Antimicrobial Susceptibility Pattern and Associated Factor among Sepsis Suspected Pediatrics Patients, admitted at JMC Pediatrics ward, Jimma, South West Ethiopia

Antimicrobial Susceptibility Pattern and Associated Factor among Sepsis Suspected Pediatrics Patients, admitted at JMC Pediatrics ward, Jimma, South West Ethiopia | 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 Antimicrobial Susceptibility Pattern and Associated Factor among Sepsis Suspected Pediatrics Patients, admitted at JMC Pediatrics ward, Jimma, South West Ethiopia Mekdes Ararso, Tsion Tilahun, Samuel Tadesse, Bikila Alemu, Daniel Geleta, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8991130/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 Background Worldwide, antibiotic resistance is thought to kill 700,000 people annually. Blood culture has a high positive predictive value and is essential for a precise diagnosis of bloodstream infections. It also provides current information on local etiologic patterns and drug sensitivities, which helps the doctor manage the patient. This study aimed to assess the antimicrobial susceptibility pattern and associated factors. Methods An institution-based cross sectional study design was conducted from August 1 to October 30, 2023 among sepsis suspected pediatrics patients, admitted at JMC pediatrics ward, Jimma University, Oromia, Ethiopia. Data was collected using a semi-structured questionnaire. Logistic regression analysis was done to identify covariates associated with the outcome variables. Statistical significance considered at a p-value of less than 0.05. Results Out of 148 patients participated in the study, 55(37.2%) of them has bacterial growth. A common bacterium isolated from gram negative bacteria was klebsella pneumonia. Among 55 isolated bacterial growth Drug resistant bacteria accounts about 51(92.7%), of these XDR and PDR accounts 23(45.1%) and 19(37.3%) respectively. Young age [AOR = 6.066, 95% CI, (1.112, 33.092)], previous history of admission within last 6 months [AOR = 2.704, 95% CI, (1.264, 5.784)], prolonged hospital stay more than 14 days [AOR = 4.939, 95% CI, (1.474–16.550)] and prior exposure to antibiotics [AOR = 2.338, 95% CI (1.078–5.067)] has significant association with bacterial growth and also more likely to had resistant bacteria. Conclusion In this study the prevalence of drug resistant bacteria is high. Neonates and patients who had stayed for prolonged time in the ward were more likely to have bacterial growth and resistant bacteria. Practicing rational use of antibiotic is mandatory to decrease the high prevalence of drug resistance. Blood culture Antimicrobial susceptibility Sepsis suspected Pediatrics patients Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Bacteria are major microbial pathogens responsible for life-threatening infectious diseases, contributing significantly to global morbidity and mortality(1). The emergence of bacteria resistant to multiple antimicrobial agents further complicates the effective treatment of these infections. Septicemia occurs when microorganisms enter the bloodstream and spread throughout the body, triggering systemic inflammatory responses of varying severity. The course and outcome of the disease depend on several factors, including the virulence of the pathogen, the portal of entry, the host’s susceptibility and immune response, and the progression of the infection over time (2). The predominant causative agents and their antimicrobial resistance patterns vary by geographic region and time period. Because septicemia can rapidly progress to a life-threatening condition due to widespread infection and toxin release, prompt diagnosis and aggressive antimicrobial therapy are essential (1, 2). Antimicrobial resistance (AMR) represents a critical global health and economic challenge, threatening the effectiveness of current therapeutic options and the management of infectious diseases. The emergence of bacterial strains resistant to multiple antibiotics has raised concerns about a potential post-antibiotic era, in which common infections may become untreatable. In 2019, bacterial AMR was associated with an estimated 4.95 million deaths worldwide. The major drivers of AMR include inappropriate and excessive antibiotic use, socioeconomic constraints such as poverty, inadequate sanitation, increased global mobility, and the growing frequency of healthcare-related interventions.(3). The World Health Organization (WHO) has identified a list of drug-resistant bacterial pathogens that pose the greatest threat to human health and for which the development of new antibiotics is urgently needed (4). Children are particularly vulnerable to bacterial infections due to their relatively immature immune systems. The emergence of multidrug-resistant pathogenic bacteria has become a critical global public health concern, as therapeutic options are increasingly limited—and in some cases, entirely unavailable—for infections caused by these organisms. Both Gram-positive and Gram-negative bacteria are significantly affected by the escalating problem of antimicrobial resistance (5). Sepsis remains a leading cause of mortality among children worldwide, with an estimated mortality rate of 7%. Most pediatric sepsis-related deaths occur in Sub-Saharan Africa and Asia, where healthcare access, infrastructure, and staffing are sub-optimal. Infections caused by antibiotic-resistant organisms are particularly difficult to treat with currently available antibiotics. Many bacterial species have developed resistance to multiple classes of antimicrobial due to selective pressure or horizontal gene transfer. The problem is particularly severe in developing countries, where limited antibiotic options, irrational drug use, substandard drug quality, poor sanitation, malnutrition, inadequate healthcare systems, and the lack of antibiotic stewardship programs exacerbate the situation. High levels of resistance to first- and second-line antibiotics among Gram-negative isolates causing sepsis highlight the need for enhanced AMR surveillance and reassessment of treatment options in Ethiopia (5, 6). Bacterial isolates are classified as non-susceptible or resistant when they test resistant, intermediate, or non-susceptible according to clinical breakpoints established by the European Committee on Antimicrobial Susceptibility Testing (EUCAST), the Clinical and Laboratory Standards Institute (CLSI), or the U.S. Food and Drug Administration (FDA) (7). Blood culture remains the gold standard for diagnosing bloodstream infections and plays a crucial role in guiding appropriate antimicrobial therapy, particularly in neonatal and pediatric populations. Selection of empirical therapy should consider the most probable causative pathogens based on patient characteristics such as age, gender, risk factors, and local antimicrobial susceptibility patterns. Rapid detection and identification of pathogens in blood cultures are therefore essential to reducing morbidity and mortality associated with bloodstream infections. Because antibiotic sensitivity patterns are constantly evolving, up-to-date data are vital to inform local empirical treatment guidelines (8). Globally, approximately 31.5 million cases of sepsis occur each year, resulting in an estimated 7.5 million pediatric deaths. In Sub-Saharan Africa, septicemia remains a major cause of morbidity and mortality among children, accounting for 30–70% of pediatric illnesses. The condition often leads to serious complications such as septic shock, multiple organ failure, and death (2). Antimicrobial resistance is estimated to cause 700,000 deaths annually, and projections suggest this number could rise to 10 million by 2050 if effective measures are not taken (4). According to the Ethiopian Standard Treatment Guideline, ampicillin and gentamicin are recommended as first-line therapies for pediatric sepsis, with ceftriaxone as the second-line option. However, a study conducted at Tikur Anbessa Specialized Hospital and Yekatit 12 Hospital revealed that, among Klebsiella pneumoniae isolates, 50% were resistant to both gentamicin and ceftriaxone, indicating a decline in the effectiveness of these commonly used antibiotics (9). The increasing prevalence of AMR across hospital wards in Ethiopia further underscores its growing public health importance (10). Bloodstream infections (BSIs) impose a substantial global burden, especially among neonates and children. However, data on the incidence and mortality associated with BSIs in low- and middle-income countries (LMICs) remain limited due to insufficient bacteriological diagnostic capacity and surveillance systems. Typically, only one pathogen is isolated from a positive blood culture, while poly-microbial infections account for 6–18% of cases, particularly among patients with chronic illnesses, malignancies, or hospital-acquired infections. Given the severity of BSIs, blood culture findings hold high clinical significance (11). Multiple factors are associated with pediatric sepsis, and these may vary depending on geographic location and the healthcare setting. Some of the identified factors include the presence of indwelling intravenous devices, use of steroids and immunomodulators, prolonged hospitalization, chronic antibiotic therapy, surgical procedures, burns or bedsores, and severe injuries. Underlying medical conditions such as chronic kidney disease, hematologic malignancies, immunosuppression, and HIV/AIDS can also predispose individuals to septicemia, many of which are commonly observed in our setting (12). Detection of bacteria in the bloodstream plays a crucial role in diagnosing febrile patients. It helps establish the presence of infection, supports the clinician’s decision regarding empirical therapy, and provides updated information on local etiologic patterns and antibiotic susceptibility profiles guiding effective patient management. Therefore, studying the bacteriological profile and antimicrobial susceptibility patterns is essential for the proper management of pediatric septicemia (8). Detection of bacteria in the bloodstream plays a crucial role in diagnosing febrile patients. It helps establish the presence of infection, supports the clinician’s decision regarding empirical therapy, and provides updated information on local etiologic patterns and antibiotic susceptibility profiles—guiding effective patient management. Therefore, studying the bacteriological profile and antimicrobial susceptibility patterns is essential for the proper management of pediatric septicemia (10). However, data on the etiology, epidemiology, and antimicrobial susceptibility of major pathogens causing pediatric bacteremia remain limited in low- and middle-income countries (LMICs) (5). Up-to-date information on antimicrobial resistance is essential for evaluating the appropriateness of current empiric and targeted therapies. Given the scarcity of studies on the prevalence and associated factors of drug-resistant bacteria among children in our setting, this study aims to assess the antimicrobial susceptibility pattern and associated factors among sepsis-suspected pediatric patients admitted to the Pediatrics Ward of Jimma Medical Center (JMC), Jimma, Southwest Ethiopia, from August 1 to October 30, 2023. The findings will provide insight into the etiologic agents of pediatric septicemia and support the rational use of antibiotics to improve patient management. MATERIAL AND METHODS Study area The study was conducted in Jimma medical center pediatric wards, Jimma, South-west Ethiopia. JMC is the teaching and referral hospital in southwest Ethiopia with 800 bed capacity. It gives service in different specialty and sub-specialty fields, among this pediatrics and child health is one of them. The service given at pediatrics and child health include inpatient and outpatient service including emergency, ambulatory and follow up service. The study was conducted from August1 to October 30, 2023. Institution based cross-sectional study design was conducted on 148 pediatrics patients admitted at JMC pediatrics ward in the study period who fulfill the inclusion criteria. Data collection and measurements Data collection Instruments A predefined data collection tool was used to extract all socio-demographic data and other relevant information such as previous antibacterial therapy, and application of indwelling medical device, hospitalization period, co-morbidities, clinical signs and symptoms of sepsis, immunization status, and current medication a patient is taking and patient followed till discharge. Data collection Procedures Using aseptic technique about 2–5 ml of blood was obtained after cleaning the venous site with 70% alcohol and subsequently by 10% povidone iodine solution. About 1–3 ml of venous blood was immediately inoculated into blood culture bottle and sent to laboratory. The bottles then incubated in the BD BACTEC™ FX40 automated culture machine for a maximum of seven days until they were flagged as “negative” or “positive” for growth. Positive bottles then taken out from the machine and sub-cultured on Blood, Chocolate, and MacConkey agar (Oxoid, England). Identification of culture isolates was done according to standard bacteriological techniques and their characteristic appearance on their respective media. Antibiotic susceptibility testing was carried out using Kirby-Bauer disc diffusion technique on Mueller-Hinton agar (Oxoid, England) according to Clinical Laboratory Standard Institute guidelines. The result then collected from laboratory report. Data analysis The data collected was checked for completeness and consistency and then it was cleaned, coded, and entered into Epi Data 3.1, exported, and analyzed using Statistical Package for Social Sciences (SPSS) version 25.0. Then Bivariate and multivariate logistic regression analyses was conducted to see the association between dependent and independent variables. Statistical significance was considered at p-values < 0.05 and 95% Confidence Interval. Data quality control Data was collected by the trained nurses and laboratory technician and quality control was assured by reviewing of the filled checklist every day by the principal investigator and correction of incomplete checklist was completed early. RESULTS Socio-demographic characteristic of participants Out of 148 pediatric patients participated in this study, most 108(73%), of them were younger than 5 years with slight male predominance 79(53.4%), and majority 118(79.7%) had not yet begun formal education. Most of the care givers were between the age of 25–40 years, came from rural, attend primary school, farmers in occupation, and had monthly income of 1000–5000 ETB accounting about 68.9%, 54.1%, 31.1%, 56.1% and 74.3% respectively as shown in Table 1 . Table 1 Socio-demographic characteristics of participants among sepsis suspected pediatric patients admitted at JMC pediatrics ward, 2023. Socio-demographic characteristic of respondents Frequency Percent % Age of the patient Less than 7 days 19 12.8 7–28 days 24 16.2 1–11 months 43 29.1 12–59 months 22 14.9 5–9 years 25 16.9 10 years and above 15 10.1 Total 148 100.0 Sex of the patient Male 79 53.4 Female 69 46.6 Total 148 100.0 Educational status of the patient Not started yet 118 79.7 KG 9 6.1 Primary school 21 14.2 Total 148 100.0 Age of care giver Less than 20 years 4 2.7 21–24 years 19 12.8 25–29 years 53 35.8 30–34 years 24 16.2 35–39 years 25 16.9 40–44 years 13 8.8 45–49 years 6 4.1 50–54 years 3 2.0 60 years and above 1 0.7 Total 148 100.0 Place of residency Rural 80 54.1 Urban 68 45.9 Total 148 100.0 Education status of the care giver Cannot read and write 41 27.7 Can read and write 20 13.5 Primary School 46 31.1 Secondary School 23 15.5 College/University 18 12.2 Total 148 100.0 Occupation of care giver Farmer 83 56.1 Daily labor 16 10.8 Merchant 24 16.2 Governmental Employee 15 10.1 Private Organization 7 4.7 Other 3 2.0 Total 148 100.0 Family income Less than 1000birr 10 6.8 1000–5000 birr 110 74.3 6000–10000 birr 25 16.9 More than 10000 3 2.0 Total 148 100.0 Clinical characteristics of study participants Majority of study participants were first admitted to general ward accounting about 56(37.8%) followed by NICU 42(28%), Pediatrics oncology 22(14.9%), PICU and Pediatrics cardiac unit each 12( 8.1%) and EOPD kept patients 4(2.7%). The main complaints of patients were fast breathing accounting 44(29.7%) followed by fever 31(20.9%), swelling over the lower back 16(10.8%), and cough 12(8.1%). The mean duration of complain for current admission is 2.21 days. Majority of them came to hospital within 7 days of complaint which accounts about 112 (75.7%) followed by 8 to 14 days, 15–50 days and more than 30 days of complaint accounting about 12.2%, 7.4% and 4.7% respectively. For 23 (15.5%) of patients’ blood culture was taken within 24 hours of admission and for 80(54.1%) of them it was taken between 24 hours to 7 days as shown Table 2 . Table 2 Clinical Characteristics of participants among sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023. Clinical characteristic of respondents Frequency (N) Percent % Ward first patient admitted NICU 42 28.4 Pediatrics General Ward 56 37.8 PICU 12 8.1 Pediatrics Oncology 22 14.9 Pediatrics Cardiac 12 8.1 EOPD kept 4 2.7 Duration of complaint Less than 7 days 111 75.0 8–14 days 19 12.8 15–30 days 10 6.8 Greater than 30 days 8 5.4 Time from admission to sample taken for blood culture Less than 7 days 103 69.6 8 to 14 days 29 19.6 15–30 days 12 8.1 More than 30 days 4 2.7 Added diagnosis after admission No 77 52.0 Yes 71 48.0 Procedure done at hospital Intravenous line Yes 148 100 No 0 0 Catheter Yes 23 15.5 No 125 84.5 Naso-gastric tube Yes 95 64.2 No 53 35.8 Surgery Yes 27 18.2 No 121 81.8 Lumbar Puncture Yes 35 23.8 No 113 76.4 Others Yes 8 5.4 No 140 94.6 Prior history within last 6 months Illness Yes 57 38.5 No 91 61.5 Admission Yes 52 35.1 No 96 64.9 Antibiotic use Yes 50 33.8 No 98 66.2 Serostatus Negative 67 45.3 Unknown 81 54.7 Child had chronic illness Yes 102 68.9 No 46 31.1 Immunization status Fully Immunized 56 37.8 Immunized for age 29 19.6 Partially Immunized 4 2.7 Not immunized 59 39.9 Was Antibiotics taken before presenting to this hospital Yes 74 50.0 No 74 50.0 Early and late onset sepsis with or without meningitis was the predominant clinical diagnosis upon admission accounts 38.5% followed by respiratory focus infection (23%), gastrointestinal focus infection (9.5%). Neutropenic fever and hospital acquired infection upon admission to our hospital was less which accounts about 5.4% and 2.5% respectively but it was a major diagnosis added after admission. About 71(48%) of patients had added diagnosis after admission of which the predominant added diagnosis is hospital acquired infection 36(50.7%) followed by sepsis with or without meningitis 12(16.9%). More than half of study participants 75(50.7%) had moderate (18.9%) and severe acute malnutrition (31.8%). About one third of the patients had moderate and severe stunting (31.7%). All patients had IV line, for 95(64.2%) of them NG tube was inserted. LP, catheter, surgery, accounts for 35(23.6%), 23(15.5%) and 27(18.2%) respectively. Other procedures include intubation, tracheostomy, bone marrow aspiration, and ventricular tap. Among 148 participants within the last 6 months, 57(38.5%) of them had history of previous illness, 52(35.1%) had admission and 50(33.8%) used antibiotic. Among those who had illness 39(68.4%) of them, the illness was within the last 3 months and 18(31.6%) of them had illness 3 months back. At that time 52(91.2%) of them were admitted and 50(87.7%) of them took antibiotic. From patients had illness within the last 6 month, most of them took ceftriaxone 39(76.5%) followed by Gentamycin 17(33.3%), Ampicillin 5(9.8%). There were no patient who was HIV positive from the study participants. About 67(45.3%) of them were HIV negative and most of the participants didn’t now their serostatus 81(54.7%) in which almost half of them were neonates whose mother serostatus is negative. Of the participants, 28(18.9%) of them took immunosuppressive drug, from these 18(64.3%) took chemotherapy and 10(35.3%) took corticosteroid. About 102(68.9%) of participants had one or more chronic illness among these malnutrition accounts more than two third 79(77.5%) followed by malignancy 26(25.7%), and cardiac 15(15.3%). Out of 148, 56(37.8%) of respondents were fully immunized. Those immunized for their age, partially immunized and not immunized accounts 29(19.6%), 4(2.7%) and 59(39.9%) respectively. Half of the respondents took antibiotics before presenting to this hospital, from these 69(93.2%) of them got the antibiotics from health facilities with health personnel prescription. Others took from pharmacy with health personnel prescription and by themselves without health personnel prescription accounts 4.1% and 2.7% respectively. Majority of them took two antibiotics followed by one and more than two antibiotics accounts 40(54%), 28(37.8%) and 6(8.1%) respectively. Ceftriaxone was the most drug used alone as well as with other drugs accounting about 32(43.2%) followed by Gentamycin 21(28.4%), Ampicillin 20(27%) and vancomycin 10(13.5%). The most combined drug used before presenting to this hospital was ampicillin with gentamycin accounts 18(24.3%) followed by ceftriaxone and gentamycin and then vancomycin and ceftazidime with 5(6.8%) and 3(4.1%) respectively. Other antibiotics participants took before presenting to this hospital were metronidazole, Amoxicillin, cloxacilline, ciprofloxacillin, and meropenem. For those less than 28 days postnatal age (neonatal age groups), for majority of them 33(78.6%) there were no risk factor identified for neonatal sepsis. As described in Table 3 , among identified risk factors, maternal fever, duration of labour > 24 hours and foul smelling vaginal discharge accounts about 9.5%, 9.5% and 2.4% respectively. Most of the neonate were term 30(71.4%) followed by preterm 10(23.8%). Half of them had normal birth weight 21(50%) followed by low birth weight 7(16.7%) despite 10( 23.8%) of them their birth weight is unknown. Table 3 Gestational age, birth weight and risk factors identified among sepsis suspected neonates admitted at JMC pediatrics ward, 2023. Variables Frequency (N) Percent (%) Risk factor Identified Fever 4 9.5 Foul smelling vaginal discharge 1 2.4 Duration of labour > 24 hrs 4 9.5 No risk factor identified 33 78.6 Total 42 100.0 Gestational age Preterm 10 23.8 Term 30 71.4 Post term 1 2.4 Unknown 1 2.4 Total 42 100.0 Birth weight Very low birth weight (1000-1499gm) 3 7.1 Low birth weight (1500-2499gm) 7 16.7 Normal birth weight (2500-3999gm) 21 50.0 Macrosomia 4000gm) 1 2.4 Unknown 10 23.8 Total 42 100.0 Patterns of antimicrobial susceptibility Among blood sample taken from 148 participants 55(37.2%) of them had bacterial growth on blood culture. Bacterial growth is more predominant on neonatal age group. From this study there was a slightly predominant gram positive bacteria isolated than gram negative bacterial with 28(50.9%) and 27(49.1%) respectively. The predominant bacteria grown from gram positive was Staphylococcal saprophyticus and from gram negative Klebsella pneumonia (Fig. 2 and Fig. 3 ). For all positive blood culture results antimicrobial susceptibility test was done. About 4 (7.3%) of them were susceptible for all and 51(92.7%) of them were resistant for at least one of antimicrobial categories (Fig. 4 ). Among resistant bacteria 39 (76.5%) of them had resistant to three or more classes of antimicrobial categories fulfilling the criteria of MDR. Among isolated bacteria more than 95% of gram positive and more than 88% of gram negative bacteria were resistant. Among those 16(59.3%) of gram positive and 23(95.8%) of gram negative bacteria were MDR. From all resistant bacteria, 23(45.1%) were extensive drug resistant bacteria and 19(37.3%) were PDR (resistant for all antimicrobial categories susceptibility done) as shown in Table 4 . Table 4 Resistant level of isolated bacteria with gram stain among sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023. Gram stain Total No of bacteria isolated Resistant bacteria MDR XDR PDR Yes N(%) No N(%) Yes N(%) No N(%) Yes N(%) No N(%) Yes N(%) No N(%) Gram positive 28 (50.9%) 27 (96.4) 1 (3.6) 16 (59.3) 11 (40.7) 10 (37) 17 (63) 13 (48.2) 14 (51.9) Gram Negative 27 (49.1%) 24 (88.9) 3 (11.1) 23 (95.8) 1 (4.2) 13 (54.2) 11 (54.8) 6 ( 25 ) 18 (75) Total 55 (100%) 51 (92.7) 4 (7.3) 39 (76.5) 12 (23.5) 23 (45) 28 (55) 19 (37.3) 32 (62.7) Antimicrobial susceptibility done for isolated gram positive bacteria shows susceptible on various ranges for (ciprofloxacillin 1(100%) and vancomycine 8(88.9%)) and resistant in various degrees to oxacilline 1(100%), penicillin 25(96.2%), gentamycin 17(68.0%) and doxycycline 16(59.3%. From gram negative bacteria resistant to Ampicilline was 2(100%) followed by Gentamycin 18(85.7%), Ceftriaxone 12(85%) and Ceftazidme 19(82.6%) as shown in table below. As shown in Fig. 5 , only 5(9.8%) out of 51 resistant bacteria which was not MDR. All isolated bacteria from neonates and age 1–5 years were resistant bacteria, of these more than 77% were MDR (17/22 and 7/9 respectively). Isolated bacteria from participants age between 1–12 month, 85% (17/20) of them were resistant bacteria and for those age greater than 5 years among isolated bacteria 75% (3/4) of them were resistant bacteria and all were MDR. Table 5 Antimicrobial susceptibility pattern of isolated bacteria among sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023. Gram stain Antibiotics Susceptible N (%) Intermediate N (%) Resistant N (%) Total N (%) Gram Positive Doxycycline 9(33.3.) 2(7.4) 16(59.3) 27(100.0) Gentamycin 5(20.0) 3(12.0) 17 (68.0) 25(100.0) Penicillin 1(3.8) 0(0) 25(96.2) 26(100) Oxacillin 0(0) 0(0) 1(100) 1(100) Vancomycin 8(88.9) 0(0) 1(11.1) 9(100) Tetracycline 1(50) 0(0) 1(50) 2(100) Ciprofloxacillin 1(100) 0(0) 0(0) 1(100) Gram Negative 10(38.5) 6(23.1) 10(38.5) 26(100) Gentamycin 3(14.3) 0(0.0) 18(85.7) 21(100) Ceftazidime 4(17.4) 0(0.0) 19(82.6) 23(100) Cefepime 2( 20 ) 1( 10 ) 7(70 ) 10(100) Meropenium 15(65.2) 3( 13 ) 5(21.7) 23(100) Piperazine Tazobactam 8(40 ) 1( 5 ) 11(55) 20(100) Cefotaxime 2(20 ) 1( 10 ) 7(70) 10(100) Chloramphenicol 3(42.9) 0(0.0) 4(57.1) 7(100) Ceftriaxone 2(14.3) 0(0.0) 12(85.7) 14(100) Ampicillin 0(0.0) 0(0.0) 2(100) 2(100) Cotrimoxazole 5(71.4) 0(0.0) 2(28.6) 7(100) Tobramycin 0(0.0) 1(33.3) 2(66.7) 3(100) Erythromycin 1(100) 0(0.0) 0(0.0) 1(100) Imepinem 1(50) 0(0.0) 1(50) 2(100) The antimicrobial susceptibility pattern done for isolated gram negative bacteria in this study shows most antibiotics were resistant to routinely prescribed first and second line drugs. Isolated gram negative bacteria were resistant to Ampicillin (100%), gentamycin and ceftriaxone (85.7%) followed by ceftazidime (82.6%), cefepim and cefotaxime (70%) as shown in Table 5 . Meropenem (21.7%) and cotrimoxazole (28.6%) shows low resistant among them. (MDR (Multi Drug Resistant), XDR (Extensive Drug Resistant), PDR (Pan Drug Resistant)). Out of 55 positive blood culture results 51 (92.73%) were drug resistant bacteria (Fig. 6 ), of those drug resistant bacteria 76.5% (39/51) had MDR bacteria which showed as there was a high prevalence of MDR in our setup. Fifty nine percent (23/39) of MDR were from Gram Negative bacteria and 41% (16/39) were from gram positive bacteria isolated. XDR was prevalent from gram negative bacteria isolated 56.5%(13/23) and PDR was more prevalent in gram positive bacteria isolated 68.4% (13/19) in this study. 5.3. Factors associated with antimicrobial susceptibility Among sepsis suspected admitted pediatrics patients who participated in the study, their social-demographic and clinical factors were analyzed for their association to antimicrobial susceptibility by using bi-variate and multivariate analysis with backward logistic regression. This result shows as the age of patient increase the chance of having positive blood culture result decrease. Neonatal age group had a statistically significant association 6 times more likely to have positive blood culture result [AOR = 6.066, 95% CI, (1.112, 33.092)] and 11 times more likely to had resistant bacteria [AOR = 10.913, 95% CI, (2.605, 45.719)]. Participants who were admitted to hospital for more than 14 days before sample drawn for culture were about 4.9 times more likely to had bacterial growth [AOR = 4.939, 95% CI, (1.474–16.550)] and 5.6 times more likely to have resistant bacteria. Patients who had previous admission within the last 6 month had 2.7 times to had bacterial growth among sepsis suspected admitted patients[AOR = 2.704, 95% CI, (1.264, 5.784)] and those took antibiotic during this period has 2.3 times more likely to had positive result [AOR = 2.338, 95% CI (1.078–5.067)]. Table 6 shows associations with antimicrobial susceptibility. Table 6 Multivariate analysis result of factors associated with antimicrobial susceptibility among sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023. Variables Categories Blood culture result COR (95%CI) AOR (95%CI) P value Positive N (%) 55 (37.2) Negative N (%) 93 (62.8%) Age of the patient ≤ 28 days 22 (40) 21 (22.58) 9.429(2.858,31.103) 6.066 (1.112,33.092) 0.037 1–11 months 20 (36.36) 23 (24.73) 7.826(2.371,25.834) 0.001 12–59 months 9 (16.36) 13 (13.98) 6.231(1.635,23.741) 0.007 5–15 years 4 (7.27) 36 (38.71) 1 1 Duration after admission ≤ 14 days 45(81.8) 88 (94.6) 1 1 ≥ 15 days 10 (18.2) 5 (5.4) 3.911(1.261,12.132) 4.939 (1.474,16.55) 0.010 Procedure done for patient Catheter No 49(89.09) 76(81.7) 1 1 Yes 6(10.91) 17(18.3) 1.551 (1.082,2.221) 0.236 NG tube No 12(21.82) 41(44.1) 1 1 Yes 43(78.18) 52(55.9) 3.417 (1.796, 6.501) 2.747 (1.235, 6.109) 0.013 LP No 38(69.1) 75(80.6) 1 1 Yes 17(30.9) 18(19.4) 1.974 (1.336, 2.916) 0.113 Within last 6 months history of Illness No 40 (72.73) 51 (54.84) 1 1 Yes 15 (27.27) 42 (45.16) 2.196 (1.069, 4.513) 1.385(0.612,3.132) 0.010 Admission No 43 (78.2) 53 (56.99) 1 1 Yes 12 (21.8) 40 (43.01) 0.370 (0.173, 0.791) 2.704 (1.264, 5.784) 0.010 Antibiotic taken No 43 (78.2) 55 (9.14) 1 1 Yes 12 (21.8) 38 (40.86) 2.476 (1.156, 5.304) 2.338 (1.078, 5.067) 0.031 Immunized for age No 33 (90) 30 (32.3) 1 Yes 22 (40) 63 (67.7) 0.317 (0.159, 0.635) 0.001 Serostatus Negative 17 (30.9) 50 (53.8) 1 1 Unknown 38 (69.1) 43 (46.2) 0.385 (0.191, 0.777) 1.560 (1.092, 2.227 0.014 Has MMC No 50 (90.9) 92 (98.92) 1 1 Yes 5 (9.1) 1 (1.08) 0.109 (0.012, 0.956) 0.045 Cardiac illness No 52 (94.54) 81 (87.1) 1 1 Yes 3 (5.46) 12 (12.9) 2.568 (0.691, 9.538) 0.159 Variable Categories Resistant bacteria COR (95%CI) AOR (95%CI) P value Yes No Age of the patient ≤ 28 days 22() 21() 12.921(3.452,48.357) 10.913(2.605,45.719) 0.001 1–11 months 17() 26() 8.064(2.142, 30.366) 8.229(2.050, 33.028) 0.003 12–59 months 9() 13() 8.538(2.000, 36.452) 8.334(1.796, 38.682) 0.007 5–15 years 3() 37() 1 1 Previous admission No 41(80.4) 55(56.7) 1 1 Yes 10(19.6) 42(43.3) 3.131(1.408, 6.964) 3.338(1.482,7.517) 0.004 Duration after admission ≤ 14 days 41(80.4) 92 (94.8) 1 1 ≥ 15 days 10 (19.6) 5 (5.2) 4.488 (1.443,13.960) 5.557 (1.542, 20.029 0.009 5.4. Patient outcome Out of 148 pediatrics patients participated on this study majority 108(73%) of patients improved and then discharged or transferred to other hospital for completion of antibiotics. About 13 (8.8%) of patients passed away as described in Fig. 7 . Out of 55 patients who had blood culture growth, for 30(54.5%) of them antibiotics was revised after culture sensitivity result. Among those patients 28(93.3%) of them had clinical improvement and 2(6.7%) of them had no improvement after antibiotics was revised. The improvements seen on those patients were, fever alone was subside in 12(42.9%) followed by both fever and tachypnea 10(35.7%) and tachypnea alone subsided in 6(21.4%) of patients. Among positive blood culture and microbial susceptibility done, for 25 patients antibiotic was not revised, the major reason why antibiotic not revised was because the isolated bacteria was resistant to all antimicrobial categories susceptibility done or the susceptible antibiotics were not applicable in the patients age group accounts about 13(52%) followed by result were arrived after patient leave hospital for different reason 9(36%). Regarding the length of stay in the ward, 66(44.6%) of them stays between 15–30 days. Among sepsis suspected admitted pediatrics patients those have extensive drug resistant bacteria on antimicrobial susceptibility test were 3 times more likely to die [AOR = 3.056, 95% CI (0.880-10.609) as shown in Table 7 . Table 7 Multivariate analysis result showing factors affecting patient outcome among sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023. Variable Categories Died COR (95%CI) AOR (95%CI) P value Yes 13 (8.8) N (%) No 135 (91.2) N (%) MDR No 7 (53.8) 102 (75.6) 1 1 Yes 6 (46.2) 33 (24.4) 2.649 (0.880,8.442) 0.114 XDR No 8 (61.5) 117 (86.7) 1 1 Yes 5 (38.5) 18 (13.3) 4.062 (1.196, 13.796) 3.056 (0.880, 10.609) 0.020 DISCUSSION This study showed that the overall culture positive rate among sepsis suspected pediatric patients admitted in JUMC was 37.2% which was lower when compare with study conducted in Nigeria (41.19%) ( 17 ) which was done in children less than 12 years old and inpatient and out patients, Jimma (63.5%, 61.5%) ( 6 , 19 ) and Bahirdar (41.3%) ( 24 ) which was done only in neonatal age group. It was a higher rate compared with studies done in Rwanda (11.7%), ( 16 ), Mekele (28%) ( 21 ), Gondar (20.7%) ( 22 ), and 14% ( 13 ), TASH and Yekatit 12 (18.8%) ( 9 ) and (27.9%) ( 8 ), Arbamich (11.3%) ( 1 ), TASH (15.2%) ( 26 ). The reason of this all variation may be due to socio demographic and clinical characteristic of study participants (age difference, ambulatory patients included in some study, cancer patients or febrile patient only, focusing only on gram negative), high burden of nosocomial infection, prior exposure to antibiotics, longer stay in hospital, and health-care system. From this study gram positive bacteria isolated predominantly than gram negative bacteria with 50.9% and 49.1% respectively which was in line with a study done in Arbaminch (57.1%) ( 1 ), Mekele (68%) ( 21 ), Gondar (61.1%) ( 13 ) and (69%) ( 23 ). CoNS was the predominant microorganism from gram positive bacteria isolated in this study which was similar with a study done in India ( 15 ), Jimma ( 6 , 20 ), Gondar ( 23 ) and Nigeria ( 17 ) from where CoNS were the predominant microorganism from gram positive bacteria whether gram positive was a predominant bacteria isolated or not. Staphylococcus aureus was predominant microorganism from gram positive bacteria isolated in study done at Rwanda ( 16 ), Arbaminch ( 1 ), Addis Abeba ( 8 , 26 ), Mekele ( 21 ), Bahir dar ( 24 ) and Gondar ( 13 ). The high prevalence of CoNS might be in association with an increasing burden of nosocomial infection in hospitalized patients and some of participants in this study was on vancomycin during data collection which S. aureus may be empirically treated and has influence on growth of this bacteria. In other studies gram-negative bacteria were predominant like in Iran (55%) ( 10 ), ( 8 ), Rwanda (68%) ( 16 ), Addis Abeba (51.8%) ( 8 ) and (54.7) ( 26 ), Jimma (79.4%) ( 19 ) and (58.2%) ( 20 ), and Bahirdar ( 24 ). This variation might be explained by the difference in the age of study participants, Hospital setting, In patient and ambulatory patient difference. Over all in this study as well as in majority of other studies (Rwanda ( 16 ), Nigeria( 17 ), Arbaminch ( 1 ), JUMC and Five selected Hospitals in Ethiopia ( 6 , 20 ), TASH and Yekatit 12 ( 8 ), Tikur Ambesa Specialized Hospital( 26 ), Gondar ( 13 , 22 ) Bahirdar ( 24 ), Klebsella spp was the first or the second most predominant microorganism from isolated gram negative bacteria. E. coli was the predominant bacteria isolate one study done in Jimma ( 19 ) and Mekele ( 21 ). This shows klebsella spp was the predominant bacteria isolated from most studies done In the current study, for all positive blood culture results antimicrobial susceptibility test was done. About 4 (7.3%) of them were susceptible for all and 51(92.7%) of them were resistant for at least one of antimicrobial categories. Among isolated bacteria more than 95% of gram positive and more than 88% of gram negative bacteria were resistant. Of the resistant bacteria 39(76.5%) of them were resistant to three or more classes of antimicrobial categories fulfilling the criteria of MDR. This finding was similar with a study done in Rwanda (77.1%) ( 16 ), and Bahirdar (78.2%) ( 24 ). In contrary this study finding was higher when compared with study done in Europe (39%) ( 28 ) Gondar (17.3%) ( 13 ) and Mekele (59%) ( 21 ) which might be explained by the epidemiological difference with western country, study participants were only cancer patient in study done in Gondar. As well the finding of this study is lower when compared with study done in Iran (96.8) ( 27 ), Arbaminch (82.1%) ( 1 ), JUMC (84.4%) ( 6 ), In five selected Hospitals in Ethiopia (91.3%) ( 20 ), TASH and Yekatit 12 (92.7%) ( 8 ). This variation might be explained by variation in study participants of which most drug resistant bacteria were found on neonatal age group and those study conducted on neonate had high prevalence of MDR bacteria which also similar with our finding when we categorize with their age group. On other studies where other sample used in addition to blood culture the MDR rate was high like study done in Iran. Antimicrobial susceptibility done for isolated gram positive bacteria shows susceptible from 0 to 100% (Oxacilline (0%) and Penicilline (3.8%) to vancomycine (88.9%) and ciprofloxacillin (100%)) and resistant rate from 0 to 100% ciprofloxacillin (0%) to oxacilline (100%), with different range like penicillin (96.2%), gentamycin (68.0%) and doxycycline (59.3%). From gram negative bacteria resistant to Ampicilline(100%) followed by Gentamycin (85.7%), Ceftriaxone (85%) and Ceftazidme (82.6%). The result of the study shows isolated gram positive and gram negative bacteria were resistant to routinely prescribed medications which was in the line with other studies done in Rwanda ( 16 ), Jimma( 19 ), In five selected hospitals in Ethiopia ( 20 ), Gondar ( 22 ), Bahirdar ( 24 ), Addis Abeba ( 8 , 26 ) and in seven LMICs in Africa and South Asia ( 18 ). There were factors those associated with culture positiveness as well as for drug resistant bacteria. This result shows as the age of patient increase the chance of having positive blood culture result decrease. Neonatal age group had a statistically significant association 6 times more likely to have positive blood culture result [AOR = 6.066, 95% CI, (1.112, 33.092)P = 0.037] and 11 times more likely to had resistant bacteria [AOR = 10.913, 95% CI, (2.605, 45.719)P = 0.001]. This finding is in concordance with other research conducted in Nigeria highest rate was in neonate (57.97%) followed by infants ( 17 ), Arbaminch being infant [AOR = 4.18, 95% CI, (1.3–13.0),P = 0.014] ( 1 ), Gondar being an infant P < 0.001 and P = 0.0004 ( 22 , 23 ) and Bahirdar ( 24 ). The duration of stay in hospital before sample taken was another factor associated with drug resistant and culture positive rate in this study. Participants who were admitted to hospital for more than 14 days before sample drawn for culture were about 4.9 times more likely to had bacterial growth [AOR = 4.939, 95% CI, (1.474–16.550), P = 0.010] and 5.6 times more likely to have resistant bacteria [AOR = 5.557, 95% CI, (1.542–20.029), P = 0.009]. Patients who had previous admission within the last 6 month had 2.7 times to had bacterial growth among sepsis suspected admitted patients [AOR = 2.704, 95% CI, (1.264, 5.784), P = 0.010] and about 3.3 times more likely to have resistant bateria [AOR = 3.338, 95% CI, (1.482–7.517), P = 0.004]. Those participants who took antibiotic during that period had 2.3 times more likely to had positive result [AOR = 2.338, 95% CI (1.078–5.067, P = 0.031). Other factors associated with positive blood culture (Bacterial growth) and drug resistant bacteria identified in this study were comorbidities, history of previous illness, history of previous antibiotic use within the last 6 month, and for those procedures done in the hospital. In this study findings were inthe line with studies done in Arbaminch those had admission > 10 days [AOR = 5.54, 95% CI, (1.51–20.41), P = 0.010], ( 1 ), Addis Ababa, those had upper respiratory infection in the past 3 month [AOR = 7.02, 95% CI, (1.424–34.64), P = 0.02] ( 9 ), and in Gondar, those less than 5 years old had more culture positive rate when compared to older patients (p value 0.001) ( 22 ). Burn [AOR = 3.55, 95% CI, (1.02–12.38)] and wound cases [AOR = 5.52, 95% CI, (1.50–20.34)] in Arbaminch ( 1 ), In Bahirdar, maternal risk factors (premature rupture of membrane, urinary tract infection, duration of labour), Low birth weight and prematurity had association with positive blood culture ( 24 ) but in our study has no association with current study it may be because of small number of neonate to do the association.. Among sepsis suspected admitted pediatrics patients those had extensive drug resistant bacteria on antimicrobial susceptibility test were 3 times more likely to die [AOR = 3.056, 95% CI (0.880-10.609). In others study, presence of MDR bacteria significantly increase the mortality which was similar with our study in Europe ( 28 ), 81% of death occurred in culture confirmed sepsis in study done at Jimma even if association was not done because of smaller sample size.( 6 ). STRENGTH AND LIMITATION OF THE STUDY This study tried to address over all prevalence of positive rate, MDR, PDR and XDR rate among pediatrics patient admitted to pediatrics ward in our set up and tried to address associated factors relation to positive rate and drug resistant. As a limitation of this study, selection bias might be introduced because of the convenient sampling technique used. Unavailability of blood culture bottle all the time was another limitation in which some patients were missed during data collection. CONCLUSION Out of 148 pediatrics patients majority (73%) of them are age less than 5 years with slight male predominance. The positive rate of blood culture was 37.2% in this study. The prevalence of drug resistant bacteria was high in this study accounting about 92.7% and MDR were 76.2%. CoNs was the predominant bacteria isolated from gram positive bacteria and Klebsella pneumonia was the predominant bacteria isolated from gram negative bacteria. Isolated bacteria’s were resistant to routinely prescribed first and second line drugs. Neonates and patients who had stayed for prolonged time in the ward were more likely to had bacterial growth and resistant bacteria. Those patients who had extensive drug resistant bacteria more likely to die as compared to other patients. RECOMMENDATION Practicing antibiotic stewardship already established in our setup is mandatory to decrease the high prevalence of drug resistance bacteria. The prevalence of drug resistant bacteria in this study was high (more than 90% ) which had a negative impact on patient care as well as treating resistant bacteria costs a lot. To tackle this health professionals should be familiar with rational use of antibiotics as well as infection prevention method and proper use of updated guideline. Taking blood culture before starting antibiotic has significant benefit for a patient as well as treating physician to improve quality of care. Patients should be treated based on susceptibility pattern. Availability of blood culture bottle all the time can help to increase detection rate, identify isolated organism, know susceptibility pattern, improve patient outcome as well as decrease MDR rate as patient properly treated based on culture result. So the hospital administration with laboratory department should work collaboratively to improve the availability of blood culture bottle in order to improve patient care and tackle MDR. Abbreviations AOR, Adjusted Odd Ratio; AMR, Antimicrobial Resistance; BSI, Blood Stream Infection; CI, Confidence Interval; CLSI, Clinical and Laboratory Standards Institute; CoNS, Coagulase Negative Staphylococcus; COR, Crude Odd Ratio; EOPD, Emergency Out Patient Department; ETB, Ethiopian Birr; EUCAST, European Committee on Antimicrobial Susceptibility Testing; FDA, Food and Drug Administration; GNB, Gram Negative Bacteria; GPB, Gram Positive Bacteria; HIV/AIDS, Human Immune Virus, Acquired Immune Deficiency Virus; IV, Intra Venous; IRB, Institutional Research Board; JUIH, Jimma University Institution of Health, JUERC, Jimma University Ethical and Research Committee; JMC, Jimma Medical Center ; JUMC, Jimma University Medical Center; LMICs, Low- and Middle-Income Countries; MDR, Multi Drug Resistant; MMC, Myelomeningiocele; NICU, Neonatal Intensive Care Unit; NGT, Naso-Gastric tube; PDR, Pan Drug Resistant; PICU, Pediatrics Intensive Care Unit; SPSS, Statistical Package for Social Science; XDR, Extensive Drug Resistant; WHO, World Health Organization. Declarations Ethical Approval and consent to participants Jimma University Institutional Research Board (IRB) examined and approved the study protocol, issuing it the number IRef. No. JUIH/IRB/600/23 and permission was obtained from the authorities of the Jimma University Specialized Hospital. The goal of the study and the significance of the participants' involvement were explained to each of the study participant’s and participant’s family or caregiver before the consent is taken. Also the participants informed that those data taken are only used for the research purpose and no personal data like name and identification are not used for the the research as well as need for publication. Before any data was collected, each participant and participant’s family or caregiver gave their verbal and written informed consent both for research and publication. Confidentiality was assured by collecting data anonymously and codes was used on the questionnaire and it was locked in a secure place. During data collection local languages Afan Oromo and Amharic was used for communication with participants. Availability of data and Material The soft copy and hard copy of full document is given to Jimma University Institution of Health Science upon completion of the research to be put in Jimma University (JU) repository. Clinical Trail Number --- Not Applicable Disclosure and Funding All authors are equally contribute. The authors declare that there is no competing interest. Funding There was no funding for this research (not funded). Aknowledgment We acknowledge Jimma University Institution of Health Science, all participants, authors, data collectors and health care workers working at pediatrics ward and laboratory who directly and indirectly support us to do this research. References Ameya G, Weldemedhin T, Tsalla T, Gebremeskel F. Antimicrobial susceptibility pattern and associated factors of pediatric septicemia in Southern Ethiopia. Infection and drug resistance. 2020:3895-905. Varela MF, Stephen J, Lekshmi M, Ojha M, Wenzel N, Sanford LM, et al. Bacterial resistance to antimicrobial agents. Antibiotics. 2021;10(5):593. Dunachie SJ, Day NP, Dolecek C. The challenges of estimating the human global burden of disease of antimicrobial resistant bacteria. Current Opinion in Microbiology. 2020;57:95-101. Willyard C. Drug-resistant bacteria ranked. Nature. 2017;543(7643):15. Droz N, Hsia Y, Ellis S, Dramowski A, Sharland M, Basmaci R. Bacterial pathogens and resistance causing community acquired paediatric bloodstream infections in low-and middle-income countries: a systematic review and meta-analysis. Antimicrobial Resistance & Infection Control. 2019;8(1):1-12. Gashaw M, Ali S, Tesfaw G, Eshetu B, Workneh N, Berhane M, et al. Bacterial profile and drug resistance patterns in neonates admitted with sepsis to a tertiary teaching hospital in Ethiopia. 2019. Magiorakos A-P, Srinivasan A, Carey RB, Carmeli Y, Falagas M, Giske C, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clinical microbiology and infection. 2012;18(3):268-81. Negussie A, Mulugeta G, Bedru A, Ali I, Shimeles D, Lema T, et al. Bacteriological profile and antimicrobial susceptibility pattern of blood culture isolates among septicemia suspected children in selected hospitals Addis Ababa, Ethiopia. International journal of biological and medical research. 2015;6(1):4709. Negash AA, Asrat D, Abebe W, Hailemariam T, Wubete A, Aseffa A, et al. Etiology, antibiotic susceptibility and prognostic factors of pediatric community-acquired sepsis in Addis Ababa, Ethiopia. The Journal of Infection in Developing Countries. 2021;15(01):113-22. Azimi T, Maham S, Fallah F, Azimi L, Gholinejad Z. Evaluating the antimicrobial resistance patterns among major bacterial pathogens isolated from clinical specimens taken from patients in Mofid Children’s Hospital, Tehran, Iran: 2013–2018. Infection and drug resistance. 2019:2089-102. Ombelet S, Barbé B, Affolabi D, Ronat J-B, Lompo P, Lunguya O, et al. Best practices of blood cultures in low-and middle-income countries. Frontiers in medicine. 2019;6:131. Kebede B, Yihunie W, Abebe D, Addis Tegegne B, Belayneh A. Gram-negative bacteria isolates and their antibiotic-resistance patterns among pediatrics patients in Ethiopia: A systematic review. SAGE Open Medicine. 2022;10:20503121221094191. Worku M, Belay G, Tigabu A. Bacterial profile and antimicrobial susceptibility patterns in cancer patients. Plos one. 2022;17(4):e0266919. Alemayehu T. Prevalence of multidrug-resistant bacteria in Ethiopia: a systematic review and meta-analysis. Journal of Global Antimicrobial Resistance. 2021;26:133-9. Gandra S, Mojica N, Klein EY, Ashok A, Nerurkar V, Kumari M, et al. Trends in antibiotic resistance among major bacterial pathogens isolated from blood cultures tested at a large private laboratory network in India, 2008–2014. International Journal of Infectious Diseases. 2016;50:75-82. Habyarimana T, Murenzi D, Musoni E, Yadufashije C, N Niyonzima F. Bacteriological profile and antimicrobial susceptibility patterns of bloodstream infection at Kigali University Teaching Hospital. Infection and drug resistance. 2021:699-707. Abdu AB, Egbagba J, Alade T. Antimicrobial Susceptibility Pattern and Bacterial Isolates Profile in Septicaemia Suspected Patients Attending FMC. Yenagoa. International Journal of Research and Scientific Innovation. 2020;7(4):134-43. Sands K, Carvalho MJ, Portal E, Thomson K, Dyer C, Akpulu C, et al. Characterization of antimicrobial-resistant Gram-negative bacteria that cause neonatal sepsis in seven low-and middle-income countries. Nature microbiology. 2021;6(4):512-23. Gashaw M, Berhane M, Bekele S, Kibru G, Teshager L, Yilma Y, et al. Emergence of high drug resistant bacterial isolates from patients with health care associated infections at Jimma University medical center: a cross sectional study. Antimicrobial Resistance & Infection Control. 2018;7:1-8. Eshetu B, Gashaw M, Solomon S, Berhane M, Molla K, Abebe T, et al. Bacterial isolates and resistance patterns in preterm infants with sepsis in selected hospitals in Ethiopia: a longitudinal observational study. Global Pediatric Health. 2020;7:2333794X20953318. Wasihun AG, Wlekidan LN, Gebremariam SA, Dejene TA, Welderufael AL, Haile TD, et al. Bacteriological profile and antimicrobial susceptibility patterns of blood culture isolates among febrile patients in Mekelle Hospital, Northern Ethiopia. Springerplus. 2015;4(1):1-7. Abebe W, Tegene B, Feleke T, Sharew B. Bacterial Bloodstream Infections and their Antimicrobial Susceptibility Patterns in Children and Adults in Ethiopia: a 6-Year Retrospective Study. Clinical Laboratory. 2021;67(11). Dagnew M, Yismaw G, Gizachew M, Gadisa A, Abebe T, Tadesse T, et al. Bacterial profile and antimicrobial susceptibility pattern in septicemia suspected patients attending Gondar University Hospital, Northwest Ethiopia. BMC research notes. 2013;6:1-7. Zenebe Y, Molla T, Beza L, Mekonnen D. Bacterial profile and antimicrobial susceptibility pattern of neonatal sepsis in Felege-Hiwot Referral Hospital, Bahir Dar, northwest Ethiopia: A cross-sectional study design. Ethiopian Journal of Health Development. 2021;35(1). Legese MH, Weldearegay GM, Asrat D. Extended-spectrum beta-lactamase-and carbapenemase-producing Enterobacteriaceae among Ethiopian children. Infection and drug resistance. 2017:27-34. Bitew A. Multi-drug resistance profile of bacteria isolated from blood stream infection at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. EC Microbiol. 2018;14:119-26. Sadat SS, Ahani Azari A. Frequency of multidrug-resistant, extensively drug-resistant, and pandrug-resistant phenotypes among clinical isolates of Staphylococcus aureus. Infection Epidemiology and Microbiology. 2020;6(4):269-75. Folgori L, Livadiotti S, Carletti M, Bielicki J, Pontrelli G, Degli Atti MLC, et al. Epidemiology and clinical outcomes of multidrug-resistant, gram-negative bloodstream infections in a European tertiary pediatric hospital during a 12-month period. The Pediatric infectious disease journal. 2014;33(9):929-32. Additional Declarations No competing interests reported. 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19:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8991130/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8991130/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104180458,"identity":"c2a799a1-c390-4a01-b577-1b62c678d97e","added_by":"auto","created_at":"2026-03-08 17:14:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":116233,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 2: Culture positive rate with age distribution among sepsis suspected pediatrics patients admitted at JMC, 2023\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8991130/v1/33597c449e707ddc0d3e6ae6.png"},{"id":104180460,"identity":"5a95af0c-a718-45c2-b20a-f409a2bfa77b","added_by":"auto","created_at":"2026-03-08 17:14:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":58653,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 3: Isolated bacteria among positive blood culture results taken from sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8991130/v1/42a5b9828c8dd97167d2f9f0.png"},{"id":104404742,"identity":"91022de3-5f3f-468e-aba1-70c2491f9623","added_by":"auto","created_at":"2026-03-11 12:21:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":355482,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4: Shows Antimicrobial susceptibility pattern of isolated bacteria among sepsis suspected pediatrics patients admitted \u0026nbsp;in JMC, 2023\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8991130/v1/2dcd21e9acbf408322b02bf0.png"},{"id":104180461,"identity":"7a3ee474-0bbf-4ea0-9bbf-4f23217ca6fb","added_by":"auto","created_at":"2026-03-08 17:14:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":217893,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 5: Resistant bacteria isolated among sepsis suspected pediatrics patients admitted in pediatrics ward JMC,2023\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8991130/v1/17e052c39f6252945956452f.png"},{"id":104403829,"identity":"0bd5648c-b17b-4db0-ac25-2bf0e7f58cb6","added_by":"auto","created_at":"2026-03-11 12:19:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":88349,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 6: Pattern of drug resistant bacteria by gram stain distribution among among sepsis suspected pediatrics patients admitted in JMC,2023.\u003c/p\u003e\n\u003cp\u003e(MDR (Multi Drug Resistant), XDR (Extensive Drug Resistant), PDR (Pan Drug Resistant)).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8991130/v1/2f16a0dd37cea57f8917c2a3.png"},{"id":104180462,"identity":"e9b9360b-8a70-4614-b80f-d9b49a7aa46f","added_by":"auto","created_at":"2026-03-08 17:14:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":292737,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 7: Treatment outcome among sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8991130/v1/90a6f2b4309c58408a5b6d0c.png"},{"id":104409026,"identity":"00d33df0-9542-496f-8103-c6abedfcafe7","added_by":"auto","created_at":"2026-03-11 12:43:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2809508,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8991130/v1/0e752e3d-3a05-43a5-a9f3-d195d21486d9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Antimicrobial Susceptibility Pattern and Associated Factor among Sepsis Suspected Pediatrics Patients, admitted at JMC Pediatrics ward, Jimma, South West Ethiopia","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eBacteria are major microbial pathogens responsible for life-threatening infectious diseases, contributing significantly to global morbidity and mortality(1). The emergence of bacteria resistant to multiple antimicrobial agents further complicates the effective treatment of these infections. Septicemia occurs when microorganisms enter the bloodstream and spread throughout the body, triggering systemic inflammatory responses of varying severity. The course and outcome of the disease depend on several factors, including the virulence of the pathogen, the portal of entry, the host’s susceptibility and immune response, and the progression of the infection over time (2). The predominant causative agents and their antimicrobial resistance patterns vary by geographic region and time period. Because septicemia can rapidly progress to a life-threatening condition due to widespread infection and toxin release, prompt diagnosis and aggressive antimicrobial therapy are essential (1, 2). \u003c/p\u003e\n\u003cp\u003eAntimicrobial resistance (AMR) represents a critical global health and economic challenge, threatening the effectiveness of current therapeutic options and the management of infectious diseases. The emergence of bacterial strains resistant to multiple antibiotics has raised concerns about a potential post-antibiotic era, in which common infections may become untreatable. In 2019, bacterial AMR was associated with an estimated 4.95 million deaths worldwide. The major drivers of AMR include inappropriate and excessive antibiotic use, socioeconomic constraints such as poverty, inadequate sanitation, increased global mobility, and the growing frequency of healthcare-related interventions.(3).\u003c/p\u003e\n\u003cp\u003eThe World Health Organization (WHO) has identified a list of drug-resistant bacterial pathogens that pose the greatest threat to human health and for which the development of new antibiotics is urgently needed (4). Children are particularly vulnerable to bacterial infections due to their relatively immature immune systems. The emergence of multidrug-resistant pathogenic bacteria has become a critical global public health concern, as therapeutic options are increasingly limited—and in some cases, entirely unavailable—for infections caused by these organisms. Both Gram-positive and Gram-negative bacteria are significantly affected by the escalating problem of antimicrobial resistance (5).\u003c/p\u003e\n\u003cp\u003eSepsis remains a leading cause of mortality among children worldwide, with an estimated mortality rate of 7%. Most pediatric sepsis-related deaths occur in Sub-Saharan Africa and Asia, where healthcare access, infrastructure, and staffing are sub-optimal. Infections caused by antibiotic-resistant organisms are particularly difficult to treat with currently available antibiotics. Many bacterial species have developed resistance to multiple classes of antimicrobial due to selective pressure or horizontal gene transfer. The problem is particularly severe in developing countries, where limited antibiotic options, irrational drug use, substandard drug quality, poor sanitation, malnutrition, inadequate healthcare systems, and the lack of antibiotic stewardship programs exacerbate the situation. High levels of resistance to first- and second-line antibiotics among Gram-negative isolates causing sepsis highlight the need for enhanced AMR surveillance and reassessment of treatment options in Ethiopia (5, 6). \u003c/p\u003e\n\u003cp\u003eBacterial isolates are classified as non-susceptible or resistant when they test resistant, intermediate, or non-susceptible according to clinical breakpoints established by the European Committee on Antimicrobial Susceptibility Testing (EUCAST), the Clinical and Laboratory Standards Institute (CLSI), or the U.S. Food and Drug Administration (FDA) (7).\u003c/p\u003e\n\u003cp\u003eBlood culture remains the gold standard for diagnosing bloodstream infections and plays a crucial role in guiding appropriate antimicrobial therapy, particularly in neonatal and pediatric populations. Selection of empirical therapy should consider the most probable causative pathogens based on patient characteristics such as age, gender, risk factors, and local antimicrobial susceptibility patterns. Rapid detection and identification of pathogens in blood cultures are therefore essential to reducing morbidity and mortality associated with bloodstream infections. Because antibiotic sensitivity patterns are constantly evolving, up-to-date data are vital to inform local empirical treatment guidelines (8). \u003c/p\u003e\n\u003cp\u003eGlobally, approximately 31.5 million cases of sepsis occur each year, resulting in an estimated 7.5 million pediatric deaths. In Sub-Saharan Africa, septicemia remains a major cause of morbidity and mortality among children, accounting for 30–70% of pediatric illnesses. The condition often leads to serious complications such as septic shock, multiple organ failure, and death (2). Antimicrobial resistance is estimated to cause 700,000 deaths annually, and projections suggest this number could rise to 10 million by 2050 if effective measures are not taken (4). According to the Ethiopian Standard Treatment Guideline, ampicillin and gentamicin are recommended as first-line therapies for pediatric sepsis, with ceftriaxone as the second-line option. However, a study conducted at Tikur Anbessa Specialized Hospital and Yekatit 12 Hospital revealed that, among \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e isolates, 50% were resistant to both gentamicin and ceftriaxone, indicating a decline in the effectiveness of these commonly used antibiotics (9). The increasing prevalence of AMR across hospital wards in Ethiopia further underscores its growing public health importance (10). \u003c/p\u003e\n\u003cp\u003eBloodstream infections (BSIs) impose a substantial global burden, especially among neonates and children. However, data on the incidence and mortality associated with BSIs in low- and middle-income countries (LMICs) remain limited due to insufficient bacteriological diagnostic capacity and surveillance systems. Typically, only one pathogen is isolated from a positive blood culture, while poly-microbial infections account for 6–18% of cases, particularly among patients with chronic illnesses, malignancies, or hospital-acquired infections. Given the severity of BSIs, blood culture findings hold high clinical significance (11). \u003c/p\u003e\n\u003cp\u003eMultiple factors are associated with pediatric sepsis, and these may vary depending on geographic location and the healthcare setting. Some of the identified factors include the presence of indwelling intravenous devices, use of steroids and immunomodulators, prolonged hospitalization, chronic antibiotic therapy, surgical procedures, burns or bedsores, and severe injuries. Underlying medical conditions such as chronic kidney disease, hematologic malignancies, immunosuppression, and HIV/AIDS can also predispose individuals to septicemia, many of which are commonly observed in our setting (12). \u003c/p\u003e\n\u003cp\u003eDetection of bacteria in the bloodstream plays a crucial role in diagnosing febrile patients. It helps establish the presence of infection, supports the clinician’s decision regarding empirical therapy, and provides updated information on local etiologic patterns and antibiotic susceptibility profiles guiding effective patient management. Therefore, studying the bacteriological profile and antimicrobial susceptibility patterns is essential for the proper management of pediatric septicemia (8). Detection of bacteria in the bloodstream plays a crucial role in diagnosing febrile patients. It helps establish the presence of infection, supports the clinician’s decision regarding empirical therapy, and provides updated information on local etiologic patterns and antibiotic susceptibility profiles—guiding effective patient management. Therefore, studying the bacteriological profile and antimicrobial susceptibility patterns is essential for the proper management of pediatric septicemia (10). \u003c/p\u003e\n\u003cp\u003eHowever, data on the etiology, epidemiology, and antimicrobial susceptibility of major pathogens causing pediatric bacteremia remain limited in low- and middle-income countries (LMICs) (5). Up-to-date information on antimicrobial resistance is essential for evaluating the appropriateness of current empiric and targeted therapies. Given the scarcity of studies on the prevalence and associated factors of drug-resistant bacteria among children in our setting, this study aims to assess the antimicrobial susceptibility pattern and associated factors among sepsis-suspected pediatric patients admitted to the Pediatrics Ward of Jimma Medical Center (JMC), Jimma, Southwest Ethiopia, from August 1 to October 30, 2023. The findings will provide insight into the etiologic agents of pediatric septicemia and support the rational use of antibiotics to improve patient management.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eStudy area\u003c/h2\u003e \u003cp\u003eThe study was conducted in Jimma medical center pediatric wards, Jimma, South-west Ethiopia. JMC is the teaching and referral hospital in southwest Ethiopia with 800 bed capacity. It gives service in different specialty and sub-specialty fields, among this pediatrics and child health is one of them. The service given at pediatrics and child health include inpatient and outpatient service including emergency, ambulatory and follow up service.\u003c/p\u003e \u003cp\u003eThe study was conducted from August1 to October 30, 2023. Institution based cross-sectional study design was conducted on 148 pediatrics patients admitted at JMC pediatrics ward in the study period who fulfill the inclusion criteria.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData collection and measurements\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eData collection Instruments\u003c/h2\u003e \u003cp\u003eA predefined data collection tool was used to extract all socio-demographic data and other relevant information such as previous antibacterial therapy, and application of indwelling medical device, hospitalization period, co-morbidities, clinical signs and symptoms of sepsis, immunization status, and current medication a patient is taking and patient followed till discharge.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eData collection Procedures\u003c/h3\u003e\n\u003cp\u003eUsing aseptic technique about 2\u0026ndash;5 ml of blood was obtained after cleaning the venous site with 70% alcohol and subsequently by 10% povidone iodine solution. About 1\u0026ndash;3 ml of venous blood was immediately inoculated into blood culture bottle and sent to laboratory. The bottles then incubated in the BD BACTEC\u0026trade; FX40 automated culture machine for a maximum of seven days until they were flagged as \u0026ldquo;negative\u0026rdquo; or \u0026ldquo;positive\u0026rdquo; for growth. Positive bottles then taken out from the machine and sub-cultured on Blood, Chocolate, and MacConkey agar (Oxoid, England). Identification of culture isolates was done according to standard bacteriological techniques and their characteristic appearance on their respective media. Antibiotic susceptibility testing was carried out using Kirby-Bauer disc diffusion technique on Mueller-Hinton agar (Oxoid, England) according to Clinical Laboratory Standard Institute guidelines. The result then collected from laboratory report.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eThe data collected was checked for completeness and consistency and then it was cleaned, coded, and entered into Epi Data 3.1, exported, and analyzed using Statistical Package for Social Sciences (SPSS) version 25.0. Then Bivariate and multivariate logistic regression analyses was conducted to see the association between dependent and independent variables. Statistical significance was considered at p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and 95% Confidence Interval.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData quality control\u003c/h3\u003e\n\u003cp\u003eData was collected by the trained nurses and laboratory technician and quality control was assured by reviewing of the filled checklist every day by the principal investigator and correction of incomplete checklist was completed early.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic characteristic of participants\u003c/h2\u003e \u003cp\u003eOut of 148 pediatric patients participated in this study, most 108(73%), of them were younger than 5 years with slight male predominance 79(53.4%), and majority 118(79.7%) had not yet begun formal education. Most of the care givers were between the age of 25\u0026ndash;40 years, came from rural, attend primary school, farmers in occupation, and had monthly income of 1000\u0026ndash;5000 ETB accounting about 68.9%, 54.1%, 31.1%, 56.1% and 74.3% respectively as shown in Table \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\u003eSocio-demographic characteristics of participants among sepsis suspected pediatric patients admitted at JMC pediatrics ward, 2023.\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=\"char\" char=\".\" 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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSocio-demographic characteristic of respondents\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eAge of the patient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 7 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;28 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;11 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u0026ndash;59 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;9 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 years and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e148\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSex of the patient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e148\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEducational status of the patient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot started yet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e79.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e148\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003eAge of care giver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 20 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u0026ndash;24 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u0026ndash;29 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026ndash;39 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;44 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u0026ndash;49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;54 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 years and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e148\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePlace of residency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e148\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eEducation status of the care giver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCannot read and write\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCan read and write\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCollege/University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e148\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eOccupation of care giver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDaily labor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMerchant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGovernmental Employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate Organization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e148\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eFamily income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 1000birr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1000\u0026ndash;5000 birr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6000\u0026ndash;10000 birr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMore than 10000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e148\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\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\n\u003ch3\u003eClinical characteristics of study participants\u003c/h3\u003e\n\u003cp\u003e Majority of study participants were first admitted to general ward accounting about 56(37.8%) followed by NICU 42(28%), Pediatrics oncology 22(14.9%), PICU and Pediatrics cardiac unit each 12( 8.1%) and EOPD kept patients 4(2.7%).\u003c/p\u003e \u003cp\u003eThe main complaints of patients were fast breathing accounting 44(29.7%) followed by fever 31(20.9%), swelling over the lower back 16(10.8%), and cough 12(8.1%). The mean duration of complain for current admission is 2.21 days. Majority of them came to hospital within 7 days of complaint which accounts about 112 (75.7%) followed by 8 to 14 days, 15\u0026ndash;50 days and more than 30 days of complaint accounting about 12.2%, 7.4% and 4.7% respectively. For 23 (15.5%) of patients\u0026rsquo; blood culture was taken within 24 hours of admission and for 80(54.1%) of them it was taken between 24 hours to 7 days as shown Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical Characteristics of participants among sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eClinical characteristic of respondents\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFrequency (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePercent %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eWard first patient admitted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePediatrics General Ward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePediatrics Oncology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePediatrics Cardiac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eEOPD kept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDuration of complaint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eLess than 7 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e8\u0026ndash;14 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e15\u0026ndash;30 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eGreater than 30 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eTime from admission to sample taken for blood culture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eLess than 7 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e8 to 14 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e15\u0026ndash;30 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMore than 30 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdded diagnosis after admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"11\" rowspan=\"12\"\u003e \u003cp\u003eProcedure done at hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIntravenous line\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCatheter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNaso-gastric tube\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSurgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLumbar Puncture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003ePrior history within last 6 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIllness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdmission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAntibiotic use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSerostatus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChild had chronic illness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eImmunization status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFully Immunized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eImmunized for age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePartially Immunized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNot immunized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWas Antibiotics taken before presenting to this hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEarly and late onset sepsis with or without meningitis was the predominant clinical diagnosis upon admission accounts 38.5% followed by respiratory focus infection (23%), gastrointestinal focus infection (9.5%). Neutropenic fever and hospital acquired infection upon admission to our hospital was less which accounts about 5.4% and 2.5% respectively but it was a major diagnosis added after admission. About 71(48%) of patients had added diagnosis after admission of which the predominant added diagnosis is hospital acquired infection 36(50.7%) followed by sepsis with or without meningitis 12(16.9%).\u003c/p\u003e \u003cp\u003eMore than half of study participants 75(50.7%) had moderate (18.9%) and severe acute malnutrition (31.8%). About one third of the patients had moderate and severe stunting (31.7%).\u003c/p\u003e \u003cp\u003eAll patients had IV line, for 95(64.2%) of them NG tube was inserted. LP, catheter, surgery, accounts for 35(23.6%), 23(15.5%) and 27(18.2%) respectively. Other procedures include intubation, tracheostomy, bone marrow aspiration, and ventricular tap.\u003c/p\u003e \u003cp\u003eAmong 148 participants within the last 6 months, 57(38.5%) of them had history of previous illness, 52(35.1%) had admission and 50(33.8%) used antibiotic. Among those who had illness 39(68.4%) of them, the illness was within the last 3 months and 18(31.6%) of them had illness 3 months back. At that time 52(91.2%) of them were admitted and 50(87.7%) of them took antibiotic. From patients had illness within the last 6 month, most of them took ceftriaxone 39(76.5%) followed by Gentamycin 17(33.3%), Ampicillin 5(9.8%).\u003c/p\u003e \u003cp\u003eThere were no patient who was HIV positive from the study participants. About 67(45.3%) of them were HIV negative and most of the participants didn\u0026rsquo;t now their serostatus 81(54.7%) in which almost half of them were neonates whose mother serostatus is negative. Of the participants, 28(18.9%) of them took immunosuppressive drug, from these 18(64.3%) took chemotherapy and 10(35.3%) took corticosteroid. About 102(68.9%) of participants had one or more chronic illness among these malnutrition accounts more than two third 79(77.5%) followed by malignancy 26(25.7%), and cardiac 15(15.3%). Out of 148, 56(37.8%) of respondents were fully immunized. Those immunized for their age, partially immunized and not immunized accounts 29(19.6%), 4(2.7%) and 59(39.9%) respectively.\u003c/p\u003e \u003cp\u003eHalf of the respondents took antibiotics before presenting to this hospital, from these 69(93.2%) of them got the antibiotics from health facilities with health personnel prescription. Others took from pharmacy with health personnel prescription and by themselves without health personnel prescription accounts 4.1% and 2.7% respectively. Majority of them took two antibiotics followed by one and more than two antibiotics accounts 40(54%), 28(37.8%) and 6(8.1%) respectively. Ceftriaxone was the most drug used alone as well as with other drugs accounting about 32(43.2%) followed by Gentamycin 21(28.4%), Ampicillin 20(27%) and vancomycin 10(13.5%). The most combined drug used before presenting to this hospital was ampicillin with gentamycin accounts 18(24.3%) followed by ceftriaxone and gentamycin and then vancomycin and ceftazidime with 5(6.8%) and 3(4.1%) respectively. Other antibiotics participants took before presenting to this hospital were metronidazole, Amoxicillin, cloxacilline, ciprofloxacillin, and meropenem.\u003c/p\u003e \u003cp\u003eFor those less than 28 days postnatal age (neonatal age groups), for majority of them 33(78.6%) there were no risk factor identified for neonatal sepsis. As described in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, among identified risk factors, maternal fever, duration of labour\u0026thinsp;\u0026gt;\u0026thinsp;24 hours and foul smelling vaginal discharge accounts about 9.5%, 9.5% and 2.4% respectively. Most of the neonate were term 30(71.4%) followed by preterm 10(23.8%). Half of them had normal birth weight 21(50%) followed by low birth weight 7(16.7%) despite 10( 23.8%) of them their birth weight is unknown.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGestational age, birth weight and risk factors identified among sepsis suspected neonates admitted at JMC pediatrics ward, 2023.\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eRisk factor Identified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFoul smelling vaginal discharge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuration of labour\u0026thinsp;\u0026gt;\u0026thinsp;24 hrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo risk factor identified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e42\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eGestational age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePreterm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTerm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e42\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery low birth weight (1000-1499gm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow birth weight (1500-2499gm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal birth weight (2500-3999gm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMacrosomia 4000gm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e42\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePatterns of antimicrobial susceptibility\u003c/h2\u003e \u003cp\u003eAmong blood sample taken from 148 participants 55(37.2%) of them had bacterial growth on blood culture. Bacterial growth is more predominant on neonatal age group.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFrom this study there was a slightly predominant gram positive bacteria isolated than gram negative bacterial with 28(50.9%) and 27(49.1%) respectively. The predominant bacteria grown from gram positive was Staphylococcal saprophyticus and from gram negative Klebsella pneumonia (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor all positive blood culture results antimicrobial susceptibility test was done. About 4 (7.3%) of them were susceptible for all and 51(92.7%) of them were resistant for at least one of antimicrobial categories (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Among resistant bacteria 39 (76.5%) of them had resistant to three or more classes of antimicrobial categories fulfilling the criteria of MDR.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong isolated bacteria more than 95% of gram positive and more than 88% of gram negative bacteria were resistant. Among those 16(59.3%) of gram positive and 23(95.8%) of gram negative bacteria were MDR. From all resistant bacteria, 23(45.1%) were extensive drug resistant bacteria and 19(37.3%) were PDR (resistant for all antimicrobial categories susceptibility done) as shown in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResistant level of isolated bacteria with gram stain among sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGram stain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal No of bacteria isolated\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eResistant bacteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMDR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eXDR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003ePDR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes N(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes N(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes N(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes N(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGram positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (50.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (96.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10 (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17 (63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13 (48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e14 (51.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGram Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (49.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003cp\u003e(88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e(11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23 (95.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13 (54.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e18 (75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003cp\u003e(92.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003e(7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003cp\u003e(76.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e(23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23\u003c/p\u003e \u003cp\u003e(45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28\u003c/p\u003e \u003cp\u003e(55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19\u003c/p\u003e \u003cp\u003e(37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e32\u003c/p\u003e \u003cp\u003e(62.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAntimicrobial susceptibility done for isolated gram positive bacteria shows susceptible on various ranges for (ciprofloxacillin 1(100%) and vancomycine 8(88.9%)) and resistant in various degrees to oxacilline 1(100%), penicillin 25(96.2%), gentamycin 17(68.0%) and doxycycline 16(59.3%. From gram negative bacteria resistant to Ampicilline was 2(100%) followed by Gentamycin 18(85.7%), Ceftriaxone 12(85%) and Ceftazidme 19(82.6%) as shown in table below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e, only 5(9.8%) out of 51 resistant bacteria which was not MDR. All isolated bacteria from neonates and age 1\u0026ndash;5 years were resistant bacteria, of these more than 77% were MDR (17/22 and 7/9 respectively). Isolated bacteria from participants age between 1\u0026ndash;12 month, 85% (17/20) of them were resistant bacteria and for those age greater than 5 years among isolated bacteria 75% (3/4) of them were resistant bacteria and all were MDR.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAntimicrobial susceptibility pattern of isolated bacteria among sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGram stain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAntibiotics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSusceptible\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResistant\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eGram Positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDoxycycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(33.3.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16(59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27(100.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (68.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25(100.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePenicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25(96.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOxacillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVancomycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCiprofloxacillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"13\" rowspan=\"14\"\u003e \u003cp\u003eGram Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10(38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18(85.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCeftazidime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19(82.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCefepime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(70 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMeropenium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(65.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePiperazine Tazobactam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(40 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11(55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCefotaxime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(20 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChloramphenicol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4(57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCeftriaxone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12(85.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmpicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCotrimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTobramycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErythromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImepinem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe antimicrobial susceptibility pattern done for isolated gram negative bacteria in this study shows most antibiotics were resistant to routinely prescribed first and second line drugs. Isolated gram negative bacteria were resistant to Ampicillin (100%), gentamycin and ceftriaxone (85.7%) followed by ceftazidime (82.6%), cefepim and cefotaxime (70%) as shown in Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Meropenem (21.7%) and cotrimoxazole (28.6%) shows low resistant among them.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(MDR (Multi Drug Resistant), XDR (Extensive Drug Resistant), PDR (Pan Drug Resistant)).\u003c/p\u003e \u003cp\u003eOut of 55 positive blood culture results 51 (92.73%) were drug resistant bacteria (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e), of those drug resistant bacteria 76.5% (39/51) had MDR bacteria which showed as there was a high prevalence of MDR in our setup. Fifty nine percent (23/39) of MDR were from Gram Negative bacteria and 41% (16/39) were from gram positive bacteria isolated. XDR was prevalent from gram negative bacteria isolated 56.5%(13/23) and PDR was more prevalent in gram positive bacteria isolated 68.4% (13/19) in this study.\u003c/p\u003e \u003cp\u003e \u003cb\u003e5.3. Factors associated with antimicrobial susceptibility\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAmong sepsis suspected admitted pediatrics patients who participated in the study, their social-demographic and clinical factors were analyzed for their association to antimicrobial susceptibility by using bi-variate and multivariate analysis with backward logistic regression. This result shows as the age of patient increase the chance of having positive blood culture result decrease. Neonatal age group had a statistically significant association 6 times more likely to have positive blood culture result [AOR\u0026thinsp;=\u0026thinsp;6.066, 95% CI, (1.112, 33.092)] and 11 times more likely to had resistant bacteria [AOR\u0026thinsp;=\u0026thinsp;10.913, 95% CI, (2.605, 45.719)]. Participants who were admitted to hospital for more than 14 days before sample drawn for culture were about 4.9 times more likely to had bacterial growth [AOR\u0026thinsp;=\u0026thinsp;4.939, 95% CI, (1.474\u0026ndash;16.550)] and 5.6 times more likely to have resistant bacteria. Patients who had previous admission within the last 6 month had 2.7 times to had bacterial growth among sepsis suspected admitted patients[AOR\u0026thinsp;=\u0026thinsp;2.704, 95% CI, (1.264, 5.784)] and those took antibiotic during this period has 2.3 times more likely to had positive result [AOR\u0026thinsp;=\u0026thinsp;2.338, 95% CI (1.078\u0026ndash;5.067)]. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows associations with antimicrobial susceptibility.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate analysis result of factors associated with antimicrobial susceptibility among sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c4\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eBlood culture result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003cp\u003e55 (37.2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003cp\u003e93 (62.8%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge of the patient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e 28 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21 (22.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.429(2.858,31.103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.066 (1.112,33.092)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1\u0026ndash;11 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (36.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23 (24.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.826(2.371,25.834)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e12\u0026ndash;59 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (16.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (13.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.231(1.635,23.741)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e5\u0026ndash;15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (7.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36 (38.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDuration after admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;14 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45(81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88 (94.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;15 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.911(1.261,12.132)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.939 (1.474,16.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProcedure done for patient\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eCatheter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49(89.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76(81.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6(10.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17(18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.551 (1.082,2.221)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.236\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eNG tube\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12(21.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41(44.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43(78.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52(55.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.417 (1.796, 6.501)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.747 (1.235, 6.109)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eLP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38(69.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75(80.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17(30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18(19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.974 (1.336, 2.916)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.113\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWithin last 6 months history of\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eIllness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40 (72.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51 (54.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15 (27.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42 (45.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.196 (1.069, 4.513)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.385(0.612,3.132)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eAdmission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43 (78.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53 (56.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40 (43.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.370 (0.173, 0.791)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.704 (1.264, 5.784)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eAntibiotic taken\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43 (78.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55 (9.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38 (40.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.476 (1.156, 5.304)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.338 (1.078, 5.067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.031\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eImmunized for age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33 (90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30 (32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63 (67.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.317 (0.159, 0.635)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSerostatus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50 (53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38 (69.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.385 (0.191, 0.777)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.560 (1.092, 2.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHas MMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50 (90.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92 (98.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.109 (0.012, 0.956)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.045\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCardiac illness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52 (94.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81 (87.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (5.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.568 (0.691, 9.538)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.159\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c4\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003eResistant bacteria\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCOR (95%CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAOR (95%CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge of the patient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e 28 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22()\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21()\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.921(3.452,48.357)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.913(2.605,45.719)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e1\u0026ndash;11 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17()\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26()\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.064(2.142, 30.366)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.229(2.050, 33.028)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e12\u0026ndash;59 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9()\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13()\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.538(2.000, 36.452)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.334(1.796, 38.682)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e5\u0026ndash;15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3()\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37()\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePrevious admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41(80.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55(56.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10(19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42(43.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.131(1.408, 6.964)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.338(1.482,7.517)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDuration after admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;14 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41(80.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92 (94.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;15 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.488 (1.443,13.960)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.557 (1.542, 20.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e5.4. Patient outcome\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOut of 148 pediatrics patients participated on this study majority 108(73%) of patients improved and then discharged or transferred to other hospital for completion of antibiotics. About 13 (8.8%) of patients passed away as described in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOut of 55 patients who had blood culture growth, for 30(54.5%) of them antibiotics was revised after culture sensitivity result. Among those patients 28(93.3%) of them had clinical improvement and 2(6.7%) of them had no improvement after antibiotics was revised. The improvements seen on those patients were, fever alone was subside in 12(42.9%) followed by both fever and tachypnea 10(35.7%) and tachypnea alone subsided in 6(21.4%) of patients. Among positive blood culture and microbial susceptibility done, for 25 patients antibiotic was not revised, the major reason why antibiotic not revised was because the isolated bacteria was resistant to all antimicrobial categories susceptibility done or the susceptible antibiotics were not applicable in the patients age group accounts about 13(52%) followed by result were arrived after patient leave hospital for different reason 9(36%). Regarding the length of stay in the ward, 66(44.6%) of them stays between 15\u0026ndash;30 days.\u003c/p\u003e \u003cp\u003eAmong sepsis suspected admitted pediatrics patients those have extensive drug resistant bacteria on antimicrobial susceptibility test were 3 times more likely to die [AOR\u0026thinsp;=\u0026thinsp;3.056, 95% CI (0.880-10.609) as shown in Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate analysis result showing factors affecting patient outcome among sepsis suspected pediatrics patients admitted at JMC pediatrics ward, 2023.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eDied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCOR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes 13 (8.8)\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo 135 (91.2)\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102 (75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.649 (0.880,8.442)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eXDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e117 (86.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.062 (1.196, 13.796)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.056 (0.880, 10.609)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\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"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study showed that the overall culture positive rate among sepsis suspected pediatric patients admitted in JUMC was 37.2% which was lower when compare with study conducted in Nigeria (41.19%) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) which was done in children less than 12 years old and inpatient and out patients, Jimma (63.5%, 61.5%) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and Bahirdar (41.3%) (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) which was done only in neonatal age group. It was a higher rate compared with studies done in Rwanda (11.7%), (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), Mekele (28%) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), Gondar (20.7%) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), and 14% (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), TASH and Yekatit 12 (18.8%) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) and (27.9%) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), Arbamich (11.3%) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), TASH (15.2%) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). The reason of this all variation may be due to socio demographic and clinical characteristic of study participants (age difference, ambulatory patients included in some study, cancer patients or febrile patient only, focusing only on gram negative), high burden of nosocomial infection, prior exposure to antibiotics, longer stay in hospital, and health-care system.\u003c/p\u003e \u003cp\u003eFrom this study gram positive bacteria isolated predominantly than gram negative bacteria with 50.9% and 49.1% respectively which was in line with a study done in Arbaminch (57.1%) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), Mekele (68%) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), Gondar (61.1%) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) and (69%) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). CoNS was the predominant microorganism from gram positive bacteria isolated in this study which was similar with a study done in India (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), Jimma (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), Gondar (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) and Nigeria (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) from where CoNS were the predominant microorganism from gram positive bacteria whether gram positive was a predominant bacteria isolated or not. Staphylococcus aureus was predominant microorganism from gram positive bacteria isolated in study done at Rwanda (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), Arbaminch (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), Addis Abeba (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), Mekele (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), Bahir dar (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) and Gondar (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The high prevalence of CoNS might be in association with an increasing burden of nosocomial infection in hospitalized patients and some of participants in this study was on vancomycin during data collection which S. aureus may be empirically treated and has influence on growth of this bacteria. In other studies gram-negative bacteria were predominant like in Iran (55%) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), Rwanda (68%) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), Addis Abeba (51.8%) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) and (54.7) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), Jimma (79.4%) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and (58.2%) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), and Bahirdar (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). This variation might be explained by the difference in the age of study participants, Hospital setting, In patient and ambulatory patient difference. Over all in this study as well as in majority of other studies (Rwanda (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), Nigeria(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), Arbaminch (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), JUMC and Five selected Hospitals in Ethiopia (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), TASH and Yekatit 12 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), Tikur Ambesa Specialized Hospital(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), Gondar (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) Bahirdar (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), Klebsella spp was the first or the second most predominant microorganism from isolated gram negative bacteria. E. coli was the predominant bacteria isolate one study done in Jimma (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and Mekele (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). This shows klebsella spp was the predominant bacteria isolated from most studies done\u003c/p\u003e \u003cp\u003eIn the current study, for all positive blood culture results antimicrobial susceptibility test was done. About 4 (7.3%) of them were susceptible for all and 51(92.7%) of them were resistant for at least one of antimicrobial categories. Among isolated bacteria more than 95% of gram positive and more than 88% of gram negative bacteria were resistant. Of the resistant bacteria 39(76.5%) of them were resistant to three or more classes of antimicrobial categories fulfilling the criteria of MDR. This finding was similar with a study done in Rwanda (77.1%) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), and Bahirdar (78.2%) (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). In contrary this study finding was higher when compared with study done in Europe (39%) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) Gondar (17.3%) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) and Mekele (59%) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) which might be explained by the epidemiological difference with western country, study participants were only cancer patient in study done in Gondar. As well the finding of this study is lower when compared with study done in Iran (96.8) (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), Arbaminch (82.1%) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), JUMC (84.4%) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), In five selected Hospitals in Ethiopia (91.3%) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), TASH and Yekatit 12 (92.7%) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). This variation might be explained by variation in study participants of which most drug resistant bacteria were found on neonatal age group and those study conducted on neonate had high prevalence of MDR bacteria which also similar with our finding when we categorize with their age group. On other studies where other sample used in addition to blood culture the MDR rate was high like study done in Iran.\u003c/p\u003e \u003cp\u003eAntimicrobial susceptibility done for isolated gram positive bacteria shows susceptible from 0 to 100% (Oxacilline (0%) and Penicilline (3.8%) to vancomycine (88.9%) and ciprofloxacillin (100%)) and resistant rate from 0 to 100% ciprofloxacillin (0%) to oxacilline (100%), with different range like penicillin (96.2%), gentamycin (68.0%) and doxycycline (59.3%). From gram negative bacteria resistant to Ampicilline(100%) followed by Gentamycin (85.7%), Ceftriaxone (85%) and Ceftazidme (82.6%). The result of the study shows isolated gram positive and gram negative bacteria were resistant to routinely prescribed medications which was in the line with other studies done in Rwanda (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), Jimma(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), In five selected hospitals in Ethiopia (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), Gondar (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), Bahirdar (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), Addis Abeba (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) and in seven LMICs in Africa and South Asia (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere were factors those associated with culture positiveness as well as for drug resistant bacteria. This result shows as the age of patient increase the chance of having positive blood culture result decrease. Neonatal age group had a statistically significant association 6 times more likely to have positive blood culture result [AOR\u0026thinsp;=\u0026thinsp;6.066, 95% CI, (1.112, 33.092)P\u0026thinsp;=\u0026thinsp;0.037] and 11 times more likely to had resistant bacteria [AOR\u0026thinsp;=\u0026thinsp;10.913, 95% CI, (2.605, 45.719)P\u0026thinsp;=\u0026thinsp;0.001]. This finding is in concordance with other research conducted in Nigeria highest rate was in neonate (57.97%) followed by infants (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), Arbaminch being infant [AOR\u0026thinsp;=\u0026thinsp;4.18, 95% CI, (1.3\u0026ndash;13.0),P\u0026thinsp;=\u0026thinsp;0.014] (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), Gondar being an infant P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and P\u0026thinsp;=\u0026thinsp;0.0004 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) and Bahirdar (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe duration of stay in hospital before sample taken was another factor associated with drug resistant and culture positive rate in this study. Participants who were admitted to hospital for more than 14 days before sample drawn for culture were about 4.9 times more likely to had bacterial growth [AOR\u0026thinsp;=\u0026thinsp;4.939, 95% CI, (1.474\u0026ndash;16.550), P\u0026thinsp;=\u0026thinsp;0.010] and 5.6 times more likely to have resistant bacteria [AOR\u0026thinsp;=\u0026thinsp;5.557, 95% CI, (1.542\u0026ndash;20.029), P\u0026thinsp;=\u0026thinsp;0.009]. Patients who had previous admission within the last 6 month had 2.7 times to had bacterial growth among sepsis suspected admitted patients [AOR\u0026thinsp;=\u0026thinsp;2.704, 95% CI, (1.264, 5.784), P\u0026thinsp;=\u0026thinsp;0.010] and about 3.3 times more likely to have resistant bateria [AOR\u0026thinsp;=\u0026thinsp;3.338, 95% CI, (1.482\u0026ndash;7.517), P\u0026thinsp;=\u0026thinsp;0.004]. Those participants who took antibiotic during that period had 2.3 times more likely to had positive result [AOR\u0026thinsp;=\u0026thinsp;2.338, 95% CI (1.078\u0026ndash;5.067, P\u0026thinsp;=\u0026thinsp;0.031). Other factors associated with positive blood culture (Bacterial growth) and drug resistant bacteria identified in this study were comorbidities, history of previous illness, history of previous antibiotic use within the last 6 month, and for those procedures done in the hospital. In this study findings were inthe line with studies done in Arbaminch those had admission\u0026thinsp;\u0026gt;\u0026thinsp;10 days [AOR\u0026thinsp;=\u0026thinsp;5.54, 95% CI, (1.51\u0026ndash;20.41), P\u0026thinsp;=\u0026thinsp;0.010], (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), Addis Ababa, those had upper respiratory infection in the past 3 month [AOR\u0026thinsp;=\u0026thinsp;7.02, 95% CI, (1.424\u0026ndash;34.64), P\u0026thinsp;=\u0026thinsp;0.02] (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), and in Gondar, those less than 5 years old had more culture positive rate when compared to older patients (p value 0.001) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Burn [AOR\u0026thinsp;=\u0026thinsp;3.55, 95% CI, (1.02\u0026ndash;12.38)] and wound cases [AOR\u0026thinsp;=\u0026thinsp;5.52, 95% CI, (1.50\u0026ndash;20.34)] in Arbaminch (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), In Bahirdar, maternal risk factors (premature rupture of membrane, urinary tract infection, duration of labour), Low birth weight and prematurity had association with positive blood culture (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) but in our study has no association with current study it may be because of small number of neonate to do the association..\u003c/p\u003e \u003cp\u003eAmong sepsis suspected admitted pediatrics patients those had extensive drug resistant bacteria on antimicrobial susceptibility test were 3 times more likely to die [AOR\u0026thinsp;=\u0026thinsp;3.056, 95% CI (0.880-10.609). In others study, presence of MDR bacteria significantly increase the mortality which was similar with our study in Europe (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), 81% of death occurred in culture confirmed sepsis in study done at Jimma even if association was not done because of smaller sample size.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSTRENGTH AND LIMITATION OF THE STUDY\u003c/h2\u003e \u003cp\u003eThis study tried to address over all prevalence of positive rate, MDR, PDR and XDR rate among pediatrics patient admitted to pediatrics ward in our set up and tried to address associated factors relation to positive rate and drug resistant. As a limitation of this study, selection bias might be introduced because of the convenient sampling technique used. Unavailability of blood culture bottle all the time was another limitation in which some patients were missed during data collection.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eOut of 148 pediatrics patients majority (73%) of them are age less than 5 years with slight male predominance. The positive rate of blood culture was 37.2% in this study. The prevalence of drug resistant bacteria was high in this study accounting about 92.7% and MDR were 76.2%. CoNs was the predominant bacteria isolated from gram positive bacteria and Klebsella pneumonia was the predominant bacteria isolated from gram negative bacteria. Isolated bacteria\u0026rsquo;s were resistant to routinely prescribed first and second line drugs. Neonates and patients who had stayed for prolonged time in the ward were more likely to had bacterial growth and resistant bacteria. Those patients who had extensive drug resistant bacteria more likely to die as compared to other patients.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eRECOMMENDATION\u003c/h2\u003e \u003cp\u003ePracticing antibiotic stewardship already established in our setup is mandatory to decrease the high prevalence of drug resistance bacteria. The prevalence of drug resistant bacteria in this study was high (more than 90% ) which had a negative impact on patient care as well as treating resistant bacteria costs a lot. To tackle this health professionals should be familiar with rational use of antibiotics as well as infection prevention method and proper use of updated guideline. Taking blood culture before starting antibiotic has significant benefit for a patient as well as treating physician to improve quality of care. Patients should be treated based on susceptibility pattern. Availability of blood culture bottle all the time can help to increase detection rate, identify isolated organism, know susceptibility pattern, improve patient outcome as well as decrease MDR rate as patient properly treated based on culture result. So the hospital administration with laboratory department should work collaboratively to improve the availability of blood culture bottle in order to improve patient care and tackle MDR.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAOR, Adjusted Odd Ratio; AMR, Antimicrobial Resistance; BSI, Blood Stream Infection; \u0026nbsp;CI, Confidence Interval; CLSI, Clinical and Laboratory Standards Institute; CoNS, Coagulase Negative Staphylococcus; COR, Crude Odd Ratio; EOPD, Emergency Out Patient Department; ETB, Ethiopian Birr; EUCAST, European Committee on Antimicrobial Susceptibility Testing; FDA, Food and Drug Administration; GNB, Gram Negative Bacteria; GPB, Gram Positive Bacteria; HIV/AIDS, Human Immune Virus, Acquired Immune Deficiency Virus; IV, Intra Venous; IRB, Institutional Research Board; JUIH, Jimma University Institution of Health, JUERC, Jimma University Ethical and Research Committee; JMC, Jimma Medical Center ; JUMC, Jimma University Medical Center; LMICs, Low- and Middle-Income Countries; MDR, Multi Drug Resistant; MMC, Myelomeningiocele; NICU, Neonatal Intensive Care Unit; NGT, Naso-Gastric tube; PDR, Pan Drug Resistant; PICU, Pediatrics Intensive Care Unit; SPSS, Statistical Package for Social Science; XDR, Extensive Drug Resistant; WHO, World Health Organization. \u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthical Approval and consent to participants\u003c/h2\u003e\n\u003cp\u003eJimma University Institutional Research Board (IRB) examined and approved the study protocol, issuing it the number IRef. No. JUIH/IRB/600/23 and permission was obtained from the authorities of the Jimma University Specialized Hospital.\u0026nbsp;The goal of the study and the significance of the participants' involvement were explained to\u0026nbsp;each of the study participant’s and participant’s family or caregiver before the consent is taken.\u0026nbsp;Also the participants informed that those data taken are only used for the research purpose and no personal data like name and identification are not used for the the research as well as need for publication.\u003c/p\u003e\n\u003cp\u003eBefore any data was collected, each participant and\u0026nbsp;participant’s family or caregiver\u0026nbsp;gave their verbal and written informed consent both for research and publication.\u0026nbsp;Confidentiality was assured by collecting data anonymously and codes was used on the questionnaire and it was locked in a secure place. During data collection local languages Afan Oromo and Amharic was used for communication with participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and Material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe soft copy and hard copy of full document is given to Jimma University Institution of Health Science upon completion of the research to be put in Jimma University (JU) repository.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trail Number\u003c/strong\u003e--- Not Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure and Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors are equally contribute. The authors declare that there is no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no funding for this research (not funded).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAknowledgment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge Jimma University Institution of Health Science, all participants, authors, data collectors and health care workers working at pediatrics ward and laboratory who directly and indirectly support us to do this research.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmeya G, Weldemedhin T, Tsalla T, Gebremeskel F. Antimicrobial susceptibility pattern and associated factors of pediatric septicemia in Southern Ethiopia. Infection and drug resistance. 2020:3895-905.\u003c/li\u003e\n\u003cli\u003eVarela MF, Stephen J, Lekshmi M, Ojha M, Wenzel N, Sanford LM, et al. Bacterial resistance to antimicrobial agents. Antibiotics. 2021;10(5):593.\u003c/li\u003e\n\u003cli\u003eDunachie SJ, Day NP, Dolecek C. The challenges of estimating the human global burden of disease of antimicrobial resistant bacteria. Current Opinion in Microbiology. 2020;57:95-101.\u003c/li\u003e\n\u003cli\u003eWillyard C. Drug-resistant bacteria ranked. Nature. 2017;543(7643):15.\u003c/li\u003e\n\u003cli\u003eDroz N, Hsia Y, Ellis S, Dramowski A, Sharland M, Basmaci R. Bacterial pathogens and resistance causing community acquired paediatric bloodstream infections in low-and middle-income countries: a systematic review and meta-analysis. Antimicrobial Resistance \u0026amp; Infection Control. 2019;8(1):1-12.\u003c/li\u003e\n\u003cli\u003eGashaw M, Ali S, Tesfaw G, Eshetu B, Workneh N, Berhane M, et al. Bacterial profile and drug resistance patterns in neonates admitted with sepsis to a tertiary teaching hospital in Ethiopia. 2019.\u003c/li\u003e\n\u003cli\u003eMagiorakos A-P, Srinivasan A, Carey RB, Carmeli Y, Falagas M, Giske C, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clinical microbiology and infection. 2012;18(3):268-81.\u003c/li\u003e\n\u003cli\u003eNegussie A, Mulugeta G, Bedru A, Ali I, Shimeles D, Lema T, et al. Bacteriological profile and antimicrobial susceptibility pattern of blood culture isolates among septicemia suspected children in selected hospitals Addis Ababa, Ethiopia. International journal of biological and medical research. 2015;6(1):4709.\u003c/li\u003e\n\u003cli\u003eNegash AA, Asrat D, Abebe W, Hailemariam T, Wubete A, Aseffa A, et al. Etiology, antibiotic susceptibility and prognostic factors of pediatric community-acquired sepsis in Addis Ababa, Ethiopia. The Journal of Infection in Developing Countries. 2021;15(01):113-22.\u003c/li\u003e\n\u003cli\u003eAzimi T, Maham S, Fallah F, Azimi L, Gholinejad Z. Evaluating the antimicrobial resistance patterns among major bacterial pathogens isolated from clinical specimens taken from patients in Mofid Children\u0026rsquo;s Hospital, Tehran, Iran: 2013\u0026ndash;2018. Infection and drug resistance. 2019:2089-102.\u003c/li\u003e\n\u003cli\u003eOmbelet S, Barb\u0026eacute; B, Affolabi D, Ronat J-B, Lompo P, Lunguya O, et al. Best practices of blood cultures in low-and middle-income countries. Frontiers in medicine. 2019;6:131.\u003c/li\u003e\n\u003cli\u003eKebede B, Yihunie W, Abebe D, Addis Tegegne B, Belayneh A. Gram-negative bacteria isolates and their antibiotic-resistance patterns among pediatrics patients in Ethiopia: A systematic review. SAGE Open Medicine. 2022;10:20503121221094191.\u003c/li\u003e\n\u003cli\u003eWorku M, Belay G, Tigabu A. Bacterial profile and antimicrobial susceptibility patterns in cancer patients. Plos one. 2022;17(4):e0266919.\u003c/li\u003e\n\u003cli\u003eAlemayehu T. Prevalence of multidrug-resistant bacteria in Ethiopia: a systematic review and meta-analysis. Journal of Global Antimicrobial Resistance. 2021;26:133-9.\u003c/li\u003e\n\u003cli\u003eGandra S, Mojica N, Klein EY, Ashok A, Nerurkar V, Kumari M, et al. Trends in antibiotic resistance among major bacterial pathogens isolated from blood cultures tested at a large private laboratory network in India, 2008\u0026ndash;2014. International Journal of Infectious Diseases. 2016;50:75-82.\u003c/li\u003e\n\u003cli\u003eHabyarimana T, Murenzi D, Musoni E, Yadufashije C, N Niyonzima F. Bacteriological profile and antimicrobial susceptibility patterns of bloodstream infection at Kigali University Teaching Hospital. Infection and drug resistance. 2021:699-707.\u003c/li\u003e\n\u003cli\u003eAbdu AB, Egbagba J, Alade T. Antimicrobial Susceptibility Pattern and Bacterial Isolates Profile in Septicaemia Suspected Patients Attending FMC. Yenagoa. International Journal of Research and Scientific Innovation. 2020;7(4):134-43.\u003c/li\u003e\n\u003cli\u003eSands K, Carvalho MJ, Portal E, Thomson K, Dyer C, Akpulu C, et al. Characterization of antimicrobial-resistant Gram-negative bacteria that cause neonatal sepsis in seven low-and middle-income countries. Nature microbiology. 2021;6(4):512-23.\u003c/li\u003e\n\u003cli\u003eGashaw M, Berhane M, Bekele S, Kibru G, Teshager L, Yilma Y, et al. Emergence of high drug resistant bacterial isolates from patients with health care associated infections at Jimma University medical center: a cross sectional study. Antimicrobial Resistance \u0026amp; Infection Control. 2018;7:1-8.\u003c/li\u003e\n\u003cli\u003eEshetu B, Gashaw M, Solomon S, Berhane M, Molla K, Abebe T, et al. Bacterial isolates and resistance patterns in preterm infants with sepsis in selected hospitals in Ethiopia: a longitudinal observational study. Global Pediatric Health. 2020;7:2333794X20953318.\u003c/li\u003e\n\u003cli\u003eWasihun AG, Wlekidan LN, Gebremariam SA, Dejene TA, Welderufael AL, Haile TD, et al. Bacteriological profile and antimicrobial susceptibility patterns of blood culture isolates among febrile patients in Mekelle Hospital, Northern Ethiopia. Springerplus. 2015;4(1):1-7.\u003c/li\u003e\n\u003cli\u003eAbebe W, Tegene B, Feleke T, Sharew B. Bacterial Bloodstream Infections and their Antimicrobial Susceptibility Patterns in Children and Adults in Ethiopia: a 6-Year Retrospective Study. Clinical Laboratory. 2021;67(11).\u003c/li\u003e\n\u003cli\u003eDagnew M, Yismaw G, Gizachew M, Gadisa A, Abebe T, Tadesse T, et al. Bacterial profile and antimicrobial susceptibility pattern in septicemia suspected patients attending Gondar University Hospital, Northwest Ethiopia. BMC research notes. 2013;6:1-7.\u003c/li\u003e\n\u003cli\u003eZenebe Y, Molla T, Beza L, Mekonnen D. Bacterial profile and antimicrobial susceptibility pattern of neonatal sepsis in Felege-Hiwot Referral Hospital, Bahir Dar, northwest Ethiopia: A cross-sectional study design. Ethiopian Journal of Health Development. 2021;35(1).\u003c/li\u003e\n\u003cli\u003eLegese MH, Weldearegay GM, Asrat D. Extended-spectrum beta-lactamase-and carbapenemase-producing Enterobacteriaceae among Ethiopian children. Infection and drug resistance. 2017:27-34.\u003c/li\u003e\n\u003cli\u003eBitew A. Multi-drug resistance profile of bacteria isolated from blood stream infection at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. EC Microbiol. 2018;14:119-26.\u003c/li\u003e\n\u003cli\u003eSadat SS, Ahani Azari A. Frequency of multidrug-resistant, extensively drug-resistant, and pandrug-resistant phenotypes among clinical isolates of Staphylococcus aureus. Infection Epidemiology and Microbiology. 2020;6(4):269-75.\u003c/li\u003e\n\u003cli\u003eFolgori L, Livadiotti S, Carletti M, Bielicki J, Pontrelli G, Degli Atti MLC, et al. Epidemiology and clinical outcomes of multidrug-resistant, gram-negative bloodstream infections in a European tertiary pediatric hospital during a 12-month period. The Pediatric infectious disease journal. 2014;33(9):929-32.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","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":"Blood culture, Antimicrobial susceptibility, Sepsis suspected, Pediatrics patients","lastPublishedDoi":"10.21203/rs.3.rs-8991130/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8991130/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWorldwide, antibiotic resistance is thought to kill 700,000 people annually. Blood culture has a high positive predictive value and is essential for a precise diagnosis of bloodstream infections. It also provides current information on local etiologic patterns and drug sensitivities, which helps the doctor manage the patient. This study aimed to assess the antimicrobial susceptibility pattern and associated factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn institution-based cross sectional study design was conducted from August 1 to October 30, 2023 among sepsis suspected pediatrics patients, admitted at JMC pediatrics ward, Jimma University, Oromia, Ethiopia. Data was collected using a semi-structured questionnaire. Logistic regression analysis was done to identify covariates associated with the outcome variables. Statistical significance considered at a p-value of less than 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOut of 148 patients participated in the study, 55(37.2%) of them has bacterial growth. A common bacterium isolated from gram negative bacteria was klebsella pneumonia. Among 55 isolated bacterial growth Drug resistant bacteria accounts about 51(92.7%), of these XDR and PDR accounts 23(45.1%) and 19(37.3%) respectively. Young age [AOR = 6.066, 95% CI, (1.112, 33.092)], previous history of admission within last 6 months [AOR = 2.704, 95% CI, (1.264, 5.784)], prolonged hospital stay more than 14 days [AOR = 4.939, 95% CI, (1.474–16.550)] and prior exposure to antibiotics [AOR = 2.338, 95% CI (1.078–5.067)] has significant association with bacterial growth and also more likely to had resistant bacteria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study the prevalence of drug resistant bacteria is high. Neonates and patients who had stayed for prolonged time in the ward were more likely to have bacterial growth and resistant bacteria. Practicing rational use of antibiotic is mandatory to decrease the high prevalence of drug resistance.\u003c/p\u003e","manuscriptTitle":"Antimicrobial Susceptibility Pattern and Associated Factor among Sepsis Suspected Pediatrics Patients, admitted at JMC Pediatrics ward, Jimma, South West Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 17:14:45","doi":"10.21203/rs.3.rs-8991130/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":"11462362-ebbc-4f16-a4c7-967c6326a9bc","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-10T04:55:26+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 17:14:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8991130","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8991130","identity":"rs-8991130","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}