Literature DB >> 31258218

Available evidence of antibiotic resistance from extended-spectrum β-lactamase-producing Enterobacteriaceae in paediatric patients in 20 countries: a systematic review and meta-analysis.

Yanhong Jessika Hu1, Anju Ogyu1, Benjamin J Cowling1, Keiji Fukuda1, Herbert H Pang1.   

Abstract

OBJECTIVE: To make a systematic review of risk factors, outcomes and prevalence of extended-spectrum β-lactamase-associated infection in children and young adults in South-East Asia and the Western Pacific.
METHODS: Up to June 2018 we searched online databases for published studies of infection with extended-spectrum β-lactamase-producing Enterobacteriaceae in individuals aged 0-21 years. We included case-control, cohort, cross-sectional and observational studies reporting patients positive and negative for these organisms. For the meta-analysis we used random-effects modelling of risk factors and outcomes for infection, and meta-regression for analysis of subgroups. We mapped the prevalence of these infections in 20 countries and areas using available surveillance data.
FINDINGS: Of 6665 articles scanned, we included 40 studies from 11 countries and areas in the meta-analysis. The pooled studies included 2411 samples testing positive and 2874 negative. A higher risk of infection with extended-spectrum β-lactamase-producing bacteria was associated with previous hospital care, notably intensive care unit stays (pooled odds ratio, OR: 6.5; 95% confidence interval, CI: 3.04 to 13.73); antibiotic exposure (OR: 4.8; 95% CI: 2.25 to 10.27); and certain co-existing conditions. Empirical antibiotic therapy was protective against infection (OR: 0.29; 95% CI: 0.11 to 0.79). Infected patients had longer hospital stays (26 days; 95% CI: 12.81 to 38.89) and higher risk of death (OR: 3.2; 95% CI: 1.82 to 5.80). The population prevalence of infection was high in these regions and surveillance data for children were scarce.
CONCLUSION: Antibiotic stewardship policies to prevent infection and encourage appropriate treatment are needed in South-East Asia and the Western Pacific.

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Year:  2019        PMID: 31258218      PMCID: PMC6593334          DOI: 10.2471/BLT.18.225698

Source DB:  PubMed          Journal:  Bull World Health Organ        ISSN: 0042-9686            Impact factor:   9.408


Introduction

Antimicrobial resistance occurs when bacteria are no longer susceptible to the drugs used for treatment. Increasingly, there are fewer antimicrobial drugs available to effectively treat common as well as life-threatening infections. Annual deaths from untreatable infections may rise from estimated 700 000 in 2015 to 10 million by 2050 if antimicrobial resistance is not controlled. Common procedures such as surgery or cancer chemotherapy may become too dangerous to perform without effective antibiotics. Extended-spectrum β-lactamases are enzymes that cause resistance to some of the most commonly used antibiotics, including all penicillins, cephalosporins and monobactams. Fortunately these enzymes have yet to confer resistance to carbapenems, making these drugs valuable for serious extended-spectrum β-lactamase-producing bacterial infections. However, there have been recent outbreaks of extended-spectrum β-lactamase-producing Klebsiella spp. with carbapenem resistance, resulting in extremely high rates of mortality., Within the already limited selection of antibiotics available to treat these infections, fewer are approved for use in children. Children are particularly vulnerable to bacterial infections compared with young adults, due to their immature immune systems., The World Health Organization (WHO) South-East Asia and Western Pacific Regions have over 4.3 billion of the world’s population of 7.7 billion, including two of the most populous countries with heavy consumption of antibiotics: China and India. Research suggests these regions have high antimicrobial resistance rates to extended-spectrum β-lactamase-producing bacteria in the paediatric population. Poor-quality antibiotics and unsupervised use are common across the Regions. The available studies provide an overall impression of the prevalence of antibiotic resistance in the Regions, but better evidence is needed about the risk factors and outcomes for children with these infections. We therefore aimed to make a systematic review and meta-analysis of the risk factors and outcomes of infection with extended-spectrum β-lactamase-producing Enterobacteriaceae in children and young adults in the South-East Asia and the Western Pacific. We also mapped the prevalence of extended-spectrum β-lactamase-associated infections in countries and areas of the Regions using the available surveillance data.

Methods

Meta-analysis

We conducted the meta-analysis in accordance with the Cochrane handbook for systematic reviews of interventions. All procedures followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The study was registered in the PROSPERO International prospective register of systematic reviews (CRD42017069701).

Search strategy

We made a comprehensive search, without language limitation, of online databases for articles published from 1 January 1940 to 30 June 2018 (Box 1). Two researchers independently conducted the search and screened the titles, abstracts and full texts of the papers. We used a standardized, piloted data collection form to determine whether papers were appropriate for inclusion. The researchers applied the Newcastle–Ottawa scale to assess risk of bias in non-randomized studies. Studies scoring ≥ 5 and ≤ 8 were designated low risk of bias, ≥ 3 and ≤ 4 as moderate and ≤ 2 as high. We incorporated the quality assessment results into our sensitivity analysis using the Meta-analyses Of Observational Studies in Epidemiology checklist. Discrepancies at any stage of the analysis were resolved by consensus of the researchers. We searched online databases (Embase®, MEDLINE®, Cochrane Library, Web of Science, Scopus, OvidSP®, EBSCO), electronic abstract databases and references in published articles. For the prevalence study we also searched the grey literature, including the websites of the World Health Organization and the United States Centers for Disease Control, surveillance systems related to antimicrobial resistance, dissertations, conference reports and country reports. When more information about studies was needed we contacted authors or website administrators. We used the following keywords: extended-spectrum beta-lactamase OR extended-spectrum beta-lactamase OR ESBL* OR ESBLs OR ESBL-producing* AND paediatric OR pediatric OR juvenile OR child OR children OR adolescence OR infant OR neonat* OR neonatal OR newborn OR nursery AND Asia OR Asia Pacific OR South Asia OR The Western Pacific OR South-East Asia OR Australia OR Bangladesh OR Bhutan OR Brunei Darussalam OR Cambodia OR China OR Cook Islands OR Democratic People's Republic of Korea OR Fiji OR India OR Indonesia OR Japan OR Kiribati OR Lao People's Democratic Republic OR Malaysia OR Maldives OR Marshall Islands OR Federated States of Micronesia (Federated States of) OR Mongolia OR Myanmar OR Nauru OR Nepal OR New Zealand OR Niue OR Palau OR Papua New Guinea OR Philippines OR Republic of Korea OR Samoa OR Singapore OR Solomon Islands OR Sri Lanka OR Thailand OR Timor-Leste OR Tonga OR Tuvalu OR Vanuatu OR VietNam

Selection criteria

We included cohort, case–control and observational or cross-sectional studies. We defined the target population as children aged from birth to 21 years, according the American Academy of Paediatrics guidelines. We included studies that were conducted in the WHO South-East Asia and Western Pacific Regions and that recorded both positive and negative results of testing for extended-spectrum β-lactamase-producing bacteria.

Outcome measures

The principal outcome measure was patients’ infection status, defined by whether specimens obtained tested positive or negative for infection with extended-spectrum β-lactamase-producing bacteria. We analysed infection status by risk sub-groups: medical history in the 3 months before the infection (hospital stay, intensive care unit admission, surgery), exposure to invasive life support, antibiotic therapy and co-morbidities or underlying conditions. Other outcomes recorded were: hospital length of stay, mortality, persistent bacteraemia, antibiotic residence and duration of fever after antibiotic therapy.

Data synthesis and analysis

For the meta-analysis we pooled the data on number of isolates (four studies) or patients with isolates (37 studies) using a Mantel–Haenszel random-effects model to determine the risk of infection with extended-spectrum β-lactamase-producing bacteria. We calculated pooled odds ratio (OR) and 95% confidence intervals (CI) for dichotomous outcomes and weighted mean difference and 95% CI for continuous outcomes. All tests were two-tailed and P < 0.05 was considered statistically significant. If studies provided median and interquartile range, we made estimates of the mean and standardized deviation (SD). We assessed the heterogeneity of the studies using the I statistic, which evaluates the consistency of study results. The cut-off for defining heterogeneity was I > 50%. Our sensitivity analyses were based on sample size on the overall summary estimates. We evaluated whether this restricted analysis affected the magnitude, direction and statistical significance of the overall summary estimate. Additional sensitivity analyses assessed the different types of study designs, settings and risk of bias. We carried out meta-regression to explore each potential factor contributing to heterogeneity between studies, such as study location, design, duration and setting, and patients’ age and diagnosis, for all included studies reporting mortality and persistent bacteraemia. We used funnel plots with Egger regression test to assess publication bias (P < 0.1). All statistical analyses were performed with R software, version 3.4.0 (R Foundation for Statistical Computing, Vienna, Austria), using the Meta and Metafor meta-analysis packages.

Prevalence study

We obtained data on the prevalence of extended-spectrum β-lactamase-associated infection from the same studies included in the meta-analysis. We also made a search for other data sources in the published and grey literature (Box 1). We included data on children (ages 0–21 years), where available, and all age groups, if data for these ages were unavailable. We calculated percentage prevalence by the number of people or isolates testing positive for extended-spectrum β-lactamases out of the total population or isolates tested. For case–control studies, the overall prevalence rate was extracted instead. Numbers of cases and samples were extracted if stated by the source. Where population maps were provided in the source material, the average of the range were extracted as the prevalence in the country. We pooled the prevalence data by calculating the mean of the extracted data from all sources for each country.

Results

Study selection and characteristics

The database search yielded 6665 articles. We removed 1089 duplicates and excluded a further 3046 studies after screening titles and abstracts. After assessing the full text of 577 studies, we excluded 537. Screening of reference lists and conference abstracts yielded no additional studies. In total, 40 studies were included in the meta-analysis (Fig. 1). Three studies were reported in Chinese language, one study each in Korean and French, and the remaining 35 were in English.
Fig. 1

Flow diagram of the systematic review of extended-spectrum β-lactamase-associated infection among children and young adults in South-East Asia and Western Pacific countries

Flow diagram of the systematic review of extended-spectrum β-lactamase-associated infection among children and young adults in South-East Asia and Western Pacific countries EBSL: extended-spectrum β-lactamase-producing bacteria; WHO: World Health Organization. Overall, the 40 studies reported 46 960 bacterial isolates from 17 829 children providing samples. We pooled data from 2411 samples testing positive and 2874 testing negative for extended-spectrum β-lactamase-producing bacteria over the study period up to June 2018. The most common method of detection of bacterial phenotypes was agar disk diffusion in 32 studies. The study designs were 11 retrospective cohort studies, 14 prospective cohort studies, six observational studies, two cross-sectional studies and seven case–control studies. We found studies from 11 different countries and areas: Taiwan, China; India; Indonesia; Japan; Malaysia; Republic of Korea; Singapore; Sri Lanka; Thailand; and Viet Nam. In 15 studies the focus was specifically on neonates (< 28 days old), 15 studies were of age groups 0–21 years (excluding neonates), seven studies were of age 0–5 years (excluding neonates) and three studies did not specify the ages (Table 1; available at: http://www.who.int/bulletin/volumes/96/7/18-225698).
Table 1

Characteristics of 40 studies included in the meta-analysis of extended-spectrum β-lactamase-associated infection among children and young adults in South-East Asia and Western Pacific countries, 2002–2018

AuthorCountry or areaStudy datesStudy designStudy durationStudy settingDiagnosisSpecimen siteSample agesNo. of childrenNo. of samples
Prevalence of ESBL infection, %No. of isolates or culturesBacterial speciesESBL detection methodGuidelines used
ESBL-positiveESBL-negative
Kim et al., 200220Republic of KoreaNov 1993–Dec 1998Cohort5 yearsCommunityUrinary tract infectionUrine0–17 years142499317157Escherichia coli, Klebsiella pneumoniae Double disk diffusionNCCLS, 2002
Jain et al., 200321India1 yearCohort1 yearHospitalSepsisBloodNeonates7281653679400E. coli, K. pneumoniae, Enterobacter spp.Double disk synergy testCLSI, 2000 & NCCLS, date NS
Boo et al., 200522Malaysia1996–Oct 2002Case–control7 yearsHospitalSepsisVariousNeonates350808022369K. pneumoniae, Enterobacter spp.Double disk diffusionMinistry of Health of Malaysia, 2001
Chiu et al., 200523Taiwan, ChinaJan 2001–Dec 2001Cohort1 yearHospitalNosocomial infectionVariousNeonates7634424476E. coli, K. pneumoniae, KSDouble disk diffusionNCCLS, 2001
Huang et al., 200724ChinaJan 2000–Dec 2002Cohort3 yearsHospitalNosocomial infectionVariousNeonates392217562358E. coli, K. pneumoniae Double disk diffusionNCCLS, 2000
Jain & Mondal, 200725,bIndiaJan 2004–Dec 2005Cohort2 yearsHospitalSepsisBloodNeonates1005842582995K. pneumoniae, Enterobacter spp.Double disk diffusionNCCLS, 2003
Kuo et al., 200726Taiwan, ChinaJan 2000–Oct 2005Case–control5 years 9 monthsHospitalVariousVariousBirth to NS108545428274K. pneumoniae Double disk diffusionNCCLS, 2001
Lee et al., 200727Republic of KoreaJan 1999–Dec 2005Cohort7 yearsHospitalVariousVariousNS228355429252E. coli, K. pneumoniae Double disk synergy test, Vitek-GNI cardCLSI, 2005
Sehgal et al., 200728IndiaApril 2002–May 2003Cohort1 yearHospitalSepsisBloodNeonates7538256175Multiple speciesaDouble disk diffusionNCCLS, 2002
Bhattacharjee et al., 200829,bIndia14 monthsCohort1 year 2 monthsHospitalSepsisBloodNeonates243265832243Multiple speciesaDouble disk diffusionCLSI, 2008
Anandan et al., 200930,bIndiaJan 2003–Dec 2007Cohort5 yearsHospitalSepsisBloodNeonates946826728330E. coli, K. pneumoniae Not specifyCLSI, 2008
Kim et al., 200931Republic of KoreaJan 2004–Apr 2009Cohort5 years 2 monthsCommunityUrinary tract infectionUrineChildren854328317681E. coli, K. pneumoniae Vitek 2 systemCLSI, date NS
Shakil et al., 201032IndiaJan 2006–Feb 2007Cohort1 yearsHospitalVariousVariousNeonates23810410744469E. coli, K. pneumoniae Double disk diffusionCLSI, date NS
Gaurav et al., 201133IndiaMay 2007–Apr 2008Case–control1 yearHospitalSepsisBloodNeonates3445052365116E. coli, K. pneumoniae Double disk diffusionCLSI, date NS
Liu et al., 201134ChinaFeb 2009–Jan 2011Cohort2 yearsHospitalLower respiratory tract infectionSputum< 3 years2429414839242Multiple speciesaDouble disk synergy testCLSI, date NS
Wei et al., 201135ChinaJan 2009–Dec 2009Observational1 yearHospitalLower respiratory tract infectionSputum< 1 year272144128531380Multiple speciesaDouble disk synergy testCLSI, 2009
Minami et al., 201236JapanJuly 2011 (1 day)Cross-sectional1 dayHospitalVariousRectal≤ 12 years504461262Multiple speciesaDouble disk synergy testCLSI, 2008
Zheng et al., 201237China2002–2008Cohort6 yearsHospitalHaematological malignancyBlood< 16 years1091938523264E. coli, K. pneumoniae Vitek 60 systemNCCLS, date NS
Vijayakanthi et al., 201338IndiaDec 2009–Nov 2010Cohort1 yearHospitalSepsisVariousNeonates15083917150Multiple speciesaDouble disk diffusionCLSI, date NS
Fan et al. 201439Taiwan, China2002–2006Case–control4 yearsCommunityUrinary tract infectionUrine< 15 years312104208336467E. coliDouble disk diffusionCLSI, 2007
Themphachana et al., 201440ThailandFeb–Sep 2013Observational8 monthsHospitalUrinary tract infectionUrine< 21 years166828326166E. coli, K. pneumoniae Double disk diffusionCLSI, 2012
Young et al., 201441SingaporeNov 2006–Feb 2007Observational3 monthsCommunityVariousVarious< 21 years10066912441006ESBL-producing Enterobacteriaceae, methicillin-resistant Staphylococcus aureus; vancomycin-resistant Enterococcus spp.Double disk diffusionCLSI, 2007
Zuo et al., 201442ChinaJan–Dec 2013Observational1 yearHospitalLower respiratory tract infectionSputum1‒3 months622939479379E. coli, K. pneumoniae Kirby-Bauer disk diffusionCLSI, 2012
Duong et al., 201543Viet NamJul 2011–Nov 2012Cohort1 year 4 monthsHospitalUrinary tract infectionVarious3 months‒15 years216221752143E. coli, K. pneumoniae Double disk diffusionCLSI, 2007
Han et al., 201517,cRepublic of KoreaApr 2009–Mar 2013Cohort4 yearsHospitalNeutropoenia (febrile)Blood< 20 years6121403461E. coli, K. pneumoniae Vitek 2 systemNS
Han et al., 201544,dRepublic of KoreaJan 2010–Dec 2014Cohort4 yearsHospitalUrinary tract infectionUrine< 18 years2052218910211E. coli, K. pneumoniae Vitek 2 systemNS
Nisha et al., 201545IndiaNov 2012–Jan 2015Cohort3 yearsCommunityUrinary tract infectionUrine≤ 18 years38515922641385E. coliKirby-Bauer disk diffusionCLSI, date NS
Agarwal et al., 2016 46,bIndia2009–2012Cohort4 yearsHospitalDiarrhoeaStoolYoung children63392398196339E. coli, K. pneumoniae Vitek 2 systemCLSI, date NS
Amornchaicharoensuk, 201647ThailandJan 2010–Dec 2014Cohort5 yearsHospitalUrinary tract infectionUrine0–15 years117196916117E. coli, K. pneumoniae Hospital laboratoryCLSI, date NS
Sharma et al., 201648IndiaJan 2013–Aug 2014Observational1 year 7 monthsHospitalSepsisBloodNeonates144910166611449Multiple speciesaDouble disk synergy testNCCLS, date NS
Tsai et al., 201649Taiwan, ChinaJan 2001–Dec 2012Case–control12 yearsHospitalBacteraemiaBloodNeonates3507731614542Multiple speciesaDouble disk synergy testCLSI, 2012
Chen et al., 201750Taiwan, ChinaJan 2004–Jul 2015Cross-sectional11 yearsHospitalBacteraemiaBloodNeonates275221927E. coliNot specifyNS
He et al., 201751ChinaMar 2011–Jun 2016Cohort4 years 3 monthsHospitalLower respiratory tract infectionSputum1 month‒5 years2366472472360E. coli, K. pneumoniae Double disk synergy testCLSI, date NS
Kim et al., 201752Republic of KoreaJan 2010–Jun 2015Cohort5 years 5 monthsHospitalBacteraemiaBlood≤ 17 years185499335185E. coli, K. pneumoniae Double disk synergy testNCCLS, 2001
Mandal et al., 201753IndiaTwo consecutive yearCohort2 yearsCommunityDiarrhoeaStool0–60 months6337211938633E. coliModified Kirby-Bauer disk diffusionCLSI, date NS
Nisha et al., 201754IndiaNov 2012–Mar 2016Cohort4 years 5 monthsCommunityUrinary tract infectionUrine3 months‒18 years52319632738523E. coliKirby-Bauer disk diffusionCLSI, 2010
Tsai et al., 201755Taiwan, China2010–2014Observational5 yearsHospitalBacteraemiaBlood< 3 years4114273441E. coliNSNS
Bunjoungmanee et al., 201856ThailandJun 2016–May 2017Case–control1 yearHospital & communityUrinary tract infectionUrine1 month‒5 years8040402380E. coli, K. pneumoniae Double disk diffusionCLSI, 2010
Kitagawa et al., 201857Indonesia and JapanJan–Nov 2014Case–control1 yearHospital & communityUrinary tract infectionUrine0–15 years9437133994E. coli, K. pneumoniae Double disk diffusionCLSI, date NS
Weerasinghe et al., 201858Sri LankaJan–April 2011Cohort3 monthsHospitalVariousVariousNeonates501883650E. coli, K. pneumoniae Double disk diffusionCLSI & CDC, 2011

CDC: Centers for Disease Control and Prevention; CLSI: Clinical and Laboratory Standards Institute; ESBL: extended-spectrum β-lactamase-producing bacteria; NCCLS: National Committee for Clinical Laboratory Standards; NS: not specified.

a Multiple species included Klebsiella pneumonia; Escherichia coli; Pseudomonas spp.; Acinetobacter spp.; Enterobacter spp.; and Citrobacter spp.

b Studies with data only on isolates; the remaining studies included data on patients and isolates.

c Neutrpoenia study.

d Urinary tract infection study.

CDC: Centers for Disease Control and Prevention; CLSI: Clinical and Laboratory Standards Institute; ESBL: extended-spectrum β-lactamase-producing bacteria; NCCLS: National Committee for Clinical Laboratory Standards; NS: not specified. a Multiple species included Klebsiella pneumonia; Escherichia coli; Pseudomonas spp.; Acinetobacter spp.; Enterobacter spp.; and Citrobacter spp. b Studies with data only on isolates; the remaining studies included data on patients and isolates. c Neutrpoenia study. d Urinary tract infection study.

Risk factors

The risk of infection with extended-spectrum β-lactamase-producing bacteria was significantly higher for patients whose medical history included intensive care unit admission (OR: 6.5; 95% CI: 3.04 to 13.73; I: 65%; six studies), hospitalization (OR: 3.3; 95% CI: 1.95 to 5.57; I: 80%; 11 studies) or surgery (OR: 2.3; 95% CI: 1.41 to 3.81; I: 25%; six studies; Table 2).
Table 2

Pooled risk of extended-spectrum β-lactamase-associated infection among children and young adults in South-East Asia and Western Pacific countries by medical history and co-morbid conditions, 2002–2018

SubgroupNo. of studiesTotal no. of patientsESBL-positive, no.
ESBL-negative, no.
Pooled OR (95% CI)aI2, %
EventsTotalEventsTotal
Received medical care in previous 3 months 
Recent intensive care unit stay61258124399658596.46 (3.04 to 13.73)65
Recent hospitalization11293631872736722093.30 (1.95 to 5.57)80
Recent surgery6117858433377452.32 (1.41 to 3.81)8
Pre-infection hospitalization3223NA110NA11311.42b (−7.86 to 30.71)99
Diagnosis of co-morbid or underlying conditions
Bacteraemia69581032221097365.30 (3.64 to 7.72)38
Lower respiratory tract infection48372133951344425.01 (3.50 to 7.19)79
Recurrent urinary tract infection11214935580832813412.01 (1.67 to 2.43)90
Nosocomial infection2114405521595.19 (2.23 to 12.07)92
Various diagnoses7177222954533912272.68 (2.06 to 3.48)79
Sepsis109703975501464204.61 (3.34 to 6.35)80
Received antibiotics in the previous 3 months
Third-generation cephalosporin11231838477724915414.81 (2.25 to 10.27)89
Vancomycin381369235795783.39 (2.21 to 5.20)0
Quinolone51242105477557652.99 (1.04 to 8.63)79
Carbapenem5115668405497512.85 (1.47 to 5.53)42
Aminoglycoside714441514852359592.84 (1.21 to 6.65)83
Penicillin917503807982499522.87 (1.10 to 7.47)92
Received antibiotic prophylaxis 4703842381324651.82 (1.16 to 2.86)0
Received any antibiotic 13228934058445717053.58 (2.30 to 5.57)60
Received appropriate empirical antibiotic therapy 58031021924636110.29 (0.11 to 0.79)65
Exposed to invasive life support
Total parenteral nutrition58052162833505223.77 (1.35 to 10.56)79
Continuous positive airway pressure36821482413034413.35 (0.54 to 20.61)91
Mechanical ventilation610981374322716663.29 (1.03 to 10.53)83
Endotracheal intubation811571874073477502.06 (1.22 to 3.49)61
Central venous catheter99572443524296051.69 (1.00 to 2.85)41

CI: confidence interval; EBSL: extended-spectrum β-lactamase-producing bacteria; NA: not applicable; OR: odds ratio.

a Mantel–Haenszel random-effects.

b Pre-infection hospitalization is the time of hospitalization to the time while patients with confirmed infection with extended-spectrum β-lactamase-producing Enterobacteriaceaeis, expressed as mean difference in days between positive and negative patients (standard deviation).

CI: confidence interval; EBSL: extended-spectrum β-lactamase-producing bacteria; NA: not applicable; OR: odds ratio. a Mantel–Haenszel random-effects. b Pre-infection hospitalization is the time of hospitalization to the time while patients with confirmed infection with extended-spectrum β-lactamase-producing Enterobacteriaceaeis, expressed as mean difference in days between positive and negative patients (standard deviation). The risk of infection was higher for patients with co-existing bacteraemia (OR: 5.3; 95% CI: 3.64 to 7.72; I: 38%; six studies), nosocomial infections (OR: 5.2; 95% CI: 2.23 to 12.07; I: 92%; two studies), lower respiratory tract infections (OR: 5.0; 95% CI: 13.50 to 7.19; I: 79%; four studies), sepsis (OR: 4.6 95% CI: 3.34 to 6.35; I: 80%; 10 studies) or recurrent urinary tract infections (OR: 2.0; 95% CI: 1.61 to 2.43; I: 90%; 11 studies; Table 2). Antibiotics associated with risk of infection included third-generation cephalosporins (OR: 4.8; 95% CI: 2.25 to 10.27; I: 89; 11 studies), vancomycin (OR: 3.4; 95% CI: 2.21 to 5.20; I: 0%; three studies) and quinolones (OR: 3.0; 95% CI: 1.04 to 8.63, I: 79; five studies). Five studies reported that appropriate initiation of empirical antibiotics was protective, showing a pooled OR of infection of 0.29 (95% CI: 0.11 to 0.79; I: 65%; five studies; Table 2). Exposure to continuous positive airway pressure therapy was not significantly associated with a risk of infection (OR: 3.4; 95% CI: 0.54 to 20.61; three studies). Other types of invasive life support were a risk, however. The OR for total parenteral nutrition was 3.8 (95% CI: 1.35 to 10.56; five studies). For mechanical ventilation the OR was 3.3 (95% CI: 1.03 to 10.53; six studies) and for endotracheal intubation 2.1 (95% CI: 1.22 to 3.49; eight studies). Central venous catheterization had an OR of 1.7 (95% CI: 1.00 to 2.85; nine studies; Table 2).

Treatment outcomes

Most specimens from patients with extended-spectrum β-lactamase-producing bacterial infection showed resistance to multiple antibiotics. The risk of antibiotic resistance was highest for extended-spectrum β-lactamase-positive patients treated with cephalosporins (OR: 70.5; 95% CI: 43.25 to 115.02; I: 83%; 25 studies) and lowest with cotrimoxazole (OR: 1.8; 95% CI: 1.35 to 2.47; I: 43%; 15 studies). The ORs for resistance to tetracyclines and nitrofurantoin were not statistically significant (Table 3).
Table 3

Pooled risk of antibiotic resistance to extended-spectrum β-lactamase-producing bacteria in specimens from children and young adults in South-East Asia and Western Pacific countries by antibiotic class, 2002–2018

Antibiotic classNo. of studiesTotal no. of patientsESBL-positiveESBL-negativePooled OR (95% CI)aI2, %
EventsTotalEventsTotal
Cephalosporins25344413391483632196170.50 (43.25 to 115.02)83
Monobactams88792744126346741.16 (14.05 to 120.55)58
Penicillins243148116013041091184419.41 (8.67 to 43.46)86
Aminoglyclosides253449495145227619975.71 (3.42 to 9.54)74
Combinationsb222993706114173918524.37 (1.95 to 9.82)91
Carbapenems2229407912446416963.99 (1.68 to 9.48)0
Fluoroquinolones253351627143960719123.33 (2.14 to 5.17)78
Cotrimoxazole15234654786875514781.82 (1.35 to 2.47)43
Tetracyclines714473556193578281.58 (0.76 to 3.30)81
Nitrofurantoin31039584239060.97 (0.64 to 1.46)14

CI: confidence interval; EBSL: extended-spectrum β-lactamase-producing bacteria; OR: odds ratio.

a Mantel–Haenszel random-effects.

b Combinations: Ampicillin + sulbactam; ticarcillin + clavulanic acid; amoxicillin + clavulanate; cefoperazone + sulbactam; piperacillin + tazobactam; ceftazidime+ clavulanic acid.

CI: confidence interval; EBSL: extended-spectrum β-lactamase-producing bacteria; OR: odds ratio. a Mantel–Haenszel random-effects. b Combinations: Ampicillin + sulbactam; ticarcillin + clavulanic acid; amoxicillin + clavulanate; cefoperazone + sulbactam; piperacillin + tazobactam; ceftazidime+ clavulanic acid. The duration of fever was 0.61 days longer in patients with extended-spectrum β-lactamase-producing bacteria than patients without (95% CI: 0.18 to 0.72; I: 92%; seven studies; Fig. 2). Pooling five studies we found that persistent bacteraemia was four times higher in patients positive for extended-spectrum β-lactamase-producing bacteria (95% CI: 2.66 to 6.14; I: 0%; Fig. 3). Results from eight studies showed that the mean difference in length of hospital stay was 25.9 days (95% CI: 12.81 to 38.89; I: 100%) for patients with extended-spectrum β-lactamase-associated infection than those without such infection (Fig. 4). Subgroup analysis showed that the mean length of hospital stay associated with infection was 29 days longer for patients who had recently been admitted to an intensive care unit care than the patients not receiving this care. Similar results were seen for invasive life support; the mean length of stay after central venous catheterization was 33 days longer than without catheterization.59
Fig. 2

Duration of fever after antibiotic therapy among children and young adults with and without extended-spectrum β-lactamase-associated infection in South-East Asia and Western Pacific countries

Fig. 3

Persistent bacteraemia among children and young adults with and without extended-spectrum β-lactamase-associated infection in South-East Asia and Western Pacific countries

Fig. 4

Length of hospital stay among children and young adults with and without extended-spectrum β-lactamase-associated infection in South-East Asia and Western Pacific countries

Duration of fever after antibiotic therapy among children and young adults with and without extended-spectrum β-lactamase-associated infection in South-East Asia and Western Pacific countries CI: confidence interval; EBSL: extended-spectrum β-lactamase-producing bacteria; SD: standard deviation. Note: We made inverse variance (IV) random-effects. Persistent bacteraemia among children and young adults with and without extended-spectrum β-lactamase-associated infection in South-East Asia and Western Pacific countries CI: confidence interval; EBSL: extended-spectrum β-lactamase-producing bacteria; OR: odds ratio. Note: We made Mantel–Haenszel random-effects. Length of hospital stay among children and young adults with and without extended-spectrum β-lactamase-associated infection in South-East Asia and Western Pacific countries CI: confidence interval; EBSL: extended-spectrum β-lactamase-producing bacteria; SD: standard deviation. Note: We made inverse variance (IV) random-effects. Eleven studies reported a pooled number of 188 deaths among 565 patients with extended-spectrum β-lactamase-associated infections compared with 86 deaths in 745 patients without these infections (OR: 3.2; 95% CI: 1.82 to 5.80; I 49%; Fig. 5). When analysed by subgroups, the risk of death for patients who had previously been admitted to the intensive care unit or exposed to central venous catheterization were not significant. However, the risk of death was higher among patients with sepsis (OR: 4.9 95% CI: 2.11 to 11.39; I: 38%) than those without sepsis (OR: 2.3 95% CI: 1.19 to 4.26; I: 35%;).59
Fig. 5

Mortality among children and young adults with and without extended-spectrum β-lactamase-associated infection in South-East Asia and Western Pacific countries

Mortality among children and young adults with and without extended-spectrum β-lactamase-associated infection in South-East Asia and Western Pacific countries CI: confidence interval; EBSL: extended-spectrum β-lactamase-producing bacteria; OR: odds ratio. Note: We made Mantel–Haenszel random-effects. We also looked at the ORs for neonates and non-neonates but the differences not statistically significant between these groups.59

Validity tests

None of the factors we analysed by meta-regression were contributors to between-study heterogeneity. In the Newcastle-Ottawa analysis of risk of bias, we found that 60% (24 out of 40) of studies scored high on risk of bias and 40% were low risk (Table 4; Table 5). Only four studies had clear statements about comparability and 10 about representativeness. The results from Egger’s regression test revealed that publication bias was significant (P < 0.001). Sensitivity analysis excluding small studies with samples less than 10 revealed that the funnel plots were consistently asymmetric (P < 0.001; available from the corresponding author). The sensitivity analysis showed that the data were not consistent with from the overall estimated ORs and similar trends were observed. This evaluation showed that a more restricted analysis of the data did not affect the magnitude, direction and the overall summary estimate.
Table 4

Risk of bias in case–control and cross-sectional studies included in the meta-analysis of extended-spectrum β-lactamase-associated infection among children and young adults in South-East Asia and Western Pacific countries, 2005–2018

AuthorSelection
Comparability
Exposure
Total scoreb
Representativeness of sampleSample sizeNon-respondentsAscertainment of exposure (risk factor)Different outcome groups are comparable; confounding factors are controlledaAssessment of exposure or outcomeSame method of ascertainment for cases and controlsNon-response rate or statistical test
Boo et al., 200522011101116
Kuo et al., 200726011001115
Gaurav et al., 201133011001115
Minami et al., 201236,c100001114
Fan et al. 201439011101116
Themphachana et al., 201440,c010001114
Young et al., 201441,c110101105
Zuo et al., 201442,c001011014
Sharma et al., 201648,c010101115
Tsai et al., 201755110101116
Chen et al., 201750110001115
Bunjoungmanee et al., 201856011001104
Kitagawa et al., 201857011001104

a Subjects in different outcome groups are comparable, based on the study design or analysis.

b Maximum score: 8.

c Cross-sectional study.

Notes: We applied the Newcastle–Ottawa scale to assess risk of bias in non-randomized studies. Only studies scoring ≥ 5 and ≤ 8 were designated low risk of bias, ≥ 3 and ≤ 4 as moderate and ≤ 2 as high. We made Mantel-Haenszel radom-effects

Table 5

Risk of bias in cohort studies included in the meta-analysis of extended-spectrum β-lactamase-associated infection among children and young adults in South-East Asia and Western Pacific countries, 2002–2018

AuthorSelection
Comparability
ExposureTotal scoreb
Representativeness of the exposed cohortSelection of the non-exposed cohortAscertainment of exposureDemonstration that outcome of interest was not present at the start of studyCohorts are comparable based on the design or analysisAssessment of outcomeaFollow -up long enough for outcomes to occurAdequacy of follow-up of cohorts
Kim et al., 200220001001114
Jain et al., 200321001001114
Chiu et al., 200523101001115
Huang et al., 200724001001114
Jain & Mondal, 200725001001114
Lee et al., 200727101001115
Sehgal et al., 200728001001114
Bhattacharjee et al., 200829001001114
Anandan et al., 200930001001114
Kim et al., 200931001001114
Shakil et al., 201032101001115
Liu et al., 201134001001114
Wei et al., 201135001001114
Zheng et al., 201237001001114
Vijayakanthi et al., 201338001001115
Themphachana et al., 201440001001114
Duong et al., 201543001001114
Han et al., 201517,c001001114
Han et al., 201544,d001001114
Nisha et al., 201545001011115
Agarwal et al., 2016 46 001001114
Amornchaicharoensuk, 201647001011115
He et al., 201751101001115
Kim et al., 201752101001115
Mandal et al., 201753001011104
Nisha et al., 201754001001114
Tsai et al., 201755100001114
Weerasinghe et al., 201858011001104

a Subjects in different outcome groups are comparable, based on the study design or analysis. Confounding factors are controlled

b Maximum score: 8.

C Neutropoenia study

d Urinary tract infection study.

Notes: We applied the Newcastle–Ottawa scale to assess risk of bias in non-randomized studies. Only studies scoring ≥ 5 and ≤ 8 were designated low risk of bias, ≥ 3 and ≤ 4 as moderate and ≤ 2 as high.

a Subjects in different outcome groups are comparable, based on the study design or analysis. b Maximum score: 8. c Cross-sectional study. Notes: We applied the Newcastle–Ottawa scale to assess risk of bias in non-randomized studies. Only studies scoring ≥ 5 and ≤ 8 were designated low risk of bias, ≥ 3 and ≤ 4 as moderate and ≤ 2 as high. We made Mantel-Haenszel radom-effects a Subjects in different outcome groups are comparable, based on the study design or analysis. Confounding factors are controlled b Maximum score: 8. C Neutropoenia study d Urinary tract infection study. Notes: We applied the Newcastle–Ottawa scale to assess risk of bias in non-randomized studies. Only studies scoring ≥ 5 and ≤ 8 were designated low risk of bias, ≥ 3 and ≤ 4 as moderate and ≤ 2 as high. The overall pooled prevalence of extended-spectrum β-lactamase in the studies included the meta-analysis combined with surveillance reports was 25.3%. The pooled prevalence from the studies in the meta-analysis was 39% among the 31 studies conducted in hospital settings and 31% in the seven studies conducted in community settings (two studies were in both hospital and the community). Using data from other sources, we mapped population surveillance data from a total of 21 countries and areas in the South-East Asia and the Western Pacific Regions (Table 6). The pooled data from all available surveillance resources that included adults and children showed that India had the highest pooled prevalence (90.0%) and Australia the lowest (3.6%; numerators and denominators unavailable). The pooled data specifically for children, where available from surveillance resources and published data, showed similar results (Fig. 6).
Table 6

Pooled prevalence of overall population of extended-spectrum β-lactamase-associated infection from available surveillance data in 20 South-East Asia and Western Pacific countries or areas

Country or areaData sourceaPrevalence in childrenb by data source
Prevalence in children and adultsc by data source
Pooled prevalence, %
No. of peopleNo. (%) ESBL-positiveNo. of peopleNo. (%) ESBL-positive
AustraliaSENTRY, 1998–199960NANA6608 (1.2)3.6
SMART, 201161802 (2.5)802 (2.5)
CDDEP, 2011–201410NANANRNR (4.5)
AURA, 201562NANANRNR (6.0)
BhutanCDDEP, 2011–201410NANANRNR (29.5)29.5
Brunei DarussalamCDDEP, 2011–201410NANANRNR (4.5)4.5
CambodiaCDDEP, 2011–201410NANANRNR (49.5)49.5
ChinaSENTRY, 1998–199961NANA24763 (25.5)47.5
CDDEP, 2011–201410NANANRNR (69.5)
China, Hong Kong Special Administrative Region SENTRY, 1998–199961NANA32443 (13.3)13.3
Taiwan, China SENTRY, 1998–199961NANA13911 (7.9)7.9
IndiaCDDEP, 2011–201410NANANRNR (90.0)90.0
JapanSENTRY, 1998–199961NANA27218 (6.6)10.6
CDDEP, 2011–201410NANANRNR (14.5)
MalaysiaCDDEP, 2011–201410NANANRNR (14.5)14.5
Federated States of Micronesia (Federated States of)CDDEP, 2011–201410NANANRNR (69.5)69.5
MyanmarCDDEP, 2011–201410NANANRNR (69.5)69.5
NepalCDDEP, 2011–201410NANANRNR (29.5)29.5
New ZealandCDDEP, 2011–201410NANANRNR (4.5)3.7
ESR, 201663NRNR (2.8)NRNR (2.8)
Papua New GuineaCDDEP, 2011–201410NANANRNR (29.5)29.5
PhilippinesSENTRY, 1998–199961NANA29858 (19.5)24.5
CDDEP, 2011–201410NANANRNR (29.5)
Republic of KoreaCDDEP, 2011–201410NANANRNR (29.5)29.5
SingaporeSENTRY, 1998–199961NANA15331 (20.3)20.3
ThailandCDDEP, 2011–201410NANANRNR (29.5)29.5
Viet NamSMART, 2011613815 (39.5)3815 (39.5)54.5
CDDEP, 2011–201410NANANRNR (69.5)

EBSL: extended-spectrum β-lactamase; NA: not applicable; NR: not reported.

a Data sources: AURA: Antimicrobial Use and Resistance in Australia Surveillance System; CDDEP: Center for Disease Dynamics, Economics & Policy; ESR: Institute of Environmental Science and Research Surveillance System in New Zealand; SENTRY: Antimicrobial Surveillance Program by JMI Laboratories; SMART: Study for Monitoring Antimicrobial Resistance Trends.

b Ages 0–21 years.

c Ages not specified.

Notes: We searched the published and grey literature for surveillance data from all Member States and areas in the World Health Organization South-East Asia and Western Pacific Regions. No data were available for: Bangladesh, Cook Islands, Democratic People's Republic of Korea, Fiji, Indonesia, Kiribati, Lao People's Democratic Republic, Maldives, Marshall Islands, Mongolia, Nauru, Niue, Palau, Samoa, Solomon Islands, Timor-Leste, Tonga, Tuvalu and Vanuatu.

Fig. 6

Map of prevalence of extended-spectrum β-lactamase-associated infection in South-East Asia and Western Pacific countries

EBSL: extended-spectrum β-lactamase; NA: not applicable; NR: not reported. a Data sources: AURA: Antimicrobial Use and Resistance in Australia Surveillance System; CDDEP: Center for Disease Dynamics, Economics & Policy; ESR: Institute of Environmental Science and Research Surveillance System in New Zealand; SENTRY: Antimicrobial Surveillance Program by JMI Laboratories; SMART: Study for Monitoring Antimicrobial Resistance Trends. b Ages 0–21 years. c Ages not specified. Notes: We searched the published and grey literature for surveillance data from all Member States and areas in the World Health Organization South-East Asia and Western Pacific Regions. No data were available for: Bangladesh, Cook Islands, Democratic People's Republic of Korea, Fiji, Indonesia, Kiribati, Lao People's Democratic Republic, Maldives, Marshall Islands, Mongolia, Nauru, Niue, Palau, Samoa, Solomon Islands, Timor-Leste, Tonga, Tuvalu and Vanuatu. Map of prevalence of extended-spectrum β-lactamase-associated infection in South-East Asia and Western Pacific countries ESBL: extended-spectrum β-lactamase. Notes: We pooled data from a search of the published and grey literature for surveillance data from all Member States and areas in the World Health Organization South-East Asia and Western Pacific Regions. The map for adults and children includes data from Australia; Bhutan; Brunei Darussalam; Cambodia; Taiwan, China; China, Hong Kong Special Administrative Region; India; Indonesia; Japan; Federated States of Micronesia (Federated States of); Myanmar; Nepal; New Zealand; Papua New Guinea; Philippines; Republic of Korea; Singapore; Thailand and Viet Nam. The map for children only (ages 0–21 years) includes data from Australia (2.5%); China (54.3%); Taiwan, China (28.7%); India (45.9%); Indonesia (39.0%); Japan (9.0%); New Zealand (2.8%); Republic of Korea (23.7%); Singapore (4.0%); Sri Lanka (36.0%); Thailand (21.7%); and Viet Nam (39.5%).

Discussion

This study revealed that the average combined prevalence of infection with extended-spectrum β-lactamase-producing bacteria among children in South-East Asia and the Western Pacific is high. Risk factors for infection included recent intensive care unit admission, hospitalization, surgery or antibiotic exposure, and co-existing bacteraemia, nosocomial infections, lower respiratory tract infections, sepsis or recurrent urinary tract infections. Infection was associated with higher mortality, higher morbidity and longer hospitalization. The prevalence of infection we found in South-East Asia and the Western Pacific countries are similar to those reported from other surveillance systems worldwide,although many locations do not report data for children. A review of worldwide trends in extended-spectrum β-lactamase-associated infection reported higher prevalence in Asia, Latin America and the Middle East (from 28 to 40%) compared with other, higher-income areas (from 8 to 12%). As many of the studies we found were hospital-based our results support the need for resources and policies for control of nosocomial infection. A recently published modelling study showed that antibiotic use in hospital is a major driver for antimicrobial resistance in human infection compared with animal and environmental antibiotic exposures. Although infection control and hygiene may be sub-optimal in the countries we studied, infection control is easier to manage within health-care institutions than in other unstructured systems such as animal husbandry and the environment. Without proper control of antimicrobial resistance in hospitals, patients can disseminate antibiotic residues and resistance genes to the community and environment. This still highlights the importance of hospital-based stewardship for controlling antibiotic use and how this stewardship can reduce the risk of developing multidrug resistant organisms. At the same time, the rising community prevalence of extended-spectrum β-lactamase-associated infection provides evidence for expanding prevention to other settings. Our meta-analysis showed that recent medical care, including intensive care unit stays, hospitalization, surgery and antibiotic therapy, was associated with increased risk of infection. These results suggest that children may acquire such infections during health care, especially when undergoing invasive procedures. Specifically, children who had exposure to third-generation cephalosporins, carbapenems and fluoroquinolones had three to four times greater risk for extended-spectrum β-lactamase-associated infection, which is similar to previous reports.,– As these antibiotics are primarily used for treating severe infections, their use may be a marker for disease severity rather than a direct contributor to developing resistance. Nevertheless, if excessive fluoroquinolone use does contribute to emergence of resistant bacteria this adds another reason to avoid the unnecessary use of these broad-spectrum antibiotics in children. Coexisting illnesses, including bacteraemia, nosocomial infection, lower respiratory tract infections, sepsis and recurrent urinary tract infections, were associated with increased risk of infection. These co-morbidities could be risk factors for use of invasive treatments such as a central venous catheterization, mechanical ventilation, intravenous nutrition or increased risk of interactions with health-care settings. In a two-centre case–control study of risk factors for infection with extended-spectrum β-lactamase-producers in children, multivariable analysis identified sepsis and neurological illnesses as potential risk factors, which supports our findings. Previously published studies among both young adults and children found that prolonged hospital stay or prolonged use of invasive medical devices were associated with infection by, or being colonized with, extended-spectrum β-lactamase-producing bacteria,,, which is consistent with our findings. Recent surgery and antibiotic prophylaxis were associated with extended-spectrum β-lactamase infection in our study. Others have shown that surgical antibiotic prophylaxis increases the risk for antimicrobial resistance and acquisition of infection. One study from Switzerland found that half of all surgical ward prescriptions (680 out of 1270) were inappropriate. Antibiotic stewardship programmes have been shown to improve surgical antibiotic prophylaxis and treatment of surgical site infections. Our study found that initiation of appropriate empirical antibiotics was protective against extended-spectrum β-lactamase-associated infection, indicating the importance of thoughtful selection of antibiotics. The details of this finding warrant further study. The risk is especially high for critically ill patients requiring surgery or intensive care and who need antibiotics urgently before susceptibility has been established but who are also at increased risk for drug-resistant infections. Therefore, antibiotic stewardship programmes and guidelines in health-care facilities fill an important function. Furthermore, as studies in Asia have shown a high prevalence of easy access to unsupervised antibiotics within the community, more attention is needed to improving appropriate antibiotic use through training, education, policy and regulation outside of hospitals. Children infected with extended-spectrum β-lactamase-producers had significantly longer length of hospital stays (26 days) and required more intensive care unit days (29 days) than those without such infection. This leads to higher health-care costs, in addition to the costs to society in terms of family and community pressures and lost productivity. At the same time, prolonging intensive care unit and hospital stays increases the risk of further acquisition and transmission of drug resistance. Mortality and persistent bacteraemia were three to four times higher for patients infected with extended-spectrum β-lactamase-associated infections than those without. This adds to the economic and social burden of these infections. Based on our meta-regression, the study location, study design, patient’s diagnosis, sex or intensive care unit stay did not influence mortality. This implies that worse outcomes may be directly attributable to the presence of extended-spectrum β-lactamase-associated infection. The severity of the diseases associated with these infections might also contribute to mortality risk, as the patients diagnosed with sepsis had higher risk of mortality than those without sepsis. However, we were unable to determine for each study whether other factors may have influenced outcomes because comprehensive information was not available. One of the strengths of our study was the comprehensive data collection strategy, which provided a high sample size and study power. Second, two different tools were used to assess for bias, which, together with risk factor and outcomes sensitivity analysis, strengthened the study’s validity and reliability. Third, we assessed previous antibiotic history with different antibiotic categories, providing a detailed insight into the link between antibiotic use and resistance. Fourth, we also conducted meta-regression to determine if other factors might have influenced treatment outcomes. This established association between patients’ mortality, length of stay and extended-spectrum β-lactamase infections. There were several limitations to this study. The distribution of studies between locations was not uniform. Of the 48 Member States and areas in the South-East Asia and the Western Pacific Regions, we were able to find and extract data for the meta-analysis from 12 countries. For prevalence estimates we added surveillance data from 10 other countries and areas but we found data on 0–21-years-olds for only three countries with available paediatric data, which might underestimate the real situation among children. Moreover, although we made subgroup analyses, most of the pooled prevalence from selected studies were from hospital settings. Most of the surveillance sources reported only prevalence, without denominators and numerators. Nevertheless, the study provides a rough indication of the extent of extended-spectrum β-lactamase-associated infection and highlights the need for establishment of surveillance systems in these Regions. We can expect that within large Regions, rates of infection are unlikely to be homogenous, particularly where there are large urban and rural disparities. Among 40 studies, only seven were community based. This might have underestimated antibiotic resistance in the community. With the rising concern for community-acquired infections and reports of increased rates of faecal colonization with extended-spectrum β-lactamase-producing bacteria in healthy children, risk factors might not only arise from hospital influences but also from community exposure and international travel.– Because of limited information in the articles, we are unable to determine whether longer hospitalization increased the risk of infections or vice versa. Both situations are likely and further studies are needed to clarify the associations. Another limitation we faced was the lack of laboratory standardization for the identification of the extended-spectrum β-lactamase-producer phenotypes. Quality and standardization may vary between laboratories, although most followed Clinical and Laboratory Standards Institute guidelines. Sensitivity analyses found that use of different laboratory guidelines or test methods or the study year did not affect our results. All studies used phenotypic methods, as opposed to the gold standard through genotyping, with the majority using agar double-disk diffusion test, while a few studies used the Vitek® system (bioMérieux, Marcy l’Etoile, France). Thus, detection rates could be underestimated. We hope this study will provide important information for policy-makers who need to allocate resources to improve surveillance, monitor treatment outcomes, improve infection control in intensive care unit and surgery wards and develop policies for the use of empirical and prophylactic antibiotics. Knowledge of resistance rates can guide treatment recommendations. Countries without established antibiotic stewardship programmes should prioritize these activities, along with public education programmes. With very high burden of neonatal sepsis 0.42 million (39%) of the total 1.09 million deaths related with sepsis in these Regions, scaling up strategies to prevent infection and encourage appropriate treatment for this vulnerable group is needed. More studies are also needed to measure the impact of antimicrobial resistance in children.
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