Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Faecal carriage of antibiotic resistant Escherichia coli in asymptomatic children and associations with primary care antibiotic prescribing: a systematic review and meta-analysis

  • Ashley Bryce1Email author,
  • Céire Costelloe2,
  • Claire Hawcroft1,
  • Mandy Wootton3 and
  • Alastair D. Hay1
BMC Infectious DiseasesBMC series – open, inclusive and trusted201616:359

https://doi.org/10.1186/s12879-016-1697-6

Received: 5 January 2016

Accepted: 8 July 2016

Published: 25 July 2016

We’re sorry, something doesn't seem to be working properly.

Please try refreshing the page. If that doesn't work, please contact us so we can address the problem.

Abstract

Background

The faecal reservoir provides optimal conditions for the transmission of resistance genes within and between bacterial species. As key transmitters of infection within communities, children are likely important contributors to endemic community resistance. We sought to determine the prevalence of antibiotic-resistant faecal Escherichia coli from asymptomatic children aged between 0 and 17 years worldwide, and investigate the impact of routinely prescribed primary care antibiotics to that resistance.

Methods

A systematic search of Medline, Embase, Cochrane and Web of Knowledge databases from 1940 to 2015. Pooled resistance prevalence for common primary care antibiotics, stratified by study country OECD status. Random-effects meta-analysis to explore the association between antibiotic exposure and resistance.

Results

Thirty-four studies were included. In OECD countries, the pooled resistance prevalence to tetracycline was 37.7 % (95 % CI: 25.9–49.7 %); ampicillin 37.6 % (24.9–54.3 %); and trimethoprim 28.6 % (2.2–71.0 %). Resistance in non-OECD countries was uniformly higher: tetracycline 80.0 % (59.7–95.3 %); ampicillin 67.2 % (45.8–84.9 %); and trimethoprim 81.3 % (40.4–100 %). We found evidence of an association between primary care prescribed antibiotics and resistance lasting for up to 3 months post-prescribing (pooled OR: 1.65, 1.36–2.0).

Conclusions

Resistance to many primary care prescribed antibiotics is common among faecal E. coli carried by asymptomatic children, with higher resistance rates in non-OECD countries. Despite tetracycline being contra-indicated in children, tetracycline resistance rates were high suggesting children could be important recipients and transmitters of resistant bacteria, or that use of other antibiotics is leading to tetracycline resistance via inter-bacteria resistance transmission.

Background

The global emergence of antibiotic resistant bacterial infections is arguably the greatest 21st century threat to human health. The reasons for its emergence are complex and likely to include interactions between: the way in which antibiotics are used, particularly in primary care, where 80 % of all health service antibiotics are prescribed [1]; patient misuse through suboptimal dosing and antibiotic storage for future symptoms; over-the-counter (OTC) use; and community contacts and transmission. The more antibiotics a population is exposed to, the easier it becomes for resistant bacteria to spread and persist within communities. As key transmitters of infection within communities [2], children are likely to be important contributors to endemic community resistance.

The faecal reservoir provides optimal conditions for the transmission of resistance genes within and between bacterial species. E. coli is among the most abundant organisms in the faecal flora, both in humans and animals. E. coli is an opportunistic pathogen, and a common cause of urinary tract, bloodstream, and foodborne infections, and a cause of meningitis in neonates [3]. Whilst antibiotic use is likely to be the main driver of selection pressure contributing to antibiotic resistance [4], previous research has also demonstrated that intestinal bacteria can acquire resistance to certain antibiotics in the absence of antibiotic exposure [5]. How this resistance is acquired is unclear, but could be as a result of person-to-person transmission or environmental acquisition of resistant bacteria.

There has been little research published exploring faecal carriage of bacterial resistance in any asymptomatic population. This could provide important information regarding carriage and transmission of resistant bacteria within and between populations. This is particularly important in low-income countries, where antibiotics are often available OTC, without the need for a prescription [6]. Misuse of antibiotics in this way can expose harmless or opportunistic bacteria to a plethora of antibiotics to which they develop resistance. We conducted a systematic review aimed to investigate the carriage of faecal E. coli from asymptomatic children resistant to commonly prescribed primary care antibiotics, and quantify the relationship between previous exposure to primary care antibiotics and bacterial resistance. We stratified data by study country Organisation for Economic Co-operation and Development (OECD) status, as antibiotics can often be used differently in these population groups; antibiotics are obtained mostly by prescription only in OECD countries, whereas in non-OECD countries many antibiotics can be obtained over-the-counter [711].

Methods

Search strategy and selection criteria

We searched Medline, Embase, Cochrane and ISI Web of Knowledge databases for articles published in any language between 1940 and September 2015. MeSH terms for these databases included “drug resistance”, “faeces”, “carrier state” and “children”. MeSH terms were combined with text word searches which included “antibiotics”, “resistance”, “faecal/fecal”, “colonisation”, “commensal” and “paediatric/pediatric”. Grey and unpublished literature was searched for using ISI Web of Knowledge software and included journal articles, websites, conference proceedings, government and national reports and open access material. Reference lists of selected key papers were screened and authors who appeared multiple times in our search were contacted to request details of further published and unpublished work. All full-text papers were subject to citation searches. See Additional file 1 for full search strategy. The review protocol is available on PROSPERO (http://www.crd.york.ac.uk/PROSPERO/), registration number CRD42014009691.

Two independent reviewers screened all titles and abstracts for eligibility. Studies were eligible if they met the following criteria: investigated and reported carriage of resistance in faecal E. coli from asymptomatic children, that is children who were not showing symptoms of infection at the time the sample was taken; or investigated associations between previous antibiotic exposure and carriage of resistant E. coli; and study participants were children aged 0–17 years, including healthy neonates with an uncomplicated vaginal birth.

Data extraction and quality assessment

Full-text papers for all eligible studies were obtained and three reviewers extracted data independently using a purpose-built spreadsheet. The following information was extracted from each paper, where provided: author, journal, year of publication, study design, study country, economic status, participants and recruitment location, recruitment time period, age range, method of faecal sample collection and testing, method of antimicrobial sensitivity testing, bacteria cultured and reported antibiotic sensitivities, previously prescribed antibiotics and time between antibiotic exposure and faecal sample collection. Economic status was measured using the OECD status of the country where the study was conducted [12]. The OECD is an international economic organisation first established in 1948, now made up of 34 countries, which aims to work together and with emerging and developing economies to reduce poverty through economic growth and financial stability [12]. OECD member countries tend to be ‘developed’ countries, whereas non-OECD countries tend to be ‘developing’. For the purpose of this review, we use OECD status as a general measure of country-level development, and a proxy marker for OTC antibiotic use. For antimicrobial exposure, time was generally recorded as a period of days, weeks or months prior to the faecal sample being taken and resistance being measured when the child had been exposed to any, or specific named antibiotics. Where any information was unclear in the paper, authors were contacted for clarification.

We reported resistance to antibiotics commonly prescribed to children in primary care, including for urinary tract infection or other indications including respiratory and skin infections. Resistance data was extracted and reported for the following antibiotics: ampicillin, co-amoxiclav (amoxicillin-clavulanic acid), co-trimoxazole (trimethoprim-sulfamethoxazole), trimethoprim, nitrofurantoin, ciprofloxacin, ceftazidime, tetracycline and chloramphenicol. Ceftazidime was the most frequently reported of all first to third generation cephalosporins, and acts as a marker for cephalosporin resistance.

Included papers were assessed for quality using a checklist based on Cochrane collaboration’s ‘risk of bias’ tool [13], We focused our quality criteria on factors we considered important for the review, namely: a reliable measure of antibiotic exposure and resistance, clear reporting of bacterial resistance, and clear reporting of children as asymptomatic or non-infected. For papers which included information on previous antibiotic exposure, we supplemented these with assessment of reporting adjustment for confounders including age, sex and socioeconomic status.

Data synthesis and analysis

All statistical analyses were conducted using STATA version 13 software, and all methods undertaken according to PRISMA guidelines [14].

We calculated pooled prevalence of resistance estimates by generating a Forest plot for each antibiotic, stratified by OECD status. Forest plots illustrated proportion of resistant E. coli for each country, along with 95 % confidence intervals (CI), and the pooled prevalence of resistance per antibiotic per economic country group (OECD vs. non-OECD). We calculated pooled estimates for each country and for OECD and non-OECD groups using the pooled country estimates. Pooled prevalence estimates were generated for children of all age groups (0–90 days, 0–5 years and 5–17 years) and for defined time periods (1970–1979, 1980–1989, 1990–1999, 2000–2010, 2010–2015), for comparison. An I2 of 25, 50 and 75 % were used to signify low-level, moderate-level and high-level heterogeneity, in line with Cochrane recommendations [13]. All pooled estimates and 95 % confidence intervals (CI) were generated using double arcsine transformation to adjust for variance instability. This avoids implausible 95 % CI for prevalence estimates when generated under the normal approximation [15].

For studies investigating the association between previous antibiotic exposure and bacterial resistance, the outcome measure was the odds ratio (OR) of bacterial resistance in children previously exposed to any antibiotic compared to those children who were previously unexposed. The crude estimates from these studies were grouped according to the reported preceding exposure time period (0–2 weeks, 0–1 month and 0–3 months). A random-effects meta-analysis was conducted where heterogeneity was moderate-to-high and a pooled OR was generated for each exposure time period measured. These were compared to adjusted OR for each time period, where reported. Variables which were adjusted for were family member antibiotic exposure, previous hospitalisation, day care attendance, nappy use, ethnicity and socio-economic status (see Additional file 2). We assessed heterogeneity using the I2 statistic, and the null hypothesis of no heterogeneity was tested using the Q statistic generated from the χ2 test. Finally, funnel plots were generated to explore the possibility of small study effects, which can be caused by publication bias.

Results

Study characteristics

We initially identified 12,997 potentially eligible articles. Of these, 8995 non-duplicate papers were assessed and 8697 excluded on basis of title (Fig. 1). The remaining 298 papers were assessed by abstract screening of which 240 were excluded. For the remaining 58, full-text papers were assessed, with 24 papers excluded. Thirty-four papers were therefore included in the review [1649], of which six papers reported previous antibiotic exposure data and were included in our meta-analysis [19, 27, 33, 34, 37, 49].
Fig. 1

Data search and extraction (PRISMA flowchart)

Table 1 summarises the characteristics of the 34 studies. Additional study characteristics can be found in Additional file 2. Twenty studies, reporting the resistance status of 3864 E. coli isolates were conducted in OECD countries (Fig. 2), and all were observational. Fourteen studies, reporting the resistance status of 6699 isolates were conducted in non-OECD studies (Fig. 2), and again, all were observational. Twenty-three studies (14 OECD vs. 9 non-OECD) reported stool sampling as the primary collection method, with 10 reporting rectal swabs, and one study accepting both methods of collection. Antimicrobial sensitivity testing was carried out using standard disk diffusion methods for all studies, which were interpreted and reported according to either the European Committee on Antimicrobial Susceptibility Testing (EUCAST) [50], or the Clinical and Laboratory Standards Institute (CLSI) [51]. All study participants were healthy, without symptoms of infection and recruited in the community, schools and day care centres, or at a primary care facility conducting routine child health surveillance check-ups. Three papers, OECD only, included healthy neonates following uncomplicated vaginal delivery recruited from maternity units.
Table 1

Study characteristics of included papers

Study Characteristics

OECD (n = 20)

Non-OECD (n = 14)

Number of papers

Reference number

Number of papers

Reference number

Study Design:

 Retrospective observational

12

[1627]

10

[3645]

 Prospective observational

5

[2832]

1

[46]

 Cross-sectional

3

[3335]

3

[4749]

Number of study participants:

 0–50

1

[21]

1

[38]

 51–100

5

[25, 28, 30, 31, 34]

2

[42, 46]

 101–200

7

[17, 18, 20, 22, 23, 29, 32]

2

[36, 40]

 201–500

4

[24, 27, 33, 35]

2

[41, 43]

 501–1000

3

[16, 19, 26]

5

[37, 39, 44, 47, 49]

 1000+

0

 

2

[45, 48]

Method of faecal sampling:

 Stool sample

14

[17, 1921, 23, 24, 27, 28, 3035]

9

[36, 37, 3941, 44, 4648]

 Rectal swab

5

[16, 18, 22, 25, 26]

5

[38, 42, 43, 45, 49]

 Stool sample or rectal swab

1

[29]

0

 

Age range of childrena:

 Neonates (0–90 days)

3

[3032]

0

 

 0–5 years

9

[1821, 24, 28, 3335]

7

[36, 37, 39, 41, 46, 48, 49]

 5–17 years

4

[16, 23, 24, 26]

3

[40, 42, 44]

 0–17 years

5

[17, 22, 25, 27, 29]

4

[38, 43, 45, 47]

Antibiotics reported:

 Ampicillin

15

[1619, 21, 22, 2426, 2932, 34, 35]

12

[3645, 47]

 Co-amoxiclav

5

[16, 17, 19, 21, 28]

2

[39, 47]

 Co-trimoxazole

4

[16, 17, 19, 21]

10

[3641, 4345, 47]

 Trimethoprim

7

[22, 26, 28, 29, 3335]

2

[29, 42]

 Nitrofurantoin

3

[26, 30, 35]

2

[43, 48]

 Ciprofloxacin

4

[16, 17, 21, 27]

12

[3743, 4548]

 Ceftazidime

4

[1618, 21]

3

[36, 39, 47]

 Tetracycline

13

[16, 17, 20, 21, 2326, 2932, 35]

10

[3638, 4045, 47]

 Chloramphenicol

11

[16, 17, 21, 23, 25, 26, 2932, 35]

10

[3739, 4145, 47, 48]

Previous exposure to antibioticsb:

 0–2 weeks

2

[33, 34]

0

 

 0–3 weeks

0

 

1

[37]

 0–1 month

1

[19]

0

 

 0–3 months

1

[27]

1

[49]

 0–6 months

0

 

0

 

 0–1 year

0

 

0

 

aAge 0–5 years: papers which report data specifically for this age group, 6–17 years: papers which report data specifically for this age group; 0–17 years: papers which report data for the children within 0–17 years, and do not fit into the previous reported age groups. Papers may appear more than once depending on how they have reported their results

bIndicates papers which reported information regarding previous exposure to antibiotics and the exposure time periods they investigated

Fig. 2

Geographical distribution of OECD and non-OECD countries, including number of included studies per countrya (OECD countries shown in blue) [12]. Faecal carriage of E. coli resistant to ampicillin for each reporting country are shown in red. Authors own map. a One study was conducted in the USA, but also reported resistance data from Venezuela and China, this study therefore appears three times [29]

The quality assessment ‘traffic-light’ charts for the included studies show that, for the six studies reporting antibiotic exposure information, reporting was generally good for our all our key quality indicators (Additional file 3). For studies reporting prevalence of resistance only, overall quality was good with the exception of controlling for confounding and accurate reporting of methods of analysis.

Prevalence of resistance in faecal E. coli from asymptomatic children

Figure 2 details the number of studies per country and shows the global variation in resistance to ampicillin by OECD status. Resistance to ampicillin in faecal E. coli from asymptomatic children was highest in Mexico (OECD) and Bolivia (non-OECD), with a pooled prevalence of 90 and 95 %, respectively. Ampicillin resistance was lowest in Sweden (OECD), with a pooled prevalence of 12 %.

Table 2 shows the pooled prevalence of resistance to antibiotics in faecal E. coli isolates and were obtained from Forest plots generated for each antibiotic, which can be found in Additional files 4, 5, 6, 7, 8, 9, 10, 11 and 12.
Table 2

Pooled prevalence (%) of resistance to antibiotics in faecal E. coli from asymptomatic children (see Additional files 4, 5, 6, 7, 8, 9, 10, 11 and 12 for corresponding Forest plots)

Antibiotics

OECD

Non-OECD

 

Pooled prevalence

(95 % CI)

Number of isolates tested

Number of studies

I2

Ref No.

Pooled prevalence

(95 % CI)

Number of isolates tested

Number of studies

I2

Ref No.

Tetracycline

37.7 %

(25.9–49.7 %)

2438

13

(9 countries)

19.5 %

[16, 17, 20, 21, 2326, 2932, 35]

80.0 %

(59.7–95.3 %)

5401

10

(8 countries)

62.9 %

[3638, 4045, 47]

Ampicillin

37.6 %

(24.9–54.3 %)

3053

15

(11 countries)

34.6 %

[1619, 21, 22, 2426, 2932, 34, 35]

67.2 %

(45.8–84.9 %)

6139

12

(10 countries)

58.1 %

[3645, 47]

Trimethoprim

28.6 %

(2.2–71.0 %)

862

7

(4 countries)

47.2 %

[22, 26, 28, 29, 3335]

81.3 %

(40.4–100 %)

359

2

(3 countries)

50.3 %

[29, 42]

Chloramphenicol

13.4 %

(5.2–24.0 %)

2224

11

(8 countries)

58.1 %

[16, 17, 21, 23, 25, 26, 2932, 35]

44.5 %

(24.1–66.6 %)

5665

10

(9 countries)

39.0 %

[3739, 4145, 47, 48]

Co-trimoxazole

10.8 %

(5.7–16.7 %)

1007

4

(4 countries)

33.5 %

[16, 17, 19, 21]

59.5 %

(31.3–85.7 %)

5439

10

(6 countries)

61.4 %

[3641, 4345, 47]

Co-amoxiclav

7.2 %

(1.8–13.5 %)

1066

5

(5 countries)

37.9 %

[16, 17, 19, 21, 28]

18.1 %

(14.7–21.6 %)

745

2

(2 countries)

8.8 %

[39, 47]

Ciprofloxacin

5.1 %

(0.2–17.8 %)

586

4

(4 countries)

36.0 %

[16, 17, 21, 27]

9.3 %

(3.4–17.2 %)

6231

12

(7 countries)

60.3 %

[3743, 4548]

Nitrofurantoin

4.4 %

(0.6–9.3 %)

673

3

(3 countries)

54.4 %

[26, 30, 35]

7.3 %

(5.9–9.7 %)

715

2

(2 countries)

0.0 %

[43, 48]

Ceftazidime

0.3 %

(0.1–0.8 %)

177

4

(4 countries)

0.0 %

[1618, 21]

5.0 %

(0.7–15.6 %)

654

3

(3 countries)

28.8 %

[36, 39, 47]

Ordered by pooled resistance prevalence in OECD countries (highest to lowest)

In OECD countries, the highest pooled resistance prevalence was for tetracycline at 37.7 % (95 % CI: 25.9–49.7 %), with ampicillin and trimethoprim resistance also high at 37.6 and 28.6 %, respectively. Resistance to ceftazidime was lowest in OECD countries at 0.3 % (0.1–0.8 %).

Similarly to OECD countries, in non-OECD countries the highest pooled prevalence of resistance was observed in the same antibiotics, with trimethoprim highest at 81.3 % (95 % CI: 40.4–100 %), followed by tetracycline and ampicillin at 80.0 and 67.2 %, respectively.

Prevalence of resistance in different age groups

There were too few data to report pooled resistance prevalence estimates for any given age group (0–90 days, 0–5 years, 5–17 years) for any antibiotic reported in this review.

Prevalence of resistance across different time periods

Figure 3 shows a Forest plot of the pooled resistance prevalence to ampicillin and tetracycline (for which data were most complete), by OECD status, by decade. There were too few data for all other antibiotics to report time period estimates. For OECD countries, included studies were conducted between 1970 and 2014, compared with non-OECD countries which were conducted from 1990 to 2014. Once again, the graphs show the higher resistance rates in non-OECD compared to OECD countries, however there is no evidence of a change in resistance over time as the confidence intervals for each time period and each antibiotic overlap.
Fig. 3

Pooled prevalence (%) of resistance to antibiotics in faecal E. coli from asymptomatic children across different time periods for ampicillin (a and b) and tetracycline (c and d), split by OECD (a and c) and non-OECD (b and d) countries. Studies included more than once reported resistance separately in different age groups or different geographic locations

Association between previous antibiotic exposure and bacterial resistance

Figure 4 shows a Forest plot of six studies investigating the relationship between previous exposure to antibiotics and resistance to a range of commonly used primary care antibiotics. Within all antibiotic exposure time periods, the crude odds of resistance were generally greater for children exposed to antibiotics than those unexposed, though exposure at 0–2 weeks was not found to be significantly associated with resistance. The effect sizes are reasonably similar for all time periods, with the pooled OR of resistance rising as the cumulative antibiotic exposure period increases, though confidence intervals do overlap between different time periods. Given the overlap in exposure time periods, meta-regression analysis was not appropriate.
Fig. 4

Meta-analysis of individual studies examining association between previous primary care antibiotic exposure and carriage of bacterial resistance. The Forest plot shows pooled crude and individual OR (log scale) for resistance in asymptomatic children’s faecal E. coli bacteria and previous exposure to any antibiotic. Studies grouped according to time period during which exposure was measured and ordered within each time period by increasing standard error

There was no evidence of within group heterogeneity in the 0–3 month time period, with low heterogeneity in the 0–2 week period and moderate heterogeneity in the 0–1 month periods. For those studies which reported adjusted ORs, adjusting for family member antibiotic exposure, previous hospitalisation, day care attendance, nappy use, ethnicity and socio-economic status; we compared these results with our crude estimates, though we only had sufficient data to do this for exposure at 0–3 months. The pooled adjusted (OR 1.70, 95 % CI: 1.36–2.12) and crude (OR 1.65, 1.36–2.00) did not differ substantially.

Publication bias

There were too few studies for any given exposure time period to assess publication bias.

Discussion

Principal findings

In asymptomatic children, we found evidence of high rates of faecal E. coli resistance to several commonly prescribed primary care antibiotics, and we have shown that resistance rates were consistently higher in non-OECD compared to OECD countries. The routine use of primary care antibiotics could be an important contributor to carriage of resistant E. coli which we showed persists at both 1 and 3 months post-antibiotic prescription.

Strengths and weaknesses

To our knowledge, this is the first systematic review and meta-analysis to explore and report global evidence regarding faecal carriage of resistant bacteria in healthy, community-resident children and associations with the routine use of antibiotics in primary care. Our review was rigorously conducted according to the Cochrane guidelines for Systematic Reviews [13]. We chose to stratify our results by OECD status to reflect both national development and likely OTC antibiotic availability [6, 52].

We are aware of four main limitations. First, antibiotics are used very differently within OECD and non-OECD countries [5356], and OTC antibiotic use is difficult to measure. A systematic review conducted in 2011 reported high non-prescription antibiotic variability across countries worldwide [52], and there is not 100 % agreement between OECD status and OTC antibiotic availability. However, we are not aware of a better country-level alternative with respect to measuring global prevalence of antibiotic resistance in relation to antibiotic use, and none of the included studies reported or measured OTC antibiotic availability. There was some variation in heterogeneity for our pooled prevalence of resistance estimates. Most heterogeneity was moderate at around 50 %, higher heterogeneity was observed most frequently in our estimates from non-OECD countries. This may be due to the lack of information provided regarding the study populations; although all children were asymptomatic of infection, they may vary in other factors from country to country, for example the comorbidities. Higher heterogeneity in non-OECD countries may also be a reflection of the availability of certain antibiotics OTC in some countries. We also acknowledge that factors other than antibiotic usage and OTC availability can account for differences in carriage of resistant bacteria between OECD and non-OECD countries, including; poverty, poor sanitation, unstable governance, and lower levels of medicine regulation [57]. Additionally, the majority of our non-OECD studies were conducted in either South America or Asia, with African countries under-represented in this group.

Second, reverse causality and other confounding associations including age, sex and previous hospitalisation, could have introduced bias to our meta-analysis findings. However, analyses adjusting for confounding factors did not demonstrate substantial differences between crude and adjusted association estimates. Third, our meta-analysis of the association between antibiotic exposure and resistance reported moderate heterogeneity within the 0–1 month time period, however the difficulty in estimating a more accurate point of antibiotic exposure may have accounted for this. In addition to this, only six studies, conducted between 1987 and 2012 reported data on antibiotic exposure, therefore these findings must be interpreted with caution, but nevertheless provide some evidence to support the possibility of an association between antibiotic exposure and carriage of resistant bacteria. Finally, there were insufficient studies to adequately assess publication bias.

Results in the context of existing research

Carriage of resistant faecal E. coli in healthy children

Resistance to ampicillin in faecal E. coli isolates was high for both OECD and non-OECD countries, particularly non-OECD countries which reached almost 65 %. There is little data other than that which was included in this review with which to compare estimates. However, the highest reported resistance to ampicillin was very similar to reported aminopenicillin group resistance in the European Antimicrobial Resistance Surveillance Network (EARS-Net) database and US Centre for Disease Dynamics, Economics and Policy (CDDEP) databases [58, 59]. Given that such databases include clinical samples from the general population, including older adults, the similarities observed here could be a result of between age-group transmission of genetic resistance factors such as plasmids; facilitated via frequent interaction between children and adults. In addition, the EARS-Net and CDDEP databases constitute ‘invasive’ clinical E. coli samples, taken from blood or urine. This could suggest that the resistance profiles of both commensal and pathogenic organisms are similar. A recent systematic review exploring prevalence of resistance to antibiotics in E. coli causing urinary tract infection in children also reported similar estimates to faecal E. coli [60], which further supports this theory.

Tetracycline can be used for a number of indications, but is not recommended for use in children under 8 years due to its association with permanent tooth discolouration [61]. Despite this, the pooled resistance prevalence to tetracycline was high in faecal E. coli from healthy children in both OECD and non-OECD countries. Previous studies in human faecal bacteria have reported that bacteria such as E. coli which are resistant to tetracycline also tend to be co-resistant to other antibiotics, including ampicillin and sulphonamides [62]. A UK study reported that following administration of amoxicillin in healthy adults, an increase in tetracycline resistance genes was observed in E. coli faecal isolates, an indication of co-selection of multiple antibiotic resistance genes [63]. The reason for the high-level resistance to tetracycline in asymptomatic children may not necessarily reflect exposure in individual children, but exposure from their contacts; indicating that community-level exposure to antibiotics may play a greater role in the dissemination of resistant bacteria than individual exposure in children. Additionally, there is considerable evidence demonstrating the transfer of resistance genes between animals and humans, whether through direct contact with animals such as pets [64], or through the ingestion of animal food-products [65]. Whilst the use of antibiotics, including tetracycline, as growth promoters in food animals is no longer recommended in many European countries, transfer of resistant bacteria in this manner continues to pose a global threat [66], as does veterinary use of antibiotics, which is less well regulated than human use.

Association between antibiotic exposure and carriage of resistant E. coli

Our meta-analysis of the association between previous exposure to antibiotics and bacterial resistance observed associations which were stronger for longer time periods, namely 0–1 month and 0–3 months compared with 0–2 weeks. There was no association found between antibiotic exposure within 0–2 weeks and carriage of resistance; this may have been due to insufficient sample size, or the fact that the studies measuring association within this time period were almost 30 years old, whereas the studies measuring associations in other time periods were more recent. Of the six studies included in our meta-analysis, most reported the association between previous antibiotic exposure and resistance within overlapping time periods. This implies that the associations with longer time periods (i.e. 0–3 months) could reflect either long or short-term relationships. A previous systematic review demonstrated similar effects in urinary and respiratory bacteria, in patients of all ages [67]. That review found that the effect of antibiotic exposure on the isolation of a resistant isolate may persist for up to 12 months, something we were unable to explore because our review studies did not measure exposure for this period.

Clinical, public health and research implications

Our findings demonstrate the high-level resistance to some of the most commonly prescribed primary care antibiotics in faecal isolates from healthy children, and suggest that one cause of carrying bacterial resistant faecal flora in healthy children could be previous exposure to antibiotics. Despite our data being obtained from asymptomatic children, the clinical and public health implications of these findings are significant. First, they provide further empirical data to support the importance of antimicrobial stewardship and good sanitation, and that the more antibiotics are prescribed and used within communities, either in humans, food products or farm animals and pets, the greater the selection pressure is for resistance to develop and persist. Resistant bacteria can be shed from humans and animals in faeces which can contaminate the environment, including water supplies. Second, faecal bacteria have been shown to be the source of auto-infection, in which safely carried bacteria invade other body areas and become pathogenic, leading to UTI, meningitis, septicaemia and pneumonia [3]. Autoinfection of resistant bacteria could result in the ineffectiveness of first-line antibiotic treatments, and without the development of any new antibiotics, this poses hazardous limitations on our continued ability to treat. For primary care clinicians, the best course of action is to consider the impact of any antibiotic use on antimicrobial resistance, and avoid their unnecessary use by following local and national guidance wherever possible.

Future studies should identify the extent of faecal shedding and modes of antibiotic-resistant bacteria transmission within and between communities of humans, animals and the surrounding environments.

Conclusions

Resistance to many commonly used primary care antibiotics in faecal E. coli isolates from asymptomatic children ranged from moderate to very high, with resistance being higher in non-OECD countries. Routine antibiotic use is likely to be an important contributor to resistance, which may persist for up to 3 months post-antibiotic treatment. Despite the fact that tetracycline is contra-indicated in children, the high rates of tetracycline resistance suggest healthy children could be important recipients and transmitters of resistant bacteria and, or, that use of other antibiotics is leading to tetracycline resistance via inter-bacteria resistance transmission.

Abbreviations

CDDEP, US centre for disease dynamics, economics and policy; CI, confidence interval; CLSI, clinical and Laboratory Standards Institute; EARS-net, European antimicrobial resistance surveillance network; EUCAST, European committee on antimicrobial sensitivity testing; OECD, Organisation for Economic Cooperation and Development; OR, odds ratio; OTC, over the counter

Declarations

Acknowledgements

Not applicable.

Funding

This work was funded by the National Institute of Health School for Primary Care Research (NIHR-SPCR). The NIHR is the research arm of the NHS. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Availability of data and material

The dataset supporting the conclusions of this article are included within this article and its Additional files 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12.

Authors’ contributions

AB, ADH and CC conceived the study. AB performed the searches. AB and CC identified eligible studies. AB, CC and ADH appraised study quality; data was extracted by AB, CC and CH. AB and CC transformed data and performed the meta-analyses. AB drafted first sections of the text. ADH, CC and MW provided critical revision of the draft for intellectual content. All authors contributed to the final draft. All authors received access to all of the data (including statistical reports and tables) in the study and can take responsibility for the integrity of the data and the accuracy of the data analysis. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Centre for Academic Primary Care, NIHR School for Primary Care Research, School of Social and Community Medicine, University of Bristol
(2)
NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, Hammersmith Campus
(3)
Specialist Antimicrobial Chemotherapy Unit, Public Health Wales Microbiology Cardiff, University Hospital of Wales, Heath Park

References

  1. Majeed A, Moser K. Age- and sex-specific antibiotic prescribing patterns in general practice in England and Wales in 1996. Br J Gen Pract. 1999;49:735–6.PubMedPubMed CentralGoogle Scholar
  2. Dick G. Immunisation. California: Springer Netherlands; 2012. ISBN 978-0-906141-03-8. Google Scholar
  3. Antimicrobial Resistance: Global report on surveillance [http://www.who.int/drugresistance/documents/surveillancereport/en/]. Accessed 2 Mar 2015.
  4. Laxminarayan R, Duse A, Wattal C, Zaidi AKM, Wertheim HFL, Sumpradit N, Vlieghe E, Hara GL, Gould IM, Goossens H, et al. Antibiotic resistance—the need for global solutions. Lancet Infect Dis. 2013;13(12):1057–98.View ArticlePubMedGoogle Scholar
  5. Qin X, Razia Y, Johnson JR, Stapp JR, Boster DR, Tsosie T, Smith DL, Braden CR, Gay K, Angulo FJ, et al. Ciprofloxacin-resistant gram-negative bacilli in the fecal microflora of children. Antimicrob Agents Chemother. 2006;50(10):3325–9.View ArticlePubMedPubMed CentralGoogle Scholar
  6. Planta MB. The role of poverty in antimicrobial resistance. J Am Board Fam Med. 2007;20(6):533–9.View ArticlePubMedGoogle Scholar
  7. Special Eurobarometer 338: Antimicrobial Resistance [http://ec.europa.eu/health/antimicrobial_resistance/docs/ebs_338_en.pdf]. Accessed 2 Mar 2015.
  8. Guneysel O, Onur O, Erdede M, Denizbasi A. Trimethoprim/sulfamethoxazole resistance in urinary tract infections. J Emerg Med. 2009;36(4):338–41.View ArticlePubMedGoogle Scholar
  9. Cizman M, Beovic B, Krcmery V, Barsic B, Tamm E, Ludwig E, Pelemis M, Karovski K, Grzesiowski P, Gardovska D, et al. Antibiotic policies in Central Eastern Europe. Int J Antimicrob Agents. 2004;24(3):199–204.View ArticlePubMedGoogle Scholar
  10. Levy SB. The challenge of antibiotic resistance. Sci Am. 1998;278(3):46–53.View ArticlePubMedGoogle Scholar
  11. Chen CJ, Huang YC. New epidemiology of staphylococcus aureus infection in Asia. Clin Microbiol Infect. 2014;20:605–23.View ArticlePubMedGoogle Scholar
  12. Organisation for Economic Co-operation and Development (OECD) [http://www.oecd.org/]. Accessed 12 Nov 2014.
  13. Cochrane Handbook for Systematic Reviews of Interventions [www.cochrane-handbook.org]. Accessed 3 Nov 2014.
  14. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151:264–9.View ArticlePubMedGoogle Scholar
  15. Barendregt JJ, Doi SA, Lee YY, Norman RE, Vos T. Meta-analysis of prevalence. Epidemiol Community Health. 2013;67:974–8.View ArticleGoogle Scholar
  16. Literak I, Petro R, Dolejska M, Gruberova E, Dobiasova H, Petr J, Cizek A. Antimicrobial resistance in fecal Escherichia coli isolates from healthy urban children of two age groups in relation to their antibiotic therapy. Antimicrob Agents Chemother. 2011;55(6):3005–7.View ArticlePubMedPubMed CentralGoogle Scholar
  17. Barreto A, Guimaraes B, Radhouani H, Araujo C, Goncalves A, Gaspar E, Rodrigues J, Igrejas G, Poeta P. Detection of antibiotic resistant E. Coli and Enterococcus spp. In stool of healthy growing children in Portugal. J Basic Microbiol. 2009;49(6):503–12.View ArticlePubMedGoogle Scholar
  18. Karami N, Hannoun C, Adlerberth I, Wold AE. Colonization dynamics of ampicillin-resistant Escherichia coli in the infantile colonic microbiota. J Antimicrob Chemother. 2008;62(4):703–8.View ArticlePubMedGoogle Scholar
  19. Lietzau S, Raum E, von Baum H, Marre R, Brenner H. Household contacts were key factor for children’s colonization with resistant Escherichia coli in community setting. J Clin Epidemiol. 2007;60(11):1149–55.View ArticlePubMedGoogle Scholar
  20. Karami N, Nowrouzian F, Adlerberth I, Wold AE. Tetracycline resistance in escherichia coli and persistence in the infantile colonic microbiota. Antimicrob Agents Chemother. 2006;50(1):156–61.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Dominguez E, Zarazaga M, Saenz Y, Brinas L, Torres C. Mechanisms of antibiotic resistance in Escherichia coli isolates obtained from healthy children in Spain. Microb Drug Resist. 2002;8(4):321–7.View ArticlePubMedGoogle Scholar
  22. Vatopoulos AC, Varvaresou E, Petridou E, Moustaki M, Kyriakopoulos M, Kapogiannis D, Sarafoglou S, Fretzagias A, Kalapothaki V. High rates of antibiotic resistance among normal fecal flora Escherichia coli isolates in children from Greece. Clin Microbiol Infect. 1998;4(10):563–9.View ArticlePubMedGoogle Scholar
  23. Kanai H, Hashimoto H, Mitsuhashi S. Drug resistance and conjugative R plasmids in fecal Escherichia coli strains isolated from healthy younger animals (chickens, piglets, calves) and children. Microbiol Immunol. 1983;27(12):1031–41.View ArticlePubMedGoogle Scholar
  24. Degener JE, Smit ACW, Michel MF. Faecal carriage of aerobic gram-negative bacilli and drug resistance of Escherichia coli in different age-groups in Dutch urban communities. J Med Microbiol. 1983;16(2):139–45.View ArticlePubMedGoogle Scholar
  25. Neu HC, Cherubin C, Vogt M, Huber P, Glazer S, Winter H. Antibiotic resistance of fecal Escherichia coli. A comparison of samples from children of low and high socioeconomic groups. Am J Dis Child. 1973;126(2):174–7.View ArticlePubMedGoogle Scholar
  26. Lidin-Janson G, Falsen E, Jodal U, Kaijser B, Lincoln K. Characteristics of antibiotic-resistant Escherichia coli in the rectum of healthy school-children. J Med Microbiol. 1976;10(3):299–308.View ArticleGoogle Scholar
  27. Zaidi MB, Zamora E, Diaz P, Tollefson L, Fedorka-Cray PJ, Headrick ML. Risk factors for fecal quinolone-resistant Escherichia coli in Mexican children. Antimicrob Agents Chemother. 2003;47(6):1999–2001.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Singh KV, Reves RR, Pickering LK, Murray BE. Comparative in vitro activities of amoxicillin-clavulanic acid, cefuroxime, cephalexin, and cephalothin against trimethoprim-resistant Escherichia coli isolated from stools of children attending day-care centers. Antimicrob Agents Chemother. 1990;34(11):2047–9.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Lester SC, Del Pilar PM, Wang F, Perez Schael I, Jiang H, O’Brien TF. The carriage of Escherichia coli resistant to antimicrobial agents by healthy children in Boston, in Caracas, Venezuela, and in Qin Pu. China New England J Med. 1990;323(5):285–9.View ArticleGoogle Scholar
  30. Feeney AR, Cooke EM, Shinebaum R. A comparative study of gram-negative aerobic bacilli in the faeces of babies born in hospital and at home. J Hyg. 1980;84(1):91–6.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Mitsuhashi N, Kaneko M. Isolation of drug-resistant bacteria from newborn infants. Tohoku J Exp Med. 1977;121(1):77–80.View ArticlePubMedGoogle Scholar
  32. Dailey KM, Sturtevant Jr AB, Feary TW. Incidence of antibiotic resistance and R factors among gram-negative bacteria isolated from the neonatal intestine. J Pediatr. 1972;80(2):198–203.View ArticlePubMedGoogle Scholar
  33. Reves RR, Fong M, Pickering LK, Bartlett IA, Alvarez M, Murray BE. Risk factors for fecal colonization with trimethoprim-resistant and multiresistant Escherichia coli among children in day-care centers in Houston, Texas. Antimicrob Agents Chemother. 1990;34(7):1429–34.View ArticlePubMedPubMed CentralGoogle Scholar
  34. Reves RR, Murray BE, Pickering LK, Prado D, Maddock M, Bartlett IAV. Children with trimethoprim- and ampicillin-resistant fecal Escherichia coli in day care centers. J Infect Dis. 1987;156(5):758–62.View ArticlePubMedGoogle Scholar
  35. Calva JJ, Sifuentes-Osornio J, Ceron C. Antimicrobial resistance in fecal flora: Longitudinal community-based surveillance of children from urban Mexico. Antimicrob Agents Chemother. 1996;40(7):1699–702.PubMedPubMed CentralGoogle Scholar
  36. Garcia PG, Silva VL, Diniz CG. Occurrence and antimicrobial drug susceptibility patterns of commensal and diarrheagenic Escherichia coli in fecal microbiota from children with and without acute diarrhea. J Microbiol. 2011;49(1):46–52.View ArticlePubMedGoogle Scholar
  37. Dyar OJ, Hoa NQ, Trung NV, Phuc HD, Larsson M, Chuc NT, Lundborg CS. High prevalence of antibiotic resistance in commensal Escherichia coli among children in rural Vietnam. BMC Infect Dis. 2012;12:92.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Riccobono E, Pallecchi L, Mantella A, Bartalesi F, Zeballos IC, Trigoso C, Villagran AL, Bartoloni A, Rossolini GM. Carriage of antibiotic-resistant Escherichia coli among healthy children and home-raised chickens: a household study in a resource-limited setting. Microb Drug Resist. 2012;18(1):83–7.View ArticlePubMedGoogle Scholar
  39. Amaya E, Reyes D, Vilchez S, Paniagua M, Mollby R, Nord CE, Weintraub A. Antibiotic resistance patterns of intestinal Escherichia coli isolates from Nicaraguan children. J Med Microbiol. 2011;60(2):216–22.View ArticlePubMedGoogle Scholar
  40. Seidman JC, Anitha KP, Kanungo R, Bourgeois AL, Coles CL. Risk factors for antibiotic-resistant E. coli in children in a rural area. Epidemiol Infect. 2009;137(6):879–88.View ArticlePubMedGoogle Scholar
  41. Djie-Maletz A, Reither K, Danour S, Anyidoho L, Saad E, Danikuu F, Ziniel P, Weitzel T, Wagner J, Bienzle U, et al. High rate of resistance to locally used antibiotics among enteric bacteria from children in Northern Ghana. J Antimicrob Chemother. 2008;61(6):1315–8.View ArticlePubMedGoogle Scholar
  42. Zhang XL, Wang F, Zhu DM, Wu S, Wu PC, Chen YD, Wang YQ, Zhou L. The carriage of Escherichia coli resistant to antibiotics in healthy populations in Shanghai. BES. 1998;11(4):314–20.PubMedGoogle Scholar
  43. Bartoloni A, Cutts F, Leoni S, Austin CC, Mantella A, Guglielmetti P, Roselli M, Salazar E, Paradisi F. Patterns of antimicrobial use and antimicrobial resistance among healthy children in bolivia. Trop Med Int Health. 1998;3(2):116–23.View ArticlePubMedGoogle Scholar
  44. Souza TB, Morais MB, Tahan S, Melli LC, Rodrigues MS, Scaletsky IC. High prevalence of antimicrobial drug-resistant diarrheagenic Escherichia coli in asymptomatic children living in an urban slum. J Infect. 2009;59(4):247–51.View ArticlePubMedGoogle Scholar
  45. Bartoloni A, Pallecchi L, Benedetti M, Fernandez C, Vallejos Y, Guzman E, Villagran AL, Mantella A, Lucchetti C, Bartalesi F, et al. Multidrug-resistant commensal Escherichia coli in children, Peru and Bolivia. Emerg Infect Dis. 2006;12(6):907–13.View ArticlePubMedPubMed CentralGoogle Scholar
  46. Pons MJ, Mosquito S, Gomesa C, Del Valle LJ, Ochoa TJ, Ruiz J. Analysis of quinolone-resistance in commensal and diarrheagenic escherichia coli isolates from infants in lima, Peru. Trans R Soc Trop Med Hyg. 2014;108(1):22–8.View ArticlePubMedGoogle Scholar
  47. Shakya P, Barrett P, Diwan V, Marothi Y, Shah H, Chhari N, Tamhankar AJ, Pathak A, Lundborg CS. Antibiotic resistance among Escherichia coli isolates from stool samples of children aged 3 to 14 years from Ujjain, India. BMC Infect Dis. 2013;13(1):477.View ArticlePubMedPubMed CentralGoogle Scholar
  48. Kristiansson C, Grape M, Gotuzzo E, Samalvides F, Chauca J, Larsson M, Bartoloni A, Pallecchi L, Kronvall G, Petzold M. Socioeconomic factors and antibiotic use in relation to antimicrobial resistance in the Amazonian area of Peru. Scand J Infect Dis. 2009;41(4):303–12.View ArticlePubMedGoogle Scholar
  49. Kalter HD, Gilman RH, Moulton LH, Cullotta AR, Cabrera L, Velapatino B. Risk factors for antibiotic-resistant Escherichia coli carriage in young children in Peru: Community-based cross-sectional prevalence study. Am J Trop Med Hyg. 2010;82(5):879–88.View ArticlePubMedPubMed CentralGoogle Scholar
  50. EUCAST: Clinical Breakpoints [http://www.eucast.org/clinical_breakpoints/]. Accessed 27 Jan 2015.
  51. Clinical Laboratory Standards Institute [http://clsi.org/about-clsi/]. Accessed 17 Dec 2014.
  52. Morgan DJ, Okeke IN, Laxminarayan R, Perencevich EN, Weisenberg S. Non-prescription antimicrobial use worldwide: a systematic review. Lancet Infect Dis. 2011;11(9):692–701.View ArticlePubMedPubMed CentralGoogle Scholar
  53. Wachter DA, Joshi MP, Rimal B. Antibiotic dispensing by drug retailers in Kathmandu, Nepal. Trop Med Int Health. 1999;4(11):782–8.View ArticlePubMedGoogle Scholar
  54. Akinyandenu O, Akinyandenu A. Irrational use and non-prescription sale of antibiotics in Nigeria, a need for change. J Sci Innov Res. 2014;3(2):251–7.Google Scholar
  55. Bin Abdulhak AA, Altannir MA, Almansor MA, Almohaya MS, Onazi AS, Marei MA, Aldossary OF, Obeidat SA, Obeidat MA, Riaz MS, et al. Non prescribed sale of antibiotics in Riyadh, Saudi Arabia: a cross sectional study. BMC Public Health. 2011;11:538.View ArticlePubMedPubMed CentralGoogle Scholar
  56. Donkor ES, Tetteh-Quarcoo PB, Nartey P, Agyeman IO. Self-medication practices with antibiotics among tertiary level students in Accra, Ghana: a cross-sectional study. Int J Environ Res Public Health. 2012;9(10):3519–29.View ArticlePubMedPubMed CentralGoogle Scholar
  57. Collington P, Athukorala PC, Senanayake S, Khan F. Antimicrobial resistance: the major contribution of poor governance and corruption to this growing problem. PLoS One. 2015;10(3):e0116746.View ArticleGoogle Scholar
  58. European Centre for Disease Prevention and Control: Antimicrobial resistance interactive database: EARS-Net. 2014.Google Scholar
  59. Centre for Disease Dynamics Economics and Policy (CDDEP) Resistance Map [http://www.cddep.org/projects/resistance-map]. Accessed 15 Dec 2014.
  60. Bryce A, Hay AD, Lane IF, Thornton HV, Wootton M, Costelloe C. Global prevalence of antibiotic resistance in paediatric urinary tract infections caused by Escherichia coli and association with routine use of antibiotics in primary care: systematic review and meta-analysis. BMJ. 2016;352:i939.View ArticlePubMedPubMed CentralGoogle Scholar
  61. World Health Organisation: Second Meeting of the Subcommittee of the Expert Committee on the Selection and Use of Essential Medicines: Tetracycline group in children. In: 2008; Geneva; 2008.Google Scholar
  62. Tadesse DA, Zhao S, Tong E, Ayers S, Singh A, Bartholomew MJ, McDermott PF. Antimicrobial drug resistance in Escherichia coli from humans and food animals, United States, 1950-2002. Emerg Infect Dis. 2012;18(5):741–9.View ArticlePubMedPubMed CentralGoogle Scholar
  63. Kirchner M, Mafura M, Hunt T, Abu-Oun M, Nunez-Garcia J, Hu Y, Weile J, Coates A, Card R, Anjum MF. Antimicrobial resistance characteristics and fitness of gram-negative fecal bacteria from volunteers treated with minocycline or amoxicillin. Front Microbiol. 2014;17(5):722.Google Scholar
  64. Lloyd DH. Reservoirs of antimicrobial resistance in pet animals. Clin Infect Dis. 2007;45(2):S148–152.View ArticlePubMedGoogle Scholar
  65. van den Bogaard AE, London N, Driessen C, Stobberingh EE. Antibiotic resistance of faecal Escherichia coli in poultry, poultry farmers and poultry slaughterers. J Antimicrob Chemother. 2001;47(6):763–71.View ArticlePubMedGoogle Scholar
  66. Cogliani C, Goossens H, Greko C. Restricting antimicrobial use in food animals: lessons from Europe. Microbe. 2011;6(6):274–9.Google Scholar
  67. Costelloe C, Metcalfe C, Lovering A, Mant D, Hay AD. Effect of antibiotic prescribing in primary care on antimicrobial resistance in individual patients: systematic review and meta-analysis. BMJ. 2010;340:c2096.View ArticlePubMedGoogle Scholar

Copyright

© The Author(s). 2016