Epidemiology and drug resistance analysis of bloodstream infections in intensive care unit from a children's medical center in eastern China for six consecutive years

Epidemiology and drug resistance analysis of bloodstream infections in intensive care unit from a children's medical center in eastern China for six consecutive years | 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 Epidemiology and drug resistance analysis of bloodstream infections in intensive care unit from a children's medical center in eastern China for six consecutive years Huijiang Shao, Xin Zhang, Yang Li, Yuanyuan Gao, Yunzhong Wang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3460595/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Jan, 2024 Read the published version in International Microbiology → Version 1 posted 7 You are reading this latest preprint version Abstract Background Children with severe basic diseases and low immunity in the intensive care unit (ICU) are usually in critical condition. It is important to help clinicians choose the appropriate empirical antibiotic therapy for clinical infection control. Methods 281 children with bloodstream infection (BSI) were retrospectively analyzed. Statistical software was used to compare and analyse the basic data, pathogenic information, and drug resistance of the main bacteria. Results A total of 328 strains were detected, including gram-positive bacteria (223, 68%), mainly including coagulase-negative staphylococci (CoNS), gram-negative bacteria (91, 27.7%), fungi (14, 4.3%). There were 243 cases of single pathogen infection and 38 cases of mixed pathogen infection. Results of binary logistic regression analysis showed that lengths of hospitalization of 0～<30d was an independent risk factor for mixed infection, and length of hospitalization of 15～<60d was an independent risk factor related to death. Compared with Escherichia coli , the proportion of extended-spectrum β-lactamases (ESBLs) was higher producing by Klebsiella pneumoniae , and its resistance to some β-lactamides, quinolones antibiotics were lower. 27 isolates of multi-drug resistant (MDR) bacteria were detected, among which carbapenem-resistant Acinetobacter baumannii (CRAB) accounted for the highest proportion (13, 48.2%). Conclusion CoNS was the principal pathogen of BSI in the intensive care unit (ICU) of children, and Escherichia coli was the most common gram-negative pathogen. It is necessary to continuously monitor patients with positive blood culture, pay special attention to the detected MDR bacteria, and strengthen the application management of antibiotics and the prevention and control of nosocomial infection. Children Pathogen ICU Bloodstream infection Drug resistance MDR bacteria Figures Figure 1 Figure 2 1 Introduction Bloodstream infection (BSI) is a systemic infectious disease caused by pathogenic microorganisms entering the blood system, which can be manifested as bacteremia, or even sepsis(Gouel-Cheron et al. 2022 ). Sepsis is a serious systemic inflammatory reaction, which is one of the main causes of death in children (Zhang et al. 2022 ). Children in the intensive care unit (ICU) are usually in critical condition, with severe basic diseases and low immunity. In addition to various invasive operations, they are more prone to infection (Yan et al. 2021 ). According to statistics, the hospital infection of children in the ICU is about 2–5 times that of children in general wards (Bassetti et al. 2015 ; Bammigatti et al. 2017 ). Once a child suffers from BSI, it will not only aggravate the illness and increase the pain, but also lead to a longer hospital stays, significantly increase hospital costs, seriously threaten the life of the child, and increase the family burden of the child (Tran et al. 2017 ; Zhu et al. 2019 ). In recent years, the incidence and mortality of BSI remain high. Studies have shown that BSI is the most common hospital-acquired infection in the ICU, with a mortality of 18.6%~52.3% (Shime et al. 2012 ; Marsillio et al. 2015 ; Schwab et al. 2018 ; Markwart et al. 2020 ). Therefore, early and appropriate antibiotic therapy can improve the prognosis of children with sepsis in the ICU. Blood culture is considered to be the most effective laboratory method for diagnosing BSI. Pathogens are identified through blood culture results in clinical practice, and rational drug use is based on drug sensitivity results. However, the positive rate of blood culture is low and the reporting time of positive and drug sensitivity results is late, so it is difficult to guide the selection of antibiotics in a timely and correct manner. Therefore, it is of great significance for clinicians to accurately evaluate the condition of children with BSI and timely grasp the characteristics and drug resistance of pathogens for empirically selecting antibiotics and improving the success rate of infection treatment. There have been previous studies on BSI in ICU, but infection control and antimicrobial management policies are different in different countries, regions and hospitals, and the clinical characteristics of BSI pathogens are quite different (Timsit et al. 2020 ; Xie et al. 2020 ). The data survey found that there was no report on the characteristics and drug resistance of pathogenic bacteria of BSI in ICU children in the Suzhou area in recent six years. Therefore, the purpose of this study is to retrospectively analyze the distribution of pathogenic bacteria, death risk factors and drug resistance of children with BSI admitted to the ICU of Children's Hospital Affiliated to Suzhou University from January 2016 to December 2021, to guide clinicians to select appropriate empirical treatment schemes by observing the clinical symptoms of children and combining research data before receiving feedback from the laboratory to reduce the problem of antibiotic abuse and the producing of MDR bacteria. 2 Materials and Methods 2.1 Study Site This study was conducted at Children's Hospital of Soochow University, which is a children's medical centre in East China and the only provincial tertiary children's hospital in Jiangsu Province. Children's Hospital of Soochow University has 1500 beds and serves > 70,000 inpatients and > 2 million outpatients annually. This study was approved by the Ethics Committee of Children's Hospital of Soochow University (No. 2021CS158). 2.2 General information 281 cases with BSI admitted to the ICU of Children's Hospital of Soochow University from January 2016 to December 2021 were selected as the study subjects. Among them, 167 cases were male (59.4%), age (3.8 ± 4.4) years old, and 114 cases were female (40.6%), age (3.9 ± 4.1) years old. The ratio of male to female was 1.5: 1. The basic diseases were mainly hematological tumor diseases (74, 26.3%), respiratory system diseases (57, 20.3%), heart diseases (51, 18.2%), and central nervous system disease (39, 13.9%). The children were divided into two groups according to the number of pathogenic bacteria isolated from blood culture samples: the children with only one kind of pathogenic bacteria in blood culture samples were included in the single infection group; The children with two or more pathogens cultured at the same time or two or more pathogens isolated for several times in a row were included in the mixed infection group. There were 243 cases in the single infection group and 38 cases in the mixed infection group. Compared with the mixed infection group, the age of children in the single infection group (age: 3.7 ± 4.2 vs 4.6 ± 5.0, t = 1.095, P = 0.279) had no significant difference. 2.3 Diagnostic criteria for BSI Regarding to the national diagnostic standard for hospital infection ( Diagnostic criteria for nosocomial infection (Trial) , 2003) and the latest definition and diagnostic standard for hospital infection of CDC/NHSN in the United States ( CDC/NHSN , 2017): the patient isolated pathogenic bacteria from blood samples during hospitalization and had any of the following symptoms or signs: (1) Temperature > 38℃ or < 36℃, accompanied by chills; (2) Invasive portals or migratory lesions of pathogens can be found from patients; (3) The patient had obvious symptoms of systemic infection and poisoning but no clear infection focus; (4) The systolic blood pressure of the patient is lower than 90mmHg or more than 40mmHg lower than the original systolic blood pressure. Exclusion criteria: (1) incomplete case data, (2) elimination of contaminated strains, and (3) repeated strains detected continuously in the same child. 2.4 Strain identification and drug sensitivity test Blood culture bottles were placed into the instrument for incubation. The positive samples were transferred to the culture plate and incubated at 37℃ for 18–24 h (5% CO 2 ). The colonies were identified by the mass spectrometer. The automatic bacterial detection and analysis system and Kirby-Bauer (KB) method were used for the drug sensitivity test. The results were judged according to the latest standards of the Clinical Laboratory Standardization Association. Extended-spectrum β-lactamases (ESBLs) were determined by the automatic bacterial detection and analysis system. The judgment results were obtained according to its expert system. The quality control strains were Escherichia coli (ATCC 25922), Pseudomonas aeruginosa (ATCC 27853), Staphylococcus aureus (ATCC 25923 and ATCC 29213), Enterococcus faecalis (ATCC 29212) and Streptococcus pneumoniae (ATCC 49619), which were purchased from the clinical testing center of the National Health Commission. 2.5 Data analysis SPSS 20.0 and WHONET 5.6 (WHO Collaborating Centre for Surveillance of Antimicrobial Resistance, Boston, MA, USA) was used to analyze data. The measurement data were expressed by the mean and standard deviation (‾x ± s). The t -test was used in univariate analysis. The counting data were expressed as the number of cases (n) and rate (%). Mon-factor analysis adopted the χ 2 test. Multi-factor analysis adopted binary logistic regression analysis, with P < 0.05 as the difference. 3 Results 3.1 Annual distribution of pathogenic bacteria [n (%)] In Fig. 1 , Gram-positive bacteria are the main pathogenic bacteria causing BSI in children living in the ICU, and the positive rate has always been higher than that of gram-negative bacteria and fungi. Among them, coagulase-negative staphylococcus (CoNS) is the most common BSI in children. See Supplementary materials Table S1 for details. The positive rate of gram-positive/negative pathogens and fungi each year is shown in Fig. 2 . 3.2 Comparative analysis of clinical characteristics with single pathogen infection and mixed pathogen infection [n (%)] As shown in Table 1 , it was found that the infection was mainly caused by a single pathogen, and the proportion of male aged 0 ~ < 3Y with basic diseases such as hematological tumor disease, respiratory system disease, heart disease, and central nervous system disease was higher. Table 1 Single factor analysis of mixed infection risk factors of children in ICU with BSI [n (%)] Group Single infection group(n = 243) Mixed infection group(n = 38) c 2 P Gender Male 144(59.3) 23(60.5) 0.022 0.882 Female 99(40.7) 15(39.5) Age 0～<3Y* 139(57.2) 20(52.6) 0.536 0.765 3～<14Y 96(39.5) 16(42.1) 14～<18Y 8(3.3) 2(5.3) Year 2016 32(13.2) 5(13.2) 5.112 0.402 2017 33(13.6) 0(0) 2018 44(18.1) 8(21.1) 2019 42(17.3) 4(10.5) 2020 45(18.5) 7(18.4) 2021 47(19.3) 14(36.8) Survival status Death 19(7.8) 3(7.9) 0 0.987 Survival 224(92.2) 35(92.1) Length of hospitalization 0～<15d* 95(39.1) 3(7.9) 36.944 < 0.001 15～<30d 77(31.7) 6(15.8) 30～<60d 61(25.1) 21(55.3) ≧ 60d 10(4.1) 8(21.1) Main basic diseases Hematological tumor disease 63(25.9) 11(29) 5.945 0.312 Respiratory diseases 45(18.5) 12(31.6) Heart disease 44(18.1) 7(18.4) Central nervous system diseases 37(15.2) 2(5.3) Traumatic disease 12(4.9) 4(10.5) Digestive system diseases 13(5.4) 2(5.3) *: Y means age, d means day. 3.3 Comparative analysis of clinical characteristics with survival group and death group [n (%)] Further analysis of infection-related risk factors in the survival group and the death group showed that there was a statistically significant difference ( P < 0.05) between at length of hospitalization and pathogen type (Table 2 ). Table 2 Single factor analysis of death risk factors of children in ICU with BSI [n (%)] Group Survival group (n = 259) Death group (n = 22) c 2 P Gender Male 155(59.9) 12(54.6) 0.236 0.627 Female 104(40.2) 10(54.5) Age 0～<3Y* 151(58.3) 8(36.4) 5.960 0.051 3～<14Y 98(37.8) 14(63.6) 14～<18Y 10(3.9) 0(0) Length of hospitalization 0～<15d* 85(32.8) 13(59.1) 15.218 0.002 15～<30d 82(31.7) 1(4.6) 30～<60d 78(30.1) 4(18.2) ≧ 60d 14(5.4) 4(18.2) Infection type Single infection group 224(86.5) 19(86.4) 0 0.987 Mixed infection group 35(13.5) 3(13.6) Pathogen type Gram-positive bacteria 178(69) 7(31.8) 16.104 0.001 Gram-negative bacteria 58(22.4) 12(54.6) Fungi 10(3.9) 0(0) Mixed infection 13(5.0) 3(13.6) Main basic diseases Hematological tumor disease 64(24.7) 10(45.5) 10.814 0.055 Respiratory diseases 55(21.2) 2(9.1) Heart disease 45(17.4) 6(27.3) Central nervous system diseases 39(15.1) 0(0) Digestive system diseases 15(5.8) 0(0) Traumatic disease 14(5.4) 2(9.1) *: Y means age, d means day 3.4 Multi-factor analysis of mixed infection and death risk factors of children in ICU with BSI To further explore the meaningful indicators of univariate analysis in Tables 1 and 2 , multi-factor analysis on the factors of mixed infection and death risk factors of children in ICU with BSI were conducted in Table 3 . Table 3 Multi-factor analysis of meaningful indicators Variable B SE Waldc 2 P OR (95% CI) Mixed infection Length of hospitalization - - 27.434 < 0.001 - 0～<15d* 3.232 0.754 18.364 < 0.001 25.333 (5.777-111.094) 15～<30d 2.329 0.636 13.404 < 0.001 10.267 (2.951–35.719) 30～<60d 0.843 0.538 2.460 0.117 2.324 (0.810–6.665) Constant 0.223 0.474 0.221 0.638 1.250 Death group Length of hospitalization - - 11.646 0.009 - 0～<15d* 0.370 0.797 0.216 0.642 1.448 (0.303–6.910) 15～<30d 3.030 1.249 6.001 0.014 21.334 (1.844-246.873) 30～<60d 1.772 0.854 4.308 0.038 5.882 (1.104–31.346) Pathogen type 0.650 0.741 0.767 0.381 1.915 Gram-positive bacteria 1.559 0.905 2.966 0.085 4.754 (0.806–28.027) Gram-negative bacteria -0.311 0.873 0.127 0.722 0.733 (0.132–4.054) Fungi 19.382 11939.854 0.000 0.999 261443910.0 *: OR, the odds ratio; 95% CI, the 95% confifidence interval. d means day. 3.5 Resistance rate of the main gram-positive bacteria to common antibiotics [n (%)] The resistance rate of staphylococcus to penicillin and erythromycin was high. No staphylococcus resistant to quinuputin/dafopratin, linezolid, vancomycin, teicoplanin, and tigecycline were detected. See Table 4 for the drug resistance analysis of main gram-positive bacteria to common antibiotics. Table 4 Resistance rate of the main gram-positive bacteria to common antibiotics [n (%)] Types of antibiotics Staphylococcus epidermidis (n = 72) Staphylococcus haemolyticus (n = 26) Staphylococcus aureus (n = 16) Streptococcus pneumoniae (n = 20) Enterococcus faecium (n = 10) Macrolides Erythromycin 60(83.3) 24(92.3) 10(62.5) 20(100) - Clindamycin 27(37.5) 15(57.7) 7(43.8) 19(95) - β-lactamides Penicillin 70(97.2) 25(96.2) 16(100) 0 9(90) Oxacillin 60(83.3) 24(92.3) 4(25) - - Amoxicillin - - - 2(10) - Ampicillin - - - - 10(100) Cefoxitin 61(84.7) 24(92.3) 4(25) - - Cefotaxime - - - 3(15) - Streptoyangmycin Quinuptin/Dafopudin 0(0) 0(0) 0(0) 13(50) 0(0) Rifamycins Rifampicin 7(9.72) 4(15.4) 0(0) 0(0) - Sulfonamides Compound sulfamethoxazole 40(55.6) 8(30.8) 0(0) 15(75) - Quinolones Ciprofloxacin 13(18.1) 16(61.5) 0(0) - 4(40) Levofloxacin 17(23.6) 13(50) 1(6.3) 0(0) 3(30) Moxifloxacin 2(2.8) 8(30.8) 1(6.3) - - Aminoglycosides Gentamicin 10(13.9) 12(46.2) 0(0) - - Chloramphenicols Chloramphenicol - - - 2(10) - Tetracyclines Tetracycline 15(20.8) 9(34.6) 3(18.8) 16(80) 3(30) Minocycline - - - - 5(50) “-”: This means it is not detected. 3.6 Resistance rate of the main gram-negative bacteria to common antibiotics [n (%)] Compared with Escherichia coli , Klebsiella pneumoniae had lower resistance rates to aztreonam, cefuroxime, cefotaxime, ceftriaxone, ciprofloxacin, levofloxacin, gentamycin and compound sulfamethoxazole. The resistance rates of Acinetobacter baumannii and Pseudomonas aeruginosa to antibiotics were shown in Table 5 . Table 5 Resistance rate of the main gram-negative bacteria to common antibiotics [n (%)] Types of antibiotics Escherichia coli (n = 19) Klebsiella pneumoniae (n = 15) Acinetobacter baumannii (n = 16) Pseudomonas aeruginosa (n = 14) ESBLs producing strains 11(57.9) 8(53.3) - - Carbapenems Imipenem 1(5.3) 3(20) 13(81.3) 6(42.7) Monobactams Aztreonam 7(36.8) 2(13.3) - 3(21.4) Penicillins Ampicillin 15(79) 14(93.3) - - Enzyme inhibitor complex Ampicillin/Sulbactam 12(63.2) 13(86.7) 12(75) - Cefoperazone/Sulbactam 3(15.8) 4(26.7) 12(75) 3(21.4) Piperacillin/Tazobactam 1(5.3) 4(26.7) 12(75) 1(7.1) Extended spectrum cephalosporin Cefazolin 10(52.6) 8(53.3) - - Cefuroxime 11(57.9) 7(46.7) - - Cefotaxime 8(42.1) 6(40) - - Cefazoxime 7(36.8) 6(40) - - Cefotetan 1(5.3) 4(26.7) - - Ceftriaxone 11(57.9) 8(53.3) 12(75) - Ceftazidime 5(26.3) 5(33.3) 12(75) 1(7.1) Cefepime 5(26.3) 5(33.3) 12(75) 2(14.3) Cephamicins Cefoxitin 2(10.5) 3(20) - - Quinolones Ciprofloxacin 8(42.1) 5(33.3) 12(75) 0(0) Levofloxacin 8(42.1) 2(13.3) 7(43.8) 0(0) Aminoglycosides Amikacin 0(0) 1(6.7) 12(75) 0(0) Gentamicin 11(57.9) 4(26.7) 12(75) 0(0) Tobramycin 2(10.5) 2(13.3) 11(68.8) 0(0) Sulfonamides Compound sulfamethoxazole 11(57.9) 5(33.3) 12(75) - Tetracyclines Minocycline - - 6(37.5) - “-”: It indicates that the strain is not tested or is naturally resistant to the antibiotic. 3.7 Comparative analysis of drug resistance rates of Escherichia coli and Klebsiella pneumoniae [n (%)] Escherichia coli and Klebsiella pneumoniae are common gram negative bacteria in bloodstream infections. See Table 6 for the results of further comparison of the drug resistance rate difference between Escherichia coli and Klebsiella pneumoniae. Table 6 Comparative analysis of drug resistance rates Types of antibiotics Escherichia coli (n = 19) Klebsiella pneumoniae (n = 15) c 2 P Imipenem 1(5.26) 3(20.00) 1.754 0.185 Aztreonam 7(36.84) 2(13.33) 2.38 0.123 Ampicillin 15(78.95) 14(93.33) 1.384 0.24 Ampicillin/Sulbactam 12(63.16) 13(86.67) 2.38 0.123 Cefoperazone/Sulbactam 3(15.8) 4(26.67) 0.607 0.436 Piperacillin/Tazobactam 1(5.26) 4(26.67) 3.061 0.08 Cefazolin 10(52.63) 8(53.3) 0.002 0.968 Cefuroxime 11(57.89) 7(46.67) 0.424 0.515 Cefotaxime 8(42.11) 6(40.00) 0.015 0.901 Cefazoxime 7(36.84) 6(40.00) 0.035 0.851 Cefotetan 1(5.26) 4(26.67) 3.061 0.080 Ceftriaxone 11(57.89) 8(53.3) 0.071 0.790 Ceftazidime 5(26.32) 5(33.33) 0.199 0.656 Cefepime 5(26.32) 5(33.33) 0.199 0.656 Cefoxitin 2(10.53) 3(20.00) 0.600 0.439 Ciprofloxacin 8(42.11) 5(33.33) 0.273 0.601 Levofloxacin 8(42.11) 2(13.33) 3.342 0.068 Amikacin 0(0) 1(6.67) 1.305 0.253 Gentamicin 11(57.89) 4(26.67) 3.316 0.069 Tobramycin 2(10.53) 2(13.33) 0.064 0.801 Compound sulfamethoxazole 11(57.89) 5(33.33) 2.03 0.154 3.8 Detection of MDR bacteria As shown in Table 7 , total of 27 common MDR bacteria were isolated, mainly including 23 strains of carbapenem-resistant gram-negative bacteria, and 4 strains of methicillin-resistant Staphylococcus aureus (MRSA). Vancomycin-resistant Enterococcus (VRE) was not detected. Table 7 Detection of MDR bacteria MDR bacteria 2016 2017 2018 2019 2020 2021 Total CRAB 0 0 2 1 4 6 13 CRPA 1 0 0 0 1 4 6 CRKP 0 0 1 1 0 1 3 CREO 0 0 0 0 1 0 1 MRSA 0 0 2 1 0 1 4 VRE 0 0 0 0 0 0 0 Total 1 0 5 3 6 12 27 4 Discussion BSI can be manifested as bacteremia, or even sepsis, which is common in ICU-critical children. In recent years, the incidence rate has increased. The children may only show transient infection, and some of them have severe sepsis and shock, with poor prognosis. Blood culture is the gold standard for diagnosis of BSI at present, and antibiotics can be reasonably selected according to the results of bacterial culture and drug sensitivity in clinical practice (Soedarmono et al. 2022 ). It is reported that the in-hospital mortality caused by severe BSI is as high as 30%~60%, which exceeds the total mortality caused by breast cancer, acquired immunodeficiency syndrome and prostate cancer (Martínez et al. 2021). Every hour of delay in treatment, the mortality of children will increase by 7.6% (Kumar et al. 2006 ). International guidelines suggest that effective antibiotics should be injected intravenously within 1 hour after the diagnosis of sepsis infection (Dellinger et al. 2013 ). Therefore, it is necessary to summarize and analyze the pathogen distribution, related risk factors and drug sensitivity results of BSI in ICU children, to help clinicians choose appropriate empirical treatment plans, improve the prognosis of children with sepsis, and reduce the mortality of BSI. The results showed that 328 strains of pathogens were isolated, including gram-positive bacteria (68%, 223/328), gram-negative bacteria (27.7%, 91/328), and fungi (4.3%, 14/328). The main gram-positive bacteria were CoNS (47.86%, 157/328), Streptococcus pneumoniae (6.10%, 20/328), and Staphylococcus aureus (4.9%, 16/328). The main gram-negative bacteria were Escherichia coli (5.8%, 19/328), Acinetobacter baumannii (4.9%, 16/328), Klebsiella pneumoniae (4.6%, 15/328), and Pseudomonas aeruginosa (4.3%, 14/328). The fungi were mainly Candida parapsilosis (3.1%, 10/328). As shown in Fig. 1 , the positive rates of blood culture were 5.6%, 3%, 3.8%, 3.1%, 4.6%, and 4.3% successively, from 2016 to 2021. Gram-positive bacteria represented by CoNS are the main pathogens that cause BSI in ICU, and the positive rate has always been higher than that of gram-negative bacteria and fungi. A study comparing the pathogens of BSI between children and adults in ICU found that the majority of adults were gram-negative bacteria and children were CoNS (Zhang et al. 2021 ). And more and more studies have shown that BSI caused by gram-positive bacteria is increasing (Santella et al. 2020 ; Wang et al. 2021 ; Dambroso-Altafini et al. 2022 ). However, some studies have shown that gram-negative bacteria are the main pathogen (Amanati et al. 2021 ; Zain et al. 2022 ). The difference in the detection of BSI pathogens may be related to the time, region and object of the study, and the results only represent the situation of the research institution in a certain period time. In addition, the same as in previous studies, the most common gram-negative bacteria causing BSI in this study is still Escherichia coli (Zain et al. 2022 ; Hu et al. 2022 ). In recent years, BSI caused by fungi has increased, and candida is the most common fungi (Lee et al. 2021 ). In this study, the fungi infection rate of children was lower than that of bacteria, with Candida parapsilosis as the main infection pathogens. Among 281 cases with BSI, 243 cases were infected by one pathogen (86.5%, 243/281), and 38 cases were infected by mixed pathogens (13.5%, 38/281), which is close to the mixed infection rate reported in previous studies (6%~13%) (Kiani et al. 1979 ; Rello et al. 1993 ; Lin et al. 2010 ). In the mixed infection, the mixed infection of two pathogens accounted for 11.03%, three pathogens accounted for 1.8%, and four pathogens accounted for 0.7%. Comparing the clinical data of children in the single infection group and the mixed infection group, it was found that the proportion of pathogenic bacteria detected in males, aged 0 ~ < 3Y, with length of hospitalization for less than 30 days, and children with hematological tumor disease was higher, which were 59.4%, 56.6%, 64.4%, and 26.3%, respectively. There was a significant difference between the two groups in lengths of hospitalization ( P < 0.05). Binary logistic regression analysis showed that lengths of hospitalization of 0ཞ<30d was an independent risk factor for mixed infection. Mixed infection is the most complex and serious infection in sepsis. Its treatment effect is poor, and the prognosis is often poor (Lin et al. 2010 ). Early diagnosis and timely and effective antibiotic therapy are the keys to improving the prognosis of children with sepsis. To further explore the risk factors of death from BSI, 281 children with BSI in ICU were divided into a survival group (259 cases) and a death group (22 cases). Table 2 shows that lengths of hospitalization and pathogen type have significant differences between the two groups ( P < 0.05). Binary logistic regression analysis showed that lengths of hospitalization of 15ཞ<60d was an independent risk factor related to death, as shown in Table 3 . There were 281 children with BSI in the ICU, 22 of whom died, with a fatality rate of 7.8% (22/281). The case fatality rate of children in the mixed infection group was 7.89% (3/38), which was slightly higher than that in the single infection group (7.82% (19/243)). Most mixed infections are initially considered as single pathogen infections, and empirical drug treatment is insufficient, thus aggravating the condition of children, prolonging lengths of hospitalization, and increasing mortality (Shen et al. 2015 ). Therefore, it is particularly necessary to timely identify children with the high risk of mixed infection, find out the suspected source of infection and the most common pathogens as soon as possible, and understand the antimicrobial resistance pattern of local medical institutions. The main gram-positive bacteria include Staphylococcus epidermidis , Staphylococcus haemolyticus , Streptococcus pneumoniae , Staphylococcus aureus and Enterococcus faecium . In Table 4 , the resistance rates of staphylococcus to penicillin and erythromycin were high. At present, vancomycin-resistant strains have been reported (Fournier et al. 2013 ). No gram-positive bacteria resistant to linezolid, vancomycin, teicoplanin, and tigecycline were detected in this study. CoNS belongs to the normal flora of human skin and mucosal tissue, and more and more reports about its related infectious diseases, especially catheter-related BSI (May et al. 2014 ; Matarrese et al. 2021 ). The majority of CoNS are methicillin-resistant coagulase-negative staphylococcus (MRCoNS). 61 strains of methicillin-resistant coagulase-negative Staphylococcus epidermidis (84.7%, 61/72) and 24 strains of methicillin-resistant coagulase-negative Staphylococcus haemolyticus (92.3%, 24/26) were isolated in this study, both of which showed multiple drug resistance. This was consistent with the results of other study (Peng et al. 2021 ). Compared with Staphylococcus epidermidis and Staphylococcus haemolyticus , Staphylococcus aureus showed a lower drug resistance rate to some β-lactamides and quinolone antibiotics, and they were 100% sensitive to compound sulfamethoxazole, gentamicin and tigecycline. 4 strains of MRSA and 5 strains of Staphylococcus aureus with positive D test were detected. MRSA is resistant to all β-lactamides antibiotics. Streptococcus pneumoniae was more than 95% resistant to macrolide antibiotics (erythromycin and clindamycin), and more than 50% resistant to tetracycline, compound sulfamethoxazole, and quinuputin/dafopratin. However, the drug resistance rate to amoxicillin was low, only 10%. Enterococcus faecium is 100% sensitive to quinuputin/dafopratin, linezolid, vancomycin, teicoplanin and tigecycline, which is consistent with a recent study (Tian 2022 ). The resistance rate of Enterococcus faecium to penicillins was as high as 90%, while the resistance rate to some quinolone antibiotics was low, which was 30%-40%. The resistance rate of the gram-positive bacteria isolated this time to quinolones (ciprofloxacin, levofloxacin, moxifloxacin) and aminoglycoside antibiotics (gentamicin) is lower than that of other antibiotics, which may be related to the influence of quinolones on bone development, the nephrotoxicity and ototoxicity of aminoglycoside antibiotics, and the less use of children. Of the 22 dead children in this study, 14 were infected with gram-negative bacteria (63.6%, 14/22). Special attention should be paid to children in ICU infected with gram-negative bacteria. Studies have shown that BSI caused by gram-negative bacteria is an independent risk factor for high mortality in ICU (Dat et al. 2018 ). 91 strains of gram-negative bacteria were isolated, mainly including Escherichia coli , Acinetobacter baumannii , Klebsiella pneumoniae and P seudomonas aeruginosa. The drug sensitivity results of the four bacteria are shown in Table 5 . The composition ratio of ESBLs-producing strains of Escherichia coli and Klebsiella pneumoniae was 57.9% (11/19) and 53.3% (8/15) respectively. However, the drug resistance rate of Klebsiella pneumoniae to imipenem was higher than that of Escherichia coli (20%>5.6%). Studies have shown that the incidence rate of BSI caused by carbapenem-resistant Klebsiella pneumoniae (CRKP) is increasing (Stein et al. 2019 ; Guo et al. 2023 ). According to the data of the National Drug Resistance Monitoring Network ( http://www.carss.cn/ ), the isolation rate of CRKP among children in China rose from 3.0–20.9% from 2005 to 2017, significantly higher than that of adults (Wang et al. 2020 ). Compared with Escherichia coli , Klebsiella pneumoniae has a lower resistance rate to aztreonam, cefuroxime, cefotaxime, ceftriaxone, ciprofloxacin, levofloxacin, gentamycin, and cotrimoxazole. Further analysis of the difference in drug resistance rate found that the difference between Escherichia coli and Klebsiella pneumoniae was not significant. The resistance rate of Acinetobacter baumannii to various antibiotics was higher than 75%, while the resistance rate to levofloxacin and minocycline was lower, which were 43.8% and 37.5% respectively. The above results indicate that Acinetobacter baumannii has serious drug resistance, and the effective drugs available for clinical treatment are limited. The combination of tegacycline-based drugs for the treatment of severe infections caused by Acinetobacter baumannii is currently a more commonly used program. Recently, our research group conducted a study on the carbapenem-resistance and virulence of Acinetobacter baumannii , and analyzed the reasons for its multiple drug resistance (Zhu et al. 2022 ). Pseudomonas aeruginosa is sensitive to commonly used clinical anti-pseudomonas drugs, and the resistance rates to aztreonam, cefoperazone/sulbactam, piperacillin/tazobactam, ceftazidime and cefepime are 21.4%, 21.4%, 7.1%, 7.1%, and 21.4%, respectively. It is 100% resistant to quinolones (ciprofloxacin, levofloxacin) and aminoglycosides (gentamicin, tobramycin, amikacin) antibiotics. Among 328 pathogenic bacteria, a total of 27 common MDR bacteria were isolated, mainly including 13 strains of carbapenem-resistant Acinetobacter baumannii (CRAB), 6 strains of carbapenem-resistant Pseudomonas aeruginosa (CRPA), 3 strains of carbapenem-resistant Klebsiella pneumoniae (CRKP), 1 strain of carbapenem-resistant Escherichia coli (CREO) and 4 strains of methicillin-resistant Staphylococcus aureus (MRSA). Vancomycin-resistant Enterococcus (VRE) was not detected. There will be more MDR bacteria detected in 2021. In this study, the proportion of CRAB is the highest, reaching 48.2% (13/27), which is consistent with Bedenić et al (Bedenić et al. 2023 ). The proportion of CRPA was the second, accounting for 22.2% (6/27). Among the 22 dead children, 4 cases were infected with CRAB and 2 cases were infected with CRPA. Carbapenem-resistant enterobacter (CRE) can be found in samples of urine, respiratory, feces, blood, and other specimen (Kotb et al. 2020 ; Sexton et al. 2022 ; Xiong et al. 2023 ). There were 4 CRE strains in the present study. These results suggest that attention should be paid to the BSI caused by CR-bacteria. Studies have shown that the main reason for the resistance of pathogenic bacteria to carbapenem antibiotics in children is the production of metalloenzymes (class B) (Buys et al. 2016 ). At present, the most effective antibiotic for CRE is polymyxin combined with tigecycline (Vanegas et al. 2016 ). However, because tigecycline will cause tooth staining, it is rarely used in children. Polymyxin alone is still a relatively safe treatment scheme for children. In summary, the pathogens of BSI of children living in the ICU are mainly gram-positive bacteria represented by CoNS in the past six years. Escherichia coli is the most common gram-negative bacteria. It is necessary to continuously monitor the blood culture of critically ill children with BSI, pay special attention to the MDR bacteria detected, strengthen the application and management of antibiotics, and better prevent and control hospital infection. However, this study also has some limitations. Due to the small number of different pathogens detected each year, and the lack of analysis of the annual changes in antimicrobial resistance, we will expand the study period in the follow-up study to more accurately analyze the changes in drug resistance rate. Abbreviations Kirby-Baue (KB) Intensive care unit (ICU) Multi-drug resistant (MDR) Bloodstream infection (BSI) Vancomycin-resistant Enterococcus (VRE) Coagulase-negative staphylococci (CoNS) Extended-spectrum β-lactamases (ESBLs) Carbapenem-resistant enterobacter (CRE) Carbapenem-resistant Escherichia coli (CREO) Carbapenem-resistant Klebsiella pneumoniae (CRKP) Carbapenem-resistant Acinetobacter baumannii (CRAB) Carbapenem-resistant Pseudomonas aeruginosa (CRPA) Methicillin-resistant Staphylococcus aureus (MRSA) Methicillin-resistant coagulase-negative staphylococcus (MRCoNS) Declarations Acknowledgments We thank the staff from the Department of Clinical Laboratory, Children's Hospital of Soochow University , who took part in the study. Disclaimer The views, opinions, assumptions, or any other information set out in this article are solely those of the authors and should not be attributed to the funders or any other person connected with the funders. Ethics Approval and Consent to Participate It was reviewed and approved by the Medical Ethics Committee of the Children's Hospital of Soochow University (Ethics batch number: 2021CS158). Informed consent was obtained from all subjects and/or their legal guardian(s). All methods were performed in accordance with the relevant guidelines and regulations. Author contributions HJ S and L D conceived the study and designed the experiments. Y L and XJ S provide financial support. HJ S, X Z and YY G collected and analyzed the data, YZ W and L D interpreted the results. HJ S and X Z drafted the manuscript, and all authors critically revised the manuscript for intellectual content, and read and approved the final manuscript. Funding support This study was supported by grants from the Special Foundation for National Science and Technology Basic Research Program of China (2019FY101200), the High-level Innovative and Entrepreneurial Talents Introduction Program of Jiangsu Province (2020-30191), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (20KJB310012), the Medical Research Project of Jiangsu Commission of Health (M2020027), The "National Tutorial System" Project for Suzhou Young Health Talents (Qngg2022011), the Science and Technology Program of Suzhou (SYS2020163, SYSD2019120, SLC201904). Availability of Data and Materials The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Declaration of Interest Statement All other authors report no potential conflicts of interest. The funding body played no role in the design of the study and collection, analysis, interpretation of data, and in writing the manuscript. Consent for publication Not applicable. References Amanati, A., Sajedianfard, S., Khajeh, S., Ghasempour, S., Mehrangiz, S., Nematolahi, S., & Shahhosein, Z. (2021). Bloodstream infections in adult patients with malignancy, epidemiology, microbiology, and risk factors associated with mortality and multi-drug resistance. BMC infectious diseases, 21(1), 636. https://doi.org/10.1186/s12879-021-06243-z Bassetti, M., De Waele, J. J., Eggimann, P., Garnacho-Montero, J., Kahlmeter, G., Menichetti, F., Nicolau, D. P., Paiva, J. A., Tumbarello, M., Welte, T., Wilcox, M., Zahar, J. R., & Poulakou, G. (2015). Preventive and therapeutic strategies in critically ill patients with highly resistant bacteria. Intensive care medicine, 41(5), 776–795. https://doi.org/10.1007/s00134-015-3719-z Buys, H., Muloiwa, R., Bamford, C., & Eley, B. (2016). Klebsiella pneumoniae bloodstream infections at a South African children's hospital 2006-2011, a cross-sectional study. BMC infectious diseases, 16(1), 570. https://doi.org/10.1186/s12879-016-1919-y Bammigatti, C., Doradla, S., Belgode, H. N., Kumar, H., & Swaminathan, R. P. (2017). Healthcare Associated Infections in a Resource Limited Setting. Journal of clinical and diagnostic research : JCDR, 11(1), OC01-OC04. https://doi.org/10.7860/JCDR/2017/23076.9150 Bedenić, B., Bratić, V., Mihaljević, S., Lukić, A., Vidović, K., Reiner, K., Schöenthaler, S., Barišić, I., Zarfel, G., & Grisold, A. (2023). Multidrug-Resistant Bacteria in a COVID-19 Hospital in Zagreb. Pathogens (Basel, Switzerland), 12(1), 117. https://doi.org/10.3390/pathogens12010117 Centers for Disease Control and Prevention/National Healthcare Safety Network. CDC/NHSN Surveillance Definitions for Specific Types of Infections. January 2017. Dellinger P, Levy MM, Rhodes A, et al. (2013). Action to save patients with sepsis: International Guidelines for the Treatment of Severe Sepsis and Septic Shock 2012[S]. Critical Care Medicine, 2013, 41 (2): 580-586 Dat, V. Q., Long, N. T., Hieu, V. N., Phuc, N. D. H., Kinh, N. V., Trung, N. V., van Doorn, H. R., Bonell, A., & Nadjm, B. (2018). Clinical characteristics, organ failure, inflammatory markers and prediction of mortality in patients with community acquired bloodstream infection. BMC infectious diseases, 18(1), 535. https://doi.org/10.1186/s12879-018-3448-3 Dambroso-Altafini, D., Menegucci, T. C., Costa, B. B., Moreira, R. R. B., Nishiyama, S. A. B., Mazucheli, J., & Tognim, M. C. B. (2022). Routine laboratory biomarkers used to predict Gram-positive or Gram-negative bacteria involved in bloodstream infections. Scientific reports, 12(1), 15466. https://doi.org/10.1038/s41598-022-19643-1 Fournier, P. E., Drancourt, M., Colson, P., Rolain, J. M., La Scola, B., & Raoult, D. (2013). Modern clinical microbiology: new challenges and solutions. Nature reviews. Microbiology, 11(8), 574–585. https://doi.org/10.1038/nrmicro3068 Gouel-Cheron, A., Swihart, B. J., Warner, S., Mathew, L., Strich, J. R., Mancera, A., Follmann, D., & Kadri, S. S. (2022). Epidemiology of ICU-Onset Bloodstream Infection: Prevalence, Pathogens, and Risk Factors Among 150,948 ICU Patients at 85 U.S. Hospitals. Critical care medicine,50(12), 1725–1736. https://doi.org/10.1097/CCM.0000000000005662 Guo, Y., Liu, F., Zhang, Y., Wang, X., Gao, W., Xu, B., Li, Y., & Song, N. (2023). Virulence, antimicrobial resistance, and molecular characteristics of carbapenem-resistant Klebsiella pneumoniae in a hospital in Shijiazhuang City from China. International microbiology : the official journal of the Spanish Society for Microbiology, 10.1007/s10123-023-00357-x. Advance online publication. https://doi.org/10.1007/s10123-023-00357-x Hu, F., Yuan, L., Yang, Y., Xu, Y., Huang, Y., Hu, Y., Ai, X., Zhuo, C., Su, D., Shan, B., Du, Y., Yu, Y., Lin, J., Sun, Z., Chen, Z., Xu, Y., Zhang, X., Wang, C., He, L., Ni, Y., … Zhang, Y. (2022). A multicenter investigation of 2,773 cases of bloodstream infections based on China antimicrobial surveillance network (CHINET). Frontiers in cellular and infection microbiology, 12, 1075185. https://doi.org/10.3389/fcimb.2022.1075185 Kiani, D., Quinn, E. L., Burch, K. H., Madhavan, T., Saravolatz, L. D., & Neblett, T. R. (1979). The increasing importance of polymicrobial bacteremia. JAMA, 242(10), 1044–1047. PMID: 470044 Kumar, A., Roberts, D., Wood, K. E., Light, B., Parrillo, J. E., Sharma, S., Suppes, R., Feinstein, D., Zanotti, S., Taiberg, L., Gurka, D., Kumar, A., & Cheang, M. (2006). Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Critical care medicine, 34(6), 1589-1596. https://doi.org/10.1097/01.CCM.0000217961.75225.E9 Kotb, S., Lyman, M., Ismail, G., Abd El Fattah, M., Girgis, S. A., Etman, A., Hafez, S., El-Kholy, J., Zaki, M. E. S., Rashed, H. G., Khalil, G. M., Sayyouh, O., & Talaat, M. (2020). Epidemiology of Carbapenem-resistant Enterobacteriaceae in Egyptian intensive care units using National Healthcare-associated Infections Surveillance Data, 2011-2017. Antimicrobial resistance and infection control, 9(1), 2. https://doi.org/10.1186/s13756-019-0639-7 Lin, J. N., Lai, C. H., Chen, Y. H., Chang, L. L., Lu, P. L., Tsai, S. S., Lin, H. L., & Lin, H. H. (2010). Characteristics and outcomes of polymicrobial bloodstream infections in the emergency department: A matched case-control study. Academic emergency medicine : official journal of the Society for Academic Emergency Medicine, 17(10), 1072–1079. https://doi.org/10.1111/j.1553-2712.2010.00871.x\ Lee, Y., Puumala, E., Robbins, N., & Cowen, L. E. (2021). Antifungal Drug Resistance: Molecular Mechanisms in Candida albicans and Beyond. Chemical reviews, 121(6), 3390–3411. https://doi.org/10.1021/acs.chemrev.0c00199 Ministry of health of the people's Republic of China. Diagnostic criteria for nosocomial infection (Trial)[M](2003). Modern Practical Medicine, 15(7): 460-464. May, L., Klein, E. Y., Rothman, R. E., & Laxminarayan, R. (2014). Trends in antibiotic resistance in coagulase-negative staphylococci in the United States, 1999 to 2012. Antimicrobial agents and chemotherapy, 58(3), 1404–1409. https://doi.org/10.1128/AAC.01908-13 Marsillio, L. E., Ginsburg, S. L., Rosenbaum, C. H., Coffin, S. E., Naim, M. Y., Priestley, M. A., & Srinivasan, V. (2015). Hyperglycemia at the Time of Acquiring Central Catheter-Associated Bloodstream Infections Is Associated With Mortality in Critically Ill Children. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies, 16(7), 621-628. https://doi.org/10.1097/PCC.0000000000000445 Markwart, R., Saito, H., Harder, T., Tomczyk, S., Cassini, A., Fleischmann-Struzek, C., Reichert, F., Eckmanns, T., & Allegranzi, B. (2020). Epidemiology and burden of sepsis acquired in hospitals and intensive care units: a systematic review and meta-analysis. Intensive care medicine, 46(8), 1536–1551. https://doi.org/10.1007/s00134-020-06106-2 Martínez Pérez-Crespo, P. M., López-Cortés, L. E., Retamar-Gentil, P., García, J. F. L., Vinuesa García, D., León, E., Calvo, J. M. S., Galán-Sánchez, F., Natera Kindelan, C., Del Arco Jiménez, A., Sánchez-Porto, A., Herrero Rodríguez, C., Becerril Carral, B., Molina, I. M. R., Iglesias, J. M. R., Pérez Camacho, I., Guzman García, M., López-Hernández, I., Rodríguez-Baño, J., & PROBAC REIPI/GEIH-SEIMC/SAEI Group (2021). Epidemiologic changes in bloodstream infections in Andalucía (Spain) during the last decade. Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases, 27(2), 283.e9-283.e16. https://doi.org/10.1016/j.cmi.2020.05.015 Matarrese, A. N., Ivulich, D. I., Cesar, G., Alaniz, F., Ruiz, J. J., & Osatnik, J. (2021). Análisis epidemiológico de bacteriemias asociadas a catéter en una terapia intensiva médico-quirúrgica [Epidemiological analysis of catheter-related bloodstream infections in medical-surgical intensive care units]. Medicina, 81(2), 159–165. Peng ZL, Jiang Y, Jia LJ, et al. (2021). Analysis of drug resistance and prognosis of bloodstream infection pathogens. Clinical Meta Analysis, 36(8): 724-729. Rello, J., Quintana, E., Mirelis, B., Gurguí, M., Net, A., & Prats, G. (1993). Polymicrobial bacteremia in critically ill patients. Intensive care medicine, 19(1), 22–25. https://doi.org/10.1007/BF01709273 Shime, N., Kawasaki, T., Saito, O., Akamine, Y., Toda, Y., Takeuchi, M., Sugimura, H., Sakurai, Y., Iijima, M., Ueta, I., Shimizu, N., & Nakagawa, S. (2012). Incidence and risk factors for mortality in paediatric severe sepsis: results from the national paediatric intensive care registry in Japan. Intensive care medicine, 38(7), 1191–1197. https://doi.org/10.1007/s00134-012-2550-z Shen FC, Xie D, Han QP, Zeng HK, Deng XY. (2015). Pathogen characteristics of bloodstream infection in ICU and risk factors analysis of mixed blood flow infection. China critical care medicine, 27(9): 718-723. doi：10.3760/cma.j.issn.2095-4352.2015.09.004 Schwab, F., Geffers, C., Behnke, M., & Gastmeier, P. (2018). ICU mortality following ICU-acquired primary bloodstream infections according to the type of pathogen: A prospective cohort study in 937 Germany ICUs (2006-2015). PloS one, 13(3), e0194210. https://doi.org/10.1371/journal.pone.0194210 Stein, C., Vincze, S., Kipp, F., Makarewicz, O., Al Dahouk, S., & Pletz, M. W. (2019). Carbapenem-resistant Klebsiella pneumoniae with low chlorhexidine susceptibility. The Lancet. Infectious diseases, 19(9), 932–933. https://doi.org/10.1016/S1473-3099(19)30427-X Santella, B., Folliero, V., Pirofalo, G. M., Serretiello, E., Zannella, C., Moccia, G., Santoro, E., Sanna, G., Motta, O., De Caro, F., Pagliano, P., Capunzo, M., Galdiero, M., Boccia, G., & Franci, G. (2020). Sepsis-A Retrospective Cohort Study of Bloodstream Infections. Antibiotics (Basel, Switzerland), 9(12), 851. https://doi.org/10.3390/antibiotics9120851 Sexton, M. E., Bower, C., & Jacob, J. T. (2022). Risk factors for isolation of carbapenem-resistant Enterobacterales from normally sterile sites and urine. American journal of infection control, 50(8), 929–933. https://doi.org/10.1016/j.ajic.2021.12.007 Soedarmono, P., Diana, A., Tauran, P., Lokida, D., Aman, A. T., Alisjahbana, B., Arlinda, D., Tjitra, E., Kosasih, H., Merati, K. T. P., Arif, M., Gasem, M. H., Susanto, N. H., Lukman, N., Sugiyono, R. I., Hadi, U., Lisdawati, V., Tchos, K. G. F., Neal, A., & Karyana, M. (2022). The characteristics of bacteremia among patients with acute febrile illness requiring hospitalization in Indonesia. PloS one, 17(9), e0273414. https://doi.org/10.1371/journal.pone.0273414 Tran, K., Bell, C., Stall, N., Tomlinson, G., McGeer, A., Morris, A., Gardam, M., & Abrams, H. B. (2017). The Effect of Hospital Isolation Precautions on Patient Outcomes and Cost of Care: A Multi-Site, Retrospective, Propensity Score-Matched Cohort Study. Journal of general internal medicine, 32(3), 262–268. https://doi.org/10.1007/s11606-016-3862-4 Timsit, J. F., Ruppé, E., Barbier, F., Tabah, A., & Bassetti, M. (2020). Bloodstream infections in critically ill patients: an expert statement. Intensive care medicine, 46(2), 266–284. https://doi.org/10.1007/s00134-020-05950-6 Tian Q. (2022). Analysis of pathogenic bacteria distribution and drug resistance in patients with bloodstream infection in ICU. Exploration of rational drug use in China, 19(2): 29-35. Vanegas, J. M., Parra, O. L., & Jiménez, J. N. (2016). Molecular epidemiology of carbapenem resistant gram-negative bacilli from infected pediatric population in tertiary - care hospitals in Medellín, Colombia: an increasing problem. BMC infectious diseases, 16(1), 463. https://doi.org/10.1186/s12879-016-1805-7 Wang, B., Pan, F., Wang, C., Zhao, W., Sun, Y., Zhang, T., Shi, Y., & Zhang, H. (2020). Molecular epidemiology of Carbapenem-resistant Klebsiella pneumoniae in a paediatric hospital in China. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 93, 311–319. https://doi.org/10.1016/j.ijid.2020.02.009 Wang, C., Hao, W., Yu, R., Wang, X., Zhang, J., & Wang, B. (2021). Analysis of Pathogen Distribution and Its Antimicrobial Resistance in Bloodstream Infections in Hospitalized Children in East China, 2015-2018. Journal of tropical pediatrics, 67(1), fmaa077. https://doi.org/10.1093/tropej/fmaa077 Xie, J., Li, S., Xue, M., Yang, C., Huang, Y., Chihade, D. B., Liu, L., Yang, Y., & Qiu, H. (2020). Early- and Late-Onset Bloodstream Infections in the Intensive Care Unit: A Retrospective 5-Year Study of Patients at a University Hospital in China. The Journal of infectious diseases, 221(Suppl 2), S184-S192. https://doi.org/10.1093/infdis/jiz606 Xiong, Z., Zhang, C., Sarbandi, K., Liang, Z., Mai, J., Liang, B., Cai, H., Chen, X., Gao, F., Lan, F., Liu, X., Liu, S., & Zhou, Z. (2023). Clinical and molecular epidemiology of carbapenem-resistant Enterobacteriaceae in pediatric inpatients in South China. Microbiology spectrum, e0283923. Advance online publication. https://doi.org/10.1128/spectrum.02839-23 Yan, G., Liu, J., Chen, W., Chen, Y., Cheng, Y., Tao, J., Cai, X., Zhou, Y., Wang, Y., Wang, M., & Lu, G. (2021). Metagenomic Next-Generation Sequencing of Bloodstream Microbial Cell-Free Nucleic Acid in Children With Suspected Sepsis in Pediatric Intensive Care Unit. Frontiers in cellular and infection microbiology, 11, 665226. https://doi.org/10.3389/fcimb.2021.665226 Zhu, S., Kang, Y., Wang, W., Cai, L., Sun, X., & Zong, Z. (2019). The clinical impacts and risk factors for non-central line-associated bloodstream infection in 5046 intensive care unit patients: an observational study based on electronic medical records. Critical care (London, England), 23(1), 52. https://doi.org/10.1186/s13054-019-2353-5 Zhang Y, Zhou J, Cao T, Li Zheqian. (2021). Comparison of pathogenic bacteria distribution, drug resistance and clinical characteristics of bloodstream infection between children and adults admitted to intensive care unit. Shandong medicine, 61(12): 4-10. https://doi.org/10.3969/j.issn.1002-266X.2021.12.005 Zain, O. M., Elsayed, M. Y., Abdelkhalig, S. M., Abdelaziz, M., Ibrahim, S. Y., Bashir, T., & Hamadalnil, Y. (2022). Bloodstream infection in cancer patients; susceptibility profiles of the isolated pathogens, at Khartoum Oncology Hospital, Sudan. African health sciences, 22(4), 70–76. https://doi.org/10.4314/ahs.v22i4.10 Zhang, Y., Cao, B., Cao, W., Miao, H., & Wu, L. (2022). Clinical Characteristics and Death Risk Factors of Severe Sepsis in Children. Computational and mathematical methods in medicine, 2022, 4200605. https://doi.org/10.1155/2022/4200605 Zhu, Y., Zhang, X., Wang, Y., Tao, Y., Shao, X., Li, Y., & Li, W. (2022). Insight into carbapenem resistance and virulence of Acinetobacter baumannii from a children's medical centre in eastern China. Annals of clinical microbiology and antimicrobials, 21(1), 47. https://doi.org/10.1186/s12941-022-00536-0 Additional Declarations No competing interests reported. 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Dai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBACfmaG5AcJPDZy/OwNRGqRbGd4ZvBAJs1YsucAkVoMzjM+kHxgcyhxw40EYl12mDnBICHnQOKGm4833mCosYkmqIOxmS3hQcKZO8Yzb6cVWzAcS8ttIKSFmZknwSCx55ls3+0cMwnGhsOEtbAx83+QSPx3mLHh5hkitfAwMyRIJPAcVpxwg4dILRLMDGkGCTygQAb6JYEYv9ifP5D88Ac4Kg9vvPGhxoawFmRgIJFAinKIFlJ1jIJRMApGwcgAADLrQ0MjLD64AAAAAElFTkSuQmCC","orcid":"","institution":"Children's Hospital of Soochow University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ling","middleName":"","lastName":"Dai","suffix":""}],"badges":[],"createdAt":"2023-10-18 05:29:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3460595/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3460595/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10123-024-00481-2","type":"published","date":"2024-01-18T15:01:40+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":45387899,"identity":"0c08c53a-2f70-4381-876c-76939cd1da51","added_by":"auto","created_at":"2023-10-29 01:26:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":332420,"visible":true,"origin":"","legend":"\u003cp\u003eThe proportion of the total number of cases each year ascribed to each species.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3460595/v1/92dade77b7d449786c9b311e.png"},{"id":45387897,"identity":"fefaa6d0-6dc1-4054-9f0a-886739fef64f","added_by":"auto","created_at":"2023-10-29 01:26:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":39181,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of the positive rates of BSI in the ICU from 2016 to 2021\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3460595/v1/07ae1bb91370f91b551464b8.png"},{"id":49979129,"identity":"b53a7875-14f7-4dfe-bf0e-914b86f1db63","added_by":"auto","created_at":"2024-01-22 15:11:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":826457,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3460595/v1/62c9a37b-39e0-4d19-9dc2-462456048423.pdf"},{"id":45387898,"identity":"e591105b-5041-4573-882d-1c5dde58af28","added_by":"auto","created_at":"2023-10-29 01:26:18","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":25399,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-3460595/v1/31a00bd23e43133e64bc0db1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epidemiology and drug resistance analysis of bloodstream infections in intensive care unit from a children's medical center in eastern China for six consecutive years","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eBloodstream infection (BSI) is a systemic infectious disease caused by pathogenic microorganisms entering the blood system, which can be manifested as bacteremia, or even sepsis(Gouel-Cheron et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Sepsis is a serious systemic inflammatory reaction, which is one of the main causes of death in children (Zhang et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Children in the intensive care unit (ICU) are usually in critical condition, with severe basic diseases and low immunity. In addition to various invasive operations, they are more prone to infection (Yan et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). According to statistics, the hospital infection of children in the ICU is about 2\u0026ndash;5 times that of children in general wards (Bassetti et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Bammigatti et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Once a child suffers from BSI, it will not only aggravate the illness and increase the pain, but also lead to a longer hospital stays, significantly increase hospital costs, seriously threaten the life of the child, and increase the family burden of the child (Tran et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhu et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In recent years, the incidence and mortality of BSI remain high. Studies have shown that BSI is the most common hospital-acquired infection in the ICU, with a mortality of 18.6%~52.3% (Shime et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Marsillio et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Schwab et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Markwart et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, early and appropriate antibiotic therapy can improve the prognosis of children with sepsis in the ICU. Blood culture is considered to be the most effective laboratory method for diagnosing BSI. Pathogens are identified through blood culture results in clinical practice, and rational drug use is based on drug sensitivity results. However, the positive rate of blood culture is low and the reporting time of positive and drug sensitivity results is late, so it is difficult to guide the selection of antibiotics in a timely and correct manner. Therefore, it is of great significance for clinicians to accurately evaluate the condition of children with BSI and timely grasp the characteristics and drug resistance of pathogens for empirically selecting antibiotics and improving the success rate of infection treatment. There have been previous studies on BSI in ICU, but infection control and antimicrobial management policies are different in different countries, regions and hospitals, and the clinical characteristics of BSI pathogens are quite different (Timsit et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xie et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The data survey found that there was no report on the characteristics and drug resistance of pathogenic bacteria of BSI in ICU children in the Suzhou area in recent six years. Therefore, the purpose of this study is to retrospectively analyze the distribution of pathogenic bacteria, death risk factors and drug resistance of children with BSI admitted to the ICU of Children's Hospital Affiliated to Suzhou University from January 2016 to December 2021, to guide clinicians to select appropriate empirical treatment schemes by observing the clinical symptoms of children and combining research data before receiving feedback from the laboratory to reduce the problem of antibiotic abuse and the producing of MDR bacteria.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Study Site\u003c/h2\u003e\n \u003cp\u003eThis study was conducted at Children\u0026apos;s Hospital of Soochow University, which is a children\u0026apos;s medical centre in East China and the only provincial tertiary children\u0026apos;s hospital in Jiangsu Province. Children\u0026apos;s Hospital of Soochow University has 1500 beds and serves\u0026thinsp;\u0026gt;\u0026thinsp;70,000 inpatients and \u0026gt;\u0026thinsp;2\u0026nbsp;million outpatients annually. This study was approved by the Ethics Committee of Children\u0026apos;s Hospital of Soochow University (No. 2021CS158).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 General information\u003c/h2\u003e\n \u003cp\u003e281 cases with BSI admitted to the ICU of Children\u0026apos;s Hospital of Soochow University from January 2016 to December 2021 were selected as the study subjects. Among them, 167 cases were male (59.4%), age (3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4) years old, and 114 cases were female (40.6%), age (3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1) years old. The ratio of male to female was 1.5: 1. The basic diseases were mainly hematological tumor diseases (74, 26.3%), respiratory system diseases (57, 20.3%), heart diseases (51, 18.2%), and central nervous system disease (39, 13.9%). The children were divided into two groups according to the number of pathogenic bacteria isolated from blood culture samples: the children with only one kind of pathogenic bacteria in blood culture samples were included in the single infection group; The children with two or more pathogens cultured at the same time or two or more pathogens isolated for several times in a row were included in the mixed infection group. There were 243 cases in the single infection group and 38 cases in the mixed infection group. Compared with the mixed infection group, the age of children in the single infection group (age: 3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2 vs 4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.095, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.279) had no significant difference.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Diagnostic criteria for BSI\u003c/h2\u003e\n \u003cp\u003eRegarding to the national diagnostic standard for hospital infection (\u003cem\u003eDiagnostic criteria for nosocomial infection (Trial)\u003c/em\u003e, 2003) and the latest definition and diagnostic standard for hospital infection of CDC/NHSN in the United States (\u003cem\u003eCDC/NHSN\u003c/em\u003e, 2017): the patient isolated pathogenic bacteria from blood samples during hospitalization and had any of the following symptoms or signs: (1) Temperature\u0026thinsp;\u0026gt;\u0026thinsp;38℃ or \u0026lt;\u0026thinsp;36℃, accompanied by chills; (2) Invasive portals or migratory lesions of pathogens can be found from patients; (3) The patient had obvious symptoms of systemic infection and poisoning but no clear infection focus; (4) The systolic blood pressure of the patient is lower than 90mmHg or more than 40mmHg lower than the original systolic blood pressure. Exclusion criteria: (1) incomplete case data, (2) elimination of contaminated strains, and (3) repeated strains detected continuously in the same child.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Strain identification and drug sensitivity test\u003c/h2\u003e\n \u003cp\u003eBlood culture bottles were placed into the instrument for incubation. The positive samples were transferred to the culture plate and incubated at 37℃ for 18\u0026ndash;24 h (5% CO\u003csub\u003e2\u003c/sub\u003e). The colonies were identified by the mass spectrometer. The automatic bacterial detection and analysis system and Kirby-Bauer (KB) method were used for the drug sensitivity test. The results were judged according to the latest standards of the Clinical Laboratory Standardization Association. Extended-spectrum \u0026beta;-lactamases (ESBLs) were determined by the automatic bacterial detection and analysis system. The judgment results were obtained according to its expert system. The quality control strains were \u003cem\u003eEscherichia coli\u003c/em\u003e (ATCC 25922), \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (ATCC 27853), \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (ATCC 25923 and ATCC 29213), \u003cem\u003eEnterococcus faecalis\u003c/em\u003e (ATCC 29212) and \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e (ATCC 49619), which were purchased from the clinical testing center of the National Health Commission.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5 Data analysis\u003c/h2\u003e\n \u003cp\u003eSPSS 20.0 and WHONET 5.6 (WHO Collaborating Centre for Surveillance of Antimicrobial Resistance, Boston, MA, USA) was used to analyze data. The measurement data were expressed by the mean and standard deviation (\u0026oline;x\u0026thinsp;\u0026plusmn;\u0026thinsp;s). The \u003cem\u003et\u003c/em\u003e-test was used in univariate analysis. The counting data were expressed as the number of cases (n) and rate (%). Mon-factor analysis adopted the \u0026chi;\u003csup\u003e2\u003c/sup\u003e test. Multi-factor analysis adopted binary logistic regression analysis, with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as the difference.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003e3.1 Annual distribution of pathogenic bacteria [n (%)]\u003c/h2\u003e\n \u003cp\u003eIn Fig.\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e, Gram-positive bacteria are the main pathogenic bacteria causing BSI in children living in the ICU, and the positive rate has always been higher than that of gram-negative bacteria and fungi. Among them, coagulase-negative \u003cem\u003estaphylococcus\u003c/em\u003e (CoNS) is the most common BSI in children. See \u003cem\u003eSupplementary materials Table \u003cspan\u003eS1\u003c/span\u003e\u003c/em\u003e for details. The positive rate of gram-positive/negative pathogens and fungi each year is shown in Fig.\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003e3.2 Comparative analysis of clinical characteristics with single pathogen infection and mixed pathogen infection [n (%)]\u003c/h2\u003e\n \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e, it was found that the infection was mainly caused by a single pathogen, and the proportion of male aged 0\u0026thinsp;~\u0026thinsp;\u0026lt;\u0026thinsp;3Y with basic diseases such as hematological tumor disease, respiratory system disease, heart disease, and central nervous system disease was higher.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSingle factor analysis of mixed infection risk factors of children in ICU with BSI [n (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSingle infection group(n\u0026thinsp;=\u0026thinsp;243)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMixed infection group(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ec\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e144(59.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23(60.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e99(40.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15(39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0～\u0026lt;3Y*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e139(57.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20(52.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.765\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3～\u0026lt;14Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96(39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16(42.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14～\u0026lt;18Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e5.112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"6\"\u003e\n \u003cp\u003e0.402\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33(13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44(18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42(17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45(18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47(19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14(36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSurvival status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDeath\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19(7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurvival\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e224(92.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35(92.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eLength of hospitalization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0～\u0026lt;15d*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e95(39.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e36.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15～\u0026lt;30d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e77(31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30～\u0026lt;60d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61(25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21(55.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e≧\u0026thinsp;60d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003eMain basic diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHematological tumor disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63(25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e5.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"6\"\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45(18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44(18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral nervous system diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37(15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTraumatic disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDigestive system diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e*: Y means age, d means day.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003e3.3 Comparative analysis of clinical characteristics with survival group and death group [n (%)]\u003c/h2\u003e\n \u003cp\u003eFurther analysis of infection-related risk factors in the survival group and the death group showed that there was a statistically significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between at length of hospitalization and pathogen type (Table\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSingle factor analysis of death risk factors of children in ICU with BSI [n (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSurvival group\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;259)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDeath group\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ec\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e155(59.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(54.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.627\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e104(40.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(54.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0～\u0026lt;3Y*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e151(58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(36.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e5.960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3～\u0026lt;14Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98(37.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14(63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14～\u0026lt;18Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eLength of hospitalization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0～\u0026lt;15d*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85(32.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13(59.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e15.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15～\u0026lt;30d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82(31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30～\u0026lt;60d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78(30.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e≧\u0026thinsp;60d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14(5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eInfection type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle infection group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e224(86.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(86.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed infection group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35(13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003ePathogen type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGram-positive bacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e178(69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e16.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGram-negative bacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58(22.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(54.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFungi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13(5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003eMain basic diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHematological tumor disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64(24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(45.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e10.814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"6\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55(21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45(17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral nervous system diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39(15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDigestive system diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15(5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTraumatic disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14(5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e*: Y means age, d means day\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003e3.4 Multi-factor analysis of mixed infection and death risk factors of children in ICU with BSI\u003c/h2\u003e\n \u003cp\u003eTo further explore the meaningful indicators of univariate analysis in Tables\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e and \u003cspan\u003e2\u003c/span\u003e, multi-factor analysis on the factors of mixed infection and death risk factors of children in ICU with BSI were conducted in Table\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eMulti-factor analysis of meaningful indicators\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWaldc\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eMixed infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of hospitalization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0～\u0026lt;15d*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.333 (5.777-111.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15～\u0026lt;30d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.267 (2.951\u0026ndash;35.719)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30～\u0026lt;60d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.324 (0.810\u0026ndash;6.665)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.250\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"8\"\u003e\n \u003cp\u003eDeath group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of hospitalization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0～\u0026lt;15d*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.448 (0.303\u0026ndash;6.910)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15～\u0026lt;30d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.334 (1.844-246.873)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30～\u0026lt;60d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.038\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.882 (1.104\u0026ndash;31.346)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePathogen type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.767\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.915\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGram-positive bacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.754 (0.806\u0026ndash;28.027)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGram-negative bacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.733 (0.132\u0026ndash;4.054)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFungi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11939.854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e261443910.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e*: OR, the odds ratio; 95% CI, the 95% confifidence interval. d means day.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003e3.5 Resistance rate of the main gram-positive bacteria to common antibiotics [n (%)]\u003c/h2\u003e\n \u003cp\u003eThe resistance rate of \u003cem\u003estaphylococcus\u003c/em\u003e to penicillin and erythromycin was high. No \u003cem\u003estaphylococcus\u003c/em\u003e resistant to quinuputin/dafopratin, linezolid, vancomycin, teicoplanin, and tigecycline were detected. See Table\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e for the drug resistance analysis of main gram-positive bacteria to common antibiotics.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eResistance rate of the main gram-positive bacteria to common antibiotics [n (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTypes of antibiotics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;72)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStreptococcus pneumoniae (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eEnterococcus faecium\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMacrolides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eErythromycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24(92.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20(100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClindamycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27(37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15(57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e\u0026beta;-lactamides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePenicillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70(97.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25(96.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16(100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9(90)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOxacillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24(92.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmoxicillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmpicillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefoxitin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61(84.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24(92.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefotaxime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStreptoyangmycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuinuptin/Dafopudin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRifamycins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRifampicin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(9.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSulfonamides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCompound sulfamethoxazole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40(55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(30.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eQuinolones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCiprofloxacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13(18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16(61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLevofloxacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(23.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMoxifloxacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(30.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAminoglycosides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGentamicin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChloramphenicols\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChloramphenicol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTetracyclines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTetracycline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15(20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9(34.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16(80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMinocycline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026ldquo;-\u0026rdquo;: This means it is not detected.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003e3.6 Resistance rate of the main gram-negative bacteria to common antibiotics [n (%)]\u003c/h2\u003e\n \u003cp\u003eCompared with \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e had lower resistance rates to aztreonam, cefuroxime, cefotaxime, ceftriaxone, ciprofloxacin, levofloxacin, gentamycin and compound sulfamethoxazole. The resistance rates of \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e to antibiotics were shown in Table\u0026nbsp;\u003cspan\u003e5\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eResistance rate of the main gram-negative bacteria to common antibiotics [n (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTypes of antibiotics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;19)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAcinetobacter baumannii\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eESBLs producing strains\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(57.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCarbapenems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eImipenem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13(81.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(42.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonobactams\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAztreonam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePenicillins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmpicillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15(79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14(93.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eEnzyme inhibitor complex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmpicillin/Sulbactam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(63.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13(86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefoperazone/Sulbactam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePiperacillin/Tazobactam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"8\"\u003e\n \u003cp\u003eExtended spectrum cephalosporin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefazolin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(52.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefuroxime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(57.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(46.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefotaxime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(42.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefazoxime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefotetan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCeftriaxone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(57.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCeftazidime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefepime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCephamicins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefoxitin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eQuinolones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCiprofloxacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(42.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLevofloxacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(42.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eAminoglycosides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmikacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGentamicin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(57.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTobramycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(68.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSulfonamides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCompound sulfamethoxazole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(57.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTetracyclines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMinocycline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026ldquo;-\u0026rdquo;: It indicates that the strain is not tested or is naturally resistant to the antibiotic.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003e3.7 Comparative analysis of drug resistance rates of \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e [n (%)]\u003c/h2\u003e\n \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e are common gram negative bacteria in bloodstream infections. See Table\u0026nbsp;\u003cspan\u003e6\u003c/span\u003e for the results of further comparison of the drug resistance rate difference between \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eKlebsiella pneumoniae.\u003c/em\u003e\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eComparative analysis of drug resistance rates\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTypes of antibiotics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;19)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ec\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eImipenem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(5.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAztreonam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(36.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(13.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmpicillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15(78.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(93.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmpicillin/Sulbactam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(63.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(86.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefoperazone/Sulbactam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(26.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.436\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePiperacillin/Tazobactam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(5.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(26.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefazolin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(52.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.968\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefuroxime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(57.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(46.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.515\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefotaxime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(42.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(40.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefazoxime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(36.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(40.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.851\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefotetan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(5.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(26.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCeftriaxone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(57.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.790\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCeftazidime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(26.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(33.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.656\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefepime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(26.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(33.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.656\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCefoxitin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(10.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.439\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCiprofloxacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(42.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(33.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLevofloxacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(42.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(13.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmikacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(6.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.253\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGentamicin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(57.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(26.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTobramycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(10.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(13.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCompound sulfamethoxazole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(57.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(33.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\"\u003e\n \u003ch2\u003e3.8 Detection of MDR bacteria\u003c/h2\u003e\u003cbr\u003e\n \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan\u003e7\u003c/span\u003e, total of 27 common MDR bacteria were isolated, mainly including 23 strains of carbapenem-resistant gram-negative bacteria, and 4 strains of methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (MRSA). Vancomycin-resistant \u003cem\u003eEnterococcus\u003c/em\u003e (VRE) was not detected.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 7\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eDetection of MDR bacteria\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMDR bacteria\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRAB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRKP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCREO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMRSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eBSI can be manifested as bacteremia, or even sepsis, which is common in ICU-critical children. In recent years, the incidence rate has increased. The children may only show transient infection, and some of them have severe sepsis and shock, with poor prognosis. Blood culture is the gold standard for diagnosis of BSI at present, and antibiotics can be reasonably selected according to the results of bacterial culture and drug sensitivity in clinical practice (Soedarmono et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). It is reported that the in-hospital mortality caused by severe BSI is as high as 30%~60%, which exceeds the total mortality caused by breast cancer, acquired immunodeficiency syndrome and prostate cancer (Mart\u0026iacute;nez et al. 2021). Every hour of delay in treatment, the mortality of children will increase by 7.6% (Kumar et al. \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e). International guidelines suggest that effective antibiotics should be injected intravenously within 1 hour after the diagnosis of sepsis infection (Dellinger et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). Therefore, it is necessary to summarize and analyze the pathogen distribution, related risk factors and drug sensitivity results of BSI in ICU children, to help clinicians choose appropriate empirical treatment plans, improve the prognosis of children with sepsis, and reduce the mortality of BSI.\u003c/p\u003e\n\u003cp\u003eThe results showed that 328 strains of pathogens were isolated, including gram-positive bacteria (68%, 223/328), gram-negative bacteria (27.7%, 91/328), and fungi (4.3%, 14/328). The main gram-positive bacteria were CoNS (47.86%, 157/328), \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e (6.10%, 20/328), and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (4.9%, 16/328). The main gram-negative bacteria were \u003cem\u003eEscherichia coli\u003c/em\u003e (5.8%, 19/328), \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e (4.9%, 16/328), \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (4.6%, 15/328), and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (4.3%, 14/328). The fungi were mainly \u003cem\u003eCandida parapsilosis\u003c/em\u003e (3.1%, 10/328). As shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, the positive rates of blood culture were 5.6%, 3%, 3.8%, 3.1%, 4.6%, and 4.3% successively, from 2016 to 2021. Gram-positive bacteria represented by CoNS are the main pathogens that cause BSI in ICU, and the positive rate has always been higher than that of gram-negative bacteria and fungi. A study comparing the pathogens of BSI between children and adults in ICU found that the majority of adults were gram-negative bacteria and children were CoNS (Zhang et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). And more and more studies have shown that BSI caused by gram-positive bacteria is increasing (Santella et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wang et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Dambroso-Altafini et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, some studies have shown that gram-negative bacteria are the main pathogen (Amanati et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zain et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). The difference in the detection of BSI pathogens may be related to the time, region and object of the study, and the results only represent the situation of the research institution in a certain period time. In addition, the same as in previous studies, the most common gram-negative bacteria causing BSI in this study is still \u003cem\u003eEscherichia coli\u003c/em\u003e (Zain et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hu et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). In recent years, BSI caused by fungi has increased, and candida is the most common fungi (Lee et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this study, the fungi infection rate of children was lower than that of bacteria, with \u003cem\u003eCandida parapsilosis\u003c/em\u003e as the main infection pathogens.\u003c/p\u003e\n\n\n\u003cp\u003eAmong 281 cases with BSI, 243 cases were infected by one pathogen (86.5%, 243/281), and 38 cases were infected by mixed pathogens (13.5%, 38/281), which is close to the mixed infection rate reported in previous studies (6%~13%) (Kiani et al. \u003cspan class=\"CitationRef\"\u003e1979\u003c/span\u003e; Rello et al. \u003cspan class=\"CitationRef\"\u003e1993\u003c/span\u003e; Lin et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e). In the mixed infection, the mixed infection of two pathogens accounted for 11.03%, three pathogens accounted for 1.8%, and four pathogens accounted for 0.7%. Comparing the clinical data of children in the single infection group and the mixed infection group, it was found that the proportion of pathogenic bacteria detected in males, aged 0\u0026thinsp;~\u0026thinsp;\u0026lt;\u0026thinsp;3Y, with length of hospitalization for less than 30 days, and children with hematological tumor disease was higher, which were 59.4%, 56.6%, 64.4%, and 26.3%, respectively. There was a significant difference between the two groups in lengths of hospitalization (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Binary logistic regression analysis showed that lengths of hospitalization of 0ཞ\u0026lt;30d was an independent risk factor for mixed infection. Mixed infection is the most complex and serious infection in sepsis. Its treatment effect is poor, and the prognosis is often poor (Lin et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e). Early diagnosis and timely and effective antibiotic therapy are the keys to improving the prognosis of children with sepsis. To further explore the risk factors of death from BSI, 281 children with BSI in ICU were divided into a survival group (259 cases) and a death group (22 cases). Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows that lengths of hospitalization and pathogen type have significant differences between the two groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Binary logistic regression analysis showed that lengths of hospitalization of 15ཞ\u0026lt;60d was an independent risk factor related to death, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. There were 281 children with BSI in the ICU, 22 of whom died, with a fatality rate of 7.8% (22/281). The case fatality rate of children in the mixed infection group was 7.89% (3/38), which was slightly higher than that in the single infection group (7.82% (19/243)). Most mixed infections are initially considered as single pathogen infections, and empirical drug treatment is insufficient, thus aggravating the condition of children, prolonging lengths of hospitalization, and increasing mortality (Shen et al. \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Therefore, it is particularly necessary to timely identify children with the high risk of mixed infection, find out the suspected source of infection and the most common pathogens as soon as possible, and understand the antimicrobial resistance pattern of local medical institutions.\u003c/p\u003e\n\u003cp\u003eThe main gram-positive bacteria include \u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e, \u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e, \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e, \u003cem\u003eStaphylococcus aureus\u003c/em\u003e and \u003cem\u003eEnterococcus faecium\u003c/em\u003e. In Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, the resistance rates of \u003cem\u003estaphylococcus\u003c/em\u003e to penicillin and erythromycin were high. At present, vancomycin-resistant strains have been reported (Fournier et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). No gram-positive bacteria resistant to linezolid, vancomycin, teicoplanin, and tigecycline were detected in this study. CoNS belongs to the normal flora of human skin and mucosal tissue, and more and more reports about its related infectious diseases, especially catheter-related BSI (May et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; Matarrese et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). The majority of CoNS are methicillin-resistant coagulase-negative \u003cem\u003estaphylococcus\u003c/em\u003e (MRCoNS). 61 strains of methicillin-resistant coagulase-negative \u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e (84.7%, 61/72) and 24 strains of methicillin-resistant coagulase-negative \u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e (92.3%, 24/26) were isolated in this study, both of which showed multiple drug resistance. This was consistent with the results of other study (Peng et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Compared with \u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e and \u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e, \u003cem\u003eStaphylococcus aureus\u003c/em\u003e showed a lower drug resistance rate to some \u0026beta;-lactamides and quinolone antibiotics, and they were 100% sensitive to compound sulfamethoxazole, gentamicin and tigecycline. 4 strains of MRSA and 5 strains of \u003cem\u003eStaphylococcus aureus\u003c/em\u003e with positive D test were detected. MRSA is resistant to all \u0026beta;-lactamides antibiotics. \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e was more than 95% resistant to macrolide antibiotics (erythromycin and clindamycin), and more than 50% resistant to tetracycline, compound sulfamethoxazole, and quinuputin/dafopratin. However, the drug resistance rate to amoxicillin was low, only 10%. \u003cem\u003eEnterococcus faecium\u003c/em\u003e is 100% sensitive to quinuputin/dafopratin, linezolid, vancomycin, teicoplanin and tigecycline, which is consistent with a recent study (Tian \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). The resistance rate of \u003cem\u003eEnterococcus faecium\u003c/em\u003e to penicillins was as high as 90%, while the resistance rate to some quinolone antibiotics was low, which was 30%-40%. The resistance rate of the gram-positive bacteria isolated this time to quinolones (ciprofloxacin, levofloxacin, moxifloxacin) and aminoglycoside antibiotics (gentamicin) is lower than that of other antibiotics, which may be related to the influence of quinolones on bone development, the nephrotoxicity and ototoxicity of aminoglycoside antibiotics, and the less use of children.\u003c/p\u003e\n\u003cp\u003eOf the 22 dead children in this study, 14 were infected with gram-negative bacteria (63.6%, 14/22). Special attention should be paid to children in ICU infected with gram-negative bacteria. Studies have shown that BSI caused by gram-negative bacteria is an independent risk factor for high mortality in ICU (Dat et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). 91 strains of gram-negative bacteria were isolated, mainly including \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e and \u003cem\u003eP\u003c/em\u003eseudomonas aeruginosa. The drug sensitivity results of the four bacteria are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. The composition ratio of ESBLs-producing strains of \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e was 57.9% (11/19) and 53.3% (8/15) respectively. However, the drug resistance rate of \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e to imipenem was higher than that of \u003cem\u003eEscherichia coli\u003c/em\u003e (20%\u0026gt;5.6%). Studies have shown that the incidence rate of BSI caused by carbapenem-resistant \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (CRKP) is increasing (Stein et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Guo et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). According to the data of the National Drug Resistance Monitoring Network (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.carss.cn/\u003c/span\u003e\u003c/span\u003e), the isolation rate of CRKP among children in China rose from 3.0\u0026ndash;20.9% from 2005 to 2017, significantly higher than that of adults (Wang et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Compared with \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e has a lower resistance rate to aztreonam, cefuroxime, cefotaxime, ceftriaxone, ciprofloxacin, levofloxacin, gentamycin, and cotrimoxazole. Further analysis of the difference in drug resistance rate found that the difference between \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e was not significant. The resistance rate of \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e to various antibiotics was higher than 75%, while the resistance rate to levofloxacin and minocycline was lower, which were 43.8% and 37.5% respectively. The above results indicate that \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e has serious drug resistance, and the effective drugs available for clinical treatment are limited. The combination of tegacycline-based drugs for the treatment of severe infections caused by \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e is currently a more commonly used program. Recently, our research group conducted a study on the carbapenem-resistance and virulence of \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e, and analyzed the reasons for its multiple drug resistance (Zhu et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e is sensitive to commonly used clinical anti-pseudomonas drugs, and the resistance rates to aztreonam, cefoperazone/sulbactam, piperacillin/tazobactam, ceftazidime and cefepime are 21.4%, 21.4%, 7.1%, 7.1%, and 21.4%, respectively. It is 100% resistant to quinolones (ciprofloxacin, levofloxacin) and aminoglycosides (gentamicin, tobramycin, amikacin) antibiotics.\u003c/p\u003e\n\u003cp\u003eAmong 328 pathogenic bacteria, a total of 27 common MDR bacteria were isolated, mainly including 13 strains of carbapenem-resistant \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e (CRAB), 6 strains of carbapenem-resistant \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (CRPA), 3 strains of carbapenem-resistant \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (CRKP), 1 strain of carbapenem-resistant \u003cem\u003eEscherichia coli\u003c/em\u003e (CREO) and 4 strains of methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (MRSA). Vancomycin-resistant \u003cem\u003eEnterococcus\u003c/em\u003e (VRE) was not detected. There will be more MDR bacteria detected in 2021. In this study, the proportion of CRAB is the highest, reaching 48.2% (13/27), which is consistent with Bedenić et al (Bedenić et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). The proportion of CRPA was the second, accounting for 22.2% (6/27). Among the 22 dead children, 4 cases were infected with CRAB and 2 cases were infected with CRPA. Carbapenem-resistant enterobacter (CRE) can be found in samples of urine, respiratory, feces, blood, and other specimen (Kotb et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sexton et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Xiong et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). There were 4 CRE strains in the present study. These results suggest that attention should be paid to the BSI caused by CR-bacteria. Studies have shown that the main reason for the resistance of pathogenic bacteria to carbapenem antibiotics in children is the production of metalloenzymes (class B) (Buys et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). At present, the most effective antibiotic for CRE is polymyxin combined with tigecycline (Vanegas et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, because tigecycline will cause tooth staining, it is rarely used in children. Polymyxin alone is still a relatively safe treatment scheme for children.\u003c/p\u003e\n\u003cp\u003eIn summary, the pathogens of BSI of children living in the ICU are mainly gram-positive bacteria represented by CoNS in the past six years. \u003cem\u003eEscherichia coli\u003c/em\u003e is the most common gram-negative bacteria. It is necessary to continuously monitor the blood culture of critically ill children with BSI, pay special attention to the MDR bacteria detected, strengthen the application and management of antibiotics, and better prevent and control hospital infection. However, this study also has some limitations. Due to the small number of different pathogens detected each year, and the lack of analysis of the annual changes in antimicrobial resistance, we will expand the study period in the follow-up study to more accurately analyze the changes in drug resistance rate.\u003c/p\u003e\n\n"},{"header":"Abbreviations","content":"\u003cp\u003eKirby-Baue (KB)\u003c/p\u003e\n\u003cp\u003eIntensive care unit (ICU)\u003c/p\u003e\n\u003cp\u003eMulti-drug resistant (MDR)\u003c/p\u003e\n\u003cp\u003eBloodstream infection (BSI)\u003c/p\u003e\n\u003cp\u003eVancomycin-resistant \u003cem\u003eEnterococcus\u003c/em\u003e (VRE)\u003c/p\u003e\n\u003cp\u003eCoagulase-negative staphylococci (CoNS)\u003c/p\u003e\n\u003cp\u003eExtended-spectrum \u0026beta;-lactamases (ESBLs)\u003c/p\u003e\n\u003cp\u003eCarbapenem-resistant enterobacter (CRE)\u003c/p\u003e\n\u003cp\u003eCarbapenem-resistant \u003cem\u003eEscherichia coli\u003c/em\u003e (CREO)\u003c/p\u003e\n\u003cp\u003eCarbapenem-resistant \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (CRKP)\u003c/p\u003e\n\u003cp\u003eCarbapenem-resistant \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e (CRAB)\u003c/p\u003e\n\u003cp\u003eCarbapenem-resistant \u003cem\u003ePseudomonas aeruginosa\u0026nbsp;\u003c/em\u003e(CRPA)\u003c/p\u003e\n\u003cp\u003eMethicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (MRSA)\u003c/p\u003e\n\u003cp\u003eMethicillin-resistant coagulase-negative \u003cem\u003estaphylococcus\u003c/em\u003e (MRCoNS)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the staff from the\u0026nbsp;\u003cem\u003eDepartment of Clinical Laboratory, Children\u0026apos;s Hospital of Soochow University\u003c/em\u003e,\u0026nbsp;who took part in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclaimer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe views, opinions, assumptions, or any other information set out in this article are solely those of the authors and should not be attributed to the funders or any other person connected with the funders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIt was reviewed and approved by the Medical Ethics Committee of the Children\u0026apos;s Hospital of Soochow University (Ethics batch number: 2021CS158). Informed consent was obtained from all subjects and/or their legal guardian(s). All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHJ S and L D conceived the study and designed the experiments. Y L and XJ S provide financial support. HJ S, X Z and YY G collected and analyzed the data, YZ W and L D interpreted the results. HJ S and X Z drafted the manuscript, and all authors critically revised the manuscript for intellectual content, and read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding support\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from the Special Foundation for National Science and Technology Basic Research Program of China (2019FY101200), the High-level Innovative and Entrepreneurial Talents Introduction Program of Jiangsu Province (2020-30191), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (20KJB310012), the Medical Research Project of Jiangsu Commission of Health (M2020027), The \u0026quot;National Tutorial System\u0026quot; Project for Suzhou Young Health Talents (Qngg2022011), the Science and Technology Program of Suzhou (SYS2020163, SYSD2019120, SLC201904).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll other authors report no potential conflicts of interest. The funding body played no role in the design of the study and collection, analysis, interpretation of data, and in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmanati, A., Sajedianfard, S., Khajeh, S., Ghasempour, S., Mehrangiz, S., Nematolahi, S., \u0026amp; Shahhosein, Z. (2021). Bloodstream infections in adult patients with malignancy, epidemiology, microbiology, and risk factors associated with mortality and multi-drug resistance. BMC infectious diseases, 21(1), 636. https://doi.org/10.1186/s12879-021-06243-z\u003c/li\u003e\n\u003cli\u003eBassetti, M., De Waele, J. J., Eggimann, P., Garnacho-Montero, J., Kahlmeter, G., Menichetti, F., Nicolau, D. P., Paiva, J. A., Tumbarello, M., Welte, T., Wilcox, M., Zahar, J. R., \u0026amp; Poulakou, G. (2015). Preventive and therapeutic strategies in critically ill patients with highly resistant bacteria. Intensive care medicine, 41(5), 776\u0026ndash;795. https://doi.org/10.1007/s00134-015-3719-z\u003c/li\u003e\n\u003cli\u003eBuys, H., Muloiwa, R., Bamford, C., \u0026amp; Eley, B. (2016). Klebsiella pneumoniae bloodstream infections at a South African children\u0026apos;s hospital 2006-2011, a cross-sectional study. BMC infectious diseases, 16(1), 570. https://doi.org/10.1186/s12879-016-1919-y\u003c/li\u003e\n\u003cli\u003eBammigatti, C., Doradla, S., Belgode, H. N., Kumar, H., \u0026amp; Swaminathan, R. P. (2017). Healthcare Associated Infections in a Resource Limited Setting. Journal of clinical and diagnostic research : JCDR, 11(1), OC01-OC04. https://doi.org/10.7860/JCDR/2017/23076.9150\u003c/li\u003e\n\u003cli\u003eBedenić, B., Bratić, V., Mihaljević, S., Lukić, A., Vidović, K., Reiner, K., Sch\u0026ouml;enthaler, S., Bari\u0026scaron;ić, I., Zarfel, G., \u0026amp; Grisold, A. (2023). Multidrug-Resistant Bacteria in a COVID-19 Hospital in Zagreb. Pathogens (Basel, Switzerland), 12(1), 117. https://doi.org/10.3390/pathogens12010117\u003c/li\u003e\n\u003cli\u003eCenters for Disease Control and Prevention/National Healthcare Safety Network. CDC/NHSN Surveillance Definitions for Specific Types of Infections. January 2017.\u003c/li\u003e\n\u003cli\u003eDellinger P, Levy MM, Rhodes A, et al. (2013). Action to save patients with sepsis: International Guidelines for the Treatment of Severe Sepsis and Septic Shock 2012[S]. Critical Care Medicine, 2013, 41 (2): 580-586\u003c/li\u003e\n\u003cli\u003eDat, V. Q., Long, N. T., Hieu, V. N., Phuc, N. D. H., Kinh, N. V., Trung, N. V., van Doorn, H. R., Bonell, A., \u0026amp; Nadjm, B. (2018). Clinical characteristics, organ failure, inflammatory markers and prediction of mortality in patients with community acquired bloodstream infection. BMC infectious diseases, 18(1), 535. https://doi.org/10.1186/s12879-018-3448-3\u003c/li\u003e\n\u003cli\u003eDambroso-Altafini, D., Menegucci, T. C., Costa, B. B., Moreira, R. R. B., Nishiyama, S. A. B., Mazucheli, J., \u0026amp; Tognim, M. C. B. (2022). Routine laboratory biomarkers used to predict Gram-positive or Gram-negative bacteria involved in bloodstream infections. Scientific reports, 12(1), 15466. https://doi.org/10.1038/s41598-022-19643-1\u003c/li\u003e\n\u003cli\u003eFournier, P. E., Drancourt, M., Colson, P., Rolain, J. M., La Scola, B., \u0026amp; Raoult, D. (2013). Modern clinical microbiology: new challenges and solutions. Nature reviews. Microbiology, 11(8), 574\u0026ndash;585. https://doi.org/10.1038/nrmicro3068\u003c/li\u003e\n\u003cli\u003eGouel-Cheron, A., Swihart, B. J., Warner, S., Mathew, L., Strich, J. R., Mancera, A., Follmann, D., \u0026amp; Kadri, S. S. (2022). Epidemiology of ICU-Onset Bloodstream Infection: Prevalence, Pathogens, and Risk Factors Among 150,948 ICU Patients at 85 U.S. Hospitals. Critical care medicine,50(12), 1725\u0026ndash;1736. https://doi.org/10.1097/CCM.0000000000005662\u003c/li\u003e\n\u003cli\u003eGuo, Y., Liu, F., Zhang, Y., Wang, X., Gao, W., Xu, B., Li, Y., \u0026amp; Song, N. (2023). Virulence, antimicrobial resistance, and molecular characteristics of carbapenem-resistant Klebsiella pneumoniae in a hospital in Shijiazhuang City from China. International microbiology : the official journal of the Spanish Society for Microbiology, 10.1007/s10123-023-00357-x. Advance online publication. https://doi.org/10.1007/s10123-023-00357-x\u003c/li\u003e\n\u003cli\u003eHu, F., Yuan, L., Yang, Y., Xu, Y., Huang, Y., Hu, Y., Ai, X., Zhuo, C., Su, D., Shan, B., Du, Y., Yu, Y., Lin, J., Sun, Z., Chen, Z., Xu, Y., Zhang, X., Wang, C., He, L., Ni, Y., \u0026hellip; Zhang, Y. (2022). A multicenter investigation of 2,773 cases of bloodstream infections based on China antimicrobial surveillance network (CHINET). Frontiers in cellular and infection microbiology, 12, 1075185. https://doi.org/10.3389/fcimb.2022.1075185\u003c/li\u003e\n\u003cli\u003eKiani, D., Quinn, E. L., Burch, K. H., Madhavan, T., Saravolatz, L. D., \u0026amp; Neblett, T. R. (1979). The increasing importance of polymicrobial bacteremia. JAMA, 242(10), 1044\u0026ndash;1047. PMID: 470044\u003c/li\u003e\n\u003cli\u003eKumar, A., Roberts, D., Wood, K. E., Light, B., Parrillo, J. E., Sharma, S., Suppes, R., Feinstein, D., Zanotti, S., Taiberg, L., Gurka, D., Kumar, A., \u0026amp; Cheang, M. (2006). Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Critical care medicine, 34(6), 1589-1596. https://doi.org/10.1097/01.CCM.0000217961.75225.E9\u003c/li\u003e\n\u003cli\u003eKotb, S., Lyman, M., Ismail, G., Abd El Fattah, M., Girgis, S. A., Etman, A., Hafez, S., El-Kholy, J., Zaki, M. E. S., Rashed, H. G., Khalil, G. M., Sayyouh, O., \u0026amp; Talaat, M. (2020). Epidemiology of Carbapenem-resistant Enterobacteriaceae in Egyptian intensive care units using National Healthcare-associated Infections Surveillance Data, 2011-2017. Antimicrobial resistance and infection control, 9(1), 2. https://doi.org/10.1186/s13756-019-0639-7\u003c/li\u003e\n\u003cli\u003eLin, J. N., Lai, C. H., Chen, Y. H., Chang, L. L., Lu, P. L., Tsai, S. S., Lin, H. L., \u0026amp; Lin, H. H. (2010). Characteristics and outcomes of polymicrobial bloodstream infections in the emergency department: A matched case-control study. Academic emergency medicine : official journal of the Society for Academic Emergency Medicine, 17(10), 1072\u0026ndash;1079. https://doi.org/10.1111/j.1553-2712.2010.00871.x\\\u003c/li\u003e\n\u003cli\u003eLee, Y., Puumala, E., Robbins, N., \u0026amp; Cowen, L. E. (2021). Antifungal Drug Resistance: Molecular Mechanisms in Candida albicans and Beyond. Chemical reviews, 121(6), 3390\u0026ndash;3411. https://doi.org/10.1021/acs.chemrev.0c00199\u003c/li\u003e\n\u003cli\u003eMinistry of health of the people\u0026apos;s Republic of China. Diagnostic criteria for nosocomial infection (Trial)[M](2003). Modern Practical Medicine, 15(7): 460-464.\u003c/li\u003e\n\u003cli\u003eMay, L., Klein, E. Y., Rothman, R. E., \u0026amp; Laxminarayan, R. (2014). Trends in antibiotic resistance in coagulase-negative staphylococci in the United States, 1999 to 2012. Antimicrobial agents and chemotherapy, 58(3), 1404\u0026ndash;1409. https://doi.org/10.1128/AAC.01908-13\u003c/li\u003e\n\u003cli\u003eMarsillio, L. E., Ginsburg, S. L., Rosenbaum, C. H., Coffin, S. E., Naim, M. Y., Priestley, M. A., \u0026amp; Srinivasan, V. (2015). Hyperglycemia at the Time of Acquiring Central Catheter-Associated Bloodstream Infections Is Associated With Mortality in Critically Ill Children. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies, 16(7), 621-628. https://doi.org/10.1097/PCC.0000000000000445\u003c/li\u003e\n\u003cli\u003eMarkwart, R., Saito, H., Harder, T., Tomczyk, S., Cassini, A., Fleischmann-Struzek, C., Reichert, F., Eckmanns, T., \u0026amp; Allegranzi, B. (2020). Epidemiology and burden of sepsis acquired in hospitals and intensive care units: a systematic review and meta-analysis. Intensive care medicine, 46(8), 1536\u0026ndash;1551. https://doi.org/10.1007/s00134-020-06106-2\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;nez P\u0026eacute;rez-Crespo, P. M., L\u0026oacute;pez-Cort\u0026eacute;s, L. E., Retamar-Gentil, P., Garc\u0026iacute;a, J. F. L., Vinuesa Garc\u0026iacute;a, D., Le\u0026oacute;n, E., Calvo, J. M. S., Gal\u0026aacute;n-S\u0026aacute;nchez, F., Natera Kindelan, C., Del Arco Jim\u0026eacute;nez, A., S\u0026aacute;nchez-Porto, A., Herrero Rodr\u0026iacute;guez, C., Becerril Carral, B., Molina, I. M. R., Iglesias, J. M. R., P\u0026eacute;rez Camacho, I., Guzman Garc\u0026iacute;a, M., L\u0026oacute;pez-Hern\u0026aacute;ndez, I., Rodr\u0026iacute;guez-Ba\u0026ntilde;o, J., \u0026amp; PROBAC REIPI/GEIH-SEIMC/SAEI Group (2021). Epidemiologic changes in bloodstream infections in Andaluc\u0026iacute;a (Spain) during the last decade. Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases, 27(2), 283.e9-283.e16. https://doi.org/10.1016/j.cmi.2020.05.015\u003c/li\u003e\n\u003cli\u003eMatarrese, A. N., Ivulich, D. I., Cesar, G., Alaniz, F., Ruiz, J. J., \u0026amp; Osatnik, J. (2021). An\u0026aacute;lisis epidemiol\u0026oacute;gico de bacteriemias asociadas a cat\u0026eacute;ter en una terapia intensiva m\u0026eacute;dico-quir\u0026uacute;rgica [Epidemiological analysis of catheter-related bloodstream infections in medical-surgical intensive care units]. Medicina, 81(2), 159\u0026ndash;165.\u003c/li\u003e\n\u003cli\u003ePeng ZL, Jiang Y, Jia LJ, et al. (2021). Analysis of drug resistance and prognosis of bloodstream infection pathogens. Clinical Meta Analysis, 36(8): 724-729.\u003c/li\u003e\n\u003cli\u003eRello, J., Quintana, E., Mirelis, B., Gurgu\u0026iacute;, M., Net, A., \u0026amp; Prats, G. (1993). Polymicrobial bacteremia in critically ill patients. Intensive care medicine, 19(1), 22\u0026ndash;25. https://doi.org/10.1007/BF01709273\u003c/li\u003e\n\u003cli\u003eShime, N., Kawasaki, T., Saito, O., Akamine, Y., Toda, Y., Takeuchi, M., Sugimura, H., Sakurai, Y., Iijima, M., Ueta, I., Shimizu, N., \u0026amp; Nakagawa, S. (2012). Incidence and risk factors for mortality in paediatric severe sepsis: results from the national paediatric intensive care registry in Japan. Intensive care medicine, 38(7), 1191\u0026ndash;1197. https://doi.org/10.1007/s00134-012-2550-z\u003c/li\u003e\n\u003cli\u003eShen FC, Xie D, Han QP, Zeng HK, Deng XY. (2015). Pathogen characteristics of bloodstream infection in ICU and risk factors analysis of mixed blood flow infection. China critical care medicine, 27(9): 718-723. doi：10.3760/cma.j.issn.2095-4352.2015.09.004\u003c/li\u003e\n\u003cli\u003eSchwab, F., Geffers, C., Behnke, M., \u0026amp; Gastmeier, P. (2018). ICU mortality following ICU-acquired primary bloodstream infections according to the type of pathogen: A prospective cohort study in 937 Germany ICUs (2006-2015). PloS one, 13(3), e0194210. https://doi.org/10.1371/journal.pone.0194210\u003c/li\u003e\n\u003cli\u003eStein, C., Vincze, S., Kipp, F., Makarewicz, O., Al Dahouk, S., \u0026amp; Pletz, M. W. (2019). Carbapenem-resistant Klebsiella pneumoniae with low chlorhexidine susceptibility. The Lancet. Infectious diseases, 19(9), 932\u0026ndash;933. https://doi.org/10.1016/S1473-3099(19)30427-X\u003c/li\u003e\n\u003cli\u003eSantella, B., Folliero, V., Pirofalo, G. M., Serretiello, E., Zannella, C., Moccia, G., Santoro, E., Sanna, G., Motta, O., De Caro, F., Pagliano, P., Capunzo, M., Galdiero, M., Boccia, G., \u0026amp; Franci, G. (2020). Sepsis-A Retrospective Cohort Study of Bloodstream Infections. Antibiotics (Basel, Switzerland), 9(12), 851. https://doi.org/10.3390/antibiotics9120851\u003c/li\u003e\n\u003cli\u003eSexton, M. E., Bower, C., \u0026amp; Jacob, J. T. (2022). Risk factors for isolation of carbapenem-resistant Enterobacterales from normally sterile sites and urine. American journal of infection control, 50(8), 929\u0026ndash;933. https://doi.org/10.1016/j.ajic.2021.12.007\u003c/li\u003e\n\u003cli\u003eSoedarmono, P., Diana, A., Tauran, P., Lokida, D., Aman, A. T., Alisjahbana, B., Arlinda, D., Tjitra, E., Kosasih, H., Merati, K. T. P., Arif, M., Gasem, M. H., Susanto, N. H., Lukman, N., Sugiyono, R. I., Hadi, U., Lisdawati, V., Tchos, K. G. F., Neal, A., \u0026amp; Karyana, M. (2022). The characteristics of bacteremia among patients with acute febrile illness requiring hospitalization in Indonesia. PloS one, 17(9), e0273414. https://doi.org/10.1371/journal.pone.0273414\u003c/li\u003e\n\u003cli\u003eTran, K., Bell, C., Stall, N., Tomlinson, G., McGeer, A., Morris, A., Gardam, M., \u0026amp; Abrams, H. B. (2017). The Effect of Hospital Isolation Precautions on Patient Outcomes and Cost of Care: A Multi-Site, Retrospective, Propensity Score-Matched Cohort Study. Journal of general internal medicine, 32(3), 262\u0026ndash;268. https://doi.org/10.1007/s11606-016-3862-4\u003c/li\u003e\n\u003cli\u003eTimsit, J. F., Rupp\u0026eacute;, E., Barbier, F., Tabah, A., \u0026amp; Bassetti, M. (2020). Bloodstream infections in critically ill patients: an expert statement. Intensive care medicine, 46(2), 266\u0026ndash;284. https://doi.org/10.1007/s00134-020-05950-6\u003c/li\u003e\n\u003cli\u003eTian Q. (2022). Analysis of pathogenic bacteria distribution and drug resistance in patients with bloodstream infection in ICU. Exploration of rational drug use in China, 19(2): 29-35.\u003c/li\u003e\n\u003cli\u003eVanegas, J. M., Parra, O. L., \u0026amp; Jim\u0026eacute;nez, J. N. (2016). Molecular epidemiology of carbapenem resistant gram-negative bacilli from infected pediatric population in tertiary - care hospitals in Medell\u0026iacute;n, Colombia: an increasing problem. BMC infectious diseases, 16(1), 463. https://doi.org/10.1186/s12879-016-1805-7\u003c/li\u003e\n\u003cli\u003eWang, B., Pan, F., Wang, C., Zhao, W., Sun, Y., Zhang, T., Shi, Y., \u0026amp; Zhang, H. (2020). Molecular epidemiology of Carbapenem-resistant Klebsiella pneumoniae in a paediatric hospital in China. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 93, 311\u0026ndash;319. https://doi.org/10.1016/j.ijid.2020.02.009\u003c/li\u003e\n\u003cli\u003eWang, C., Hao, W., Yu, R., Wang, X., Zhang, J., \u0026amp; Wang, B. (2021). Analysis of Pathogen Distribution and Its Antimicrobial Resistance in Bloodstream Infections in Hospitalized Children in East China, 2015-2018. Journal of tropical pediatrics, 67(1), fmaa077. https://doi.org/10.1093/tropej/fmaa077\u003c/li\u003e\n\u003cli\u003eXie, J., Li, S., Xue, M., Yang, C., Huang, Y., Chihade, D. B., Liu, L., Yang, Y., \u0026amp; Qiu, H. (2020). Early- and Late-Onset Bloodstream Infections in the Intensive Care Unit: A Retrospective 5-Year Study of Patients at a University Hospital in China. The Journal of infectious diseases, 221(Suppl 2), S184-S192. https://doi.org/10.1093/infdis/jiz606\u003c/li\u003e\n\u003cli\u003eXiong, Z., Zhang, C., Sarbandi, K., Liang, Z., Mai, J., Liang, B., Cai, H., Chen, X., Gao, F., Lan, F., Liu, X., Liu, S., \u0026amp; Zhou, Z. (2023). Clinical and molecular epidemiology of carbapenem-resistant Enterobacteriaceae in pediatric inpatients in South China. Microbiology spectrum, e0283923. Advance online publication. https://doi.org/10.1128/spectrum.02839-23\u003c/li\u003e\n\u003cli\u003eYan, G., Liu, J., Chen, W., Chen, Y., Cheng, Y., Tao, J., Cai, X., Zhou, Y., Wang, Y., Wang, M., \u0026amp; Lu, G. (2021). Metagenomic Next-Generation Sequencing of Bloodstream Microbial Cell-Free Nucleic Acid in Children With Suspected Sepsis in Pediatric Intensive Care Unit. Frontiers in cellular and infection microbiology, 11, 665226. https://doi.org/10.3389/fcimb.2021.665226\u003c/li\u003e\n\u003cli\u003eZhu, S., Kang, Y., Wang, W., Cai, L., Sun, X., \u0026amp; Zong, Z. (2019). The clinical impacts and risk factors for non-central line-associated bloodstream infection in 5046 intensive care unit patients: an observational study based on electronic medical records. Critical care (London, England), 23(1), 52. https://doi.org/10.1186/s13054-019-2353-5\u003c/li\u003e\n\u003cli\u003eZhang Y, Zhou J, Cao T, Li Zheqian. (2021). Comparison of pathogenic bacteria distribution, drug resistance and clinical characteristics of bloodstream infection between children and adults admitted to intensive care unit. Shandong medicine, 61(12): 4-10. https://doi.org/10.3969/j.issn.1002-266X.2021.12.005\u003c/li\u003e\n\u003cli\u003eZain, O. M., Elsayed, M. Y., Abdelkhalig, S. M., Abdelaziz, M., Ibrahim, S. Y., Bashir, T., \u0026amp; Hamadalnil, Y. (2022). Bloodstream infection in cancer patients; susceptibility profiles of the isolated pathogens, at Khartoum Oncology Hospital, Sudan. African health sciences, 22(4), 70\u0026ndash;76. https://doi.org/10.4314/ahs.v22i4.10\u003c/li\u003e\n\u003cli\u003eZhang, Y., Cao, B., Cao, W., Miao, H., \u0026amp; Wu, L. (2022). Clinical Characteristics and Death Risk Factors of Severe Sepsis in Children. Computational and mathematical methods in medicine, 2022, 4200605. https://doi.org/10.1155/2022/4200605\u003c/li\u003e\n\u003cli\u003eZhu, Y., Zhang, X., Wang, Y., Tao, Y., Shao, X., Li, Y., \u0026amp; Li, W. (2022). Insight into carbapenem resistance and virulence of Acinetobacter baumannii from a children\u0026apos;s medical centre in eastern China. Annals of clinical microbiology and antimicrobials, 21(1), 47. https://doi.org/10.1186/s12941-022-00536-0\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"intm","sideBox":"Learn more about [International Microbiology](https://www.springer.com/journal/10123)","snPcode":"10123","submissionUrl":"https://submission.nature.com/new-submission/10123/3","title":"International Microbiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Children, Pathogen, ICU, Bloodstream infection, Drug resistance, MDR bacteria","lastPublishedDoi":"10.21203/rs.3.rs-3460595/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3460595/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e Children with severe basic diseases and low immunity in the intensive care unit (ICU) are usually in critical condition. It is important to help clinicians choose the appropriate empirical antibiotic therapy for clinical infection control. \u003cstrong\u003eMethods\u003c/strong\u003e 281 children with bloodstream infection (BSI) were retrospectively analyzed. Statistical software was used to compare and analyse the basic data, pathogenic information, and drug resistance of the main bacteria.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e A total of 328 strains were detected, including gram-positive bacteria (223, 68%), mainly including coagulase-negative staphylococci (CoNS), gram-negative bacteria (91, 27.7%), fungi (14, 4.3%). There were 243 cases of single pathogen infection and 38 cases of mixed pathogen infection. Results of binary logistic regression analysis showed that lengths of hospitalization of 0～\u0026lt;30d was an independent risk factor for mixed infection, and length of hospitalization of 15～\u0026lt;60d was an independent risk factor related to death. Compared with \u003cem\u003eEscherichia coli\u003c/em\u003e, the proportion of extended-spectrum β-lactamases (ESBLs) was higher producing by \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, and its resistance to some β-lactamides, quinolones antibiotics were lower. 27 isolates of multi-drug resistant (MDR) bacteria were detected, among which carbapenem-resistant \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e (CRAB) accounted for the highest proportion (13, 48.2%). \u003cstrong\u003eConclusion\u003c/strong\u003e CoNS was the principal pathogen of BSI in the intensive care unit (ICU) of children, and \u003cem\u003eEscherichia coli \u003c/em\u003ewas the most common gram-negative pathogen. It is necessary to continuously monitor patients with positive blood culture, pay special attention to the detected MDR bacteria, and strengthen the application management of antibiotics and the prevention and control of nosocomial infection.\u003c/p\u003e","manuscriptTitle":"Epidemiology and drug resistance analysis of bloodstream infections in intensive care unit from a children's medical center in eastern China for six consecutive years","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-10-29 01:26:13","doi":"10.21203/rs.3.rs-3460595/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2023-12-15T11:52:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-11-30T15:58:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"27cc3520-c22d-4761-90c9-07c118f73f32","date":"2023-11-02T11:18:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-11-02T10:21:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-10-26T08:21:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-10-25T23:05:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Microbiology","date":"2023-10-18T05:16:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"intm","sideBox":"Learn more about [International Microbiology](https://www.springer.com/journal/10123)","snPcode":"10123","submissionUrl":"https://submission.nature.com/new-submission/10123/3","title":"International Microbiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"10bb4fc7-b20b-4132-b86c-1b71ca54b909","owner":[],"postedDate":"October 29th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-01-22T15:10:04+00:00","versionOfRecord":{"articleIdentity":"rs-3460595","link":"https://doi.org/10.1007/s10123-024-00481-2","journal":{"identity":"international-microbiology","isVorOnly":false,"title":"International Microbiology"},"publishedOn":"2024-01-18 15:01:40","publishedOnDateReadable":"January 18th, 2024"},"versionCreatedAt":"2023-10-29 01:26:13","video":"","vorDoi":"10.1007/s10123-024-00481-2","vorDoiUrl":"https://doi.org/10.1007/s10123-024-00481-2","workflowStages":[]},"version":"v1","identity":"rs-3460595","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3460595","identity":"rs-3460595","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}