Berit Muller-Pebody

Detection of the plasmid-mediated mcr-1 gene conferring colistin resistance in human and food isolates of Salmonella enterica and Escherichia coli in England and Wales

OBJECTIVES In response to the first report of transmissible colistin resistance mediated by the mcr-1 gene in Escherichia coli and Klebsiella spp. from animals and humans in China, we sought to determine its presence in Enterobacteriaceae isolated in the UK. METHODS The PHE archive of whole-genome sequences of isolates from surveillance collections, submissions to reference services and research projects was retrospectively analysed for the presence of mcr-1 using Genefinder. The genetic environment of the gene was also analysed. RESULTS Rapid screening of the genomes of ∼24 000 Salmonella enterica, E. coli, Klebsiella spp., Enterobacter spp., Campylobacter spp. and Shigella spp. isolated from food or humans identified 15 mcr-1-positive isolates. These comprised: 10 human S. enterica isolates submitted between 2012 and 2015 (8 Salmonella Typhimurium, 1 Salmonella Paratyphi B var Java and 1 Salmonella Virchow) from 10 patients; 3 isolates of E. coli from 2 patients; and 2 isolates of Salmonella Paratyphi B var Java from poultry meat imported from the EU. The mcr-1 gene was located on diverse plasmids belonging to the IncHI2, IncI2 and IncX4 replicon types and its association with ISApl1 varied. Six mcr-1-positive S. enterica isolates were from patients who had recently travelled to Asia. CONCLUSIONS Analysis of WGS data allowed rapid confirmation of the presence of the plasmid-mediated colistin resistance gene mcr-1 in diverse genetic environments and plasmids. It has been present in E. coli and Salmonella spp. harboured by humans in England and Wales since at least 2012.

Empirical treatment of neonatal sepsis: are the current guidelines adequate?

Objectives To use national laboratory surveillance data to determine whether pathogens responsible for neonatal bacteraemia were sensitive to nationally recommended antibiotic regimens. Design All reports of neonatal bacteraemia received by the Health Protection Agencys voluntary surveillance scheme in England and Wales from January 2006 until March 2008, were extracted from the database. Organisms were ranked by frequency, and proportions susceptible to antimicrobials recommended for empirical treatment of neonatal sepsis were determined. Results There were 1516 reports of bacteraemia for neonates <48 h old (early-onset) and 3482 reports for neonates 2–28 days old (late-onset). For early-onset bacteraemia, group B streptococcus (GBS) was the most frequent pathogen (31%) followed by coagulase-negative staphylococci (CoNS; 22%), non-pyogenic streptococci (9%) and Escherichia coli (9%). For late-onset bacteraemia, CoNS were isolated most frequently (45%), followed by Staphylococcus aureus (13%), Enterobacteriaceae (9%), E coli (7%) and GBS (7%). More than 94% of organisms (early-onset) were susceptible to regimens involving combinations of penicillin with either gentamicin or amoxicillin, amoxicillin combined with cefotaxime or cefotaxime monotherapy. More than 95% of organisms (late-onset) were susceptible to gentamicin with either flucloxacillin or amoxicillin and amoxicillin with cefotaxime, but only 79% were susceptible to cefotaxime monotherapy. Conclusions Current guidelines for empirical therapy in neonates with sepsis are appropriate. However, gentamicin-based regimens should be used in preference to cefotaxime-based treatments, because of lower levels of susceptibility to cefotaxime and the need to avoid exerting selective pressure for resistance. Surveillance data linked to clinical data should further inform rational antibiotic prescribing in neonatal units.

Incidence, Etiology, and Outcome of Bacterial Meningitis in Infants Aged <90 Days in the United Kingdom and Republic of Ireland: Prospective, Enhanced, National Population-Based Surveillance

BACKGROUND Bacterial meningitis remains a major cause of morbidity and mortality in young infants. Understanding the epidemiology and burden of disease is important. METHODS Prospective, enhanced, national population-based active surveillance was undertaken to determine the incidence, etiology, and outcome of bacterial meningitis in infants aged <90 days in the United Kingdom and Ireland. RESULTS During July 2010-July 2011, 364 cases were identified (annual incidence, 0.38/1000 live births; 95% confidence interval [CI], .35-.42). In England and Wales, the incidence of confirmed neonatal bacterial meningitis was 0.21 (n = 167; 95% CI, .18-.25). A total of 302 bacteria were isolated in 298 (82%) of the cases. The pathogens responsible varied by route of admission, gestation at birth, and age at infection. Group B Streptococcus (GBS) (150/302 [50%]; incidence, 0.16/1000 live births; 95% CI, .13-.18) and Escherichia coli (41/302 [14%]; incidence, 0.04/1000; 95% CI, .03-.06) were responsible for approximately two-thirds of identified bacteria. Pneumococcal (28/302 [9%]) and meningococcal (23/302 [8%]) meningitis were rare in the first month, whereas Listeria meningitis was seen only in the first month of life (11/302 [4%]). In hospitalized preterm infants, the etiology of both early- and late-onset meningitis was more varied. Overall case fatality was 8% (25/329) and was higher for pneumococcal meningitis (5/26 [19%]) than GBS meningitis (7/135 [5%]; P = .04) and for preterm (15/90 [17%]) compared with term (10/235 [4%]; P = .0002) infants. CONCLUSIONS The incidence of bacterial meningitis in young infants remains unchanged since the 1980s and is associated with significant case fatality. Prevention strategies and guidelines to improve the early management of cases should be prioritized.

Evaluating bias due to data linkage error in electronic healthcare records

BackgroundLinkage of electronic healthcare records is becoming increasingly important for research purposes. However, linkage error due to mis-recorded or missing identifiers can lead to biased results. We evaluated the impact of linkage error on estimated infection rates using two different methods for classifying links: highest-weight (HW) classification using probabilistic match weights and prior-informed imputation (PII) using match probabilities.MethodsA gold-standard dataset was created through deterministic linkage of unique identifiers in admission data from two hospitals and infection data recorded at the hospital laboratories (original data). Unique identifiers were then removed and data were re-linked by date of birth, sex and Soundex using two classification methods: i) HW classification - accepting the candidate record with the highest weight exceeding a threshold and ii) PII–imputing values from a match probability distribution. To evaluate methods for linking data with different error rates, non-random error and different match rates, we generated simulation data. Each set of simulated files was linked using both classification methods. Infection rates in the linked data were compared with those in the gold-standard data.ResultsIn the original gold-standard data, 1496/20924 admissions linked to an infection. In the linked original data, PII provided least biased results: 1481 and 1457 infections (upper/lower thresholds) compared with 1316 and 1287 (HW upper/lower thresholds). In the simulated data, substantial bias (up to 112%) was introduced when linkage error varied by hospital. Bias was also greater when the match rate was low or the identifier error rate was high and in these cases, PII performed better than HW classification at reducing bias due to false-matches.ConclusionsThis study highlights the importance of evaluating the potential impact of linkage error on results. PII can help incorporate linkage uncertainty into analysis and reduce bias due to linkage error, without requiring identifiers.

Linkage, evaluation and analysis of national electronic healthcare data: application to providing enhanced blood-stream infection surveillance in paediatric intensive care.

Background Linkage of risk-factor data for blood-stream infection (BSI) in paediatric intensive care (PICU) with bacteraemia surveillance data to monitor risk-adjusted infection rates in PICU is complicated by a lack of unique identifiers and under-ascertainment in the national surveillance system. We linked, evaluated and performed preliminary analyses on these data to provide a practical guide on the steps required to handle linkage of such complex data sources. Methods Data on PICU admissions in England and Wales for 2003-2010 were extracted from the Paediatric Intensive Care Audit Network. Records of all positive isolates from blood cultures taken for children <16 years and captured by the national voluntary laboratory surveillance system for 2003-2010 were extracted from the Public Health England database, LabBase2. “Gold-standard” datasets with unique identifiers were obtained directly from three laboratories, containing microbiology reports that were eligible for submission to LabBase2 (defined as “clinically significant” by laboratory microbiologists). Reports in the gold-standard datasets were compared to those in LabBase2 to estimate ascertainment in LabBase2. Linkage evaluated by comparing results from two classification methods (highest-weight classification of match weights and prior-informed imputation using match probabilities) with linked records in the gold-standard data. BSI rate was estimated as the proportion of admissions associated with at least one BSI. Results Reporting gaps were identified in 548/2596 lab-months of LabBase2. Ascertainment of clinically significant BSI in the remaining months was approximately 80-95%. Prior-informed imputation provided the least biased estimate of BSI rate (5.8% of admissions). Adjusting for ascertainment, the estimated BSI rate was 6.1-7.3%. Conclusion Linkage of PICU admission data with national BSI surveillance provides the opportunity for enhanced surveillance but analyses based on these data need to take account of biases due to ascertainment and linkage error. This study provides a generalisable guide for linkage, evaluation and analysis of complex electronic healthcare data.

The changing aetiology of paediatric bacteraemia in England and Wales, 1998-2007

Bacteraemia in children is a potentially life-threatening condition. The objective of this study was to determine trends in the aetiology of bacteraemia in children aged 1 month-15 years in England and Wales by collecting data voluntarily reported by National Health Service hospital microbiology laboratories. Over the 10-year period 1998-2007, a total of 51 788 bacteraemia cases involving 105 genera/species of bacteria were reported. Total annual reports of bacteraemia increased from 4125 to 6916, with a mean increase of 6.5 % per year (95 % CI: 1.3-12.1 %). In 2007, just over half the cases were accounted for by four groups of organisms: coagulase-negative staphylococci (28 %), Staphylococcus aureus (10 %), non-pyogenic streptococci (9 %) and Streptococcus pneumoniae (7 %). These organisms along with a further 13 species/genera accounted for 90 % of the cases. The commonest Gram-negative organisms were Neisseria meningitidis and Escherichia coli, which each accounted for 5 % of total bacteraemia reports in 2007. There was a significant decrease in reports of bacteraemia due to the three vaccine-preventable pathogens Haemophilus influenzae, N. meningitidis and Strep. pneumoniae, following the introduction of each vaccine programme or catch-up campaign. This study identified the commonest causes of bacteraemia in children in England and Wales, and highlighted the shifts in trends observed over time.

Opening the black box of record linkage

The UK governments plan for a secure data service— Strengthening the international competitiveness of UK life sciences research —will transform the availability of linked electronic health records to support service provision, planning and research. In April 2012, the new Clinical Practice Research Datalink was established to provide linked national e-health records, facilitating large-scale, population-based research and service evaluation. Such comprehensive data-linkages have been successfully established in other areas, notably in Western Australia, where a code of best practice …

Identifying possible false matches in anonymized hospital administrative data without patient identifiers

OBJECTIVE To identify data linkage errors in the form of possible false matches, where two patients appear to share the same unique identification number. DATA SOURCE Hospital Episode Statistics (HES) in England, United Kingdom. STUDY DESIGN Data on births and re-admissions for infants (April 1, 2011 to March 31, 2012; age 0-1 year) and adolescents (April 1, 2004 to March 31, 2011; age 10-19 years). DATA COLLECTION/EXTRACTION METHODS Hospital records pseudo-anonymized using an algorithm designed to link multiple records belonging to the same person. Six implausible clinical scenarios were considered possible false matches: multiple births sharing HESID, re-admission after death, two birth episodes sharing HESID, simultaneous admission at different hospitals, infant episodes coded as deliveries, and adolescent episodes coded as births. PRINCIPAL FINDINGS Among 507,778 infants, possible false matches were relatively rare (n = 433, 0.1 percent). The most common scenario (simultaneous admission at two hospitals, n = 324) was more likely for infants with missing data, those born preterm, and for Asian infants. Among adolescents, this scenario (n = 320) was more common for males, younger patients, the Mixed ethnic group, and those re-admitted more frequently. CONCLUSIONS Researchers can identify clinically implausible scenarios and patients affected, at the data cleaning stage, to mitigate the impact of possible linkage errors.

Neonatal sepsis – many blood samples, few positive cultures: implications for improving antibiotic prescribing

The National Institute for Health and Clinical Excellence is finalising the clinical practice guideline on antibiotics use for early-onset neonatal infection.1 The draft guideline compliments the national Antibiotic Stewardship Programme– Start Smart – then Focus2 by promoting stopping antibiotics at 36 h in infants without signs of infection and negative blood culture results, and switching from the recommended empiric broad-spectrum antibiotic treatment to a narrower-spectrum antibiotic regimen in consultation with microbiologists in those patients with infection. Prudent antibiotic prescribing …

The changing antibiotic susceptibility of bloodstream infections in the first month of life: informing antibiotic policies for early- and late-onset neonatal sepsis.

This study describes the association between antibiotic resistance of bacteria causing neonatal bloodstream infection (BSI) and neonatal age to inform empirical antibiotic treatment guidelines. Antibiotic resistance data were analysed for 14 078 laboratory reports of bacteraemia in neonates aged 0-28 days, received by the Health Protection Agencys (now Public Health England) voluntary surveillance scheme for England and Wales between January 2005 and December 2010. Linear and restricted cubic splines were used in logistic regression models to estimate the nonlinear relationship between age and resistance; the significance of confounding variables was assessed using likelihood ratio tests. An increase in resistance in bacteria causing BSI in neonates aged <4 days was observed, which was greatest between days 2-3 and identified an age (4-8 days, depending on the antibiotic) at which antibiotic resistance plateaus to almost unchanging levels. Our results indicate important age-associated changes in antibiotic resistance and support current empirical treatment guidelines.