Antimicrobial susceptibility of lower respiratory tract pathogens in Great Britain and Ireland 1999–2001 related to demographic and geographical factors: the BSAC Respiratory Resistance Surveillance Programme

Rosy Reynolds1,*, Jemma Shackcloth2, David Felmingham2 and Alasdair MacGowan1 on behalf of the BSAC Extended Working Party on Respiratory Resistance Surveillance

1 Department of Medical Microbiology, North Bristol NHS Trust, Southmead Hospital, Bristol BS10 5NB; 2 GR Micro Ltd, 7–9 William Road, London NW1 3ER, UK

Received 1 July 2003; returned 7 August 2003; revised 26 August 2003; accepted 28 August 2003


    Abstract
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Objective: The aim of this study was to assess the antimicrobial susceptibility of community-acquired lower respiratory pathogens in Great Britain and Ireland, and investigate its relationship with demographic and geographical factors using multiple logistic regression analysis.

Methods: A total of 1328 isolates of Streptococcus pneumoniae, 1894 Haemophilus influenzae and 845 Moraxella catarrhalis were collected from lower respiratory clinical specimens (primarily sputum) by 20 laboratories in Great Britain (England, Wales and Scotland) and Ireland (Northern Ireland and Eire) between 1999 and 2001.

Results: Of 1154 S. pneumoniae from Great Britain, 92–100% were susceptible to ß-lactams (only 0.2% having penicillin MICs >= 2 mg/L), 89% were susceptible to erythromycin, 93% susceptible to tetracycline, and 94–100% intermediate or susceptible to fluoroquinolones. Susceptibility to agents other than fluoroquinolones was less frequent in the 174 isolates from Ireland: ß-lactam susceptibility was 68–99% (3.4% having penicillin MICs >= 2 mg/L), erythromycin susceptibility was 78% and tetracycline susceptibility was 82%. In multivariate analysis, susceptibility in S. pneumoniae was associated with country and patient age, being most common overall in the 20–49 years age group. Of 1894 H. influenzae, 15% produced ß-lactamase and 79–100% were susceptible to ß-lactams other than cefaclor. Ninety-six per cent were intermediate and 1% susceptible to erythromycin, 97% susceptible to tetracycline, and 89% susceptible to trimethoprim. Only one isolate showed resistance to ciprofloxacin. H. influenzae from sputum were more likely to be susceptible than isolates from other sources. Of 845 M. catarrhalis, 92% produced ß-lactamase and 9% were susceptible to ampicillin, >99% were susceptible to co-amoxiclav, cefotaxime, erythromycin and fluoroquinolones.

Conclusions: Clinically relevant demographic factors predictive of susceptibility were country and patient age in S. pneumoniae, and specimen type (sputum/non-sputum) in H. influenzae. Susceptibility to most antimicrobials remains high in Ireland and very high in Great Britain.

Keywords: antibacterial, resistance epidemiology, British Isles


    Introduction
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Community-acquired lower respiratory tract infections account for a considerable proportion of morbidity and antibiotic use. Increasing resistance to some antimicrobials among the primary pathogens responsible is a cause of concern. There is a need, therefore, for surveillance of antimicrobial susceptibility in these species, both to provide early warning of emerging problematical resistances and to contribute towards understanding of the factors promoting resistance. The lack of appropriate surveillance has been highlighted as a key area to address in order to implement rational measures to tackle the resistance problem.1

Many previous surveillance studies in the UK and Ireland, of varying geographical scope and employing a variety of different methodologies, have provided snapshots of resistance at a given time. However, if meaningful conclusions and actions are to be derived from surveillance data, a long-term approach is required to track emerging resistance patterns. In the UK and Ireland, two types of international programme have so far made an attempt at long-term surveillance. The first type (e.g. SENTRY Program, Alexander Network2,3) uses central laboratory testing. Whilst providing a global overview of resistance trends, these studies are of less value from a national or regional perspective given the necessarily small number of contributing centres in each country and the consequent bias that may arise from variation in resistance patterns between regions and laboratories. The second type [e.g. the European Antimicrobial Resistance Surveillance System (EARSS),4 see www.earss.rivm.nl] uses susceptibility results obtained from diagnostic testing within individual laboratories in the reporting countries. These are able to obtain data from a larger sample of collecting centres, but the reliability of the results may be affected by variations in techniques between the various contributing laboratories. They are also limited to a rather restricted number of core antimicrobials that are common to participating laboratories, and consequently these studies do not allow for surveillance and assessment of newly licensed or developmental compounds.

The BSAC Respiratory Resistance Surveillance Programme is designed to fill the gap between the existing programmes for the UK and Ireland and provide in-depth, high-quality surveillance, allowing practical application of results at a national and regional level. The programme collects isolates from over 20 laboratories distributed across the UK and Ireland, and uses central testing to ensure consistency of technique. It tests a wide range of antimicrobials, including recently developed and investigational compounds. The programme began in 1999, is ongoing and is intended to continue long term. The results reported here for the first 2 years of the study will provide a reference baseline for comparison with future developments. Comparison between this and the international surveillance programmes will also be of interest, and will assist our understanding of whether, and to what extent, the limitations of each type of study really affect the reliability of the results obtained.

A secondary objective of the BSAC Respiratory Resistance Surveillance Programme is to investigate the relationship between resistance patterns and demographic and other factors. Other studies in various countries have reported various such relationships. The most commonly noted association is a higher frequency of penicillin-non-susceptibility in the Streptococcus pneumoniae infecting514 or colonizing1517 children, especially young children. However, these studies have often included a range of infections (upper and lower respiratory tract, middle ear and invasive infections) and they have not generally used the multivariate methods required to separate the effects of different infections and other possible explanatory factors. By collecting large numbers of isolates from only one type of infection (lower respiratory tract), and collecting information on several other possible explanatory variables in addition to age, the BSAC study is better able to assess the relationship between susceptibility and these factors.


    Methods
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Isolates

Twenty clinical laboratories in the UK and Eire were selected to give wide geographical coverage, serving urban and rural areas with a range of social deprivation scores, attached to hospitals of varying sizes, and taking varying proportions of their workload from general (non-hospital) practice. Each was asked to collect up to 50 consecutive isolates of Haemophilus influenzae and S. pneumoniae, and up to 25 consecutive isolates of Moraxella catarrhalis in each of the winters (October to April) of 1999–2000 and 2000–2001. The isolates were from lower respiratory sources of patients with presumed community-acquired infection, routinely referred for clinical testing. Repeat isolates taken within 2 weeks of a previous isolate from the same patient were excluded, as were isolates from patients with cystic fibrosis and isolates from patients who had been in hospital for more than 48 h.

Isolates were sent in Carey-Blair transport medium (Technical Service Consultants Ltd, Heywood, UK) to a central laboratory (GR Micro Ltd, London, UK) for all further testing. The identity of isolates was confirmed by colony morphology, Gram’s stain and biochemical tests as follows.

S. pneumoniae: Gram-positive diplococci, growing as {alpha}-haemolytic sometimes umbonate or mucoid colonies on horse blood agar. Catalase negative, optochin susceptible and bile soluble.

H. influenzae: Gram-negative coccobacilli, requiring a combination of haematin and nicotinamide adenine dinucleotide (NAD) when grown on a non-supplemented medium.

M. catarrhalis: Gram-negative diplococci, producing whitish/grey colonies on horse blood agar. Oxidase positive, butyrate esterase positive.

Isolates were stored frozen at –70°C, on beads (Microbank Storage System; ProLab Diagnostics, Neston, UK) in the collecting laboratories and in horse serum at the central laboratory.

Antimicrobial susceptibility testing

MICs were measured by the BSAC agar dilution method18 as defined at the time using the media, supplements and incubation conditions defined for the BSAC standardized disc method.19 The repeatability of this method has been established20 and, apart from the inoculum size for M. catarrhalis, it equates to the most recently published version of the BSAC agar dilution method.21,22 The inoculum size was 104 cfu except in the case of M. catarrhalis with ampicillin and co-amoxiclav, for which we used 106 cfu in accordance with the revised method.22 Co-amoxiclav was tested in a 2:1 ratio. IsoSensitest agar (Oxoid Ltd, Basingstoke, UK) was supplemented with 5% defibrinated whole horse blood (TCS Biosciences Ltd, Buckingham, UK) and, for H. influenzae only, 20 mg/L NAD. The incubation atmosphere was air for M. catarrhalis and air plus 4–6% CO2 for H. influenzae and S. pneumoniae.

The following reference strains were included: H. influenzae ATCC 49247 and ATCC 49766 for H. influenzae; S. pneumoniae ATCC 49619 for S. pneumoniae; and Staphylococcus aureus ATCC 29213 for M. catarrhalis.

ß-Lactamase production in H. influenzae and M. catarrhalis was assessed by testing with nitrocefin (Oxoid Ltd).

Sigma Chemical Co. (St Louis, MO, USA) supplied amoxicillin, ampicillin, cefaclor, cefotaxime, cefuroxime, clindamycin, erythromycin, penicillin, tetracycline, trimethoprim and NAD. Bayer (Newbury, UK) supplied ciprofloxacin and moxifloxacin. Aventis Pharma (formerly Hoechst-Marion-Roussel, West Malling, UK) supplied levofloxacin. GlaxoSmithKline (formerly SmithKline Beecham, Uxbridge, UK) supplied clavulanic acid.

Statistical methods

Logistic regression was used to identify factors associated with susceptibility. The following factors were considered: antibiotic, collection season (1999–2000 or 2000–2001), collection month, country (England/Wales/Scotland/Northern Ireland/Eire), specimen type (sputum/non-sputum), care setting (general practice/inpatient/other), patient age, patient sex and, for H. influenzae only, ß-lactamase production. For this purpose, S. pneumoniae not resistant to ciprofloxacin (MIC <= 2 mg/L) were treated as susceptible.

Median age values (62, 60 and 66 years, respectively) were allocated to three S. pneumoniae, three H. influenzae and three M. catarrhalis with missing age data. The modal sex (male) was allocated to three H. influenzae and two S. pneumoniae with missing sex data. One S. pneumoniae isolate was assigned to the modal (inpatient) group for care setting.

Three separate analyses were performed, one for each species.

As each isolate was tested against a series of antibiotics, each isolate record initially included multiple outcomes (susceptible/not susceptible for each antibiotic). For the purpose of logistic regression modelling, the data were transposed to give a separate record for each antibiotic–isolate combination, with a single outcome (susceptible/not susceptible) for each record. As there were then multiple records per isolate, the observations could not be assumed to be independent, so the standard errors were adjusted to allow for clustering. Each model was built in stages using the forward stepwise modelling scheme suggested by Collett.23 A 5% significance level was used for inclusion/exclusion of factors (instead of the conventional 10%) in order to reduce the chance of spurious findings arising from the large number of observations included in the analyses. Interactions among variables were examined and retained if significant at the 1% level. Goodness of fit was assessed using the Hosmer–Lemeshow test.24,25 Logistic regression analyses were performed in the statistical software package Stata, release 7.0 (Stata Corporation, College Station, TX, USA).

Associations between pairs of categorical variables were assessed using {chi}2 tests or Fisher’s exact tests as appropriate. For S. pneumoniae, 10 tests were performed to test for associations between resistance to five different antimicrobials in all possible pairwise combinations. A Bonferroni correction was applied to the P values for these tests to allow for multiple testing.

95% Confidence intervals for percentages were calculated by the exact binomial method.

All results presented are based on data from all 4067 isolates (n = 4067) unless otherwise stated.


    Results
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Demographics and collecting laboratory characteristics

The 20 contributing laboratories are listed in the Acknowledgements. They were sited in local authority areas with populations ranging from 92 000 to 961 000 and in health authority areas with populations ranging from 335 000 to 961 000. The percentage of their total workload attributable to general practice ranged from 10% to 50%. Deprivation scores (UPA scores26) were available for the 14 laboratories in England and Wales: they ranged from –0.4 to 62.2 for the related local authorities and from –19.0 to 62.2 for the health authority areas. Scatter plots showed no suggestion of a relationship between UPA scores and percentage susceptibility to penicillin, tetracycline or erythromycin in S. pneumoniae or percentage ß-lactamase production in H. influenzae in these 14 centres.

In all, 1328 isolates of S. pneumoniae, 1894 of H. influenzae and 845 of M. catarrhalis were collected between July 1999 and May 2001. Of the total of 4067 isolates, 138 were collected outside the planned winter collection seasons but were included in the analysis as there was no reason to suspect a different pattern of susceptibility in them.

Male patients contributed 60% (n = 1326), 55% (n = 1891) and 54% (n = 845) of S. pneumoniae, H. influenzae and M. catarrhalis isolates, respectively.

The proportion of isolates obtained from sputum was similar for the three species, ranging from 89% to 91%. The remainder were from other lower respiratory specimens.

The majority of isolates (2187, 54%), were obtained from patients in hospital, admitted less than 48 h earlier. Patients from general practice contributed 1718 isolates (42%), and the remaining 161 isolates (4%) came from outpatients (104), nursing home residents (51) and other care settings (six). There was strong evidence of an association between care setting (general practice/inpatient/other) and species [{chi}2(4) = 26.25, P < 0.0001, n = 4066]. Thirty-nine per cent of S. pneumoniae isolates were obtained from general practice, compared with 45% of H. influenzae and 41% of M. catarrhalis isolates.

Patient age was known for 4058 isolates. There were 419 (10%), 777 (19%), 1512 (37%) and 1350 (33%) patients in the age groups 0–19, 20–49, 50–69 and >=70 years, respectively. Infants up to the age of 2 years made up nearly half of the 0–19 age group: 114 were under the age of 1 year, 69 were 1 year old and 23 were 2 years old. The remaining 213 patients aged 3–19 years were roughly evenly distributed across the ages, with an average of 12.5 from each year group. There was strong evidence of an association between species and age group [{chi}2(6) = 54.07, P < 0.0001, n = 4058]. Thirty-three per cent of S. pneumoniae isolates came from patients aged >=70 years, compared with 29% of H. influenzae isolates and 42% of M. catarrhalis isolates.

MICs and categorical susceptibility to antimicrobial agents

Tables 13 summarize the MIC range, MIC50, MIC90 and percentage of isolates with full or intermediate susceptibility using current BSAC breakpoints27,28 for the three species in Ireland (Northern Ireland and Eire) and in the three countries of Great Britain (England, Scotland and Wales). The results for Northern Ireland and Eire are pooled in these tables to avoid identifying results from any single laboratory.


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Table 1. Per cent susceptible (intermediate) with 95% confidence limits (CLs) and MIC summary values (mg/L) for 1328 S. pneumoniae isolates 1999–2001
 

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Table 3. Per cent susceptible (intermediate) with 95% confidence limits (CLs) and MIC summary values (mg/L) for 845 M. catarrhalis isolates 1999–2001 
 
S. pneumoniae were almost universally susceptible to cefotaxime, moxifloxacin and levofloxacin, and universally resistant to trimethoprim. Percentage susceptibility varied with location for other ß-lactams, erythromycin and clindamycin and tetracycline. Depending on the particular antimicrobial, 89–99% of isolates from Great Britain were susceptible, compared with 68–95% of isolates from Ireland. The difference between Great Britain and Ireland was also apparent in the MIC90s for these agents. Among isolates from Ireland (compared with those from Great Britain), MIC90s were 5–6 doubling dilutions higher for all the ß-lactams tested including cefotaxime, at least 3 doubling dilutions higher for erythromycin and clindamycin, and 6 doubling dilutions higher for tetracycline.

Fifteen per cent of the H. influenzae isolates produced ß-lactamase [95% confidence interval (CI) 13.6–16.9%]. Only 4% were susceptible to cefaclor, but susceptibility to other ß-lactams ranged from 79% (amoxicillin) to 100% (cefotaxime). Ninety-six per cent were intermediate to erythromycin, and 97% susceptible to tetracycline. Susceptibility to fluoroquinolones was practically universal in H. influenzae, with just one isolate showing resistance to ciprofloxacin.

Ninety-two per cent of M. catarrhalis produced ß-lactamase (95% CI 90.0–93.8%) and so only 9% were susceptible to ampicillin. An apparent 44% susceptibility to amoxicillin resulted from the use of the 104 cfu inoculum (now superseded);22 among a subset of isolates tested with an inoculum of 106 cfu, susceptibility to amoxicillin and ampicillin was closely comparable. M. catarrhalis were also non-susceptible to trimethoprim, but percentage susceptibility to other agents was high: 67% were susceptible to cefaclor, 89% susceptible to cefuroxime and >99% susceptible to all other antimicrobials tested.

Factors associated with susceptibility, identified by logistic regression analysis

S. pneumoniae. Amoxicillin, cefotaxime, levofloxacin, moxifloxacin and trimethoprim could not be included in the logistic regression analysis as there was insufficient balance in the number of isolates susceptible and not susceptible. For example, the vast majority of isolates were susceptible to the first four agents, so there were too few non-susceptible isolates to compare them with. The seven antibiotics included were penicillin, cefaclor, cefuroxime, erythromycin, clindamycin, ciprofloxacin and tetracycline. [S. pneumoniae not resistant to ciprofloxacin (MIC <= 2 mg/L) were treated as susceptible in this analysis.]

In initial univariate analysis, only antimicrobial, patient age, care setting (general practice/inpatient/other) and country had a significant association with susceptibility of S. pneumoniae. In the case of age, the relationship was of quadratic form, with susceptibility less likely in isolates from both younger and older patients. For ease of interpretation, patient age was divided into four categories (<20/20–49/50–69/>=70 years) and age was fitted as a categorical variable in subsequent models. Figure 1 illustrates the susceptibility of S. pneumoniae to penicillin, erythromycin, tetracycline and ciprofloxacin for these age groups. In the case of care setting, isolates from general practice were more likely to be susceptible than those from hospital inpatients (odds ratio 1.66, 95% CI 1.25–2.21).



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Figure 1. Percentage of susceptible (intermediate for ciprofloxacin, as there is no susceptible category) isolates according to age group in S. pneumoniae. The breakpoints used are shown in the key.

 
Details of the final multivariate model are shown in Table 4. The model contained the variables antimicrobial, country and patient age, with an interaction between antimicrobial and country indicating that the effect of country was not the same for all antimicrobials. There was no evidence to suggest a lack of model fit [Hosmer–Lemeshow test {chi}2(8) = 8.06, P = 0.43]. For any given age group, isolates from Scotland, Wales and Northern Ireland showed no difference in susceptibility to any of the agents considered when compared with isolates from England. However, for all agents considered except ciprofloxacin, isolates from Eire were less likely to be susceptible than were those from England. For any given country and antibiotic, isolates from patients aged 20–49 years were more likely to be susceptible than those from patients aged 50–69 years.


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Table 4. Multiple logistic regression model for S. pneumoniae: coefficients and 95% CIs
 
H. influenzae. Cefotaxime, erythromycin, ciprofloxacin, levofloxacin and moxifloxacin could not be included in this analysis as there was insufficient balance in the number of isolates susceptible and not susceptible. The seven antibiotics included were ampicillin, amoxicillin, co-amoxiclav, cefaclor, cefuroxime, tetracycline and trimethoprim.

Unlike S. pneumoniae, H. influenzae showed no association between susceptibility of isolates and age or care setting of patients, and although country was just significant in univariate analysis (P = 0.03), it was not required in the multivariate model.

Table 5 gives details of the final multivariate model. It contained the variables antimicrobial, year, ß-lactamase status and source of specimen (sputum/other), with antibiotic–year and antibiotic–ß-lactamase interactions. There was no evidence to suggest a lack of model fit [Hosmer–Lemeshow test: {chi}2(8) = 3.48, P = 0.90].


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Table 5. Multiple logistic regression model for H. influenzae: coefficients and 95% CIs
 
According to the model, for any given combination of antibiotic, year and ß-lactamase status, isolates from a sputum sample were more likely to be susceptible than those from a non-sputum sample (odds ratio 1.53, 95% CI 1.11–2.09). The effect of year differed for the different antibiotics, as did the effect of ß-lactamase. To illustrate the interaction between antimicrobial and year, estimates and 99% CIs for the differences between the effects of years 1999/2000 and 2000/2001 were calculated for each antibiotic. These estimates were calculated for a ß-lactamase-negative isolate obtained from sputum (i.e. the values of the other two factors in the model were fixed at their modal values for the purpose of this calculation). There was no evidence of difference between the two years in isolates’ susceptibility to amoxicillin, ampicillin, cefuroxime, tetracycline or trimethoprim. There was some evidence in the model suggesting greater susceptibility to co-amoxiclav and cefaclor in 2000/2001 compared with 1999/2000, but we have doubts about the reliability of this evidence. In particular, we suspect a technical source for the apparent difference in cefaclor susceptibility, as there was a wholesale shift of 1 doubling dilution in the MIC distribution between the two years. To illustrate the interaction between antimicrobial and ß-lactamase, estimates and 99% CIs for the differences between the effects of presence and absence of ß-lactamase were calculated for each antibiotic, based on an isolate obtained from sputum in 2000–2001. There was evidence to suggest lower percentage susceptibility to amoxicillin, ampicillin and tetracycline, and slightly higher percentage susceptibility to co-amoxiclav in ß-lactamase-positive isolates compared with ß-lactamase-negative isolates. There was no evidence of difference in the susceptibility to cefaclor or trimethoprim between ß-lactamase-positive and -negative isolates, and it was not possible to estimate the effect of ß-lactamase on cefuroxime due to collinearity in the model.

M. catarrhalis. Statistical modelling proved unprofitable and was abandoned. Only four agents (amoxicillin, ampicillin, cefaclor and cefuroxime) could be included in the analysis and two of these (cefaclor and cefuroxime) had been tested at the now-superseded inoculum of 104 cfu. Factors appearing significant in univariate analysis could not be interpreted in a clinically meaningful way, and multiple interaction terms made multivariate models unstable.

Multiple and linked resistances in S. pneumoniae (n = 1328)

Penicillin, amoxicillin, tetracycline, erythromycin and ciprofloxacin were considered in the analysis of multiple and linked resistance. Isolates intermediate to penicillin were counted as resistant for this purpose. The resistance rates in S. pneumoniae were 10.5, 1.3, 8.4, 12.3 and 5.3% for penicillin, amoxicillin, tetracycline, erythromycin and ciprofloxacin, respectively.

All 17 amoxicillin-resistant isolates (1.3%) were non-susceptible to penicillin, and 123 isolates (9.3%) were resistant to two or more unrelated antimicrobials. The most common double non-susceptibilities were to tetracycline/erythromycin (6.1%), penicillin/tetracycline (5.3%) and penicillin/erythromycin (5.2%). No other particular double resistances occurred in more than 1% of isolates. Fifty-five isolates (4.1%) were resistant to three or more unrelated antimicrobials, the great majority of them (51, 3.8%) being non-susceptible to penicillin, tetracycline and erythromycin. Of these, eight were resistant to amoxicillin and two others were resistant to ciprofloxacin. In addition, three isolates (0.2%) were resistant to penicillin, erythromycin and ciprofloxacin (but not tetracycline), one of which was also resistant to amoxicillin. One further isolate (0.1%) was resistant to tetracycline, erythromycin and ciprofloxacin (but susceptible to penicillin and amoxicillin). No isolate was resistant to amoxicillin, tetracycline, erythromycin and ciprofloxacin.

There was no evidence of association between ciprofloxacin resistance and any of the other resistances (adjusted P value >0.99 in every case). Resistance to the other four antibiotics showed positive associations in all possible pairwise combinations (adjusted P value <0.0001 in every case).


    Discussion
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Antimicrobial resistance surveillance has a central role in all well-designed strategies to manage the problem of antibiotic resistance. Surveillance is required to determine the size of resistance problems, ascertain trends over time, perhaps allow for the detection of previously unknown resistances, determine risk factors and inform clinical practice.1,29 As such, surveillance is an instrument, and surveillance on its own is unlikely to produce benefits in terms of clinical patient care or the wider public health: indeed recently it has been suggested there is too much emphasis on surveillance.30 Clearly, then, all resistance surveillance programmes need a justification in terms of both purpose and methodology employed.

There are many factors that determine surveillance study design, and to some degree all surveillance programmes are a compromise between that which is desirable and that which is achievable and practical. All commonly employed methods depend on phenotypic detection of resistance, though genotypic detection is now also used. Standard methodologies with use of appropriate clinical or epidemiological breakpoints ensure the most robust data, and use of centralized laboratory testing ensures optimal reproducibility while minimizing the need for external quality control. Importantly, early communication of results helps to inform clinical and public health interventions.31 An important criticism of community respiratory tract surveillance data based on specimens sent to diagnostic laboratories is the lack of good-quality denominator data. This is in part due to the difficulty in getting routine specimens from some patients, for example those with pneumonia and acute sinusitis, and secondly the bias that may be present in the patients selected for routine culture of specimens.32,33 Initial data suggested an overestimation of resistance in the community, especially in respiratory tract specimens, and there is now much ongoing research into this issue. However, at present there is little alternative to the use of isolates from routine laboratory specimens.

The BSAC resistance surveillance programme for respiratory pathogens seeks to add new and robust information on resistance in S. pneumoniae, H. influenzae and M. catarrhalis. As it uses BSAC MIC methodology and breakpoints, the information should be consistent with larger and as yet unpublished databases resultant from passive routine surveillance conducted by regular downloads of laboratory test data.34 The study design used here allowed centralized laboratory testing with the advantages of speed and reliability of testing combined with a network of laboratories representing areas with a wide range of deprivation scores. As expected, given the higher incidence of chronic obstructive pulmonary diseases in men,35 males contributed more isolates than females. S. pneumoniae was more associated with patients in hospitals with community-acquired infection, perhaps related to its greater pathogenicity compared with non-capsulate H. influenzae, most of which are serum sensitive. Also as expected, relatively more isolates were provided by the young and old, and this follows the age-specific requesting rates for microbiology requests (A. Lovering, personal communication). This in turn may reflect the incidence of more severe disease or increased use of antibiotics in these age groups. The influence of other patient factors such as smoking history could not be investigated, as this information is not available in routine laboratory practice.

This study is the largest conducted in the UK and Eire in recent years.36 Penicillin susceptibility (MIC <= 0.06 mg/L) in S. pneumoniae was 89.5% overall, with 92.8% susceptible in Great Britain and 67.8% in Ireland. The prevalence of clinically relevant penicillin resistance (MIC > 2 mg/L37) in S. pneumoniae related to pulmonary infection remained low, at 0.3% overall. The high rate of penicillin susceptibility found is similar to that reported in the EARSS programme (n = 554, S. pneumoniae from bacteraemia; www.earss.rivm.nl) and that reported in the late 1990s in the Nearchus programmes using isolates from respiratory samples.36 Lower rates of penicillin resistance were reported in the early 1990s.38 The penicillin susceptibility rates reported here are similar to those in a smaller study performed in 1999/2000 and 2000/2001, in which 86% and 92% of pneumococci from the UK were penicillin susceptible (MIC <= 0.06 mg/L, n = 91 in both seasons; data online at www.protekt.org). Although we detected no change in penicillin susceptibility between the two years studied, this is too short a time for trend analysis. However, there seems to be no noteworthy increase in penicillin non-susceptibility in recent years, and clinically important penicillin resistance likely to affect therapeutic outcomes is rare.37

A significant difference between the UK and Eire in penicillin non-susceptibility (MIC > 0.06 mg/L) of S. pneumoniae, as seen here, has been noted in other recent comparisons,39,40 but may date back much earlier.38 The reasons for these differences are unclear and are not associated with markedly different total outpatient antibiotic use in the two countries.41

Erythromycin resistance among S. pneumoniae in the UK and Eire has recently been reported, in a series of small studies, to be in the range 12–18%. These studies include those with data available online at www.earss.rivm.nl and www.protekt.org, and that by Schito.39 Our study with much larger numbers confirms this with an erythromycin resistance rate of 12.3% overall.

In 1992–1993 the prevalence of ß-lactamase production in community-acquired H. influenzae from respiratory samples in two UK centres was 6–7%.38 More recent data based on a large sample size has indicated ß-lactamase production to be in the range of 16–18%.36,39 In this collection, 15.2% (95% CI 13.6–16.9%) of H. influenzae produced ß-lactamases, similar to other studies performed in the mid to late 1990s. The poor utility of cefaclor and uncertain role of erythromycin in the management of H. influenzae was highlighted in this study by the use of BSAC rather than NCCLS breakpoints.36

Ninety-two per cent (95% CI 90.0–93.8%) of M. catarrhalis isolates produced ß-lactamase, and while this is higher than the percentage reported 10 years ago,38 it is in keeping with other reported studies (www.protekt.org) using strains collected in 1999–2000.

Many other important resistances had prevalence rates under 10%, for example cefotaxime resistance in S. pneumoniae (0.2%), tetracycline resistance in S. pneumoniae (8.4%) and fluoroquinolone resistance in H. influenzae (<=0.5%). As yet, resistance to moxifloxacin and levofloxacin in S. pneumoniae isolated in Great Britain and Ireland does not appear to be a problem, unlike the situation in Hong Kong.42 In keeping with the general low rates of resistance, strains with multiple resistances were also uncommon.

The reduced susceptibility of S. pneumoniae strains from the young and old has been noted previously and associated with prior antibiotic exposure and children’s attendance at day-care facilities.43 Prior antibiotic exposure also seems a likely explanation for the increased frequency of resistance with age, and the finding that care settings such as hospital inpatients and outpatients and nursing home residents were also associated with an increased risk of resistance supports this suggestion.

In conclusion, this study adds to our understanding of antibiotic resistance in respiratory pathogens by allowing the monitoring of trends, defining risk groups where resistance is greatest and providing data that are informative to clinical practices. As such, it contributes positively to the requirements for surveillance of the UK Antimicrobial Resistance Strategy and Action Plan.1

Isolates from the BSAC Respiratory Resistance Surveillance Programme can be made available to other workers wishing to investigate mechanisms of resistance and possible explanations for the associations seen between susceptibility and demographic factors. Investigators can also access and analyse the data in detail through the BSAC website at www.bsac.org.uk.


    Acknowledgements
 
Collecting laboratories: England: City Hospital, Birmingham; Southmead Hospital, Bristol; Addenbrooke’s Hospital, Cambridge; St James’s University Hospital, Leeds; Royal Infirmary, Leicester; University of Liverpool; St Bartholomew’s and Royal London School of Medicine and Dentistry, London; University College Hospital, London; Royal Victoria Infirmary, Newcastle upon Tyne; Derriford Hospital, Plymouth; Hope Hospital, Salford; Southampton General Hospital, Southampton; Ireland: The Royal Hospitals, Belfast; Meath Adelaide and Children’s Hospital, Dublin; University College Hospital, Galway; Scotland: Royal Infirmary, Aberdeen; Western General Hospital, Edinburgh; Southern General Hospital, Glasgow; Wales: University Hospital of Wales, Cardiff; Wrexham Maelor Hospital, Wrexham.

Members of the Working Party and contributors: Working Party members, June 2003: A. P. MacGowan (Chair) (Department of Medical Microbiology, North Bristol NHS Trust), J. Booth (Bayer Pharmaceuticals, Slough), D. F. J. Brown (Addenbrookes Hospital, Cambridge), S. Coles (Abbott Laboratories Ltd, Maidenhead), D. Felmingham (GR Micro Ltd, London), I. Harding (Micron Research Limited, Wisbech), D. M. Livermore (Health Protection Agency, London), V. Reed (Micron Research Limited, Wisbech), R. A. Reynolds (Department of Medical Microbiology, North Bristol NHS Trust), J. Shackcloth (GR Micro Ltd, London), D. Lofland (GeneSoft Pharmaceuticals, San Francisco, CA, USA), C. Thomson (Bayer Pharmaceuticals, Slough), A. White (GlaxoSmithKline, Harlow), R. Wise (City Hospital, Birmingham); statistical advice and logistic regression analysis: K. Parry (Research and Development Support Unit, North Bristol NHS Trust); scientific services management: M. Robbins (GR Micro Ltd, London).

Supporters and sponsors: the BSAC Respiratory Resistance Surveillance Programme 1999/2001 was supported by the British Society for Antimicrobial Chemotherapy and sponsored by Abbott Laboratories Ltd, Aventis Pharma Ltd, Bayer Pharmaceuticals, and GlaxoSmithKline. The Research and Development Support Unit at North Bristol NHS Trust is supported by a grant from the Department of Health and Social Care (South).


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Table 2. Per cent susceptible (intermediate) with 95% confidence limits (CLs) and MIC summary values (mg/L) for 1894 H. influenzae isolates 1999–2001
 

    Footnotes
 
* Corresponding author. Tel: +44-117-959-4080; Fax: +44-117-959-3154; E-mail: rosy.reynolds{at}btinternet.com Back


    References
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
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