Bacterial Isolates and Predictors of High-Risk Antimicrobial Resistance Among Pediatric Intensive Care Unit Patients in Ethiopia: A Hospital-Based Cross-Sectional Study

Bacterial Isolates and Predictors of High-Risk Antimicrobial Resistance Among Pediatric Intensive Care Unit Patients in Ethiopia: A Hospital-Based Cross-Sectional Study | 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 Bacterial Isolates and Predictors of High-Risk Antimicrobial Resistance Among Pediatric Intensive Care Unit Patients in Ethiopia: A Hospital-Based Cross-Sectional Study Abdi Hayato, Tesfa Gebremeskel, Solomon Tejineh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9163036/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 14 You are reading this latest preprint version Abstract Background: Antimicrobial resistance (AMR) is a major threat in pediatric intensive care units (PICUs). Data on resistance patterns in non-neonatal pediatric cohorts in Ethiopia remain scarce. This study assessed Bacterial Isolates and Predictors of High-Risk Antimicrobial Resistance Among PICU at Asella Teaching and Referral Hospital. Methods: A five-year (2020–2025) hospital-based cross-sectional study was conducted among patients aged 29 days to 14 years. Data were extracted from records using a structured checklist. Independent predictors of high-risk AMR were identified via multivariable logistic regression (p<0.05). Results: Among 217 participants, 52.5% had positive microbial growth. Gram-negative bacteria accounted for 54.5% of isolates, slightly predominating over Gram-positive organisms. Among 66 isolates, high-risk AMR prevalence was 68.2%, including extended-spectrum beta-lactamase (ESBL) (19.7%) and extensively drug-resistant (XDR) (15.2%) strains. Multivariable analysis identified length of PICU stay (AOR 7.59, 95% CI: 1.10–52.60; p=0.040) and adverse outcome at discharge (AOR 8.22, 95% CI: 1.39–48.63; p=0.020) as independent predictors. Invasive device duration and Gram-negative status were significant only in bivariate models. Conclusion: High-risk AMR (68.2%) is independently associated with prolonged hospitalization and adverse outcomes. These findings necessitate strengthened infection control, enhanced microbiological surveillance, and robust antimicrobial stewardship to mitigate multidrug-resistant pathogens in high-acuity settings. Antimicrobial resistance Pediatric ICU Microbial profile Ethiopia High-risk AMR Figures Figure 1 Introduction Background Antimicrobial resistance (AMR) is a global public health crisis, particularly in low-resource settings where empirical antibiotic use is widespread ( 1 ). In 2021, AMR was directly responsible for an estimated 1.14 million deaths, with projections reaching 1.91 million by 2025( 2 ). Pediatric intensive care units (PICUs) are high-risk environments for multidrug-resistant organisms (MDROs) due to invasive procedures, frequent broad-spectrum antibiotic use, and patient vulnerability ( 3 ). Africa bears the highest AMR-associated mortality globally. In 2019, 1.05 million deaths were reported in the World Health Organization (WHO) African region, with MRSA and third-generation cephalosporin-resistant Klebsiella pneumoniae as leading contributors ( 4 , 5 ). In Sub-Saharan Africa, AMR prevalence continues to rise, with MRSA and ESBL-producing Enterobacterales reaching 40%. Without intervention, AMR could cause 4.1 million annual deaths by 2050 ( 4 , 6 ). In Ethiopia, studies at University of Gondar and Nekemte hospitals reported multidrug resistance rates of 76% and 56.4%, respectively, with E. coli , Klebsiella spp., and S. aureus as predominant MDR pathogens ( 7 – 9 ). At Asella Teaching and Referral Hospital (ATRH), neonatal and surgical populations show high resistance rates to first-line antibiotics, highlighting a growing local AMR burden( 10 , 11 ). Infectious diseases remain a leading cause of morbidity and mortality among children globally, particularly in low-resource settings ( 12 , 13 ). PICU patients are especially vulnerable to MDR infections due to invasive procedures, being immunocompromised, and prolonged hospitalization ( 14 , 15 ). AMR increases mortality, prolongs hospital stay, and raises healthcare costs ( 16 – 19 ). In Ethiopia, retrospective data indicate alarming MDR rates, with K. pneumoniae and Acinetobacter spp. showing 80% to 84% resistance, and an overall MDR prevalence of 64.3% ( 20 ). The spread of drug-resistant bacteria challenges antibiotic treatments for widespread bacterial infections; infections from Klebsiella pneumoniae , Escherichia coli , Staphylococcus aureus , and Enterobacteriaceae resistant to last-resort carbapenem antibiotics have spread globally ( 21 ). Limited data are available on microbial profiles, resistance patterns, and risk factors among non-neonatal PICU patients at ATRH. Local evidence is needed to guide therapy, strengthen antimicrobial stewardship, and improve infection prevention. This study aims to address these gaps. Methods and Materials Study Design and Setting A hospital-based cross-sectional study was conducted from September to November 2025 at Asella Teaching and Referral Hospital (ATRH). ATRH is located in Asella town, 165 km southeast of Addis Ababa in the Arsi Zone of Oromia Regional State, Ethiopia. As a major referral center, it serves a catchment population of approximately 3.5 million with 284 inpatient beds. The hospital provides comprehensive services across departments including Pediatrics, Internal Medicine, Surgery, and Oncology, and serves as a teaching institution for medical training. The Department of Pediatrics and Child Health contains 106 beds across emergency, outpatient, neonatal intensive care (NICU), and general wards. The Pediatric Intensive Care Unit (PICU), which shares space with the adult ICU, operates six beds for critically ill patients. It is staffed by 14 pediatricians, 23 residents, 4 general practitioners, and 15 dedicated PICU nurses. Study Population and Eligibility The source population included all pediatric patients aged 29 days to 14 years admitted to the ATRH PICU between July 1, 2020, and June 30, 2025. The study population consisted of those with complete medical records, including microbiological culture and antimicrobial susceptibility results. Patients were excluded if they had incomplete records, if culture specimens were not collected, or if laboratory results were missing. Variables of the Study Dependent Variable : Antimicrobial resistance. Independent Variables : Sociodemographic factors (age, sex, residence), clinical variables (admission diagnosis, comorbidities, prior antibiotic use, invasive procedures), microbiological data (pathogen type, specimen source), and health service variables (length of stay, empirical antibiotic use). Operational Definitions To ensure clarity in the analysis, the following definitions were applied: Antimicrobial Resistance (AMR) : Resistance of bacterial isolates to one or more antibiotics tested using standard susceptibility testing. High-risk AMR : Resistance requiring special emphasis with limited or no treatment options, including MDR, extensively drug-resistant (XDR), pan-drug-resistant (PDR), carbapenem-resistant Enterobacterales (CRE), and ESBL-producing organisms ( 22 , 23 ). High AMR Prevalence : Resistance to at least one first-line antimicrobial agent in ≥ 50% of isolates, or the presence of MDR, XDR, or carbapenem-resistant organisms (CRO) regardless of prevalence ( 24 ). Multidrug-resistant (MDR) : Resistance to at least one agent in three or more antimicrobial classes. Hospital-acquired Infection (HAI) : Infection developing 48 hours after admission that was not present or incubating at the time of admission. Invasive Procedures : Medical procedures requiring entry into the body, such as central venous catheters, urinary catheterization, or mechanical ventilation. Sample Size and Sampling Technique A census of all eligible patients admitted during the five-year study period was performed. Out of 403 total PICU admissions recorded, 217 patients fulfilled the inclusion criteria and were included in the final analysis. Data Collection and Quality Assurance Data were extracted using a structured checklist adapted from the Global Antimicrobial Resistance and Use Surveillance System (GLASS) 2022 and African regional guidance ( 24 ). Four trained general practitioners served as data collectors. To ensure tool clarity, a pre-test was conducted on 5% of the sample (20 children) at Adama Comprehensive Specialized Hospital. Data quality was maintained through daily supervision, the use of unique study codes for anonymity, and PI verification of all collected data. Statistical Analysis Data were cleaned and coded in Epi-Info version 7.2.7.0 before being exported to SPSS version 27 for analysis. Descriptive statistics summarized pathogen prevalence and susceptibility patterns. Binary logistic regression was used to assess associations between AMR and independent variables. Variables with p < 0.25 in bivariate analysis were entered into a multivariable model to control for confounders. Model fitness was verified using the Hosmer-Lemeshow test. Strength of association was measured via Adjusted Odds Ratios (AOR) with 95% Confidence Intervals (CI), with statistical significance set at p ≤ 0.05. Results Socio-demographic and Clinical Characteristics A total of 217 pediatric ICU patients were enrolled in the study. The median age of participants was 12 months (IQR: 6–36), with nearly half (48.8%, n=106) being infants under one year of age . Males comprised 52.5% (n=114) of the cohort, and a significant majority (84.8%, n=184) resided in rural areas. Regarding clinical status, 78.8% (n=171) of the children had normal nutritional status, while 21.2% were affected by acute malnutrition (6.5% moderate and 14.7% severe). Immunization coverage was high, with 80.6% (n=175) fully vaccinated according to the national schedule. The primary indications for PICU admission were pneumonia (40.6%), meningitis (18.0%), and septic shock (10.6%). The median length of PICU stay was 7 days (IQR: 4–11 days), ranging from 1 to 57 days. Approximately half of the patients (49.8%, n=108) required hospitalization for more than seven days. Complications developed in 17.5% (n=38) of patients during their stay, the most frequent being hospital-acquired infections (42.1% of complications) and ventilator-associated pneumonia (23.7%). The overall mortality rate during the PICU stay was 24.0% (n=52). The detailed socio-demographic and clinical profiles of the participants are summarized in Table 1. Table 1: Socio-demographic and Clinical Characteristics of paediatrics ICU Patients at ARTH 2025 (N = 217) Variable Category (n) (%) Sex Male 114 52.5 Female 103 47.5 Age <1 year 106 48.8 1–5 years 74 34.1 5–14 years 37 17.1 Residence Urban 33 15.2 Rural 184 84.8 Nutritional status Normal 171 78.8 Moderate acute malnutrition 14 6.5 Severe acute malnutrition 32 14.7 Immunization status Fully vaccinated 175 80.6 Unvaccinated 19 8.8 Primary reason for PICU admission Pneumonia 88 40.6 Meningitis 39 18.0 Septic shock 23 10.6 Risk factor assessment Recent hospitalization* 36 16.6 Recent antibiotic use* 63 29.0 Invasive device used in PICU 202 93.1 Length of stay in PICU ≤7 days 109 50.2 >7 days 108 49.8 Outcome at discharge Improved/Discharged 165 76.0 Died 52 24.0 Complications in PICU Yes 37 17.5 Microbiological Profiles Positive microbial growth was observed in 52.5% (n=114) of the collected cultures. Gram-negative bacteria were the predominant isolates (54.5%), while Gram-positive bacteria accounted for 45.5%. As detailed in Table 2 , Coagulase-negative staphylococci (CoNS) were the most frequently isolated organisms (40.4%, n=46), followed by Klebsiella species (21.9%, n=25) and Enterobacter species (8.8%, n=10) . Other pathogens identified included Acinetobacter , Escherichia coli , and Pseudomonas species, each representing 4.4% (n=5) of the total isolates. Table 2: Distribution of Identified Pathogens, ARTH 2025 (N = 114) Pathogen (n) (%) Coagulase-negative Staphylococci (CoNS) 46 40.4 Klebsiella species 25 21.9 Enterobacter 10 8.8 Escherichia coli 5 4.4 Acinetobacter 5 4.4 Pseudomonas 5 4.4 Serratia 4 3.5 Streptococcus pneumoniae 3 2.6 Citrobacter 3 2.6 Staphylococcus aureus 2 1.8 Shigella species 2 1.8 Haemophilus influenzae 2 1.8 Fungal yeast 2 1.8 Antimicrobial Susceptibility and Resistance Patterns Antibiotic susceptibility testing (AST) was performed for 66 (57.9%) of the 114 microbial isolates. An alarmingly high proportion of these isolates (92.4%) demonstrated resistance to at least one antibiotic, with only 7.6% remaining fully susceptible. High-risk AMR phenotypes were identified in 68.2% (n=45) of the tested isolates, with the distribution comprising extended-spectrum β-lactamase (ESBL) production in 19.7% (n=13), extensively drug-resistant (XDR) strains in 15.2% (n=10), and both multidrug-resistant (MDR) and pan-drug-resistant (PDR) phenotypes occurring in 13.6% (n=9) each, while carbapenem-resistant Enterobacterales (CRE) accounted for 6.1% (n=4) Resistance was notably high for commonly utilized β-lactam antibiotics, including ampicillin (91.3%), ceftazidime (92.3%), and ceftriaxone (81.0%). High resistance rates were also recorded for non-β-lactam agents such as gentamicin (76.9%) and cotrimoxazole (77.6%). Conversely, amikacin showed the most favorable susceptibility profile (83.0%). Factors Associated with Bacterial Isolates The study evaluated several clinical and demographic variables for their association with bacterial isolates using both bivariate and multivariate logistic regression ( Table 3 ). Length of Stay and Device Use : In the bivariate analysis, both the duration of invasive device use (COR 1.28, 95% CI: 1.05–1.55; p=0.012) and the length of stay in the PICU (COR 1.16, 95% CI: 1.01–1.34; p=0.033) were significantly associated with the presence of isolates. However, in the multivariate model, only the length of PICU stay remained a significant independent predictor (AOR 7.59, 95% CI: 1.10–52.60; p=0.040). Microbiological and Clinical Outcomes : The Gram reaction of bacterial isolates was significant in the crude analysis (COR 10.35, 95% CI: 1.07–99.37; p=0.043) but did not reach significance in the adjusted model (p=0.086). Notably, the outcome at discharge was strongly associated with isolates in both models; patients with specific outcomes were over eight times more likely to have bacterial isolates after adjusting for other variables (AOR 8.22, 95% CI: 1.39–48.63; p=0.020). Complications : While complications developed in the PICU showed a trend toward association, they did not reach statistical significance in either the bivariate (p=0.063) or multivariate (p=0.081) analyses. Table 3: Logistic Regression Analysis of Factors Associated with Bacterial Isolates Variables COR (95% CI) AOR (95% CI) Duration of invasive devices (days) 1.28 (1.05–1.55)* 0.53 (0.09–3.33) Length of stay in PICU (days) 1.16 (1.01–1.34)* 7.59 (1.10–52.60)* Complication developed in PICU 3.64 (0.93–14.23) 5.27 (0.82–34.11) Gram reaction of isolates 10.35 (1.07–99.37)* 22.37 (0.64–781.30) Outcome at discharge 4.80 (1.23–18.63)* 8.22 (1.39–48.63)* Abbreviations: COR, Crude Odds Ratio; AOR, Adjusted Odds Ratio; CI, Confidence Interval; PICU, Pediatric Intensive Care Unit. Note: Statistical significance determined via binary logistic regression. * p<0.05. Discussion This hospital-based cross-sectional study demonstrates a substantial burden of antimicrobial resistance (AMR) among pediatric ICU patients beyond the neonatal period. Of the 217 participants, 52.5% had positive microbial growth, with Gram-negative bacteria (54.5%) slightly predominating over Gram-positive organisms (45.5%). Coagulase-negative staphylococci (CoNS) were the most frequently isolated pathogens, followed by Klebsiella species. Among Gram-negative isolates, Klebsiella and Enterobacter species were predominant, while Escherichia coli , Acinetobacter , and Pseudomonas were less common. These findings are consistent with the WHO GLASS 2025 surveillance data ( 24 ) , the WHO priority bacterial pathogens report (22), and data from the Ethiopian Public Health Institute ( 20 ) , as well as other studies ( 3 , 5 , 8 , 9 , 11 , 25-33 ) , reinforcing the predominance of Gram-negative organisms in pediatric critical care settings. Among tested isolates, 68.2% exhibited high-risk AMR (MDR, XDR, PDR, CRE, or ESBL-producing organisms). This prevalence is comparable to other Ethiopian reports ( 8 , 11 , 20 ) and aligns with WHO estimates indicating high regional resistance rates in Africa (24). However, it exceeds some Sub-Saharan African findings ( 4 ) and other studies ( 30 , 31 , 34-37 ) , while remaining lower than reports from Egypt ( 5 , 38 ) . Prolonged PICU stay (>7 days) was independently associated with high-risk AMR (AOR = 7.59; 95% CI: 1.10–52.60), consistent with findings from Ayder Hospital, Ethiopia ( 19 ) , Minia University Children’s Hospital, Egypt ( 5 ) , and other studies ( 4 , 16 , 37 , 39 , 40 ) . Extended hospitalization likely reflects severe illness, repeated antibiotic exposure, and increased environmental contact, facilitating resistant pathogen acquisition. Mortality was strongly and independently associated with high-risk AMR (AOR = 8.22; 95% CI: 1.39–48.63). This is in agreement with global data identifying AMR as a major contributor to death in low-resource settings ( 24 , 41 ) . Our results align with studies linking mortality to highly resistant pathogens, such as XDR Klebsiella pneumoniae ( 5 , 26 , 31 , 34 , 37 , 42-44 ) , although one specific study noted no significant difference in mortality rates ( 45 ) . This discrepancy may be attributed to variations in sample sizes and the specific resistance profiles of the bacterial isolates studied. Strengths and Limitations Strengths Despite its limitations, this study has several notable strengths. It provides critical, site-specific data on antimicrobial resistance patterns in a Pediatric Intensive Care Unit (PICU) setting, which is essential for tailoring local empirical therapy. The use of both bivariate and multivariate logistic regression allowed for a robust attempt to control for confounding variables, ensuring that the identified associations—such as the link between length of stay and bacterial isolates—are internally valid within this cohort. Furthermore, the inclusion of specific resistance profiles (ESBL, CRE, MDR) offers a detailed microbiological map that can inform future infection control strategies. Limitations Several limitations should be considered when interpreting these findings. First, this study was conducted at a single center using a cross-sectional design, which limits the generalizability of the results and precludes the establishment of causal relationships. Second, antimicrobial susceptibility testing was not performed for coagulase-negative Staphylococci (CoNS), as these were laboratory-classified as contaminants in this specific clinical context. Furthermore, the relatively small sample size resulted in statistical instability for certain variables in the multivariable logistic regression model. Specifically, variables such as Gram reaction exhibited wide confidence intervals, indicating a lack of precision. While these factors did not reach statistical significance in the adjusted model, these wide intervals suggest the study may have been underpowered to detect these specific associations independently. This instability likely reflects the distribution of isolates within specific clinical sub-categories. Conclusion and Recommendations This study highlights a substantial burden of high-risk antimicrobial resistance (68.2%) among pediatric ICU patients. The multivariable logistic regression analysis identified length of PICU stay and outcome at discharge as the primary independent predictors of bacterial isolation. While prolonged use of invasive devices and Gram-negative status showed significant associations in bivariate models, these effects were largely secondary to the duration of hospitalization. These findings emphasize the importance of strengthening national AMR surveillance systems and expanding access to routine antimicrobial susceptibility testing ( 24 ) . Targeted interventions are urgently needed to mitigate the spread of resistant pathogens. Specifically, it is recommended that: Enhanced IPC Strategies : Infection prevention and control measures should be prioritized to reduce the transmission of high-risk profiles like ESBL and CRE. Antimicrobial Stewardship : Site-specific empirical therapy protocols should be developed, focusing on the high prevalence of multidrug-resistant organisms identified in this cohort. Hospitalization Management : Strategies aimed at reducing the length of PICU stay may serve as a critical leverage point in decreasing the incidence of healthcare-associated infections. Abbreviations AOR Adjusted odds ratio AMR Antimicrobial Resistance ATRH Asella Teaching and Referral Hospital BSI Blood Stream Infections CAI Community Acquired Infection CI Confidence Interval CoNS Coagulase-negative staphylococci (CoNS) CRE Carbapenem-Resistant Enterobacteriaceae ESBL Extended-Spectrumβ-lactamase HAI Hospital Acquired Infection KPCs Klebsiella Pneumoniae-associated Carbapenemases MDR Multidrug-Resistant MRSA Methicillin-Resistant Staphylococcus Aureus OR Odds Ratio PICU Pediatric Intensive Care Unit SPSS Statistical Package for the Social Sciences Declarations Ethics approval and consent to participate Ethical clearance was obtained from the Arsi University, College of Health Sciences Ethical Review Committee (Protocol No. CoHS/R/222/2025). A formal letter of cooperation was submitted to the management of Asella Referral and Teaching Hospital to obtain permission for access to pediatric ICU medical records. As the study utilized anonymized secondary data, the requirement for obtaining individual informed consent was not mandated by the Ethical Review Committee. To ensure confidentiality, all data were anonymized and assigned unique identification codes in accordance with the principles of the World Medical Association Declaration of Helsinki. Trial registration : Not applicable . This study was not a clinical trial. Consent for publication Not applicable. Data availability statement Findings from this study are based on hospital medical records from ARTH. The raw data set is attached to this submission; further inquiries regarding data usage may be directed to the corresponding author, subject to Arsi University guidelines. Competing interests The authors declare that they have no competing interests. Funding This research received no external funding. Authors’ contributions AH conceived the study, collected the data, performed the analysis, and drafted the manuscript. TG and ST supervised the study, TG and ST validation, contributed to interpretation of results, and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript. Acknowledgements The authors would like to thank Arsi University College of Health Sciences and ARTH for providing access to PICU records. We also acknowledge the data collectors and hospital staff for their cooperation and support during data extraction. References Murray CJ, Ikuta KS, Sharara F, Swetschinski L, Robles Aguilar G, Gray A, et al. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022;399(10325):629–55. GBD 2021 Antimicrobial Resistance Collaborators. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9163036","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":627153501,"identity":"8ea7e123-c4e0-470c-b213-316095d7a703","order_by":0,"name":"Abdi Hayato","email":"","orcid":"","institution":"Arsi U niversity","correspondingAuthor":false,"prefix":"","firstName":"Abdi","middleName":"","lastName":"Hayato","suffix":""},{"id":627153503,"identity":"26ae3588-4da4-4bba-a5db-4f79ec5ccf00","order_by":1,"name":"Tesfa Gebremeskel","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYJCCD0Asx8be2PgAyODhI6Sch4GBcQaQNubnOdxsABJgI1ZL4swZ6W0SIBGCWuzZ2x82/Pi1jXHDgcS2yq85djJsDMwPH93AZwvPGcPG3r7bzAYHDrbdlt2WDHQYm7FxDj4tEjnsD3h7brMZHGxsuy25jRmohYdNGq8W+ecPG//23OYxOMzYViy5rZ4ILRIMhs08P25LSLYxtjF+3HaYCC1ncgybZRtuG/DzMDZLM247zsPGTMAv7O3HHza++XO7vg3owo8/t1Xb87M3P3yMTwsYMLZBaGYeMElIORj8gWr9QZTqUTAKRsEoGGkAAOVaTI5ZHKZdAAAAAElFTkSuQmCC","orcid":"","institution":"Arsi U niversity","correspondingAuthor":true,"prefix":"","firstName":"Tesfa","middleName":"","lastName":"Gebremeskel","suffix":""},{"id":627153505,"identity":"58bb56d3-055e-451d-a997-de249a70f673","order_by":2,"name":"Solomon Tejineh","email":"","orcid":"","institution":"Arsi University","correspondingAuthor":false,"prefix":"","firstName":"Solomon","middleName":"","lastName":"Tejineh","suffix":""}],"badges":[],"createdAt":"2026-03-18 21:23:53","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9163036/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9163036/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107616695,"identity":"b7bb5bda-c275-40bb-b5ea-ae95c936e310","added_by":"auto","created_at":"2026-04-23 09:15:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":104446,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of antimicrobial resistance patterns among isolated pathogens of pediatric ICU Patients, ARTH (n = 217)\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9163036/v1/5430691c25be9ae768fd5681.png"},{"id":107707276,"identity":"fdf3567f-4a80-4616-bc48-e55d21b853b1","added_by":"auto","created_at":"2026-04-24 09:19:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":486892,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9163036/v1/3a1263a3-0a5c-4d4d-9a54-1d1df9802c17.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bacterial Isolates and Predictors of High-Risk Antimicrobial Resistance Among Pediatric Intensive Care Unit Patients in Ethiopia: A Hospital-Based Cross-Sectional Study","fulltext":[{"header":"Introduction","content":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAntimicrobial resistance (AMR) is a global public health crisis, particularly in low-resource settings where empirical antibiotic use is widespread (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In 2021, AMR was directly responsible for an estimated 1.14\u0026nbsp;million deaths, with projections reaching 1.91\u0026nbsp;million by 2025(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Pediatric intensive care units (PICUs) are high-risk environments for multidrug-resistant organisms (MDROs) due to invasive procedures, frequent broad-spectrum antibiotic use, and patient vulnerability (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfrica bears the highest AMR-associated mortality globally. In 2019, 1.05\u0026nbsp;million deaths were reported in the World Health Organization (WHO) African region, with MRSA and third-generation cephalosporin-resistant \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e as leading contributors (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In Sub-Saharan Africa, AMR prevalence continues to rise, with MRSA and ESBL-producing Enterobacterales reaching 40%. Without intervention, AMR could cause 4.1\u0026nbsp;million annual deaths by 2050 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Ethiopia, studies at University of Gondar and Nekemte hospitals reported multidrug resistance rates of 76% and 56.4%, respectively, with \u003cem\u003eE. coli\u003c/em\u003e, \u003cem\u003eKlebsiella\u003c/em\u003e spp., and \u003cem\u003eS. aureus\u003c/em\u003e as predominant MDR pathogens (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). At Asella Teaching and Referral Hospital (ATRH), neonatal and surgical populations show high resistance rates to first-line antibiotics, highlighting a growing local AMR burden(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInfectious diseases remain a leading cause of morbidity and mortality among children globally, particularly in low-resource settings (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). PICU patients are especially vulnerable to MDR infections due to invasive procedures, being immunocompromised, and prolonged hospitalization (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). AMR increases mortality, prolongs hospital stay, and raises healthcare costs (\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Ethiopia, retrospective data indicate alarming MDR rates, with \u003cem\u003eK. pneumoniae\u003c/em\u003e and \u003cem\u003eAcinetobacter\u003c/em\u003e spp. showing 80% to 84% resistance, and an overall MDR prevalence of 64.3% (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The spread of drug-resistant bacteria challenges antibiotic treatments for widespread bacterial infections; infections from \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, and \u003cem\u003eEnterobacteriaceae\u003c/em\u003e resistant to last-resort carbapenem antibiotics have spread globally (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLimited data are available on microbial profiles, resistance patterns, and risk factors among non-neonatal PICU patients at ATRH. Local evidence is needed to guide therapy, strengthen antimicrobial stewardship, and improve infection prevention. This study aims to address these gaps.\u003c/p\u003e"},{"header":"Methods and Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eA hospital-based cross-sectional study was conducted from September to November 2025 at Asella Teaching and Referral Hospital (ATRH). ATRH is located in Asella town, 165 km southeast of Addis Ababa in the Arsi Zone of Oromia Regional State, Ethiopia. As a major referral center, it serves a catchment population of approximately 3.5\u0026nbsp;million with 284 inpatient beds. The hospital provides comprehensive services across departments including Pediatrics, Internal Medicine, Surgery, and Oncology, and serves as a teaching institution for medical training.\u003c/p\u003e \u003cp\u003eThe Department of Pediatrics and Child Health contains 106 beds across emergency, outpatient, neonatal intensive care (NICU), and general wards. The Pediatric Intensive Care Unit (PICU), which shares space with the adult ICU, operates six beds for critically ill patients. It is staffed by 14 pediatricians, 23 residents, 4 general practitioners, and 15 dedicated PICU nurses.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population and Eligibility\u003c/h3\u003e\n\u003cp\u003eThe \u003cb\u003esource population\u003c/b\u003e included all pediatric patients aged 29 days to 14 years admitted to the ATRH PICU between July 1, 2020, and June 30, 2025. The \u003cb\u003estudy population\u003c/b\u003e consisted of those with complete medical records, including microbiological culture and antimicrobial susceptibility results. Patients were \u003cb\u003eexcluded\u003c/b\u003e if they had incomplete records, if culture specimens were not collected, or if laboratory results were missing.\u003c/p\u003e\n\u003ch3\u003eVariables of the Study\u003c/h3\u003e\n\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eDependent Variable\u003c/b\u003e: Antimicrobial resistance.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eIndependent Variables\u003c/b\u003e: Sociodemographic factors (age, sex, residence), clinical variables (admission diagnosis, comorbidities, prior antibiotic use, invasive procedures), microbiological data (pathogen type, specimen source), and health service variables (length of stay, empirical antibiotic use).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003eOperational Definitions\u003c/h3\u003e\n\u003cp\u003eTo ensure clarity in the analysis, the following definitions were applied:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eAntimicrobial Resistance (AMR)\u003c/b\u003e: Resistance of bacterial isolates to one or more antibiotics tested using standard susceptibility testing.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eHigh-risk AMR\u003c/b\u003e: Resistance requiring special emphasis with limited or no treatment options, including MDR, extensively drug-resistant (XDR), pan-drug-resistant (PDR), carbapenem-resistant Enterobacterales (CRE), and ESBL-producing organisms (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eHigh AMR Prevalence\u003c/b\u003e: Resistance to at least one first-line antimicrobial agent in \u0026ge;\u0026thinsp;50% of isolates, or the presence of MDR, XDR, or carbapenem-resistant organisms (CRO) regardless of prevalence (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eMultidrug-resistant (MDR)\u003c/b\u003e: Resistance to at least one agent in three or more antimicrobial classes.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eHospital-acquired Infection (HAI)\u003c/b\u003e: Infection developing 48 hours after admission that was not present or incubating at the time of admission.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eInvasive Procedures\u003c/b\u003e: Medical procedures requiring entry into the body, such as central venous catheters, urinary catheterization, or mechanical ventilation.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003eSample Size and Sampling Technique\u003c/h3\u003e\n\u003cp\u003eA census of all eligible patients admitted during the five-year study period was performed. Out of 403 total PICU admissions recorded, 217 patients fulfilled the inclusion criteria and were included in the final analysis.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Collection and Quality Assurance\u003c/h2\u003e \u003cp\u003eData were extracted using a structured checklist adapted from the Global Antimicrobial Resistance and Use Surveillance System (GLASS) 2022 and African regional guidance (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Four trained general practitioners served as data collectors. To ensure tool clarity, a pre-test was conducted on 5% of the sample (20 children) at Adama Comprehensive Specialized Hospital. Data quality was maintained through daily supervision, the use of unique study codes for anonymity, and PI verification of all collected data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData were cleaned and coded in Epi-Info version 7.2.7.0 before being exported to SPSS version 27 for analysis. Descriptive statistics summarized pathogen prevalence and susceptibility patterns. Binary logistic regression was used to assess associations between AMR and independent variables. Variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.25 in bivariate analysis were entered into a multivariable model to control for confounders. Model fitness was verified using the Hosmer-Lemeshow test. Strength of association was measured via Adjusted Odds Ratios (AOR) with 95% Confidence Intervals (CI), with statistical significance set at p\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003ch4\u003eSocio-demographic and Clinical Characteristics\u003c/h4\u003e\n\u003cp\u003eA total of 217 pediatric ICU patients were enrolled in the study. The median age of participants was 12 months (IQR: 6\u0026ndash;36), with nearly half (48.8%, n=106) being infants under one year of age\u0026nbsp;. Males comprised 52.5% (n=114) of the cohort, and a significant majority (84.8%, n=184) resided in rural areas.\u003c/p\u003e\n\u003cp\u003eRegarding clinical status, 78.8% (n=171) of the children had normal nutritional status, while 21.2% were affected by acute malnutrition (6.5% moderate and 14.7% severe). Immunization coverage was high, with 80.6% (n=175) fully vaccinated according to the national schedule. The primary indications for PICU admission were pneumonia (40.6%), meningitis (18.0%), and septic shock (10.6%).\u003c/p\u003e\n\u003cp\u003eThe median length of PICU stay was 7 days (IQR: 4\u0026ndash;11 days), ranging from 1 to 57 days. Approximately half of the patients (49.8%, n=108) required hospitalization for more than seven days. Complications developed in 17.5% (n=38) of patients during their stay, the most frequent being hospital-acquired infections (42.1% of complications) and ventilator-associated pneumonia (23.7%). The overall mortality rate during the PICU stay was 24.0% (n=52). The detailed socio-demographic and clinical profiles of the participants are summarized in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Socio-demographic and Clinical Characteristics of paediatrics ICU Patients at ARTH 2025 (N = 217)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e(n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e47.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;1 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e48.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u0026ndash;5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u0026ndash;14 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e84.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNutritional status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e78.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eModerate acute malnutrition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSevere acute malnutrition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eImmunization status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFully vaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e80.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnvaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrimary reason for PICU admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePneumonia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMeningitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSeptic shock\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRisk factor assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRecent hospitalization*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRecent antibiotic use*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInvasive device used in PICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e93.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLength of stay in PICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026le;7 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026gt;7 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOutcome at discharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eImproved/Discharged\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e76.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDied\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eComplications in PICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eMicrobiological Profiles\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePositive microbial growth was observed in 52.5% (n=114) of the collected cultures. Gram-negative bacteria were the predominant isolates (54.5%), while Gram-positive bacteria accounted for 45.5%.\u003c/p\u003e\n\u003cp\u003eAs detailed in \u003cstrong\u003eTable 2\u003c/strong\u003e, \u003cem\u003eCoagulase-negative staphylococci\u003c/em\u003e (CoNS) were the most frequently isolated organisms (40.4%, n=46), followed by \u003cem\u003eKlebsiella\u003c/em\u003e species (21.9%, n=25) and \u003cem\u003eEnterobacter\u003c/em\u003e species (8.8%, n=10) . Other pathogens identified included \u003cem\u003eAcinetobacter\u003c/em\u003e, \u003cem\u003eEscherichia coli\u003c/em\u003e, and \u003cem\u003ePseudomonas\u003c/em\u003e species, each representing 4.4% (n=5) of the total isolates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Distribution of Identified Pathogens, ARTH 2025 (N = 114)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePathogen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eCoagulase-negative Staphylococci\u003c/em\u003e (CoNS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eKlebsiella\u003c/em\u003e species\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eEnterobacter\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eAcinetobacter\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ePseudomonas\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eSerratia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eCitrobacter\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eShigella\u003c/em\u003e species\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eHaemophilus influenzae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFungal yeast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAntimicrobial Susceptibility and Resistance Patterns\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAntibiotic susceptibility testing (AST) was performed for 66 (57.9%) of the 114 microbial isolates. An alarmingly high proportion of these isolates (92.4%) demonstrated resistance to at least one antibiotic, with only 7.6% remaining fully susceptible.\u003c/p\u003e\n\u003cp\u003eHigh-risk AMR phenotypes were identified in 68.2% (n=45) of the tested isolates, with the distribution comprising extended-spectrum \u0026beta;-lactamase (ESBL) production in 19.7% (n=13), extensively drug-resistant (XDR) strains in 15.2% (n=10), and both multidrug-resistant (MDR) and pan-drug-resistant (PDR) phenotypes occurring in 13.6% (n=9) each, while carbapenem-resistant Enterobacterales (CRE) accounted for 6.1% (n=4)\u003c/p\u003e\n\u003cp\u003eResistance was notably high for commonly utilized \u0026beta;-lactam antibiotics, including ampicillin (91.3%), ceftazidime (92.3%), and ceftriaxone (81.0%). High resistance rates were also recorded for non-\u0026beta;-lactam agents such as gentamicin (76.9%) and cotrimoxazole (77.6%). Conversely, amikacin showed the most favorable susceptibility profile (83.0%).\u003c/p\u003e\n\u003cp\u003eFactors Associated with Bacterial Isolates\u003c/p\u003e\n\u003cp\u003eThe study evaluated several clinical and demographic variables for their association with bacterial isolates using both bivariate and multivariate logistic regression (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003e\u003cstrong\u003eLength of Stay and Device Use\u003c/strong\u003e: In the bivariate analysis, both the duration of invasive device use (COR 1.28, 95% CI: 1.05\u0026ndash;1.55; p=0.012) and the length of stay in the PICU (COR 1.16, 95% CI: 1.01\u0026ndash;1.34; p=0.033) were significantly associated with the presence of isolates. However, in the multivariate model, only the length of PICU stay remained a significant independent predictor (AOR 7.59, 95% CI: 1.10\u0026ndash;52.60; p=0.040).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMicrobiological and Clinical Outcomes\u003c/strong\u003e: The Gram reaction of bacterial isolates was significant in the crude analysis (COR 10.35, 95% CI: 1.07\u0026ndash;99.37; p=0.043) but did not reach significance in the adjusted model (p=0.086). Notably, the outcome at discharge was strongly associated with isolates in both models; patients with specific outcomes were over eight times more likely to have bacterial isolates after adjusting for other variables (AOR 8.22, 95% CI: 1.39\u0026ndash;48.63; p=0.020).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eComplications\u003c/strong\u003e: While complications developed in the PICU showed a trend toward association, they did not reach statistical significance in either the bivariate (p=0.063) or multivariate (p=0.081) analyses.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Logistic Regression Analysis of Factors Associated with Bacterial Isolates\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\" width=\"618\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDuration of invasive devices (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.28 (1.05\u0026ndash;1.55)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.53 (0.09\u0026ndash;3.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLength of stay in PICU (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.16 (1.01\u0026ndash;1.34)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.59 (1.10\u0026ndash;52.60)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eComplication developed in PICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.64 (0.93\u0026ndash;14.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.27 (0.82\u0026ndash;34.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGram reaction of isolates\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.35 (1.07\u0026ndash;99.37)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.37 (0.64\u0026ndash;781.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOutcome at discharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.80 (1.23\u0026ndash;18.63)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.22 (1.39\u0026ndash;48.63)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e COR, Crude Odds Ratio; AOR, Adjusted Odds Ratio; CI, Confidence Interval; PICU, Pediatric Intensive Care Unit.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e Statistical significance determined via binary logistic regression. * p\u0026lt;0.05.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis hospital-based cross-sectional study demonstrates a substantial burden of antimicrobial resistance (AMR) among pediatric ICU patients beyond the neonatal period. Of the 217 participants, 52.5% had positive microbial growth, with Gram-negative bacteria (54.5%) slightly predominating over Gram-positive organisms (45.5%). \u003cem\u003eCoagulase-negative staphylococci\u003c/em\u003e (CoNS) were the most frequently isolated pathogens, followed by \u003cem\u003eKlebsiella\u003c/em\u003e species. Among Gram-negative isolates, \u003cem\u003eKlebsiella\u003c/em\u003e and \u003cem\u003eEnterobacter\u003c/em\u003e species were predominant, while \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003eAcinetobacter\u003c/em\u003e, and \u003cem\u003ePseudomonas\u003c/em\u003e were less common. These findings are consistent with the WHO GLASS 2025 surveillance data\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e24\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e, the WHO priority bacterial pathogens report (22), and data from the Ethiopian Public Health Institute \u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e20\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e, as well as other studies\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e25-33\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e, reinforcing the predominance of Gram-negative organisms in pediatric critical care settings.\u003c/p\u003e\n\u003cp\u003eAmong tested isolates, 68.2% exhibited high-risk AMR (MDR, XDR, PDR, CRE, or ESBL-producing organisms). This prevalence is comparable to other Ethiopian reports \u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e20\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003eand aligns with WHO estimates indicating high regional resistance rates in Africa (24). However, it exceeds some Sub-Saharan African findings \u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e and other studies \u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e30\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e31\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e34-37\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e, while remaining lower than reports from Egypt\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e38\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eProlonged PICU stay (\u0026gt;7 days) was independently associated with high-risk AMR (AOR = 7.59; 95% CI: 1.10\u0026ndash;52.60), consistent with findings from Ayder Hospital, Ethiopia \u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e19\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e, Minia University Children\u0026rsquo;s Hospital, Egypt \u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e, and other studies \u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e16\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e37\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e39\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e40\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e. Extended hospitalization likely reflects severe illness, repeated antibiotic exposure, and increased environmental contact, facilitating resistant pathogen acquisition.\u003c/p\u003e\n\u003cp\u003eMortality was strongly and independently associated with high-risk AMR (AOR = 8.22; 95% CI: 1.39\u0026ndash;48.63). This is in agreement with global data identifying AMR as a major contributor to death in low-resource settings\u0026nbsp;\u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e24\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e41\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e. Our results align with studies linking mortality to highly resistant pathogens, such as XDR \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e26\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e31\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e34\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e37\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e42-44\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e, although one specific study noted no significant difference in mortality rates\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e45\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e. This discrepancy may be attributed to variations in sample sizes and the specific resistance profiles of the bacterial isolates studied.\u003c/p\u003e\n\u003ch3\u003eStrengths and Limitations\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths\u003c/strong\u003e Despite its limitations, this study has several notable strengths. It provides critical, site-specific data on antimicrobial resistance patterns in a Pediatric Intensive Care Unit (PICU) setting, which is essential for tailoring local empirical therapy. The use of both bivariate and multivariate logistic regression allowed for a robust attempt to control for confounding variables, ensuring that the identified associations\u0026mdash;such as the link between length of stay and bacterial isolates\u0026mdash;are internally valid within this cohort. Furthermore, the inclusion of specific resistance profiles (ESBL, CRE, MDR) offers a detailed microbiological map that can inform future infection control strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e Several limitations should be considered when interpreting these findings. First, this study was conducted at a single center using a cross-sectional design, which limits the generalizability of the results and precludes the establishment of causal relationships. Second, antimicrobial susceptibility testing was not performed for coagulase-negative Staphylococci (CoNS), as these were laboratory-classified as contaminants in this specific clinical context.\u003c/p\u003e\n\u003cp\u003eFurthermore, the relatively small sample size resulted in statistical instability for certain variables in the multivariable logistic regression model. Specifically, variables such as Gram reaction exhibited wide confidence intervals, indicating a lack of precision. While these factors did not reach statistical significance in the adjusted model, these wide intervals suggest the study may have been underpowered to detect these specific associations independently. This instability likely reflects the distribution of isolates within specific clinical sub-categories.\u003c/p\u003e"},{"header":"Conclusion and Recommendations","content":"\u003cp\u003eThis study highlights a substantial burden of high-risk antimicrobial resistance (68.2%) among pediatric ICU patients. The multivariable logistic regression analysis identified \u003cstrong\u003elength of PICU stay\u003c/strong\u003e and \u003cstrong\u003eoutcome at discharge\u003c/strong\u003e as the primary independent predictors of bacterial isolation. While prolonged use of invasive devices and Gram-negative status showed significant associations in bivariate models, these effects were largely secondary to the duration of hospitalization. These findings emphasize the importance of strengthening national AMR surveillance systems and expanding access to routine antimicrobial susceptibility testing\u0026nbsp;\u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e24\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eTargeted interventions are urgently needed to mitigate the spread of resistant pathogens. Specifically, it is recommended that:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eEnhanced IPC Strategies\u003c/strong\u003e: Infection prevention and control measures should be prioritized to reduce the transmission of high-risk profiles like ESBL and CRE.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAntimicrobial Stewardship\u003c/strong\u003e: Site-specific empirical therapy protocols should be developed, focusing on the high prevalence of multidrug-resistant organisms identified in this cohort.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eHospitalization Management\u003c/strong\u003e: Strategies aimed at reducing the length of PICU stay may serve as a critical leverage point in decreasing the incidence of healthcare-associated infections.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdjusted odds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAMR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAntimicrobial Resistance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eATRH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAsella Teaching and Referral Hospital\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBSI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBlood Stream Infections\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCommunity Acquired Infection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCoNS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCoagulase-negative staphylococci (CoNS)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCarbapenem-Resistant Enterobacteriaceae\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eESBL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExtended-Spectrumβ-lactamase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHAI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHospital Acquired Infection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKPCs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKlebsiella Pneumoniae-associated Carbapenemases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMDR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMultidrug-Resistant\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRSA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMethicillin-Resistant Staphylococcus Aureus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePediatric Intensive Care Unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPSS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance was obtained from the Arsi University, College of Health Sciences Ethical Review Committee (Protocol No. CoHS/R/222/2025). A formal letter of cooperation was submitted to the management of Asella Referral and Teaching Hospital to obtain permission for access to pediatric ICU medical records. As the study utilized anonymized secondary data, the requirement for obtaining individual informed consent was not mandated by the Ethical Review Committee. To ensure confidentiality, all data were anonymized and assigned unique identification codes in accordance with the principles of the World Medical Association Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration\u003c/strong\u003e: \u003cstrong\u003eNot applicable\u003c/strong\u003e. This study was not a clinical trial.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFindings from this study are based on hospital medical records from ARTH. The raw data set is attached to this submission; further inquiries regarding data usage may be directed to the corresponding author, subject to Arsi University guidelines.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAH conceived the study, collected the data, performed the analysis, and drafted the manuscript. TG and ST supervised the study, TG and ST validation, contributed to interpretation of results, and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Arsi University College of Health Sciences and ARTH for providing access to PICU records. We also acknowledge the data collectors and hospital staff for their cooperation and support during data extraction.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMurray CJ, Ikuta KS, Sharara F, Swetschinski L, Robles Aguilar G, Gray A, et al. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022;399(10325):629\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGBD 2021 Antimicrobial Resistance Collaborators. Global burden of bacterial antimicrobial resistance 1990\u0026ndash;2021: a systematic analysis with forecasts to 2050. 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Bacterial Profile and Their Antibiotic Resistance Patterns from Blood Culture and Associated Risk Factors in ICU at the University Of Gondar. Ethiop J Health Biomed Sci. 2020;10(1):65\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiriba A, Gizaw S, Alemu F, et al. Prevalence, antimicrobial sensitivity patterns and associated factors of urinary tract infection among patients attending Nekemte Comprehensive Specialized Hospital. BMC Infect Dis. 2025;25(1):474.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAtay G, Kara M, Sutcu M, et al. Resistant gram-negative infections in a pediatric intensive care unit: a retrospective study in a tertiary care center. Turk Pediatri Ars. 2019;54(2):105\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWattal C, Goel N. Pediatric Blood Cultures and Antibiotic Resistance: An Overview. 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Curr Opin Infect Dis. 2015;28(4):307\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCassini A, H\u0026ouml;gberg LD, Plachouras D, et al. Attributable deaths caused by infections with antibiotic-resistant bacteria in the EU. Lancet Infect Dis. 2019;19(1):56\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Global Antimicrobial Resistance and Use Surveillance System (GLASS) Report: 2023. Geneva: WHO; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeshah D, Desta A, Belay G, et al. Antimicrobial Resistance and Associated Risk Factors of Gram-Negative Bacterial Bloodstream Infections in Tikur Anbessa Specialized Hospital, Addis Ababa. Infect Drug Resist. 2022;15:5043\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGadisa BE, Fekede E, Adu B, Danso J. Epidemiology, antimicrobial resistance profile, and management of carbapenem resistant Klebsiella pneumoniae in children under 5 in Ethiopia. BMC Infect Dis. 2024;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang N, Zhang X, Guo Y, et al. Clinical and metagenomic predicted antimicrobial resistance in pediatric critically ill patients. Ann Clin Microbiol Antimicrob. 2024;23(1):107.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaylor NR, Atun R, Zhu N, et al. Estimating the burden of antimicrobial resistance: a systematic review of methods used in studies of cost and mortality. J Antimicrob Chemother. 2018;73(suppl4):iv27\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Antimicrobial resistance, Pediatric ICU, Microbial profile, Ethiopia, High-risk AMR","lastPublishedDoi":"10.21203/rs.3.rs-9163036/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9163036/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Antimicrobial resistance (AMR) is a major threat in pediatric intensive care units (PICUs). Data on resistance patterns in non-neonatal pediatric cohorts in Ethiopia remain scarce. This study assessed Bacterial Isolates and Predictors of High-Risk Antimicrobial Resistance Among PICU at Asella Teaching and Referral Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A five-year (2020–2025) hospital-based cross-sectional study was conducted among patients aged 29 days to 14 years. Data were extracted from records using a structured checklist. Independent predictors of high-risk AMR were identified via multivariable logistic regression (p\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong 217 participants, 52.5% had positive microbial growth. Gram-negative bacteria accounted for 54.5% of isolates, slightly predominating over Gram-positive organisms. Among 66 isolates, high-risk AMR prevalence was 68.2%, including extended-spectrum beta-lactamase (ESBL) (19.7%) and extensively drug-resistant (XDR) (15.2%) strains. Multivariable analysis identified length of PICU stay (AOR 7.59, 95% CI: 1.10–52.60; p=0.040) and adverse outcome at discharge (AOR 8.22, 95% CI: 1.39–48.63; p=0.020) as independent predictors. Invasive device duration and Gram-negative status were significant only in bivariate models.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e High-risk AMR (68.2%) is independently associated with prolonged hospitalization and adverse outcomes. These findings necessitate strengthened infection control, enhanced microbiological surveillance, and robust antimicrobial stewardship to mitigate multidrug-resistant pathogens in high-acuity settings.\u003c/p\u003e","manuscriptTitle":"Bacterial Isolates and Predictors of High-Risk Antimicrobial Resistance Among Pediatric Intensive Care Unit Patients in Ethiopia: A Hospital-Based Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 09:15:35","doi":"10.21203/rs.3.rs-9163036/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-15T15:23:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-06T12:04:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T06:11:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-01T14:04:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265128090084461179648716041052135117519","date":"2026-04-28T08:28:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"218464439497189627100322335720497027611","date":"2026-04-25T09:00:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-20T18:42:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"139710583342034207883453613856289595012","date":"2026-04-20T01:11:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"334673175416876269537771439231069981372","date":"2026-04-15T10:40:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-14T19:37:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-24T21:13:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-23T01:23:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-23T01:23:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2026-03-18T21:13:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"75ae9245-71df-4bbf-8754-ea88cb7e44a4","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-15T15:23:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-06T12:04:05+00:00","index":63,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T06:11:37+00:00","index":62,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-01T14:04:25+00:00","index":61,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T15:38:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 09:15:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9163036","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9163036","identity":"rs-9163036","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}