae ssp ), respectively. Molecular characterization showed that out of the 12 phenotypically positive ESBL isolates, 33% (4 out of 12) were positive for the blaCTX-M (Fig 4.3, lane 3, 4, 5, 6, 8). It consisted of 29% (2 out of 7) of Escherichia coli ( B. cepacia-komplex ) and 40% (2 out of 5) of Klebsiella pneumonia ( E.cloacae ssp ). Generally, TEM (42%) was the most common genotype followed by CTX-M (33%), SHV (17%) and VEB (8%) both in single or when combined. No isolates harbored ermF, ermX, ereA, and MsrS genes (Table 9). In total, 35% of the total ESBL-positive isolates harboured the three ESBL genes, while 61% carried two of the tested ESBL genes. Table 9: Distribution of different genes in ESBL-producing Escherichia coli ( B. cepacia-komplex ) and Klebsiella pneumoniae ( E. cloacae ssp ) isolates Escherichia coli ( B. cepacia-komplex ) (N = 7) (%) Klebsiella pneumonia ( E.cloacae ssp ) (N = 5) (%) Total (N = 12) (%) ermF ermX ereA MsrS VEB CTX-M SHV TEM 0 (0) 0 (0) 0 (0) 0 (0) 1 (14) 2 (29) 1 (14) 3 (43) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 2 (40) 1 (20) 2 (40) 0 (0) 0 (0) 0 (0) 0 (0) 1 (8) 4 (33) 2 (17) 5 (42) 4 Discussion The Prevalence and Distribution of Antimicrobial-Resistant Pathogen (AMRP) causing Bloodstream Infections present in Admitted Patients (BSI-PAP). The patients receiving healthcare treatment in Nigeria Airforce Medical Center Onikan, Lagos State from January to June 2024 were 315, out of which 30 were cases of BSI-PAP that led to a prevalence rate of 9.5%. Even when accounting for age, patients who were admitted and screened with these media cultures; Eosin methylene blue (EMB) and Salmonella-Shigella Agar (SSA) were significantly and had more chances to have a BSI-PAP than patients who were admitted and screened with MacConkey agar (MAC) culture media. Consistently, other researchers investigated BSI among nursing home (NH) and non-nursing home (NNH) admissions and ascertained that NH exposure was a risk factor for BSI-PAP caused by gram-positive and gram-negative organisms (Karaman et al. 2020 ) and another investigator reported that patients admitted for a long-term in a medical care facility was associated with gram-negative BSI-PAP (Algammal et al. 2020 ). One of the limitations of these studies was that the patients were from a single hospital, which is also applicable to the current study. The Risk Factors and Predictors contributing to the Development of AMRP-Associated Bloodstream Infections present in Admitted Patients (BSI-PAP). The multivariable analysis of the association between Patients’ characteristics and BSI-PAP was performed, and the Patients with younger ages 18 to 34 years and male gender were the significant predictors of BSI-PAP and this is contrary to the results of other investigators who found older age and male gender to be significant predictors of BSI-PAP (Uslan et al. 2007 ; Akoua-Koffi et al. 2015 ). Sequel to the patient characteristics studied, patients with diabetes mellitus, prior hospitalisation, renal failure and chronic dermatitis had the highest odds ratios of being admitted with a BSI. These findings are consistent with two previous studies that reported renal failure and prior hospitalisation to be associated with BSI-PAP (Rodriguez-Bano et al. 2010 ; Sainfer et al. 2018 ). Generally, patients with these conditions have multiple co-morbidities which include changes in immune function which influence their risk of BSI acquisition (Stewart et al. 2009 ) and dermatitis which menaced the skin barrier. However, this finding follows the study that reported that diabetes mellitus increased the odds of BSI-PAP in chronically sick patients (OR = 1.42, 95% CI = 1.10– 1.82) (McKane et al. 2014 ). The isolates associated with BSI-PAP which accounted for almost half of the isolates were S. scuri ssp lentus among the organisms studied and had a higher proportion of resistant strains among those screened with media culture from SSA when compared with those screened with EMB and MAC. This finding is in contrast with the reports of other investigators by Sainfer et al. ( 2018 ), which reports that S. aureus accounted for most of the isolates with a higher proportion of resistant strains among the patients admitted from nursing homes. However, the resistant strains were highest among patients screened with the media culture from SSA; this is not surprising considering that patients who have had been previously screened with EMB are exposed to more multidrug-resistant pathogens and are more likely to have received antibiotics (Karkada et al. 2011 ). Seventy-eight per cent of the S. gallinarum -resistant strains were isolated from patients screened with a media culture EMB, perhaps related to prior antibiotic exposure. Most of the organisms’ results were not significant and this could be due to the small number of organisms with resistant strains. The resistant strains in isolates causing BSI-PAP were high for patients screened with EMB, SSA and MAC (78%, 86% and 75%, respectively), P = 0.001 among the seven organisms studied. However, when broken down by organisms, only S. scurissp Lentus showed a significantly higher proportion of resistant strains in patients screened with culture media from SSA. In that effect, prospective surveillance might be indicated when patients are screened for BSI with these settings. The AMRP of Bacterial Isolates of BSI-PAP among Commonly Prescribed Antibiotics During the period of this investigation, 30 (34.7%) were microbiologically documented BSI with all being mono-microbial. This value follows the range reported by other researchers in Nigeria (Sainfer et al. 2018 ) and other countries (Hugonnet et al. 2004 ). This implies that most of the BSIs in the tropical region are massively uncharacterized microbiologically and are hence, empirically treated. The Gram-negative bacteria were more frequently involved (56.7%), which are E.cloacae ssp, B.cepacia-komplex , and C.freundi than the gram-positive bacteria (43.3%) in BSI in this study which are S.scuri ssp lentus, S.gallinarum. S. eqourum and S. xylulosus . The most frequently isolated bacterium was B.cepacia-komplex . The high level of resistance to commonly available antibiotics that were used for the empirical treatment of BSI in this study was obtained among both the Gram-positive (4–100%) and Gram-negative bacterial isolates (3–100%). However, there is an association with increased mortality rates, overstay in hospital admission and costs due to BSI-PAP-resistant organisms (Rello et al. 2000 ), this makes it more important for microbiology laboratories to always give out information on antibiotic susceptibility patterns of the prevalent micro-organisms involved in BSI-PAP, that can be used as a guide for antibiotic selection. The Efficacy of the Antibiotic Combination used as first line Empirical Treatment of BSI-PAP The pattern of the drug resistance for both Gram-positive and Gram-negative isolates revealed single and multiple drug resistance patterns with the number of antibiotics ranging from two to five and from two to six for Gram-positive and Gram-negative respectively. This is not consistent with the study conducted by Majumder et al. ( 2020 ), where the drug resistance pattern of both the Gram-positive and Gram-negative isolates revealed single and multiple drug resistance patterns with the number of antibiotics ranging from two to seven. For the drug resistance pattern of Gram-positive isolates; Gen E and E Sxt Te resistance phenotypes occurred most frequently among the patients aged 18–29 years (54%), while for the Gram-negative isolates, the resistance phenotypes E Sxt and E Sxt Cip Amp occurred most frequently in the age group 30–44 years (72%). Gentamicin, Erythromycin, Sulfamethoxazole, and Tetracycline are widely used for the treatment of BSI by younger adults, while Erythromycin, Ciprofloxacin, Tetracycline and Ampicillin are mostly used by middle-aged patients and are easily obtained without medical authorization. Extended-Spectrum Beta-Lactamase (ESBL) Screening and Confirmatory Testing and the Molecular Analysis of the resistant genes The highly prevalent co-morbidity in this study is the major issue among the patients that were hospitalized, and multidrug-resistant E. coli ( B. cepacia-komplex ) and K. pneumonia ( E. cloacae ssp ), were the most important pathogens (Prasada et al., 2019 ). generally, 29% (2 out of 7) isolates of E. coli (B. cepacia-komplex) and 20% (1 out of 5) K. pnemonia (E. cloacae ssp) isolates show resistance to the third-generation cephalosporin by phenotypic screening tests. 100% (7 out of 7) of ESBL was detected among isolates of E. coli (B. cepacia-komplex) and 100% (5 out of 5) isolates of K. pnemonia (E. cloacae ssp) , which was somehow lower when compared with other studies. The production of ESBL production in different studies in India found a prevalence of 60.80, 46.26, 66.78, 34, 63.60, 18.80%, and 39.20, 25.1, 61.70, 42.0, 66.70, and 35.50% in E. coli and K. pneumoniae isolates, respectively (Gautam et al. 2019 ). The prevalence of ESBL production all over the world among the clinical isolates ranges from less than 1 to 88% (Veeraraghavan et al. 2018 ). The overall incidence of βeta-lactamase genes was found to be 30.7%. Molecular characterization showed that out of the 12 phenotypically positive ESBL isolates, 33% was positive for the blaCTX-M. Generally, TEM (42%) was the most common genotype followed by CTX-M (33%), SHV (17%) and VEB (8%) both in single or when combined. No isolates harbored ermF, ermX, ereA, and MsrS genes. In total, 35% of the total ESBL-positive isolates harbored the three ESBL genes, while 61% carried two of the tested ESBL genes. There is a probability of community-based dissemination of ESBL-producing isolates because this is a serious issue. There is a significant implication with the high rate of various ESBL-producing genes for patient treatment and outline the benefits that strengthens the antimicrobial surveillance, antibiotic stewardship, and continuous monitoring of the rate of ESBL production along with multidrug resistance among nosocomial isolates. This is in tune with a study conducted in North East districts in India, where cefotaximase-type extended-spectrum beta-lactamase (CTX-M) was found in E. coli (88.67%) and beta-lactamase and enzyme (blaTEM) in K. pneumoniae (77.58%) as the genotype that predominates the most. (Bora et al. 2014 ). Another team of researcher, Roy et al. ( 2013 ) identified a higher rate of cefotaximase-type extended-spectrum beta-lactamase 15 (blaCTX-M15) (100%) compared with this current study (33%). Conclusion This study highlights a 9.5% prevalence of bloodstream infections (BSI) and identifies key risk factors, including younger adults, males, diabetes, prior hospitalization, renal failure, and chronic dermatitis. High antimicrobial resistance was noted among clinical isolates, particularly to gentamicin, erythromycin, sulfamethoxazole, and tetracycline. The study underscores the increasing complexity of healthcare delivery and its role in disseminating resistant organisms. Extended-spectrum beta-lactamase (ESBL) prevalence in UTIs caused by Escherichia coli and Klebsiella pneumoniae is significant, with resistance linked to TEM, CTX-M, SHV, and VEB beta-lactamases. Findings emphasize stricter control measures and the cautious use of ceftazidime in managing ESBL infections. Declarations Ethnical Consideration/Informed Consent Informed written consent was sought and obtained from all study participants. Additionally, a letter of introduction (FUT/SOHT/PUH/CS.0012/VOL.2) to carry out the study was obtained from the Department of Public Health Technology, FUTO, to the ethics committee of the Nigerian Air Force Medical Centre, Onikan, Lagos State. The study was approved by the 055 NAF Medical Centre Ethics Committee of Nigerian Air Force on 11/10/2023 with the reference number 055 CAMP/405/MEDCEN. Consent for the publication: Not applicable. Availability of data and materials: All data generated or analysed during this study are included in this published article. Competing interests: There is no competing interest among the authors. Funding: This research was self-funded by the authors. Authors' contributions: UGE and BCA designed research; QCO, IGC, CCO, CCU, CLO, ABN conducted research; CCAO analyzed data; COA, QCO, IGC, and CLO wrote the paper; UMC, UMD, VNU, BCA and UGE had primary responsibility for the final content. All authors read and approved the final manuscript. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5784386","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":399107041,"identity":"2916903e-c7e7-4d04-870c-89677a1b67b6","order_by":0,"name":"Uzochukwu Godswill Ekeleme","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-6375-8060","institution":"Federal University of Technology Owerri","correspondingAuthor":true,"prefix":"","firstName":"Uzochukwu","middleName":"Godswill","lastName":"Ekeleme","suffix":""}],"badges":[],"createdAt":"2025-01-07 22:35:19","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":true,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5784386/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5784386/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73518298,"identity":"a2a0174c-18b5-48de-bbff-09e4d967e133","added_by":"auto","created_at":"2025-01-10 18:01:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":19311,"visible":true,"origin":"","legend":"\u003cp\u003eThe participants’ Age with Febrile Illness.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5784386/v1/5412d6581bb71b23c6f47bf3.png"},{"id":73520295,"identity":"ce473cf1-122f-4cbe-96e7-591177ccb6e4","added_by":"auto","created_at":"2025-01-10 18:17:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2676108,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5784386/v1/1082ab4d-581f-44e3-81ef-d2416bd2ba5f.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAntibacterial-Resistant Genes (ABRG) Associated With Bloodstream Infections In Patients Receiving Treatment: A Case Study Of Nigeria Airforce Medical Center Onikan, Lagos State\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe effectiveness of antimicrobial agents in fighting bloodstream infectious diseases is limited by antimicrobial resistance (AMR) (Zhanget al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), a growing global health concern (Silveira et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The World Health Organization (2021) ranks AMR among the top ten global public health threats. Overuse and misuse of antibiotics in healthcare and other industries have led to the emergence and spread of antimicrobial-resistant pathogens. In 2019, antimicrobial resistance directly caused about 1 in 27\u0026nbsp;million of the 495\u0026nbsp;million deaths linked to the disease. Sub-Saharan Africa and South Asia had the highest rates of antimicrobial resistance-related deaths, with 23.5 deaths per 100,000 and 21.5 deaths per 100,000 population, respectively, according to the Global Burden of Disease analysis (Murray et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBloodstream infections (BSIs) remain a significant global public health threat, despite significant advancements in management and therapy (Donkor et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In the United States, they have a high mortality rate, resulting in an estimated 200,000 deaths annually (Sautter et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Early treatment of significant bacteremia and sepsis is crucial for achieving good clinical outcomes (Spellberg \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The prevalence of antimicrobial-resistant pattern-related bloodstream infections in admitted patients (BSI-PAP) has increased recently, and it is a potentially fatal illness that consumes substantial resources and incurs significant costs (Sogaard et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The overall population-based incidence of BSI-PAP in Canada, Europe, and the US ranges from 81.6 to 189 per 100,000 person-years, with a reported incidence of 18.6 per 1000 discharges in 2013 (Laupland et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Concerns have been raised about the increasing incidence of BSI-PAP, particularly concerning multiple-resistant organisms (Orsini et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Although BSI has been the subject of several population-based studies (Artero et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), the rise of antimicrobial resistance jeopardizes the effectiveness of healthcare systems, highlighting the urgent need for comprehensive research and interventions (WHO 2015). Of particular concern are bloodstream infections caused by antimicrobial-resistant patterns in patients receiving medical care in hospitals. Treating these infections can be challenging due to the limited availability of effective antimicrobial agents that target antimicrobial-resistant strains. This study aims to identify the antibacterial-resistant genes associated with bloodstream infections in patients receiving treatment at the Nigeria Airforce Medical Center Onikan, Lagos State.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design\u003c/h2\u003e \u003cp\u003eThis study adopted the use of a hospital-based prospective cross-sectional study design approach.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study area\u003c/h2\u003e \u003cp\u003eThe study was conducted at the Nigerian Air Force Medical Centre, Onikan. The medical centre is a military health care organisation located in Lagos Island. The medical centre attends to the medical needs of residents of Lagos Island and its surroundings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Study population\u003c/h2\u003e \u003cp\u003eThe population of this study was made up of patients receiving treatment from October 2023 to June 2024 at the Nigerian Air Force Medical Centre, Onikan.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Sample size and sampling method\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1 Determination of sample size\u003c/h2\u003e \u003cp\u003eThe sample size was determined using the formula (n= (Z/2)\u003csup\u003e2\u003c/sup\u003e P (1-P)/d\u003csup\u003e2\u003c/sup\u003e), as was reviewed in similar studies reported by Ekeng et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The maximum sample size was obtained from a study conducted in southern Nigeria where the prevalence/proportion of bloodstream infections was 28.09% (0.281) (Ekeng et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs a result, n= (Z/2)\u003csup\u003e2\u003c/sup\u003e P (1- P) /d\u003csup\u003e2\u003c/sup\u003e with a margin of error (d\u0026thinsp;=\u0026thinsp;0.05) and a 95% confidence interval. p\u0026thinsp;=\u0026thinsp;0.281, d\u0026thinsp;=\u0026thinsp;0.05, Z\u0026thinsp;=\u0026thinsp;0.05\u0026thinsp;=\u0026thinsp;Z/2\u0026thinsp;=\u0026thinsp;0.025\u0026thinsp;=\u0026thinsp;1.96.\u003c/p\u003e \u003cp\u003eAs a result, n= (1.96)\u003csup\u003e2\u003c/sup\u003e x 0.281(1-0.281)/ (0.05)\u003csup\u003e2\u003c/sup\u003e =310.\u003c/p\u003e \u003cp\u003eThen, adjusting for a 5% non-response rate, the minimum sample size was 315.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2 Inclusion and exclusion criteria\u003c/h2\u003e \u003cp\u003eThis study included patients of both sexes and all ages with suspected and proven bloodstream infections. Patients who were critically ill and unable to provide a blood sample during the data collection period were excluded from the study. The study also excluded patients who were released from the hospital and then readmitted with a BSI within 30 days (Horan et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.4.3 Sampling method\u003c/h2\u003e \u003cp\u003eA convenience sampling technique was used. This was achieved when the physician attending to the patients suspects bloodstream infection in any of the hospital wards.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Method of data collection, culture and identification of antibacterial-resistant Genes\u003c/h2\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e\u003cb\u003e2.5.1 Data collection using a semi-structured questionnaire\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe sociodemographic data, and information on risk factors such as recent invasive procedures, immunosuppression, and underlying health conditions were collected from the hospitalized patients and/or their caregivers using a semi-structured questionnaire with the assistance of trained nursing staff and laboratory personnel of the hospital. Also, some of the patient information was collected from the health records, including age, gender, comorbidities, length of hospital stay, and any prior antibiotic exposure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.5.2 Blood samples collection and culture\u003c/h2\u003e \u003cp\u003eBased on the National Healthcare Safety Network (NHSN) definitions, as provided by the Centre for Disease Control and Prevention (CDC) in 2016. Patients with BSI-PAP were defined as those who had a BSI within 48 hours of admission. The patient's blood collection was performed aseptically, ensuring strict adherence to sterile techniques to avoid contamination. The venipuncture site was properly disinfected with 70% alcohol and 2% iodine tincture. Within a 30-minute interval, two bottles of blood for each patient (5 ml of blood for patients over five years of age and 2 ml of blood for patients under five years of age) were aseptically collected from any of the hands as described by Wyss et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The collected sample was inoculated into a blood culture bottle containing Brain Heart Infusion (BHI) broth as a suitable growth medium. The culture flask was incubated at 37\u0026deg;C for 24 to 48 hours to promote microbial growth. The culture was monitored regularly to detect signs of microbial proliferation by looking for turbidity and or colour changes in the medium. When microbial growth was observed, the sample was sub-cultured on solid agar media including MacConkey agar, blood agar, and chocolate agar for isolation and identification of the bacteria.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.5.3 Identification of the bacterial isolates\u003c/h2\u003e \u003cp\u003eGram staining was used to identify the gram reaction of the bacterial isolates that showed positive blood cultures. Traditional biochemical assays and other various methods including, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), and molecular techniques such as polymerase chain reaction (PCR) were used to further identify the bacterial isolates (Clark et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e2.5.4 Antimicrobial Susceptibility Testing (AST)\u003c/h2\u003e \u003cp\u003eThe disk diffusion method as described by Khan et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) was used to perform the AST. The antimicrobial susceptibility of each of the blood culture isolates was assessed following the guidelines of the Clinical and Laboratory Standards Institute (CLSI) \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e. On nutrient agar, a new subculture of every isolate was initially created. Each isolate was incubated overnight at 37\u0026ordm;C after five colonies were touched with a sterile straight wire and suspended in a sterile Bijou bottle with five millilitres of peptone water (Lab M). Using sterile saline, the overnight broth cultures were diluted to 106 colony-forming units per millilitre by comparing the inoculum's turbidity to the 0.5 McFarland turbidity standards. Mueller-Hinton agar (Oxoid, England) plates were dried and inoculated using a sterile cotton-tipped applicator mixed with a standardized inoculum. Each plate had sterile antibiotic discs, which were then incubated aerobically at 37\u0026ordm;C for 24 hours. Following the standardized CLSI 2021 guidelines, the zone diameter of inhibition of each isolate to the disc was measured using a calibrated ruler (Humphries et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOn Mueller-Hinton agar supplemented with 2 per cent NaCl, staphylococcal isolates exhibiting gentamicin resistance were identified, as previously reported (Taiwo et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Gentamicin 10\u0026micro;g (Gen), erythromycin 10\u0026micro;g (Er), sulfamethoxazole 10\u0026micro;g (Sxt), ciprofloxacin 10\u0026micro;g (Cip), ampicillin 10\u0026micro;g (Amp), tetracycline 10\u0026micro;g (Tet), and cefotaxime 10\u0026micro;g (Ctx) were the antibiotics used for Gram-positive isolates, whereas erythromycin 10\u0026micro;g (Er), sulfamethoxazole 10\u0026micro;g (Sxt), ciprofloxacin 10\u0026micro;g (Cip), ampicillin 10\u0026micro;g (Amp), ampicillin 10\u0026micro;g (Cip), ampicillin 10\u0026micro;g (Amp), tetracycline 10\u0026micro;g (Tet), cefotaxime 5\u0026micro;g (Ctx), and ampicillin-subitan 30\u0026micro;g (Sam) were the antibiotics for Gram-negative isolates.\u003c/p\u003e \u003cp\u003eTo identify infections and patterns of antimicrobial susceptibility, the algorithms used microbiology results and ICD-9-CM billing codes for the following seven organisms: \u003cem\u003eCitrobacter freundi, Burkholderia cepacia-komplex, Staphylococcus eqourum, Staphylococcus gallinarum, Staphylococcus Scurissp lentus, Staphylococcus Xylulosus, Enterobacter cloacae ssp\u003c/em\u003e, and \u003cem\u003eStaphylococcus eqourum.\u003c/em\u003e These organisms were chosen because they were among the most common causes of BSI and frequently develop resistance to one or more antimicrobials (World Health Organization 2015).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e2.5.5 Extended-Spectrum βeta-Lactamase (ESBL) Screening\u003c/h2\u003e \u003cp\u003eThe isolates were screened by one of these drugs (30 \u0026micro;g of erythromycin, sulfamethoxazole, ciprofloxacin or gentamicin, tetracycline or ampicillin-subitan) on a standard disk diffusion procedure. The zones 29 mm for erythromycin, 20 mm for tetracycline or 10 mm for ampicillin-subitan, 24 mm for gentamicin, or 30 mm for ciprofloxacin were considered as probable ESBL producers which were further confirmed by double disk diffusion testing.\u003c/p\u003e \u003cp\u003e \u003cb\u003eExtended-Spectrum β Lactamase Confirmation by Double Disk Diffusion Testing\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe disks containing erythromycin with and without absolute ethanol (8ml) were placed 20mm apart on the surface of a Kigler\u0026rsquo;s Iron Agar (KIA) plate previously inoculated with the test organism and incubated at 56\u0026deg;C for 10 minutes. A test result was considered positive if there was an increase of 5mm or higher in the zone diameter for the combination of antimicrobial agent and absolute ethanol compared with the antibiotic alone. The test was done in cognisance with the Clinical and Laboratory Standards Institute (CLSI) document M100-S21 (Cockerill et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). \u003cem\u003eStaphylococcus scurissp lentus\u003c/em\u003e was used as the ESBL-positive control, and \u003cem\u003eBarkholderia cepacia-komplex\u003c/em\u003e was used as the negative control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e2.5.6 The genomic DNA extraction\u003c/h2\u003e \u003cp\u003eThe specimen (100 \u0026micro;l) was added into a micro-centrifuge tube, followed by the addition of 500 \u0026micro;l of Lysis Buffer. The mixture was then vortexed and incubated at 56\u0026ordm;C for 10 minutes. After incubation, it was centrifuged at 10,000 rpm for 1 minute. Subsequently, 200 \u0026micro;l of absolute ethanol was added to the tube, and the mixture was transferred into a spin column.\u003c/p\u003e \u003cp\u003eThe spin column was centrifuged at 10,000 rpm for 30 seconds, after which the flow-through was discarded, and the collection tube was blotted on tissue paper. Next, 500 \u0026micro;l of Wash Buffer 1 was added to the spin column, followed by centrifugation at 10,000 rpm for 1 minute. The flow-through was discarded again, and the collection tube was blotted on tissue paper. This was repeated with 500 \u0026micro;l of Wash Buffer 2, centrifuged at 10,000 rpm for 1 minute, and the flow-through was discarded as before.\u003c/p\u003e \u003cp\u003eAll traces of ethanol were removed, and the spin column was centrifuged once more at 12,000 to 14,000 rpm for 3 minutes. The spin column was then placed into another micro-centrifuge tube, and 50 \u0026micro;l of Elution Buffer or nuclease-free water was added to the centre of the column. The setup was incubated at room temperature for 1 to 2 minutes and centrifuged at 10,000 rpm for 1 minute to elute the DNA. Finally, the DNA was stored at -20\u0026ordm;C or -80\u0026ordm;C.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e2.5.7 Detection of Antibacterial Resistance Genes\u003c/h2\u003e \u003cp\u003eThe genotypic analysis for erythromycin ribosome methylation gene F (ermF), erythromycin ribosome methylation gene X (ermX), erythromycin ribosome methylation gene A (ereA), beta-lactamase methicillin-resistance \u003cem\u003eStaphylococcus scurissp lentus\u003c/em\u003e (blaMsrS), vietnamese extended-spectrum beta-lactamase (VEB), cefotaximase-type extended-spectrum beta-lactamase (CTX-M), betal-lactamase \u003cem\u003eKlebsiella pneumonia\u003c/em\u003e (blaSHV), and beta-lactamase and enzyme (blaTEM), were performed to confirm the resistant isolates. The antimicrobial-resistant pathogens as described by Zhang et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) were determined by selecting specific genes associated with antimicrobial resistance, and amplifying them through a series of temperature changes using DNA primers and DNA polymerase. The amplified DNA was then analyzed for the presence of antimicrobial resistance genes using techniques such as gel electrophoresis. Finally, the results were compared to known resistance gene sequences to confirm the presence of specific resistance genes. The primers of the genes used are described in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimer Sequence used for Resistance Gene Detection\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTargets\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward Sequence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReverse Sequence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBand size\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eermF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCGA CAC AGC TTT GGT TGA AC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQQA CCT ACC TCA TAG ACA AG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eermX\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGAG ATC GGR CCA GGA AGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGTG TGC ACC ATC GCC TGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eereA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCC GGT GCT CAT CAT GAA CTT GAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCGA CTC TAT TCG ATC AGA GGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMsrS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCA CTT ATT GGG GGT AAT GG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGTC TAT AAG TGC TCT ATC GTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e384\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVEB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGAT GGT GTT TGG TCG CAT ATC GCA AC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAT CGC TGT TGG GGT TGC CCA ATT TT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e391\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTEM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCG CCG CAT ACA CTA TTC TCA AGA ATGAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAG CAA TAA ACC AGC CAG CCG GAA G\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e422\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCTX-M\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATG TGC AGY ACC AGT AAR GTK ATGGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGT RAA RTA RGT SACC AGA AYC AGC GG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e590\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSHV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTGT ATT ATCTC(C/T) CTG TTA GCC(A/G) CCCTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGCT CTG CTT TGT TAT TCG GGC CAA GC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e2.5.8 Method of Data Analysis\u003c/h2\u003e \u003cp\u003eAfter coding and properly sorting the data in a Microsoft Excel spreadsheet, we transferred it to SPSS version 25 software for analysis. To ensure the data's consistency and completeness, we used a cross-tabulation of all variables. We then calculated the descriptive statistics, including percentages, frequencies, means, and standard deviations (SD), for all variables. Next, we performed bivariate analyses to determine the relationships between BSI-PAP and potential predictor variables, such as source of admission, age, gender, previous hospitalization, renal failure, diabetes mellitus, malignancy, and chronic dermatitis. We used chi-square tests for categorical variables and the Wilcoxon rank sum test for confidence class interval (CCI). Multiple logistic regression was then used to include the variables significantly associated with BSI-HOA in the bivariate analyses (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Due to the small sample size (n\u0026thinsp;=\u0026thinsp;2), we excluded malignancies from the multivariable analysis. Additionally, we excluded CCI from the multivariable analysis since some of the predictors in our model were included in the CCI composite score.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Socio-Demographic Information of the Study Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 315 patients were sampled in this study on antibacterial-resistant genes associated with bloodstream infections present in admitted patients at Nigeria Air Force Medical Centre, Onikan Lagos State. All patients had received at least one antimicrobial agent during the study period. Out of these, 30 patients (10%) had bloodstream infections. Among these 30 patients, 21 (71%) were male and 9 (29%) were female. Their ages ranged from 18 to 44 years, with the following distribution: 18-24 years (35%), 25-29 years (29%), 30-34 years (18%), 35-39 years (6%), and 40-44 years (12%). The average age was 29.29 years, with a standard deviation of 7.447, as shown in table 2.\u003c/p\u003e\n\u003cp\u003eThe participants\u0026apos; educational backgrounds were as follows: 14 (47%) had a secondary school certificate, 4 (24%) had technical/vocational training, and 9 (29%) had a Bachelor\u0026apos;s degree. All participants had chronic medical conditions, including urinary tract infection (35%), renal failure (29%), chronic dermatitis (18%), Diabetes mellitus (12%), and malignancies (6%). They were all taking antibiotics, with 29% having taken them within the past 3 months, 53% within the past 6 months, and 18% within the past year. None of the patients with bloodstream infections had undergone surgery in the past 6 months.\u003c/p\u003e\n\u003cp\u003eThe lifestyle and habits of the participants were as follows: 26 (88%) did not smoke, while 4 (12%) admitted to smoking. In terms of alcohol consumption, 35% had never consumed any, 49% consumed occasionally, and 18% consumed regularly. Only 15% of the patients exercised regularly, while 85% did not.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Socio-demographic information of the study participants\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57.6923%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.1923%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57.6923%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e18- 24\u003c/p\u003e\n \u003cp\u003e25 \u0026ndash; 29\u003c/p\u003e\n \u003cp\u003e30 \u0026ndash; 34\u003c/p\u003e\n \u003cp\u003e35 - \u0026nbsp;39\u003c/p\u003e\n \u003cp\u003e40 \u0026ndash; 44\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e17\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e29.29\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e7.447\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.1923%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57.6923%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e1.29\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.469\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.1923%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57.6923%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Background\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003cp\u003eTechnical/Vocational Training\u003c/p\u003e\n \u003cp\u003eBachelor\u0026rsquo;s Degree\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e3.79\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.893\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.1923%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57.6923%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth History\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eDiagnosed with Chronic Medical Condition\u003c/p\u003e\n \u003cp\u003eYES\u003c/p\u003e\n \u003cp\u003eNO\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSpecify the Chronic Disease\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n \u003cp\u003eMalignancies\u003c/p\u003e\n \u003cp\u003eRenal Failure\u003c/p\u003e\n \u003cp\u003eChronic Dermatitis\u003c/p\u003e\n \u003cp\u003eUrinary tract infection\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCurrently Taking Antibiotics\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eYES\u003c/p\u003e\n \u003cp\u003eNO\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAntibiotics Intake\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eWithin the last 3 months\u003c/p\u003e\n \u003cp\u003eWithin the last 6 months\u003c/p\u003e\n \u003cp\u003eWithin a year\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSurgeries for last 6 Months\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eYES\u003c/p\u003e\n \u003cp\u003eNO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.00\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.00\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e4.00\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.679\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.1923%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57.6923%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLifestyle and Habits\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003cp\u003eYES\u003c/p\u003e\n \u003cp\u003eNO\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eConsume Alcoholic Beverages\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003cp\u003eOccasionally\u003c/p\u003e\n \u003cp\u003eRegularly\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDo you engage in regular exercise?\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eYES\u003c/p\u003e\n \u003cp\u003eNO\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e1.93\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.267\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e1.71\u003c/p\u003e\n \u003cp\u003e0.726\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003cp\u003e0.426\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.1923%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1 below revealed the ages of the participants with ages of 18 to 24 years having the highest frequency. The mean was 29.29 and the SD was 7.447 which indicates less variability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. 2 Prevalence and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eco-morbid conditions\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eof bloodstream infections among the admitted patients (BSI-PAP)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe patients were 315, out of which 30 (9.5%) cases were of bloodstream infection admitted. The male patients were the most admitted with a BSI (71%) than the female (29%). The urinary tract infection, diabetes mellitus, renal failure, chronic dermatitis and malignancies were significantly associated with BSI-PAP in bivariate analyses. The mean score (mean = 3.8 \u0026plusmn; SD = 3.5) of patients with BSI-PAP was significantly higher, compared with those patients without BSI-PAP (mean = 2.8 \u0026plusmn; SD = 3.3), P \u0026lt; 0.001 (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Prevalence and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eco-morbid conditions\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eof bloodstream infections among the admitted patients (BSI-PAP)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.9968%;\"\u003e\n \u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.7718%;\"\u003e\u003cstrong\u003eBSI-PAP\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003e(n = 30) (%)\u003c/strong\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.87%;\"\u003e\u003cstrong\u003eNon- BSI-PAP\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003e(n = 285) (%)\u003c/strong\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3613%;\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.9968%;\"\u003e\u003cstrong\u003eLaboratory Culture Media Source\u003c/strong\u003e\n \u003cp\u003eEosin Methylene Blue (EMB)\u003c/p\u003e\n \u003cp\u003eSalmonell-Shigella Agar (SSA)\u003c/p\u003e\n \u003cp\u003eMacConkey Agar (MAC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.7718%;\"\u003e\n \u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n \u003cp\u003e14 (47)\u003c/p\u003e\n \u003cp\u003e12 (41)\u003c/p\u003e\n \u003cp\u003e4 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.87%;\"\u003e\n \u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n \u003cp\u003e137 (48)\u003c/p\u003e\n \u003cp\u003e131 (46)\u003c/p\u003e\n \u003cp\u003e17 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3613%;\"\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.9968%;\"\u003e\u003cstrong\u003eAge Category (years)\u003c/strong\u003e\n \u003cp\u003e18 \u0026ndash; 24\u003c/p\u003e\n \u003cp\u003e25 \u0026ndash; 29\u003c/p\u003e\n \u003cp\u003e30 \u0026ndash; 34\u003c/p\u003e\n \u003cp\u003e35 \u0026ndash; 39\u003c/p\u003e\n \u003cp\u003e40 \u0026ndash; 44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.7718%;\"\u003e\n \u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n \u003cp\u003e11 (35)\u003c/p\u003e\n \u003cp\u003e9 (29)\u003c/p\u003e\n \u003cp\u003e5 (18)\u003c/p\u003e\n \u003cp\u003e1 (6)\u003c/p\u003e\n \u003cp\u003e4 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.87%;\"\u003e\n \u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n \u003cp\u003e66 (23)\u003c/p\u003e\n \u003cp\u003e51 (18)\u003c/p\u003e\n \u003cp\u003e100 (35)\u003c/p\u003e\n \u003cp\u003e23 (8)\u003c/p\u003e\n \u003cp\u003e46 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3613%;\"\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.9968%;\"\u003e\u003cstrong\u003eGender\u003c/strong\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.7718%;\"\u003e\n \u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n \u003cp\u003e21 (71)\u003c/p\u003e\n \u003cp\u003e9 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.87%;\"\u003e\n \u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n \u003cp\u003e202 (71)\u003c/p\u003e\n \u003cp\u003e83 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3613%;\"\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.9968%;\"\u003e\u003cstrong\u003eCo-Morbid Conditions\u003c/strong\u003e\u003cbr\u003e\n \u003cp\u003eUrinary tract infection\u003c/p\u003e\n \u003cp\u003eDiabetes mellitus\u003c/p\u003e\n \u003cp\u003eRenal failure\u003c/p\u003e\n \u003cp\u003eChronic Dermatitis\u003c/p\u003e\n \u003cp\u003eMalignancies\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCCI Scores: Mean [ Standard Deviation]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.7718%;\"\u003e\n \u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n \u003cp\u003e11 (53)\u003c/p\u003e\n \u003cp\u003e4 (29)\u003c/p\u003e\n \u003cp\u003e9 (35)\u003c/p\u003e\n \u003cp\u003e5 (18)\u003c/p\u003e\n \u003cp\u003e2 (12)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e3.8 [ 3.5]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.87%;\"\u003e\n \u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n \u003cp\u003e94 (33)\u003c/p\u003e\n \u003cp\u003e51 (18)\u003c/p\u003e\n \u003cp\u003e68 (24)\u003c/p\u003e\n \u003cp\u003e48 (17)\u003c/p\u003e\n \u003cp\u003e26 (9)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.8 [ 3.3]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3613%;\"\u003e\n \u003ch3\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/h3\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 The Risk Factors and Predictors contributing to the Development of AMRP-Associated Bloodstream Infections present in Admitted Patients (BSI-PAP).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 4 shows the multivariable analysis of the association between Patients\u0026rsquo; characteristics and BSI-PAP, the odds of being admitted with BSI-PAP were greatest among patients admitted with diabetes mellitus, urinary tract infection, renal failure and chronic dermatitis. The odds ratios 95% confidence interval (CI) were 4.96 (95% CI = 1.37-7.32), 2.59 (95% CI = 0.29-4.9), 2.39 (95% CI = -0.17-4.89) and 1.32 (95% CI = 0.37-4.29) and, respectively. There was no association between ages from 30 to 44 years, female gender and EMB culture media.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Association between patients\u0026rsquo; features and BSI-PAP in multivariable logistic regression analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdds Ratio (OR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% Confidence Interval (C.I)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 294px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCo-Morbid Conditions\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eUrinary tract infections\u003c/p\u003e\n \u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n \u003cp\u003eRenal Failure\u003c/p\u003e\n \u003cp\u003eChronic Dermatitis\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAge (In years)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;18 \u0026ndash; 24\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25 \u0026ndash; 29\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30 \u0026ndash; 34\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35 \u0026ndash; 39\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40 \u0026ndash; 44\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003ch3\u003e\u003cstrong\u003eLaboratory Culture Media Source\u003c/strong\u003e\u003c/h3\u003e\n \u003cp\u003eEosin Methylene Blue (EMB)\u003c/p\u003e\n \u003cp\u003eSalmonell-Shigella Agar (SSA)\u003c/p\u003e\n \u003cp\u003eMacConkey Agaar (MAC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.5899\u003c/p\u003e\n \u003cp\u003e4.9566\u003c/p\u003e\n \u003cp\u003e2.3855\u003c/p\u003e\n \u003cp\u003e1.3193\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.8777\u003c/p\u003e\n \u003cp\u003e1.8613\u003c/p\u003e\n \u003cp\u003e0.3137\u003c/p\u003e\n \u003cp\u003e0.8341\u003c/p\u003e\n \u003cp\u003e0.8536\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.0213\u003c/p\u003e\n \u003cp\u003e0.9792\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.6192\u003c/p\u003e\n \u003cp\u003e1.2158\u003c/p\u003e\n \u003cp\u003e2.0354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.2868\u003c/p\u003e\n \u003cp\u003e1.3728\u003c/p\u003e\n \u003cp\u003e-0.1677\u003c/p\u003e\n \u003cp\u003e0.3668\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.6950\u003c/p\u003e\n \u003cp\u003e0.6274\u003c/p\u003e\n \u003cp\u003e0.0718\u003c/p\u003e\n \u003cp\u003e0.1073\u003c/p\u003e\n \u003cp\u003e0.1949\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.4257\u003c/p\u003e\n \u003cp\u003e0.1273\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.2296\u003c/p\u003e\n \u003cp\u003e0.5003\u003c/p\u003e\n \u003cp\u003e0.4612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.9367\u003c/p\u003e\n \u003cp\u003e7.3295\u003c/p\u003e\n \u003cp\u003e4.8943\u003c/p\u003e\n \u003cp\u003e4.2941\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.0723\u003c/p\u003e\n \u003cp\u003e5.5220\u003c/p\u003e\n \u003cp\u003e1.3698\u003c/p\u003e\n \u003cp\u003e6.4851\u003c/p\u003e\n \u003cp\u003e3.7393\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.4500\u003c/p\u003e\n \u003cp\u003e2.4213\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.6698\u003c/p\u003e\n \u003cp\u003e2.9547\u003c/p\u003e\n \u003cp\u003e8.9836\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 \u0026nbsp; \u0026nbsp; \u0026nbsp; Bacterial isolates associated with BSI-PAP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 5 shows the isolates associated with BSI-PAP among the patients admitted with BSI-PAP (n = 30), the largest proportion presented with \u003cem\u003eS. scurissp Lentus\u003c/em\u003e (n = 6, 35.3%), followed by \u003cem\u003eS. gallinarum\u003c/em\u003e (n = 3, 17.6%), \u003cem\u003eS. eqourum\u003c/em\u003e (n = 3, 17.6%), \u0026nbsp;\u003cem\u003eE.cloacae SSP\u003c/em\u003e (n = 5, 11.8%), \u003cem\u003eB. capacia-komplex\u003c/em\u003e (n = 7, 5.9%), \u003cem\u003eS. xylulosus\u003c/em\u003e (n = 1, 5.9%), and \u003cem\u003eC. freundi\u003c/em\u003e (n = 5, 5.9%). About 76% (13) of the BSI-PAP cases with these organisms were antibiotic-resistant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5: Bacterial isolates associated with BSI-PAP among the patients admitted with BSI-PAP\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIsolates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEMB\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eResistant (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSSA\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eResistant\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMAC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eResistant (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cem\u003eS.gallinarum\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eS.scuri SSP lentus\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eS.xylulosus\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eS.eqourum\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eE. cloacae SSP\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB.cepacia-konplex\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eC.freundi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e1(95)\u003c/p\u003e\n \u003cp\u003e3 (78)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e2 (62)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e1 (92)\u003c/p\u003e\n \u003cp\u003e2 (79)\u003c/p\u003e\n \u003cp\u003e1 (95)\u003c/p\u003e\n \u003cp\u003e1 (78)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e1 (100)\u003c/p\u003e\n \u003cp\u003e1( 49)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.545*\u003c/p\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003cp\u003e0.720f\u003c/p\u003e\n \u003cp\u003e0.003f\u003c/p\u003e\n \u003cp\u003e0.842*\u003c/p\u003e\n \u003cp\u003e0.725*\u003c/p\u003e\n \u003cp\u003e0.360f\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6 (78)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (86)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 (75)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*-chi-square, f-Fisher\u0026rsquo;s exact test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 The AMRP of Bacterial Isolates from BSI-PAP among Commonly Prescribed Antibiotics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOut of which 30 (34.7%) documented BSI, gram-negative bacteria had the highest frequency (56.7%), which are \u003cem\u003eE. cloacae ssp, B. cepacia-komplex\u003c/em\u003e, and \u003cem\u003eC. freundi.\u003c/em\u003e The gram-positive bacteria had 43.3% in BSI, which \u003cem\u003eS. scuri ssp lentus, S. gallinarum. S. eqourum\u003c/em\u003e and \u003cem\u003eS.xylulosus\u0026nbsp;\u003c/em\u003ewere present. The most frequently isolated bacterium was \u003cem\u003eB. cepacia-komplex\u003c/em\u003e (23.3%) and others occurred in descending order as follows: \u003cem\u003eS. scuri ssp lentus\u003c/em\u003e (20%), \u003cem\u003eE. cloacae ssp\u003c/em\u003e and \u003cem\u003eC. freundi\u003c/em\u003e (16.7%),\u003cem\u003e\u0026nbsp;S. gallinarum\u003c/em\u003e and \u003cem\u003eS. eqourum\u003c/em\u003e (10%) and \u003cem\u003eS. xylulosus\u0026nbsp;\u003c/em\u003e(3.3%). A high level of resistance was obtained among both the gram-positive (4\u0026ndash;100%) and gram-negative bacterial isolates (3\u0026ndash;100%) (Table 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6: The Bacterial Isolates of bloodstream infection (BSI)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBacterial isolates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo of Isolates (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGram Positive\u003c/strong\u003e\u003c/p\u003e\n \u003col\u003e\n \u003cli\u003e\u003cem\u003eS.scurissp.lentus\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eS.gallinarum\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eS.xylulosus\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eS.eqourum\u003c/em\u003e\u003c/li\u003e\n \u003c/ol\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGram Negative\u003c/strong\u003e\u003c/p\u003e\n \u003col\u003e\n \u003cli\u003e\u003cem\u003eE.cloacae ssp\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eB.cepacia-komplex\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eC.freundi\u003c/em\u003e\u003c/li\u003e\n \u003c/ol\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Isolates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13 (43.3)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e6 (20) GENRSS = 5 (83%)\u003c/p\u003e\n \u003cp\u003e3 (10) GENRSG = 3 (100%)\u003c/p\u003e\n \u003cp\u003e1 (3.3)\u003c/p\u003e\n \u003cp\u003e3 (10) ERSE = 3 (100%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e17 (56.7)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e5 (16.7)\u003c/p\u003e\n \u003cp\u003e7 (23.3)\u003c/p\u003e\n \u003cp\u003e5 (16.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eGENRSS = Gentamicin-resistant Staphylococcus scuri ssp lentus\u003c/p\u003e\n\u003cp\u003eGENRSG = Gentamicin resistant gallinarum\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eERSE = Erythromicin resistant Streptococcus eqourum\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 The Efficacy of the Antibiotic Combination used as first-line Empirical Treatment of BSI-PAP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 7 displayed the pattern of the drug resistance for both gram-positive and gram-negative isolates, this revealed single and multiple drug resistance patterns with the number of antibiotics ranging from 2 to 5 and from 2 to 6 for Gram positive and Gram negative respectively. For the drug resistance pattern for Gram-positive isolates; gentamicin erythromycin and erythromycin sulfamethoxazole tetracycline resistance phenotypes occurred most frequently among the patients aged 18-29 years (54%), while for the gram-negative isolates, the resistance phenotypes erythromycin sulfamethoxazole and erythromycin sulfamethoxazole ciprofloxacin ampicillin occurred most frequently in the age group of 30\u0026ndash;44 years (72%). Erythromycin (85%), Gentamicin (55%), Sulfamethoxazole (54%) and Tetracycline (24%) are widely used for the treatment of BSI by younger adults, while Erythromycin (96%), Ciprofloxacin (72%), Tetracycline (66%) and Ampicillin (60%) are mostly used by middle-aged patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7: The Antibiotics Resistance Pattern of Gram Positive and Gram-Negative Isolates\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"655\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 655px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGram Positive Isolates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo of Antibiotics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResistance (R) Pattern\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo of Isolates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBacteria\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 318px;\"\u003e\n \u003cp\u003eGentamicin\u003c/p\u003e\n \u003cp\u003eGentamicin Erythromycin\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eErythromicin Sulfamethoxazole\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eErythromicin Sulfamethoxazole Tetracycline\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eGentamicin Erythromycin Sulfamethoxazole Ciprofloxacin\u003c/p\u003e\n \u003cp\u003eSulfamethoxazole Ciprofloxacin Ampicillin Cefotoxine\u003c/p\u003e\n \u003cp\u003eGentamicin Erythromycin Sulfamethoxazole Ciprofloxacin Ampicillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cem\u003eS.scuri ssp\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eS.xylulosus; S.equorum; S.gallinarum\u003c/em\u003e; \u003cem\u003eS.scuri ssp\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eS.gallinarum\u003c/em\u003e; \u003cem\u003eS.scuri ssp\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eS.xylulosus\u003c/em\u003e; \u003cem\u003eS.equorum\u003c/em\u003e; \u003cem\u003eS.gallinarum\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eS.scuri ssp\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eS.scuri ssp\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eS.scuri ssp\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 655px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGram Negative Isolates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 324px;\"\u003e\n \u003cp\u003eErythromicin\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eErythromicin Sulfamethoxazole\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eErythromicin Sulfamethoxazole Ciprofloxacin\u003c/p\u003e\n \u003cp\u003eErythromicin Sulfamethoxazole Ciprofloxacin\u003c/p\u003e\n \u003cp\u003eAmpicillin\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eErythromicin Sulfamethoxazole Ciprofloxacin\u003c/p\u003e\n \u003cp\u003eAmpicillin Tetracycline\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eErythromicin Sulfamethoxazole Ciprofloxacin\u003c/p\u003e\n \u003cp\u003eAmpicillin Tetracycline Cefotoxime\u003c/p\u003e\n \u003cp\u003eErythromicin Sulfamethoxazole Ciprofloxacin\u003c/p\u003e\n \u003cp\u003eAmpicillin Tetracycline Cefotoxime Ampicillin-Subitan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cem\u003eB.cepacia-komplex\u003c/em\u003e,\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003cem\u003eE.cleacole ssp\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eC.freuodii\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB.cepacia-komplex\u003c/em\u003e,\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003cem\u003eE.cleacole ssp\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eC.freuodii\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB.cepacia-komplex\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB.cepacia-komplex\u003c/em\u003e,\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003cem\u003eE.cleacole ssp\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eC.freuodii\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB.cepacia-komplex\u003c/em\u003e,\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003cem\u003eE.cleacole ssp\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eC.freuodii\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB.cepacia-komplex\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB.cepacia-komplex\u003c/em\u003e,\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003cem\u003eE.cleacole ssp\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eC.freuodii\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 324px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.7 Extended-Spectrum Beta-Lactamase (ESBL) Screening and Confirmatory Testing\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, 7 bacterial isolates of \u003cem\u003eE. coli (B. cepacia-komplex)\u003c/em\u003e and 5 bacterial isolates of \u003cem\u003eK.pnemonia (E. cloacae ssp)\u003c/em\u003e were recovered from the hospitalized patients. Generally, 29% (2 out of 7) isolates of \u003cem\u003eE. coli (B. cepacia-komplex)\u003c/em\u003e and 20% (1 out of 5) \u003cem\u003eK. pneumonia (E. cloacae ssp)\u003c/em\u003e isolates showed resistance to the third-generation cephalosporin by phenotypic screening tests. 100% (7 out of 7) of ESBL was detected among isolates of \u003cem\u003eE. coli (B. cepacia-komplex)\u003c/em\u003e and 100% (5 out of 5) isolates of \u003cem\u003eK. pneumonia (E.cloacae ssp)\u003c/em\u003e by confirmatory testing. it was observed that age was significantly associated with the incidence of both \u003cem\u003eE. coli (B. cepacia-komplex)\u0026nbsp;\u003c/em\u003eand \u003cem\u003eK. pneumonia (E. cloacae ssp)\u003c/em\u003e infection (p \u0026lt; 0.05) (Table 8).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8\u003c/strong\u003e\u003cstrong\u003e: Phenotypic Detection of ESBL Isolates.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"630\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBacterial Isolates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 427px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eESBL Screening by the disk diffusion method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eESBL confirmed by double disk diffusion testing.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eErythromycin 30(\u0026micro;g)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTetracycline 30(\u0026micro;g)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSulfamethoxazole\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e30(\u0026micro;g)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCiproflaxin 30(\u0026micro;g)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eErythromycin (30\u0026micro;g) with absolute ethanol (10 \u0026micro;g)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cem\u003eE.coli.(B. cepacia-komplex)\u0026nbsp;\u003c/em\u003e(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e7 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e3 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e6 (86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5 (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e7 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cem\u003eK.pneumonia (E.cloacae ssp)\u0026nbsp;\u003c/em\u003e(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e5 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e2 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e4 (80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e3 (60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e5 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (42)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10 (83)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8 (67)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8: Molecular detection of resistant genes\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall incidence of \u0026beta;eta-lactamase genes was found to be 30.7% (12 out of 39) which included 100% (7 out of 7) of \u003cem\u003eEscherichia coli\u0026nbsp;\u003c/em\u003e(\u003cem\u003eB. cepacia-komplex\u003c/em\u003e)\u003cem\u003e\u0026nbsp;\u003c/em\u003eand 100% (5 of 5) of \u003cem\u003eKlebsiella pneumonia\u0026nbsp;\u003c/em\u003e(\u003cem\u003eE. cloacae ssp\u003c/em\u003e), respectively. Molecular characterization showed that out of the 12 phenotypically positive ESBL isolates, 33% (4 out of 12) were positive for the blaCTX-M (Fig 4.3, lane 3, 4, 5, 6, 8). It consisted of 29% (2 out of 7) of \u003cem\u003eEscherichia coli\u0026nbsp;\u003c/em\u003e(\u003cem\u003eB. cepacia-komplex\u003c/em\u003e)\u003cem\u003e\u0026nbsp;\u003c/em\u003eand 40% (2 out of 5) of \u003cem\u003eKlebsiella pneumonia\u0026nbsp;\u003c/em\u003e(\u003cem\u003eE.cloacae ssp\u003c/em\u003e). Generally, TEM (42%) was the most common genotype followed by CTX-M (33%), SHV (17%) and VEB (8%) both in single or when combined. No isolates harbored ermF, ermX, ereA, and MsrS genes (Table 9). In total, 35% of the total ESBL-positive isolates harboured the three ESBL genes, while 61% carried two of the tested ESBL genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 9: \u0026nbsp;Distribution of different genes in ESBL-producing \u003cem\u003eEscherichia coli\u003c/em\u003e (\u003cem\u003eB. cepacia-komplex\u003c/em\u003e) and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (\u003cem\u003eE. cloacae ssp\u003c/em\u003e) isolates\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eB. cepacia-komplex\u003c/em\u003e)\u003c/p\u003e\n \u003cp\u003e(N = 7) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 173px;\"\u003e\n \u003cp\u003e\u003cem\u003eKlebsiella pneumonia\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eE.cloacae ssp\u003c/em\u003e)\u003c/p\u003e\n \u003cp\u003e(N = 5) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003e(N = 12) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003eermF\u003c/p\u003e\n \u003cp\u003eermX\u003c/p\u003e\n \u003cp\u003eereA\u003c/p\u003e\n \u003cp\u003eMsrS\u003c/p\u003e\n \u003cp\u003eVEB\u003c/p\u003e\n \u003cp\u003eCTX-M\u003c/p\u003e\n \u003cp\u003eSHV\u003c/p\u003e\n \u003cp\u003eTEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e1 (14)\u003c/p\u003e\n \u003cp\u003e2 (29)\u003c/p\u003e\n \u003cp\u003e1 (14)\u003c/p\u003e\n \u003cp\u003e3 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 173px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e2 (40)\u003c/p\u003e\n \u003cp\u003e1 (20)\u003c/p\u003e\n \u003cp\u003e2 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e1 (8)\u003c/p\u003e\n \u003cp\u003e4 (33)\u003c/p\u003e\n \u003cp\u003e2 (17)\u003c/p\u003e\n \u003cp\u003e5 (42)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"4 Discussion","content":"\u003cp\u003e \u003cb\u003eThe Prevalence and Distribution of Antimicrobial-Resistant Pathogen (AMRP) causing Bloodstream Infections present in Admitted Patients (BSI-PAP).\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe patients receiving healthcare treatment in Nigeria Airforce Medical Center Onikan, Lagos State from January to June 2024 were 315, out of which 30 were cases of BSI-PAP that led to a prevalence rate of 9.5%. Even when accounting for age, patients who were admitted and screened with these media cultures; Eosin methylene blue (EMB) and Salmonella-Shigella Agar (SSA) were significantly and had more chances to have a BSI-PAP than patients who were admitted and screened with MacConkey agar (MAC) culture media. Consistently, other researchers investigated BSI among nursing home (NH) and non-nursing home (NNH) admissions and ascertained that NH exposure was a risk factor for BSI-PAP caused by gram-positive and gram-negative organisms (Karaman et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and another investigator reported that patients admitted for a long-term in a medical care facility was associated with gram-negative BSI-PAP (Algammal et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). One of the limitations of these studies was that the patients were from a single hospital, which is also applicable to the current study.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe Risk Factors and Predictors contributing to the Development of AMRP-Associated Bloodstream Infections present in Admitted Patients (BSI-PAP).\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe multivariable analysis of the association between Patients’ characteristics and BSI-PAP was performed, and the Patients with younger ages 18 to 34 years and male gender were the significant predictors of BSI-PAP and this is contrary to the results of other investigators who found older age and male gender to be significant predictors of BSI-PAP (Uslan et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Akoua-Koffi et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Sequel to the patient characteristics studied, patients with diabetes mellitus, prior hospitalisation, renal failure and chronic dermatitis had the highest odds ratios of being admitted with a BSI. These findings are consistent with two previous studies that reported renal failure and prior hospitalisation to be associated with BSI-PAP (Rodriguez-Bano et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Sainfer et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Generally, patients with these conditions have multiple co-morbidities which include changes in immune function which influence their risk of BSI acquisition (Stewart et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and dermatitis which menaced the skin barrier. However, this finding follows the study that reported that diabetes mellitus increased the odds of BSI-PAP in chronically sick patients (OR = 1.42, 95% CI = 1.10– 1.82) (McKane et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe isolates associated with BSI-PAP which accounted for almost half of the isolates were \u003cem\u003eS. scuri ssp lentus\u003c/em\u003e among the organisms studied and had a higher proportion of resistant strains among those screened with media culture from SSA when compared with those screened with EMB and MAC. This finding is in contrast with the reports of other investigators by Sainfer et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), which reports that \u003cem\u003eS. aureus\u003c/em\u003e accounted for most of the isolates with a higher proportion of resistant strains among the patients admitted from nursing homes.\u003c/p\u003e \u003cp\u003eHowever, the resistant strains were highest among patients screened with the media culture from SSA; this is not surprising considering that patients who have had been previously screened with EMB are exposed to more multidrug-resistant pathogens and are more likely to have received antibiotics (Karkada et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Seventy-eight per cent of the \u003cem\u003eS. gallinarum\u003c/em\u003e-resistant strains were isolated from patients screened with a media culture EMB, perhaps related to prior antibiotic exposure. Most of the organisms’ results were not significant and this could be due to the small number of organisms with resistant strains. The resistant strains in isolates causing BSI-PAP were high for patients screened with EMB, SSA and MAC (78%, 86% and 75%, respectively), P = 0.001 among the seven organisms studied. However, when broken down by organisms, only \u003cem\u003eS. scurissp Lentus\u003c/em\u003e showed a significantly higher proportion of resistant strains in patients screened with culture media from SSA. In that effect, prospective surveillance might be indicated when patients are screened for BSI with these settings.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe AMRP of Bacterial Isolates of BSI-PAP among Commonly Prescribed Antibiotics\u003c/b\u003e \u003c/p\u003e \u003cp\u003eDuring the period of this investigation, 30 (34.7%) were microbiologically documented BSI with all being mono-microbial. This value follows the range reported by other researchers in Nigeria (Sainfer et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and other countries (Hugonnet et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). This implies that most of the BSIs in the tropical region are massively uncharacterized microbiologically and are hence, empirically treated. The Gram-negative bacteria were more frequently involved (56.7%), which are \u003cem\u003eE.cloacae ssp, B.cepacia-komplex\u003c/em\u003e, and \u003cem\u003eC.freundi\u003c/em\u003e than the gram-positive bacteria (43.3%) in BSI in this study which are \u003cem\u003eS.scuri ssp lentus, S.gallinarum. S. eqourum\u003c/em\u003e and \u003cem\u003eS. xylulosus\u003c/em\u003e. The most frequently isolated bacterium was \u003cem\u003eB.cepacia-komplex\u003c/em\u003e. The high level of resistance to commonly available antibiotics that were used for the empirical treatment of BSI in this study was obtained among both the Gram-positive (4–100%) and Gram-negative bacterial isolates (3–100%). However, there is an association with increased mortality rates, overstay in hospital admission and costs due to BSI-PAP-resistant organisms (Rello et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), this makes it more important for microbiology laboratories to always give out information on antibiotic susceptibility patterns of the prevalent micro-organisms involved in BSI-PAP, that can be used as a guide for antibiotic selection.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe Efficacy of the Antibiotic Combination used as first line Empirical Treatment of BSI-PAP\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe pattern of the drug resistance for both Gram-positive and Gram-negative isolates revealed single and multiple drug resistance patterns with the number of antibiotics ranging from two to five and from two to six for Gram-positive and Gram-negative respectively. This is not consistent with the study conducted by Majumder et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), where the drug resistance pattern of both the Gram-positive and Gram-negative isolates revealed single and multiple drug resistance patterns with the number of antibiotics ranging from two to seven. For the drug resistance pattern of Gram-positive isolates; Gen E and E Sxt Te resistance phenotypes occurred most frequently among the patients aged 18–29 years (54%), while for the Gram-negative isolates, the resistance phenotypes E Sxt and E Sxt Cip Amp occurred most frequently in the age group 30–44 years (72%). Gentamicin, Erythromycin, Sulfamethoxazole, and Tetracycline are widely used for the treatment of BSI by younger adults, while Erythromycin, Ciprofloxacin, Tetracycline and Ampicillin are mostly used by middle-aged patients and are easily obtained without medical authorization.\u003c/p\u003e \u003cp\u003e \u003cb\u003eExtended-Spectrum Beta-Lactamase (ESBL) Screening and Confirmatory Testing and the Molecular Analysis of the resistant genes\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe highly prevalent co-morbidity in this study is the major issue among the patients that were hospitalized, and multidrug-resistant \u003cem\u003eE. coli\u003c/em\u003e (\u003cem\u003eB. cepacia-komplex\u003c/em\u003e) and \u003cem\u003eK. pneumonia\u003c/em\u003e (\u003cem\u003eE. cloacae ssp\u003c/em\u003e), were the most important pathogens (Prasada et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). generally, 29% (2 out of 7) isolates of \u003cem\u003eE. coli (B. cepacia-komplex)\u003c/em\u003e and 20% (1 out of 5) \u003cem\u003eK. pnemonia (E. cloacae ssp)\u003c/em\u003e isolates show resistance to the third-generation cephalosporin by phenotypic screening tests. 100% (7 out of 7) of ESBL was detected among isolates of \u003cem\u003eE. coli (B. cepacia-komplex)\u003c/em\u003e and 100% (5 out of 5) isolates of \u003cem\u003eK. pnemonia (E. cloacae ssp)\u003c/em\u003e, which was somehow lower when compared with other studies. The production of ESBL production in different studies in India found a prevalence of 60.80, 46.26, 66.78, 34, 63.60, 18.80%, and 39.20, 25.1, 61.70, 42.0, 66.70, and 35.50% in \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates, respectively (Gautam et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The prevalence of ESBL production all over the world among the clinical isolates ranges from less than 1 to 88% (Veeraraghavan et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe overall incidence of βeta-lactamase genes was found to be 30.7%. Molecular characterization showed that out of the 12 phenotypically positive ESBL isolates, 33% was positive for the blaCTX-M. Generally, TEM (42%) was the most common genotype followed by CTX-M (33%), SHV (17%) and VEB (8%) both in single or when combined. No isolates harbored ermF, ermX, ereA, and MsrS genes. In total, 35% of the total ESBL-positive isolates harbored the three ESBL genes, while 61% carried two of the tested ESBL genes. There is a probability of community-based dissemination of ESBL-producing isolates because this is a serious issue. There is a significant implication with the high rate of various ESBL-producing genes for patient treatment and outline the benefits that strengthens the antimicrobial surveillance, antibiotic stewardship, and continuous monitoring of the rate of ESBL production along with multidrug resistance among nosocomial isolates. This is in tune with a study conducted in North East districts in India, where cefotaximase-type extended-spectrum beta-lactamase (CTX-M) was found in \u003cem\u003eE. coli\u003c/em\u003e (88.67%) and beta-lactamase and enzyme (blaTEM) in \u003cem\u003eK. pneumoniae\u003c/em\u003e (77.58%) as the genotype that predominates the most. (Bora et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Another team of researcher, Roy et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) identified a higher rate of cefotaximase-type extended-spectrum beta-lactamase 15 (blaCTX-M15) (100%) compared with this current study (33%).\u003c/p\u003e "},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights a 9.5% prevalence of bloodstream infections (BSI) and identifies key risk factors, including younger adults, males, diabetes, prior hospitalization, renal failure, and chronic dermatitis. High antimicrobial resistance was noted among clinical isolates, particularly to gentamicin, erythromycin, sulfamethoxazole, and tetracycline. The study underscores the increasing complexity of healthcare delivery and its role in disseminating resistant organisms. Extended-spectrum beta-lactamase (ESBL) prevalence in UTIs caused by \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e is significant, with resistance linked to TEM, CTX-M, SHV, and VEB beta-lactamases. Findings emphasize stricter control measures and the cautious use of ceftazidime in managing ESBL infections.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthnical Consideration/Informed Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed written consent was sought and obtained from all study participants. Additionally, a letter of introduction (FUT/SOHT/PUH/CS.0012/VOL.2) to carry out the study was obtained from the Department of Public Health Technology, FUTO, to the ethics committee of the Nigerian Air Force Medical Centre, Onikan, Lagos State. The study was approved by the 055 NAF Medical Centre Ethics Committee of Nigerian Air Force on 11/10/2023 with the reference number 055 CAMP/405/MEDCEN.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for the publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eAll data generated or analysed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThere is no competing interest among the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research was self-funded by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eUGE and BCA\u0026nbsp;designed research;\u0026nbsp;QCO, IGC, CCO, CCU, CLO, ABN conducted research; CCAO\u0026nbsp;analyzed data;\u0026nbsp;COA, QCO, IGC, and CLO wrote the paper; UMC, UMD, VNU,\u0026nbsp;BCA\u0026nbsp;and UGE had primary responsibility for the final content. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlgammal AM, Hetta HF, Elkelish A, Alkhalifah DHH, Hozzein WN, Batiha GE-S, El Nahhas N, Mabrok MA (2020) Methicillin-Resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (MRSA): One Health perspective approach to the bacterium epidemiology, virulence factors, antibiotic-resistance, and zoonotic impact. 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Infect Drug Resist 15:249\u0026ndash;260. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2147/IDR.S344875\u003c/span\u003e\u003cspan address=\"10.2147/IDR.S344875\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Federal University of Technology Owerri","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bloodstream infections, bacteria, prevalence, susceptibility, resistant gene","lastPublishedDoi":"10.21203/rs.3.rs-5784386/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5784386/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e: The antibacterial-resistant genes (ABRG) associated with bloodstream infections in patients (BSI-PAP) receiving treatment at the Nigerian Air Force Medical Centre, Onikan, Lagos State, were studied from October 2023 to June 2024. BSI-PAP was defined as BSI diagnosed within 48 hours of hospitalization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Hospital waste samples were analyzed for bacterial contamination and antibiotic resistance adhering to microbiological standards.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The prevalence of BSI-PAP was 30 out of 315 discharges (9.5%). The likelihood of being admitted with BSI-PAP was greatest in patients with diabetes mellitus, previous hospitalization, renal failure, and chronic dermatitis. The odds ratios with 95% confidence intervals (CI) were 4.96 (95% CI = 1.37-7.32), 2.59 (95% CI = 0.29-4.9), 2.39 (95% CI = −0.17-4.89), and 1.32 (95% CI = 0.37-4.29). Among the patients admitted with BSI-PAP who were tested with culture media with one of the seven organisms examined (n = 30), the largest proportion had \u003cem\u003eS. scurissp Lentus\u003c/em\u003e (n = 6, 35.3%), followed by \u003cem\u003eS. gallinarum\u003c/em\u003e (n = 3, 17.6%), \u003cem\u003eS. eqourum\u003c/em\u003e (n = 3, 17.6%), \u003cem\u003eE. cloacae\u003c/em\u003eSSP (n = 5, 11.8%), \u003cem\u003eB. capacia\u003c/em\u003e complex (n = 7, 5.9%), \u003cem\u003eS. xylulosus\u003c/em\u003e(n = 1, 5.9%), and \u003cem\u003eC. freundi\u003c/em\u003e (n = 5, 5.9%). Approximately 76% (13) of BSI-PAP cases with these organisms had antibiotic-resistant. In general, 86% of individuals examined with SSA culture media had antibiotic-resistant strains, while 78% had EMB and 75% MAC strains (p = 0.0001). Gram-negative bacteria were more frequently involved in BSI in this study (56.7%) than gram-positive bacteria (43.3%). The most frequently isolated bacterium was \u003cem\u003eB. cepacia\u003c/em\u003ecomplex (23.3%); others in descending order were as follows: S. \u003cem\u003escuri ssp. lentus\u003c/em\u003e (20%), E. cloacae ssp., and \u003cem\u003eC. freundi\u003c/em\u003e (16.7%). \u003cem\u003eS. gallinarum\u003c/em\u003eand \u003cem\u003eS. equourum\u003c/em\u003e (10%) and \u003cem\u003eS. xylulosus\u003c/em\u003e (3.3%). The drug resistance pattern of gram-positive isolates; Gentamicin Erythromycin and Erythromycin Sulfamethoxazole Tetracycline resistance phenotypes were most common in patients aged 18 to 29 years (54%), while among the gram-negative isolates. Erythromycin, sulfamethoxazole, ciprofloxacin and ampicillin resistance phenotypes were most common in the 30-year-old age group. Erythromycin (85%), gentamicin (55%), sulfamethoxazole (54%), and tetracycline (24%) were commonly used to treat BSI in younger adults, while erythromycin (96%), ciprofloxacin (72%), tetracycline (66%), and ampicillin (60%) were mainly used by middle-aged patients and are easily available without medical authorization. The high antimicrobial resistance has been demonstrated in clinical bacterial isolates (\u003cem\u003eS. scuri ssp. lentus, S. gallinarum, S. eqourum, and S. xylulosus\u003c/em\u003e) of BSI-PAP to commonly prescribed antibiotics, particularly gentamicin, erythromycin, sulfamethoxazole, and tetracycline. There was a high prevalence of resistant genes of TEM, CTX-M, SHV, and VEB types.\u003c/p\u003e","manuscriptTitle":"Antibacterial-Resistant Genes (ABRG) Associated With Bloodstream Infections In Patients Receiving Treatment: A Case Study Of Nigeria Airforce Medical Center Onikan, Lagos State","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-10 18:01:40","doi":"10.21203/rs.3.rs-5784386/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"12e90a98-8573-4117-a91b-630e1658e795","owner":[],"postedDate":"January 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":42598355,"name":"General Microbiology"},{"id":42598356,"name":"Infectious Diseases"}],"tags":[],"updatedAt":"2025-01-10T18:01:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-10 18:01:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5784386","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5784386","identity":"rs-5784386","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}