
==== Front
Lancet Reg Health West Pac
Lancet Reg Health West Pac
The Lancet Regional Health: Western Pacific
2666-6065
Elsevier

S2666-6065(24)00171-8
10.1016/j.lanwpc.2024.101177
101177
Articles
Antimicrobial susceptibility profiles of invasive bacterial infections among children from low- and middle-income countries in the Western Pacific Region (WPRO) – a systematic review and meta-analysis
Moore Nerida nerida.moore@nt.gov.au
a∗
Ashley Elizabeth A. bc
Dickson Benjamin F.R. de
Douangnouvong Anousone b
Panyaviseth Pathana f
Turner Paul cg
Williams Phoebe C.M. deh
a Royal Darwin Hospital, 105 Rocklands Dr, Tiwi, NT, 0810, Australia
b Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Lao PDR
c Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
d Faculty of Medicine, School of Public Health, The University of Sydney, Sydney, NSW, Australia
e Sydney Institute of Infectious Diseases (Sydney ID), Sydney, NSW, Australia
f University of Health Sciences of Lao PDR (UHS-Laos) - Faculty of Medicine
g Cambodia Oxford Medical Research Unit, Angkor Hospital for Children, Siem Reap, Cambodia
h Department of Infectious Diseases, Sydney Children's Hospital Network, Sydney, NSW, Australia
∗ Corresponding author. nerida.moore@nt.gov.au
31 8 2024
10 2024
31 8 2024
51 10117726 4 2023
25 7 2024
12 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Summary

Background

Antimicrobial resistance increasingly impacts paediatric mortality, particularly in resource-constrained settings. We aimed to evaluate the susceptibility profiles of bacteria causing infections in children from the Western Pacific region.

Methods

We conducted a systematic review and meta-analysis of bacteria responsible for common infections in children. We included studies published from January 2011 to December 2023 (PROSPERO CRD42021248722). Pooled susceptibilities were evaluated against empiric antibiotics recommended to treat common clinical syndromes.

Findings

Fifty-one papers met inclusion criteria, incorporating 18,330 bacterial isolates. Of available published data, only six countries from the region were represented. Escherichia coli revealed a pooled susceptibility to ampicillin of 17% (95% CI 12–23%, n = 3292), gentamicin 63% (95% CI 59–67%, n = 3956), and third-generation cephalosporins 59% (95% CI 49–69%, n = 3585). Susceptibility of Klebsiella spp. to gentamicin was 71% (95% CI 61–80%, n = 2323), third-generation cephalosporins 35% (95% CI 22–49%, n = 2076), and carbapenems 89% (95% CI 78–97%, n = 2080). Pooled susceptibility of Staphylococcus aureus to flucloxacillin was 72% (95% CI 58–83%, n = 1666), and susceptibility of Streptococcus pneumoniae meningitis isolates to ampicillin was 26% (95% CI 11–44%, n = 375), and 63% (95% CI 40–84%, n = 246) to third-generation cephalosporins.

Interpretation

The burden of antimicrobial resistance among bacteria responsible for common infections in children across the Western Pacific region is significant, and the currently recommended World Health Organization antibiotics to treat these infections may be inefficacious. Strategies to improve the availability of high-quality data to understand the burden of antimicrobial resistance in the region are necessary.

Funding

The study was supported by an 10.13039/100015539 Australian Government 10.13039/501100000925 National Health and Medical Research Council Investigator Grant. This research was funded in part by the 10.13039/100010269 Wellcome Trust [220211/Z/20/Z]. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.

Keywords

Antimicrobial
Susceptible
Resistant
Paediatric
Neonate
Child
Infant
Western Pacific Region
==== Body
pmc Research in context

Evidence before this study

Resistance to antimicrobials threatens to undermine advances made in child survival, particularly in resource-constrained settings. Previous research has evaluated the burden of antimicrobial resistance in children from geographic settings across Asia and Africa, but there is inadequate evidence of the evaluation of paediatric data in the WHO-defined Western Pacific Region.

Added value of this study

Data were pooled from 51 studies examining invasive bacterial infections in paediatric patients across six low- or middle-income countries from the region. A total of 18,330 isolates met the predefined inclusion criteria; of which 15,214 were included in a meta-analysis. We report susceptibility to WHO-recommended antibiotic regimens for important gram-positive and gram-negative bacteria.

Implications of all the available evidence

This review revealed alarming antibiotic resistance to empirical WHO-recommended regimens used to treat common infectious syndromes in children from the Western Pacific region. It also highlighted a distinct lack of high-quality published paediatric antimicrobial resistance data from the region. Our findings suggest that current antibiotic recommendations and prescribing practices may require reconsideration in many resource-constrained settings within the region. Enhanced efforts to strengthen antimicrobial surveillance and stewardship remains critically important.

Introduction

Resistance to antimicrobials threatens to undermine advances made in child survival in low- or middle-income countries (LMICs) of the World Health Organization (WHO)- defined Western Pacific Region (WPRO).1 In 2016, 5.6 million children under the age of five died in the WPRO region, with most deaths attributed to preventable and treatable infectious diseases such as pneumonia, diarrhoeal illness, and neonatal sepsis.1 The rise of antimicrobial resistance (AMR) within the region may stagnate progress in child health outcomes, as common infections may no longer be curable with currently available antibiotics.2

AMR is surging globally and has disproportionately affected children.3 In 2019, one in five deaths attributable to AMR occurred in young children, largely secondary to previously treatable infections.3 Neonates are a cohort of particular concern, with multidrug-resistant (MDR) pathogens accounting for 214,000 neonatal sepsis deaths globally each year.4 In the WPRO, region AMR is an increasingly urgent threat.1,2 While efforts to address the drivers of AMR are underway, there has been varied success across the region.5 In October 2014, WHO Member States endorsed the Action Agenda for Antimicrobial Resistance in WPRO; whilst promising, most progress enacting these plans has been made in high-income countries.6 As of December 2023 only six of the 18 WPRO LMICs have enrolled in the WHO-led Global Antimicrobial Resistance and Use Surveillance System (GLASS); Cambodia, Lao People's Democratic Republic, Malaysia, Papua New Guinea, Philippines and Viet Nam.7 Subsequently, only a small amount of routine AMR data from high-burden LMICs in the region are available.4

To enhance global antimicrobial stewardship, the WHO Essential Medicines List for Children classifies antibiotics into three categories (Access, Watch, and Reserve).8 While the use of Reserve antibiotics remains low in children, an alarming increase in the empiric use of Watch antibiotics has been reported in various countries, including within the WPRO region.9 This may reflect an absence of antibiotic stewardship strategies or signal the ineffectiveness of antibiotics in the ‘Access’ group.10 To address current AMR knowledge gaps in children within the WPRO region, this review aimed to examine the susceptibility profiles of key bacterial pathogens responsible for common invasive bacterial infections among children from LMICs of the Western Pacific region, and to evaluate their susceptibility against current WHO-recommended empiric antibiotics, and (commonly-prescribed) carbapenems.

Methods

Search strategy and selection criteria

A systematic literature review was performed in accordance with a pre-defined study protocol (PROSPERO registration CRD42021248722). The first search was conducted on 26 March 2021, and updated on 15 January 2024, to include papers published between 1 January 2011 and 31 December 2023. Fig. 1 depicts the search process in a PRISMA flow diagram. We searched Embase (Ovid), Global Health (EBSCO), PubMed, and the Cochrane Database of Systematic Reviews (Cochrane Library) to identify studies that reported bacterial infections in children from LMICs within the WPRO region. Search terms are described in supplementary data (Supplement 1). A citation search was conducted to identify additional studies (grey literature) by searching reference lists of publications eligible for full-text review.Fig. 1 Prisma diagram.11

All observational epidemiological studies published in English within peer-reviewed journals were included. Studies were deemed relevant if they met the following inclusion criteria: (i) research on bacterial infections (incidence, prevalence, aetiology or clinical infection); (ii) isolates from sterile sites only (plus urine if reporting clinical urinary tract infections, and stool if Shigella spp. or Salmonella spp. clinical infections); (iii) specified paediatric data (age up to and including 18 years); (iv) antimicrobial susceptibility testing (AST) methods documented and in line with Clinical and Laboratory Standards Institute (CLSI)/European Committee on Antimicrobial Susceptibility Testing (EUCAST) recommendations, and; (v) research specifically examining bacterial infections caused by organisms found on the Global Antimicrobial Resistance and Use Surveillance System (GLASS) 2020 list of organisms (i.e. Escherichia coli, Klebsiella spp., Acinetobacter spp., Staphylococcus aureus, Streptococcus pneumoniae, Salmonella spp., Shigella spp., Neisseria gonorrhoeae, and Pseudomonas aeruginosa), plus other important pathogens causing invasive infections in children (i.e. Streptococcus agalactiae, Streptococcus pyogenes, Haemophilus influenzae, and Neisseria meningitidis).

Countries were limited to those within the WHO-defined WPRO region, excluding high-income countries as defined by the World Bank.12,13 The following 18 countries were included in the search: Cambodia, China, Fiji, Kiribati, Lao People's Democratic Republic, Malaysia, Marshall Islands, Micronesia, Mongolia, Niue, Papua New Guinea, Philippines, Samoa, Solomon Islands, Tonga, Tuvalu, Vanuatu, and Viet Nam.

Abstracts and titles were compiled, and duplicates removed. NM reviewed all citations to determine eligibility; EAA, AD, and PP provided the independent second review. Disagreement over inclusion was resolved by PCMW. All eligible articles were retrieved in full text. Studies were excluded if they presented data aggregated with regions outside the pre-defined region, or if published data were aggregated with adult data. Studies were also excluded if they reported only isolates from carriage or colonisation studies, if they were case reports or small case series involving fewer than ten participants, or if they were studies focussed on high-risk populations only (i.e. children living with HIV, profoundly immunosuppressed populations, children with severe acute malnutrition).

Data extraction

Data from included studies were independently extracted by two investigators (NM and BFRD) (Supplement 2). Extracted data included the publication year, location, setting, population, age, study design, infectious syndrome, organism, microbiological methods of bacterial isolation, and antimicrobial susceptibility testing (AST) results.

Outcome measurement

The primary outcome of this review was the weighted, pooled susceptibility estimates of pre-defined key bacterial pathogens, evaluated against antimicrobials recommended in WHO treatment guidelines for children in limited resource settings.14 Susceptibility against carbapenems, frequently prescribed as an empirical therapy in the context of rising global AMR, were also evaluated.

Quality assessment

The Microbiology Investigation Criteria for Reporting Objectively (MICRO) framework was used to assess the quality of published microbiology data.15 The Grades of Recommendation, Assessment, Development and Evaluation Working Group (GRADE) method was used to summarise the quality of evidence for each study by assessment of study type, quality, limitations, inconsistency, and risk of bias.16 MICRO and GRADE reviews were undertaken independently by three authors (NM, BFRD and PCMW); discrepancies were resolved via consensus. The results of these quality assessments are summarised in Supplement 2.

Statistical analysis

Meta-analyses for a single proportion were undertaken in Stata version 18 (Stata Corporation, TX) using the in-built meta command. Effect sizes were determined with a Freeman-Tukey-transformed proportion. Summary estimates were provided, along with 95% confidence intervals (95% CIs). A random-effects model was used to account for the expected heterogeneity in susceptibilities between study populations with study weighting done using the Restricted Maximum Likelihood (REML) estimation.17 The I2 and the τ2 statistics were used to evaluate heterogeneity between studies and subgroups.18 Egger's test and funnel-plots were used to assess for potential publication bias (small-study effects).19 Possible sources of heterogeneity between studies were investigated through subgroup analyses (year of publication, country of origin, and clinical syndrome). Meta-regression for each outcome was performed to assess for evidence of a linear relationship between susceptibility and year. A value of p < 0.05 was considered significant in all analyses.

Role of the funding source

PCMW is supported by an NHMRC Investigator Grant (119735). NHMRC had no involvement in the design or conduct of the research. This research was funded in part, by the Wellcome Trust [220211/Z/20/Z]. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Wellcome Trust had no involvement in the design or conduct of the research.

Results

Characteristics of the included studies

The combined search identified 4860 relevant papers published between 1 January 2011 and 31 December 2023 (Fig. 1). Abstract reviews excluded 4620 papers. Of the 240 papers sought for full-text review, 53 were unable to be retrieved in full-text English language and were almost exclusively Chinese studies (one Malaysian study). The remaining 187 papers, plus an additional five identified from grey literature screening, underwent full-text review. This resulted in a total of 51 papers for inclusion.20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70

Of the 51 included papers, six of the 18 WPRO LMICs were represented (Fig. 2). Most papers were from China (n = 40 papers), followed by Malaysia (n = 4), Cambodia (n = 3), Vietnam (n = 2), Papua New Guinea (n = 1) and Laos (n = 1). Twenty-seven studies included all children up to adolescence (maximum upper age limit 18 years),20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,69,70 ten included neonates less than one month of age,45, 46, 47, 48, 49, 50, 51, 52,67,68 three focussed on infants zero to 12 months,53, 54, 55 and four on children zero to five years.56, 57, 58, 59 Seven studies did not specify the age range of their paediatric population.60, 61, 62, 63, 64, 65, 66Fig. 2 Number of papers by country.

Six studies specifically examined community-acquired infections20,21,25,41,54,59; three nosocomial infections23,45,52; and three studies examined both.50,63,67 The remaining 39 studies (76%) did not identify whether infections were community or hospital-acquired. One study was conducted in a rural setting,20 while the remainder of the studies were conducted in urban settings (almost exclusively tertiary health facilities).

The study design of 49 studies was a case series; ten prospective,20,24,25,28,30,37,40,54,57,64 33 retrospective,21, 22, 23,26,27,29,31,33, 34, 35,39,41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52,55,56,60, 61, 62, 63,66,67,69,70 and six not specified.32,36,38,53,58,65 There was one case–control study,59 and one cross-sectional study.68 All studies reported cumulative incidence data. There were no cohort studies identified.

Most studies (34 of 51) reported data from one bacterial clinical syndrome. These included ten studies examining neonatal sepsis/meningitis45,47, 48, 49, 50, 51, 52,54,67,68; five evaluating paediatric sepsis21,23,25,43,63; five paediatric meningitis26,28,34,39,64; nine studies focussing on acute infectious diarrhoea32,37,44,56,58, 59, 60,65,66; two assessing urinary tract infections31,61; and two on bone and joint infections20,27 while one focussed on enteric fever.35 Sixteen studies reported only one bacterial pathogen; the majority of these (n = 8) focussed on invasive S. pneumoniae infections.22,24,30,33,36,38,40,57

Across the included studies, a total of 38,314 bacterial isolates were reported. AST information was available for 29,236 isolates, of which 18,330 met the pre-defined inclusion criteria for relevant pathogens. Of these, 15,214 were tested against at least one antimicrobial recommended in WHO empirical treatment guidelines,14 or carbapenems. Not all isolates were tested against the complete set of WHO-recommended empiric antibiotics. Across the studies, only 57% (29/51) reported denominator data (i.e. the total number of cultures collected from patients over their study period which summated to 496,492 cultures for those reported).

Quality of the evidence

Only one study was defined as moderate-quality evidence (GRADE level B),23 while 23 studies were low-quality (GRADE level C),20,22,24, 25, 26,29,30,32,37,40,42, 43, 44,47,48,54,57,63,64,67, 68, 69, 70 and the remaining 27 very low quality (GRADE level D).21,27,28,31,33, 34, 35, 36,38,39,41,45,46,49, 50, 51, 52, 53,55,56,58, 59, 60, 61, 62,65,66 GRADE C scores were assigned where studies were single site, retrospective, observational studies, with risk of information, selection or publication bias. In addition to GRADE C features, very low-quality (GRADE D) publications also had small sample sizes, missing data, and errors in reporting.

Thirteen studies had overt identification and/or AST errors either detected or suspected (MICRO grade E).28,29,32, 33, 34,36,39,42,47,48,50,52,66 Thirty nine studies (76%) provided information about the susceptibility testing methods used (agar diffusion n = 28, CLSI broth microdilution n = 1, VITEK 2 n = 8, Phoenix 100 n = 1, MicroScan n = 1). The criteria to define susceptible and resistant categories was provided for 45 studies (88%), where the Clinical Laboratory and Standards Institute guidelines (CLSI) was used in all of these. Eighteen studies (35%) described use of internal quality controls. None of the studies included details of external quality assurance (EQA) programme participation.

Meta-analysis

Fifty-one studies reporting 15,214 relevant bacterial isolates were included in the meta-analysis; 9863 were gram-negative, and 5351 gram-positive bacteria. Susceptibility profiles of 34 bacteria against commonly prescribed antibiotic combinations underwent meta-analysis (Fig. 3, Fig. 4, Fig. 5, Fig. 6, Fig. 7, and Supplementary Data 1, Figures S1–S5).Fig. 3 Proportion of E. coli isolates susceptible to key antimicrobials.

Fig. 4 Proportion of Klebsiella spp. isolates susceptibile to key antimicrobials.

Fig. 5 Proportion of S. pneumoniae isolates susceptibile to key antimicrobials.

Fig. 6 Proportion of S. pneumoniae isolates susceptibile to ampicillin and third generation cephalosporins by subgroup paediatric meningitis and sepsis.

Fig. 7 Proportion of S. aureus isolates susceptible to key antimicrobials.

Susceptibility patterns of gram-negative pathogens

E. coli was the most frequently isolated gram-negative pathogen (4294 isolates). Twenty-four studies assessed susceptibility patterns of E. coli. When considering key antimicrobials included in WHO paediatric treatment guidelines,14 plus carbapenems, the pooled susceptibility for ampicillin was 17% (95% CI 12–23%, n = 3292 isolates tested), gentamicin 63% (95% CI 59–67%, n = 3956), ceftriaxone or cefotaxime (hereafter referred to as third-generation cephalosporins) 59% (95% CI 49–69%, n = 3585), and carbapenems 100% (95% CI 100 to 100%, n = 3000) (Fig. 3).

There were nineteen studies assessing susceptibility patterns of Klebsiella spp. incorporating 2680 isolates. Pooled susceptibility of Klebsiella spp. to gentamicin was 71% (95% CI 61–80%, n = 2323 isolates tested), third-generation cephalosporins 35% (95% CI 22–49%, n = 2076), and carbapenems 89% (95% CI 78–97%, n = 2080) (Fig. 4).

Salmonella spp. were frequently isolated gram-negative pathogens responsible for paediatric sepsis and acute infectious diarrhoea (2851 isolates across 19 studies). Non-typhoidal serovars were most common. Pooled susceptibility of Salmonella spp. to ampicillin was 38% (95% CI 29–49%, n = 2591 isolates tested), third-generation cephalosporins 85% (95% CI 77–92%, n = 2456), and carbapenems 100% (95% CI 99–100%, n = 952) (Supplementary Data 1, Figure S1).

Nine studies examined susceptibility patterns of P. aeruginosa, revealing a pooled susceptibility to gentamicin of 82% (95% CI 46–100%, n = 306 isolates tested), and carbapenems of 86% (95% CI 72–96%, n = 157) (Supplementary data 1, Figure S2). Seven studies reported Acinetobacter spp. susceptibility patterns noting pooled susceptibility to gentamicin of 81% (95% CI 66–93%, n = 223), and carbapenems 72% (95% CI 63–80%, n = 176) (Supplementary data 1, Figure S3).

Four studies evaluated invasive H. influenzae isolates. Across these studies, pooled susceptibility to ampicillin was 65% (95% CI 12–100%, n = 85), third-generation cephalosporins 97% (95% CI 90–100%, n = 80), chloramphenicol 100% (95% CI 99–100%, n = 18), and carbapenems 100% (95% CI 93–100%, n = 25) (Supplementary Data 1, Figure S4).

One paper meeting the inclusion criteria assessed Shigella spp. in children hospitalised with diarrhoea59 Susceptibility to third-generation cephalosporins was 27% (n = 62 isolates tested) and ciprofloxacin 98% (n = 57).59

Susceptibility patterns of gram-positive pathogens

S. pneumoniae was the most frequently reported gram-positive pathogen (4067 isolates), with 18 studies assessing susceptibility patterns of S. pneumoniae (Fig. 5). All studies used CLSI breakpoints for S. pneumoniae susceptibility testing. Fifteen of the 18 included studies differentiated meningitis and non-meningitis isolates,21, 22, 23, 24, 25, 26,28,34,36,38, 39, 40,43,57,64 and of these six explicitly reported the CLSI meningitis and non-meningitis breakpoints.22,24,36,38,40,57 Pooled susceptibility of paediatric meningitis isolates to ampicillin was 26% (95% CI 11–44%, n = 375), and third-generation cephalosporins 63% (95% CI 40–84%, n = 246) (Fig. 6a and b). Pooled susceptibility of all non-meningitis isolates to ampicillin was 83% (95% CI 71–93%, n = 2231), and third-generation cephalosporins 84% (95% CI 74–92%, n = 1859) (Fig. 6a and b). Pooled susceptibility of all isolates (across 12 studies) to chloramphenicol was 86% (95% CI 70–96%, n = 1942) (Fig. 5). Nine studies reported susceptibility to carbapenems, with a pooled susceptibility of 53% reported (95% CI 37–68%, n = 815) (Fig. 5). Of note, carbapenem susceptibility was reported as less than ampicillin susceptibility in two studies,30,33 and less than third-generation cephalosporin susceptibility in each of the nine studies, an anomaly not accounted for in any of the studies.

S. aureus was reported from 2169 isolates across 20 studies. Pooled susceptibility to flucloxacillin was 72% (95% CI 58–83%, n = 1666 isolates tested), and vancomycin 100% (95% CI 100–100%, n = 1723) (Fig. 7).

Twelve of the included studies assessed susceptibility patterns of S. agalactiae (634 isolates). Pooled susceptibility of S. agalactiae to ampicillin was 100% (95% CI 100–100%, n = 599 isolates tested), third-generation cephalosporins 100% (95% CI 100–100%, n = 201), vancomycin 100% (95% CI 100–100%, n = 341), and carbapenems 100% (95% CI 98–100%, n = 80) (Supplementary Data 1, Figure S5).

Heterogeneity

Among the 34 bacteria vs antibiotic combinations included in the meta-analyses, median I2 was 94.29% (IQR 11.65–95.92%). The majority (53%, 18/34) of outcomes demonstrated considerable heterogeneity (I2 greater than 75%) among included studies. Five outcomes had an I2 between 50 and 75%; while only eight outcomes had an I2 of less than 50% (all of which were less than 25%). The eight outcomes with low levels of heterogeneity included: S. agalactiae against ampicillin, third-generation cephalosporins, carbapenems and vancomycin; S. aureus against vancomycin; H. influenzae against third-generation cephalosporins; Salmonella spp. against azithromycin; and Acinetobacter spp. against carbapenems.

Subgroup analyses and meta-regression

The results of the subgroup analyses for clinical syndrome, year group and country are presented in Supplemental Data 1, Figures S6–S45. The results of the meta-regression by year are shown in Supplemental Data 1, Figures S46 and S47.

Susceptibility patterns by clinical syndrome

A subgroup analysis by clinical syndrome was performed. A summary of susceptibility patterns by clinical syndrome are presented in Table 1. Eleven bug–drug combinations showed significant differences between syndromes, however there was significant heterogeneity within at least one of the categories of syndrome for seven (63%) of these. Across all clinical subgroup estimates, the median I2 was 69.14% (IQR 0–94.34%), and 89% (IQR 22.35–96.39%) when restricted to categories with at least three studies per outcome.Table 1 Reported susceptibility proportions of the most likely causative organisms by relevant clinical syndrome to WHO-recommended empirical antibiotic regimens.

Organism	Number of studies (number of isolates)ref	Weighted, pooled prevalence (susceptibility) estimate% (95% CI)	Heterogeneity	
p-valuea	Iˆ2	Tauˆ2	
Neonatal Sepsis/Meningitis	
Streptococcus agalactiae	
 Ampicillin	5 (326)46,50,53,55,68	100% (95% CI 100–100%)	0.958	<0.001	<0.001	
 Gentamicin	–	–	–	–	–	
 Third-generation cephalosporins	3 (85)46,50,53	98% (95% CI 93–100%)	0.270	28.26	0.014	
Staphylococcus aureus	
 Flucloxacillinc	8 (241)45,49, 50, 51, 52,54,67,68	74% (95% CI 56–89%)	<0.001	87.97	0.246	
 Vancomycin	5 (132)45,49, 50, 51,54	100% (95% CI 99–100%)	0.989	0	<0.001	
Escherichia coli	
 Ampicillin	8 (782)47, 48, 49, 50,52,54,67,68	21% (95% CI 15–27%)	0.001	69.27	0.024	
 Gentamicin	9 (801)45,47,49, 50, 51, 52,54,67,68	66% (95% CI 59–73%)	0.001	68.93	0.027	
 Third-generation cephalosporins	8 (656)45,47,49, 50, 51,54,67,68	70% (95% CI 56–83%)	<0.001	91.35	0.143	
Klebsiellaspp.	
 Gentamicin	9 (764)39,45,47,49, 50, 51, 52,54,67	79% (95% CI 73–85%)	0.001	72.15	0.033	
 Third-generation cephalosporins	7 (596)45,47,49, 50, 51,54,67	33% (95% CI 12–59%)	<0.001	96.96	0.425	
Paediatric Sepsis	
Staphylococcus aureus	
 Flucloxacillinc	5 (1299)21,23,25,41,63	79% (95% CI 65–90%)	<0.001	92.09	0.091	
 Vancomycin	4 (1503)13,23,41,43	100% (95% CI 100–100%)	0.739	0.02	<0.001	
Streptococcus pneumoniae	
 Ampicillinb	12 (2231)21,24,30,33,36,38,40,43,57,63	83% (95% CI 71–93%)	<0.001	97.63	0.252	
 Gentamicin	–	–	–	–	–	
 Third-generation cephalosporins	11 (1859)22, 23, 24, 25,30,33,36,38,40,43,57	84% (95% CI 74–92%)	<0.001	95.56	0.152	
Escherichia coli	
 Ampicillin	4 (2124)23,43,63,69	22% (95% CI 5–46%)	<0.001	98.99	0.255	
 Gentamicin	4 (2129)23,43,63,69	60% (95% CI 58–62%)	0.195	0.01	<0.001	
 Third-generation cephalosporins	5 (1917)21,23,43,63,69	66% (95% CI 43–85%)	<0.001	98.35	0.237	
Klebsiellaspp.	
 Gentamicin	3 (1339)23,43,63	61% (95% CI 39–81%)	<0.001	98.35	0.155	
 Third-generation cephalosporins	4 (1225)21,23,43,63	44% (95% CI 19–71%)	<0.001	98.38	0.266	
Salmonellaspp.	
 Ampicillin	8 (1037)21,23,29,35,42,43,63,70	51% (95% CI 33–68%)	<0.001	96.39	0.229	
 Third-generation cephalosporins	8 (902)21,23,29,35,42,43,63,70	94% (95% CI 84–99%)	<0.001	94.34	0.164	
Haemophilus influenzae	
 Ampicillin	2 (64)26,28	78% (95% CI 14–100%)	<0.001	92.01	0.779	
 Third-generation cephalosporins	1 (57)63	–	–	–	–	
Paediatric Meningitis >1 month	
Streptococcus pneumoniae	
 Ampicillinb	11 (375)22,24,26,28,34,36,38, 39, 40,57,64	26% (95% CI 11–44%)	<0.001	91.11	0.322	
 Gentamicin	1 (32)28	–	–	–	–	
 Third-generation cephalosporins	10 (246)22,24,26,28,34,36,38, 39, 40,64	63% (95% CI 40–84%)	<0.001	91.32	0.434	
 Chloramphenicol	3 (241)26,28,34	95% (95% CI 85–100%)	0.073	63.44	0.048	
Haemophilus influenzae	
 Ampicillin	2 (21)26,28	51% (95% CI 0–100%)	<0.001	93.67	2.066	
 Third-generation cephalosporins	3 (23)26,28	97% (95% CI 83–100%)	0.679	<0.001	<0.001	
 Chloramphenicol	2 (18)26,28	100% (95% CI 100–100%)	0.520	<0.001	<0.001	
Escherichia coli	
 Ampicillin	5 (216)26,28,34,39,64	13% (95% CI 5–22%)	0.083	54.19	0.036	
 Gentamicin	4 (199)28,34,39,64	61% (95% CI 54–68%)	0.949	<0.001	<0.001	
 Third-generation cephalosporins	5 (183)26,28,34,39,64	44% (95% CI 35–52%)	0.353	13.59	0.005	
 Chloramphenicol	2 (56)26,28	92% (95% CI 82–99%)	0.500	<0.001	<0.001	
Klebsiellaspp.	
 Gentamicin	1 (33)39	–	–	–	–	
 Third-generation cephalosporins	2 (38)28,39	29% (95% CI 14–47%)	0.847	<0.001	<0.001	
 Chloramphenicol	1 (3)28	–	–	–	–	
Acute Infectious Diarrhoea	
Shigellaspp.	
 Ciprofloxacin	1 (57)59	–	–	–	–	
 Third-generation cephalosporins	1 (58)59	–	–	–	–	
Salmonellaspp.	
 Ciprofloxacin	11 (1634)27,29,32,37,42,44,52,58, 59, 60,65,66	82% (95% CI 68–94%)	<0.001	97.78	0.317	
 Third-generation cephalosporins	10 (1540)29,32,37,42,44,56,58, 59, 60,65	80% (95% CI 71–87%)	<0.001	92.51	0.087	
 Azithromycin	2 (482)37,58	83% (95% CI 79–86%)	0.835	0.00	<0.001	
Urinary Tract Infection	
Klebsiellaspp.	
 Co-trimoxazole	1 (19)61	–	–	–	–	
 Gentamicin	2 (826)31,61	50% (95% CI 4–96%)	<0.001	95.62	0.614	
Escherichia coli	
 Co-trimoxazole	1 (170)61	–	–	–	–	
 Ampicillin	1 (170)61	–	–	–	–	
 Gentamicin	2 (826)31,61	59% (95% CI 53–66%)	0.110	60.87	0.006	
Bone and Joint Infection	
Staphylococcus aureus	
 Flucloxacillin	2 (84)20,27	44% (95% CI 0–100%)20,27	<0.001	98.55	1.625	
 Vancomycin	1 (37)56	–	–	–	–	
a p value < 0.05 suggests significant evidence of heterogeneity.

b Where ampicillin data not reported susceptibility inferred from penicillin. Ampicillin resistance was not reported for Klebsiella spp. as this bacteria is intrinsically resistant.

c Where flucloxacillin data was not reported oxacillin was used to predict methicillin susceptibility and infer flucloxacillin susceptibility.

E. coli and Klebsiella spp. were the most frequently isolated pathogens causing neonatal sepsis/meningitis in this review. Within this subgroup, E. coli isolates had a pooled susceptibility to ampicillin of 21% (95% CI 15–27%, n = 782 isolates tested), gentamicin 66% (95% CI 59–73%, n = 801) and third-generation cephalosporins 70% (95% CI 56–83% n = 656). Pooled susceptibility of Klebsiella spp. to gentamicin was 79% (95% CI 73–85%, n = 764), and third-generation cephalosporins 33% (95% CI 12–59%, n = 596).

For paediatric sepsis, the most frequently isolated gram-negative pathogens E. coli and Klebsiella spp. had pooled susceptibilities to third-generation cephalosporins of 66% (95% CI 43–85%, n = 1917 isolates tested), and 44% (95% CI 19–71%, n = 1225) respectively. Salmonella spp. had a pooled susceptibility to ampicillin in paediatric sepsis of 51% (95% CI 33–68%, n = 1037), and third-generation cephalosporins 94% (95% CI 84–99%, n = 902). S. aureus and S. pneumoniae were the most frequently reported gram-positive pathogens in paediatric sepsis. S. aureus had a pooled susceptibility to flucloxacillin of 79% (95% CI 65–90%, n = 1299 isolates tested). Pooled susceptibility of S. pneumoniae against ampicillin was 83%, (95% CI 71–93%, n = 2231) and third-generation cephalosporins 84% (95% CI 74–92%, n = 1859).

In paediatric meningitis, pooled susceptibility of S. pneumoniae against ampicillin was 26% (95% CI 11–44%, n = 375). The pooled susceptibility of S. pneumoniae to third-generation cephalosporins was 63% (95% CI 40–84%, n = 246). In this subgroup E. coli had a pooled susceptibility to ampicillin of 13% (95% CI 05–22%, n = 216), gentamicin 61% (95% CI 54–68%, n = 199) and third-generation cephalosporins 44% (95% CI 35–52%, n = 183).

Susceptibility patterns by country

Twenty-six of the 34 bacteria vs antibiotic combinations were included in subgroup analysis by country. Of these, 16 (62%) showed a significant difference by country, however 15 (94%) had significant heterogeneity within at least one of the country subgroups included. No consistent trend was observed in susceptibility proportions by country. Median heterogeneity when grouped by country was 58.33 (IQR 0–93.14), and 85.18 (IQR 49.23–93.59) when limited to at least three studies per country for the outcome.

Susceptibility patterns by year of publication

Meta-regression found a significant reduction in proportion of susceptible isolates by study year for E. coli against carbapenems (p = 0.001), and S. aureus against flucloxacillin (p = 0.025) (Supplemental Data 5). E. coli against 3 GC (p = 0.069), Klebsiella spp. against carbapenems (p = 0.051), and Acinetobacter spp. against carbapenems (p = 0.055) showed some evidence of a reduction in susceptibility with time but did not meet the significance threshold. Meanwhile E. coli vs ampicillin (p = 0.013) showed a significant increase in susceptibility with time.

Publication bias

Funnel plots and results of the Egger's regression for small-study effects are shown in Supplemental Data 1, Figures S48 and S49. Among the 29 outcomes with sufficient studies for an Egger's regression, only three outcomes showed potential risk of small study bias: S. aureus against vancomycin (p = 0.008); S. agalactiae against ampicillin; and S. pneumoniae against ampicillin (p = 0.006). For S. pneumoniae, there was no evidence of bias for meningitis (p = 0.885) and non-meningitis (p = 0.456) when considered separately.

Discussion

This review demonstrates that AMR threatens child health in the WPRO region. It also highlights a need for more high-quality AMR surveillance data from the region, as only six of the 18 LMICs were represented by AMR data in this review, and more than two-thirds of the data was from China. Despite this limitation, this review reveals clear evidence of the non-susceptibility of important pathogens to WHO-recommended empiric antibiotics used to treat severe bacterial infections in children (see Table 1). For example, WHO recommends Access antibiotics ampicillin (or benzylpenicillin) and gentamicin as first-line empirical therapy in suspected neonatal sepsis and third-generation cephalosporins (Watch antibiotics) as second-line.8,14 In this review, the most common gram-negative isolates for neonatal sepsis had a susceptibility of less than 80% (and as low as 21%) to ampicillin, gentamicin, and third-generation cephalosporins, meaning current treatment regimens are unlikely to be curative for these common pathogens. A high prevalence of non-susceptibility to recommended empirical therapies has previously been described among invasive bacterial isolates throughout Africa and South Asia, with authors raising concerns about the continued use of these regimens given the low probability of treatment success.13,71, 72, 73, 74

When comparing the susceptibility profiles documented in this review to those in other parts of the globe, E. coli susceptibility to ampicillin was similar to previous reviews of Africa and South Asia.13,72,74 E. coli susceptibility to gentamicin was similar to isolates from Africa,72,74 but much higher in this study than isolates from South Asia.13,74 For Klebsiella spp., susceptibility to gentamicin was higher in this review than reported from South Asia,13,74 but similar to susceptibility reported from Africa.72,74 E. coli and Klebsiella spp. had susceptibilities to third-generation cephalosporins reported in this review that were lower than found in Africa,72,74 but higher than isolates identified in South Asia.13,74 Although S. aureus isolates in this review remained susceptible to vancomycin, similar to other regions,75 28% of isolates were flucloxacillin resistant, comparable to resistance proportions reported in other LMICs.75

Due to increasing non-susceptibility to first- and second-line therapies, carbapenems are frequently prescribed as empiric therapy. In this review, half of the bacteria tested against carbapenems (4/8 combinations) had a pooled susceptibility of <90%; these were Klebsiella spp., P. aeruginosa, Acinetobacter spp., and S. pneumoniae. The level of reduced S. pneumoniae susceptibility to carbapenems was surprising. While plausible (given that it shares resistance mechanisms with other beta-lactams), the discordance with the S. pneumoniae susceptibility results reported for other beta-lactams highlights the data quality limitations in this review. In general, data were from low-quality evidence studies that were predominately retrospective, lacked rigorous reporting of microbiological methods and standard definitions, and used passive surveillance to identify cases. The interpretation of pooled susceptibility data in this study was also limited by observed heterogeneity in testing methods and inadequate quality control protocols. This raises concerns about the reliability and reproducibility of the reported susceptibility results, ultimately impacting the ability to draw conclusions from the pooled data.

This review had additional limitations. Only six of the 18 WPRO LMICs were represented, risking an underestimation of the burden of AMR in the region. More than two-thirds described AMR data from China. This disproportionate representation suggests selection, reporting, and geographical biases for the pooled data and impacts subsequent interpretation. Non-English language studies were excluded, which may result in further selection bias. The differentiation between community- and hospital-acquired infections was infrequently defined and therefore risks over-representing non-susceptibility proportions by biasing towards the inclusion of predominantly hospital-acquired infections, an issue consistently noted in the paediatric AMR literature.76 There was only one cross-sectional study, and no studies reported prevalent cases of bacterial infections for any of the organisms of interest. Finally, while the outcomes of this study provided robust susceptibility estimates with narrow confidence intervals, there was considerable heterogeneity within estimates which were unable to be reduced by subgroup stratification by year, country or clinical syndrome, highlighting the variability of susceptibilities across the studies and the difficulties in providing accurate generalisable regional estimates.

Nevertheless, this review has important implications for clinical practice and policy framework. Considering the region is home to approximately one-quarter of the world's children,1 the 29,236 isolates with AST information over this study period demonstrates the paucity of published data for such a substantial population at risk. This review highlights the urgent need for more rigorous and routinely collected surveillance data to improve the understanding of AMR in the region and help target treatment appropriately.72 Given the limited capacity of many LMIC laboratories to support clinical decision-making, there is a necessary reliance on empiric therapy based on regional and international guidelines. Unless these guidelines are revised regularly and are based on robust AMR data, clinicians are in danger of prescribing ineffective therapy that could jeopardise patient outcomes.73

Neonates and premature infants are particularly vulnerable amongst this cohort, as they are frequently exposed to MDR bacteria (such as Klebsiella spp. and Acinetobacter spp.) during prolonged hospital stays.76 While, in general, isolates included in this review were sensitive to carbapenems, the concerning proportion of bacteria that were non-susceptible to carbapenems highlights the threat of emerging resistance in the WPRO region. Few effective antibiotics have been adequately studied to treat MDR infections in the neonatal population, resulting in substantial prescribing risks of reduced efficacy or increased toxicity due to the potential for sub- or supra-therapeutic dosing.76 Considering the inadequate pace of development of new antimicrobials and the currently cumbersome drug regulatory framework to introduce new agents to the neonatal and paediatric population, optimising the dose, duration and formulation of currently available antimicrobials to maximise clinical efficacy–while minimising toxicity and unnecessary deaths due to AMR–is paramount.77 Given there are few antimicrobial resistance awareness and stewardship programmes across the region,5 enhanced efforts to promote antimicrobial stewardship are essential to guide rational antibiotic use and prevent the spread of AMR.

In summary, the burden of antimicrobial resistance among children within the Western Pacific region is alarming. This review suggests many WHO-recommended and commonly-prescribed antibiotic regimens are inefficacious, although the quality of laboratory data supporting this conclusion is sub-optimal and geographically biased. Enhanced efforts to strengthen local microbiological capacity, antimicrobial surveillance, and stewardship programs across the region remain vital to ensure robust data can guide improved treatment regimens and reduce the morbidity and mortality burden of infectious diseases in children across the region.

Contributors

PCMW conceptualised the study. NM and PCMW performed the literature search. NM, EAA, BFRD, AD, and PP conducted title and abstract screen, and assessed studies for inclusion. In case of uncertainty consultation was sought with PCMW or EAA for a final decision. NM and BFRD performed data extraction. Grading was performed by NM and BFRD. PCMW performed a second direct assessment and verification of the underlying data, as well as second grading assessment. BFRD carried out meta-analysis. NM wrote the first draft of the paper. PCMW, EA, PT and BFRD reviewed and revised the final manuscript.

Data sharing statement

Raw antimicrobial susceptibility data extracted from the included studies are available in Supplementary Data 2.

Editor note

The Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations.

Declaration of interests

PW received support to attend conference via ECCMID to present on the topic of antimicrobial resistance in neonatal sepsis; requested testimony to report on a Serratia outbreak in a neonatal intensive care unit. Other coauthors have nothing to declare.

Appendix A Supplementary data

Supplementary Data 1

Supplement 2

Acknowledgements

We thank Professor Patricia Graves of James Cook University Cairns, Australia for advice and support with the meta-analysis.

Appendix A Supplementary data related to this article can be found at https://doi.org/10.1016/j.lanwpc.2024.101177.
==== Refs
References

1 WHO Child health in the western pacific https://www.who.int/westernpacific/health-topics/child-health
2 Loftus M.J. Stewardson A. Naidu R. Antimicrobial resistance in the Pacific Island countries and territories BMJ Glob Health 5 2020 e002418
3 Murray C.J.L. Ikuta K.S. Sharara F. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis Lancet 399 2022 629 655 35065702
4 Wen S.C.H. Ezure Y. Rolley L. Gram-negative neonatal sepsis in low- and lower-middle-income countries and WHO empirical antibiotic recommendations: a systematic review and meta-analysis PLoS Med 18 2021 e1003787
5 WHO. Regional Office for the Western Pacific Antimicrobial resistance in the Western Pacific Region: a review of surveillance and health systems response 2015 World Health Organization Geneva
6 WHO. Regional Office for the Western Pacific Action agenda for antimicrobial resistance in the Western Pacific region 2015 World Health Organization Geneva
7 WHO Global antimicrobial resistance and use surveillance System (GLASS). Country participation https://www.who.int/initiatives/glass/country-participation
8 WHO The WHO AWaRe (Access, Watch, Reserve) antibiotic book 2022 World Health Organization Geneva
9 Hsia Y. Lee B. Versporten A. Use of the WHO access, watch, and reserve classification to define patterns of hospital antibiotic use (AWaRe): an analysis of paediatric survey data from 56 countries Lancet Glob Health 7 2019 e861 e871 31200888
10 Thomson K.M. Dyer C. Liu F. Effects of antibiotic resistance, drug target attainment, bacterial pathogenicity and virulence, and antibiotic access and affordability on outcomes in neonatal sepsis: an international microbiology and drug evaluation prospective substudy (BARNARDS) Lancet Infect Dis 21 2021 P1677 P1688
11 Page M.J. McKenzie J. Bossuyt P.M. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews BMJ 372 2021 n71 33782057
12 The World Bank High income countries https://data.worldbank.org/country/XD
13 Chaurasia S. Sivanandan S. Agarwal R. Ellis S. Sharland M. Sankar M.J. Neonatal sepsis in South Asia: huge burden and spiralling antimicrobial resistance BMJ 364 2019 k5314
14 WHO Pocket book of hospital care for children: second edition. Guidelines for the management of common illnesses with limited resources 2013 World Health Organization Geneva
15 Turner P. Fox-Lewis A. Shrestha P. Microbiology investigation criteria for reporting objectively (MICRO): a framework for the reporting and interpretation of clinical microbiology data BMC Med 17 2019 70 30922309
16 Guyatt G.H. Oxman A.D. Vist G.E. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations BMJ 336 2008 924 926 18436948
17 Corbeil R.R. Searle S.R. Restricted maximum likelihood (REML) estimation of variance components in the mixed model Technometrics 18 1976 31 38
18 Higgins J. Thompson S.G. Deeks J. Altman D. Measuring inconsistency in meta-analyses BMJ 327 2003 557 560 12958120
19 Egger M. Davey Smith G. Philips A.N. Meta-analysis: principles and procedures BMJ 315 1997 1533 1537 9432252
20 Aglua I. Jaworski J. Drekore J. Methicillin-resistant staphylococcus aureus in Melanesian children with haematogenous osteomyelitis from the central highlands of Papua New Guinea Int J Pediatr 6 2018 8361 8370
21 Nor Azizah A. Fadzilah M.N. Mariam M. Community-acquired bacteremia in paediatrics: epidemiology, aetiology and patterns of antimicrobial resistance in a tertiary care centre, Malaysia Med J Malaysia 71 2016 117 121 27495884
22 Bao Y. Wang Q. Yao K. The changing phenotypes and genotypes of invasive pneumococcal isolates from children in Shenzhen during 2013-2017 Vaccine 37 2019 7248 7255 31635974
23 Wang C. Hao W. Yu R. Wang X. Zhang J. Wang B. Analysis of pathogen distribution and its antimicrobial resistance in bloodstream infections in hospitalized children in East China, 2015-2018 J Trop Pediatr 67 2020 fmaa077
24 Zhao C. Xie Y. Zhang F. Investigation of antibiotic resistance, serotype distribution, and genetic characteristics of 164 invasive streptococcus pneumoniae from North China between April 2016 and October 2017 Infect Drug Resist 13 2020 2117 2128 32753907
25 Chheng K. Carter M.J. Emary K. A prospective study of the causes of febrile illness requiring hospitalization in children in Cambodia PLoS One 8 2013 e60634
26 Li C. Feng W.Y. Lin A.W. Clinical characteristics and etiology of bacterial meningitis in Chinese children >28 days of age, January 2014-December 2016: a multicenter retrospective study Int J Infect Dis 74 2018 47 53 30100536
27 Yu F. Liu H. Li K.H. Causative organisms and their antibiotic resistance patterns for childhood septic arthritis in China between 1989 and 2008 Orthopedics 34 2011 179 21410123
28 Jiang H. Su M. Kui L. Prevalence and antibiotic resistance profiles of cerebrospinal fluid pathogens in children with acute bacterial meningitis in Yunnan province, China, 2012-2015 PLoS One 12 2017 e0180161
29 Yang J. Meng L. Liu X. Ma L. Wang W. Detection of non-typhoidal Salmonella gastroenteritis in a tertiary children's hospital in China Jundishapur J Microbiol 12 2019 e84400
30 Cai K. Wang Y. Guo Z. Xu X. Li H. Zhang Q. Clinical characteristics and antimicrobial resistance of pneumococcal isolates of pediatric invasive pneumococcal disease in China Infect Drug Resist 11 2018 2461 2469 30538512
31 Keshi L. Weiwei X. Shoulin L. Analysis of drug resistance of extended-spectrum beta-lactamases-producing Escherichia coli and Klebsiella pneumoniae in children with urinary tract infection Saudi Med J 40 2019 1111 1115 31707407
32 Xu L. Zhou X. Xu X. Antimicrobial resistance, virulence genes and molecular subtypes of S. enteritidis isolated from children in Shanghai J Infect Dev Ctries 12 2018 573 580 31954007
33 Kang L.H. Liu M.J. Xu W.C. Molecular epidemiology of pneumococcal isolates from children in China Saudi Med J 37 2016 403 413 27052283
34 Guo L.Y. Zhang Z.X. Wang X. Clinical and pathogenic analysis of 507 children with bacterial meningitis in Beijing, 2010-2014 Int J Infect Dis 50 2016 38 43 27452172
35 Mohan A. Munusamy C. Tan Y.C. Invasive Salmonella infections among children in Bintulu, Sarawak, Malaysian Borneo: a 6-year retrospective review BMC Infect Dis 19 2019 330 30999894
36 Shi W. Li J. Dong F. Serotype distribution, antibiotic resistance pattern, and multilocus sequence types of invasive Streptococcus pneumoniae isolates in two tertiary pediatric hospitals in Beijing prior to PCV13 availability Expert Rev Vaccines 18 2019 89 94 30526145
37 Duong V.T. The H.C. Nhu T.D.H. Genomic serotyping, clinical manifestations, and antimicrobial resistance of nontyphoidal Salmonella gastroenteritis in hospitalized children in Ho Chi Minh City, Vietnam J Clin Microbiol 58 2020 e01465-20
38 Xiang M. Zhao R. Ma Z. Serotype distribution and antimicrobial resistance of Streptococcus pneumoniae isolates causing invasive diseases from Shenzhen children's hospital PLoS One 8 2013 e67507
39 Peng X. Zhu Q. Liu J. Prevalence and antimicrobial resistance patterns of bacteria isolated from cerebrospinal fluid among children with bacterial meningitis in China from 2016 to 2018: a multicenter retrospective study Antimicrob Resist Infect Control 10 2021 24 33516275
40 Zhang X. Tian J. Shan W. Characteristics of pediatric invasive pneumococcal diseases and the pneumococcal isolates in Suzhou, China before introduction of PCV13 Vaccine 35 2017 4119 4125 28668572
41 Wang X. Liu Q. Zhang H. Molecular characteristics of community-associated Staphylococcus aureus isolates from pediatric patients with bloodstream infections between 2012 and 2017 in Shanghai, China Front Microbiol 9 2018 1211 29928269
42 Ke Y. Lu W. Liu W. Zhu P. Chen Q. Zhu Z. Non-typhoidal salmonella infections among children in a tertiary hospital in Ningbo, Zhejiang, China, 2012-2019 PLoS Negl Trop Dis 14 2020 1 18
43 Qiu Y. Yang J. Chen Y. Microbiological profiles and antimicrobial resistance patterns of pediatric bloodstream pathogens in China, 2016-2018 Eur J Clin Microbiol Infect Dis 40 2020 739 749 33078219
44 Li Y. Xie X. Xu X. Nontyphoidal salmonella infection in children with acute gastroenteritis: prevalence, serotypes, and antimicrobial resistance in Shanghai, China Foodborne Pathog Dis 11 2014 200 206 24313784
45 Ariffin N. Hasan H. Ramli N. Comparison of antimicrobial resistance in neonatal and adult intensive care units in a tertiary teaching hospital Am J Infect Control 40 2012 572 575 22854380
46 Dong Y. Jiang S.Y. Zhou Q. Cao Y. Group B. Streptococcus causes severe sepsis in term neonates: 8 years experience of a major Chinese neonatal unit World J Pediatr 13 2017 314 320 28560649
47 Lu Q. Zhou M. Tu Y. Yao Y. Yu J. Cheng S. Pathogen and antimicrobial resistance profiles of culture-proven neonatal sepsis in Southwest China, 1990-2014 J Paediatr Child Health 52 2016 939 943 27500793
48 Pan T. Zhu Q. Li P. Hua J. Feng X. Late-onset neonatal sepsis in Suzhou, China BMC Pediatr 20 2020 261 32471377
49 Tang X.J. Sun B. Ding X. Li H. Feng X. Changing trends in the bacteriological profiles and antibiotic susceptibility in neonatal sepsis at a tertiary children's hospital of China Transl Pediatr 9 2020 734 742 33457294
50 Li X. Ding X. Shi P. Clinical features and antimicrobial susceptibility profiles of culture-proven neonatal sepsis in a tertiary children's hospital, 2013 to 2017 Medicine (Baltimore) 98 2019 e14686
51 Jiang Y. Kuang L. Wang H. Li L. Zhou W. Li M. The clinical characteristics of neonatal sepsis infection in Southwest China Intern Med 55 2016 597 603 26984074
52 Wang S. Chen S. Feng W. Clinical characteristics of nosocomial bloodstream infections in neonates in two hospitals, China J Trop Pediatr 64 2018 231 236 28985401
53 Wang P. Ma Z. Tong J. Serotype distribution, antimicrobial resistance, and molecular characterization of invasive group B Streptococcus isolates recovered from Chinese neonates Int J Infect Dis 37 2015 115 118 26141418
54 Anderson M. Luangxay K. Sisouk K. Epidemiology of bacteremia in young hospitalized infants in Vientiane, Laos, 2000-2011 J Trop Pediatr 60 2014 10 16 23902672
55 Li J. Ji W. Gao K. Molecular characteristics of group B Streptococcus isolates from infants in southern mainland China BMC Infect Dis 19 2019 812 31533652
56 Yu F. Chen Q. Yu X. High prevalence of extended-spectrum beta lactamases among salmonella enterica typhimurium isolates from pediatric patients with diarrhea in China PLoS One 6 2011 e16801
57 Arushothy R. Ahmad N. Amran F. Hashim R. Samsudin N. Azih C.R.C. Pneumococcal serotype distribution and antibiotic susceptibility in Malaysia: a four-year study (2014-2017) on invasive paediatric isolates Int J Infect Dis 80 2019 129 133 30572022
58 Zhu X.H. Tian L. Cheng Z.J. Viral and bacterial etiology of acute diarrhea among children under 5 years of age in Wuhan, China Chin Med J (Engl) 129 2016 1939 1944 27503019
59 Thompson C.N. Phan M.V. Hoan N.V. A prospective multi-center observational study of children hospitalized with diarrhea in Ho Chi Minh City, Vietnam Am J Trop Med Hyg 92 2015 1045 1052 25802437
60 Liang B. Xie Y. He S. Prevalence, serotypes, and drug resistance of nontyphoidal Salmonella among paediatric patients in a tertiary hospital in Guangzhou, China, 2014-2016 J Infect Public Health 12 2019 252 257 30466903
61 Moore C.E. Sona S. Poda S. Antimicrobial susceptibility of uropathogens isolated from Cambodian children Paediatr Int Child Health 36 2016 113 117 25704569
62 Dong F. Zhang Y. Yao K. Epidemiology of carbapenem-resistant Klebsiella pneumoniae bloodstream infections in a Chinese children's hospital: predominance of New Delhi metallo-beta-lactamase-1 Microb Drug Resist 24 2018 154 160 28594635
63 Fox-Lewis A. Takata J. Miliya T. Antimicrobial resistance in invasive bacterial infections in hospitalized children, Cambodia, 2007-2016 Emerg Infect Dis 24 2018 841 851 29664370
64 Shen H. Zhu C. Liu X. The etiology of acute meningitis and encephalitis syndromes in a sentinel pediatric hospital, Shenzhen, China BMC Infect Dis 19 2019 560 31242869
65 Yue M. Li X. Liu D. Hu X. Serotypes, antibiotic resistance, and virulence genes of salmonella in children with diarrhea J Clin Lab Anal 34 2020 e23525
66 Xiao G. Zhou W. Shu M. Prevalent serotypes and antibiotic resistance patterns of salmonella strains isolated from diarrheic children during a 10-year period in a tertiary referral center in Chengdu, China Pediatr Infect Dis J 34 2015 798 799 26065662
67 Liu J. Fang Z. Yu Y. Pathogens distribution and antimicrobial resistance in bloodstream infections in twenty-five neonatal intensive care units in China, 2017–2019 Antimicrob Resist Infect Control 10 2021 121 34399840
68 Tan J. Wang Y. Gong X. Antibiotic resistance in neonates in China 2012-2019: a multicenter study J Microbiol Immunol Infect 55 2022 454 462 34059443
69 Wang S. Zhao S. Zhou Y. Antibiotic resistance spectrum of E. coli strains from different samples and age-grouped patients: a 10-year retrospective study BMJ Open 13 2023 e067490
70 Song W. Shan Q. Qiu Y. Clinical profiles and antimicrobial resistance patterns of invasive salmonella infections in children in China Eur J Clin Microbiol Infect Dis 41 2022 1215 1225 36040531
71 Sands K. Carvalho M. Portal E. Characterization of antimicrobial-resistant gram-negative bacteria that cause neonatal sepsis in seven low- and middle-income countries Nat Microbiol 6 2021 512 523 33782558
72 Williams P.C.M. Isaacs D. Berkley J.A. Antimicrobial resistance among children in sub-Saharan Africa Lancet Infect Dis 18 2018 e33 e44 29033034
73 Jackson C. Hsia Y. Basmaci R. Global divergence from world health organization treatment guidelines for neonatal and pediatric sepsis Pediatr Infect Dis J 38 2019 1104 1106 31425329
74 Le Doare K. Bielicki J. Heath P. Sharland M. Systematic review of antibiotic resistance rates among gram-negative bacteria in children with sepsis in resource-limited countries J Pediatr Infect Dis Soc 4 2015 11 20
75 Sands K. Carvalho M.J. Spiller O.B. Characterisation of Staphylococci species from neonatal blood cultures in low- and middle-income countries BMC Infect Dis 22 2022 593 35790903
76 Williams P.C.M. Qazi S.A. Agarwal R. Antibiotics needed to treat multidrug-resistant infections in neonates Bull World Health Organ 100 2022 797 807 36466207
77 Williams P.C.M. Bradley J. Roilides E. Harmonising regulatory approval for antibiotics in children Lancet Child Adolesc Health 5 2021 96 98 33484666
