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Background Greater use of antibiotics during the past 50 years has exerted selective pressure on susceptible bacteria and may have favoured the survival of resistant strains. Existing information on antibiotic resistance patterns from pathogens circulating among community-based patients is substantially less than from hospitalized patients on whom guidelines are often based. We therefore chose to assess the relationship between the antibiotic resistance pattern of bacteria circulating in the community and the consumption of antibiotics in the community. Methods Both gray literature and published scientific literature in English and other European languages was examined. Multiple regression analysis was used to analyse whether studies found a positive relationship between antibiotic consumption and resistance. A subsequent meta-analysis and meta-regression was conducted for studies for which a common effect size measure (odds ratio) could be calculated. Results Electronic searches identified 974 studies but only 243 studies were considered eligible for inclusion by the two independent reviewers who extracted the data. A binomial test revealed a positive relationship between antibiotic consumption and resistance (p < .001) but multiple regression modelling did not produce any significant predictors of study outcome. The meta-analysis generated a significant pooled odds ratio of 2.3 (95% confidence interval 2.2 to 2.5) with a meta-regression producing several significant predictors (F(10,77) = 5.82, p < .01). Countries in southern Europe produced a stronger link between consumption and resistance than other regions. Conclusions Using a large set of studies we found that antibiotic consumption is associated with the development of antibiotic resistance. A subsequent meta-analysis, with a subsample of the studies, generated several significant predictors. Countries in southern Europe produced a stronger link between consumption and resistance than other regions so efforts at reducing antibiotic consumption may need to be strengthened in this area. Increased consumption of antibiotics may not only produce greater resistance at the individual patient level but may also produce greater resistance at the community, country, and regional levels, which can harm individual patients.

Information about the prevalence of Staphylococcus aureus resistance to antimicrobial drugs has mainly been obtained from invasive strains, although the commensal microbiota is thought to be an important reservoir of resistance. We aimed to compare the prevalence of nasal S aureus carriage and antibiotic resistance, including meticillin-resistant S aureus (MRSA), in healthy patients across nine European countries. In this cross-sectional study, nasal swabs were obtained from 32 206 patients recruited by family doctors participating in existing nationwide family doctor networks in Austria, Belgium, Croatia, France, Hungary, Spain, Sweden, the Netherlands, and the UK. Eligible patients were aged 4 years or older (≥18 years in the UK) and presented with a non-infectious disorder. Swabs were sent to national microbiological laboratories for identification and isolation of S aureus. Antibiotic resistance testing was done at one central microbiological laboratory. We established the genotypic structure of the isolated MRSA strains with the spa typing method. S aureus was isolated from 6956 (21·6%) of 32 206 patients swabbed. The adjusted S aureus prevalence for patients older than 18 years ranged from 12·1% (Hungary) to 29·4% (Sweden). Except for penicillin, the highest recorded resistance rate was to azithromycin (from 1·6% in Sweden to 16·9% in France). In total, 91 MRSA strains were isolated, and the highest MRSA prevalence was reported in Belgium (2·1%). 53 different spa types were detected—the most prevalent were t002 (n=9) and t008 (n=8). The prevalence of S aureus nasal carriage differed across the nine European countries assessed, even after correction for age, sex, and family doctor. Generally, the prevalence of resistance, including that of MRSA, was low. The MRSA strains recorded showed genotypic heterogeneity, both within and between countries. European Commission, 7th Framework Programme(grant agreement 223083).

  [...]evaluations fulfil a real need, since a recent systematic review showed that \"most of the high quality literature regarding multifunctional health information technology systems comes from 4 benchmark research institutions\" and that \"little evidence is available on the effect of multifunctional commercially developed systems\" [3] such as those that are increasingly implemented in the NHS. Because these evaluations would inevitably be commissioned under intense political and media attention, NPFIT took the principled decision to contract the University of Birmingham to commission the research independently under Department of Health procurement rules. [...]Figure 2 also draws attention to our belief that more attention should be given in guidelines for reporting evaluation studies in health informatics to the potential effect of feedback during the course of a study [34].

Background Over 90% of all antibiotics in Europe are prescribed in primary care. It is important that antibiotics are prescribed that are likely to be effective; however, information about antibiotic resistance in the community is incomplete. The aim of our study is to investigate the appropriateness of antibiotic prescribing in primary care in Europe by collecting and combining patterns of antibiotic resistance patterns and antibiotic prescription patterns in primary care. We will also evaluate the appropriateness of national antibiotic prescription guidelines in relation to resistance patterns. Methods/Design Antibiotic resistance will be studied in an opportunistic sample from the community in nine European countries. Resistance data will be collected by taking a nose swab of persons (N = 4,000 per country) visiting a primary care practice for a non-infectious disease. Staphylococcus aureus and Streptococcus pneumoniae will be isolated and tested for resistance to a range of antibiotics in one central laboratory. Data on antibiotic prescriptions over the past 5 years will be extracted from the electronic medical records of General Practitioners (GPs). The results of the study will include the prevalence and resistance data of the two species and 5 years of antibiotic prescription data in nine European countries. The odds of receiving an effective antibiotic in each country will be calculated as a measure for the appropriateness of prescribing. Multilevel analysis will be used to assess the appropriateness of prescribing. Relevant treatment guidelines of the nine participating countries will be evaluated using a standardized instrument and related to the resistance patterns in that country. Discussion This study will provide valuable and unique data concerning resistance patterns and prescription behaviour in primary care in nine European countries. It will provide evidence-based recommendations for antibiotic treatment guidelines that take resistance patterns into account which will be useful for both clinicians and policy makers. By improving antibiotic use we can move towards controlling the resistance problem globally.

1) To use data-driven method to examine clinical codes (risk factors) of a medical condition in primary care electronic health records (EHRs) that can accurately predict a diagnosis of the condition in secondary care EHRs. 2) To develop and validate a disease phenotyping algorithm for rheumatoid arthritis using primary care EHRs. This study linked routine primary and secondary care EHRs in Wales, UK. A machine learning based scheme was used to identify patients with rheumatoid arthritis from primary care EHRs via the following steps: i) selection of variables by comparing relative frequencies of Read codes in the primary care dataset associated with disease case compared to non-disease control (disease/non-disease based on the secondary care diagnosis); ii) reduction of predictors/associated variables using a Random Forest method, iii) induction of decision rules from decision tree model. The proposed method was then extensively validated on an independent dataset, and compared for performance with two existing deterministic algorithms for RA which had been developed using expert clinical knowledge. Primary care EHRs were available for 2,238,360 patients over the age of 16 and of these 20,667 were also linked in the secondary care rheumatology clinical system. In the linked dataset, 900 predictors (out of a total of 43,100 variables) in the primary care record were discovered more frequently in those with versus those without RA. These variables were reduced to 37 groups of related clinical codes, which were used to develop a decision tree model. The final algorithm identified 8 predictors related to diagnostic codes for RA, medication codes, such as those for disease modifying anti-rheumatic drugs, and absence of alternative diagnoses such as psoriatic arthritis. The proposed data-driven method performed as well as the expert clinical knowledge based methods. Data-driven scheme, such as ensemble machine learning methods, has the potential of identifying the most informative predictors in a cost-effective and rapid way to accurately and reliably classify rheumatoid arthritis or other complex medical conditions in primary care EHRs.

We performed a systematic review of the accuracy of patient self-report of stroke to inform approaches to ascertaining and confirming stroke cases in large prospective studies. We sought studies comparing patient self-report against a reference standard for stroke. We extracted data on survey method(s), response rates, participant characteristics, the reference standard used, and the positive predictive value (PPV) of self-report. Where possible we also calculated sensitivity, specificity, negative predictive value (NPV), and stroke prevalence. Study-level risk of bias was assessed using the Quality Assessment of Diagnostic Studies tool (QUADAS-2). From >1500 identified articles, we included 17 studies. Most asked patients to report a lifetime history of stroke but a few limited recall time to ≤5 years. Some included questions for transient ischaemic attack (TIA) or stroke synonyms. No study was free of risk of bias in the QUADAS-2 assessment, the most frequent causes of bias being incomplete reference standard data, absence of blinding of adjudicators to self-report status, and participant response rates (<80%). PPV of self-report ranged from 22-87% (17 studies), sensitivity from 36-98% (10 studies), specificity from 96-99.6% (10 studies), and NPV from 88.2-99.9% (10 studies). PPV increased with stroke prevalence as expected. Among six studies with available relevant data, if confirmed TIAs were considered to be true rather than false positive strokes, PPV of self-report was >75% in all but one study. It was not possible to assess the influence of recall time or of the question(s) asked on PPV or sensitivity. Characteristics of the study population strongly influence self-report accuracy. In population-based studies with low stroke prevalence, a large proportion of self-reported strokes may be false positives. Self-report is therefore unlikely to be helpful for identifying cases without subsequent confirmation, but may be useful for case ascertainment in combination with other data sources.

Joking aside, as president of the RCGP and chair of the college's fellowship committee, I feel I have to stand up for the thousands of \"ordinary\" GPs who have worked hard to gain RCGP fellowship and who value their award as a celebration of their achievements and recognition by their peers.Far from giving fellows access to a £620 (€730; $940) a year elitist club, fellowship is a way for the college to celebrate excellence in patient care by our members, nationally and internationally.

Antimicrobial resistance (AMR) has become a global public health concern which threatens the effective treatment of bacterial infections. Resistant Staphylococcus aureus (including MRSA) increasingly appears in individuals with no healthcare associated risks. Our study assessed risk factors for nasal carriage of resistant S. aureus in a multinational, healthy, community-based population, including ecological exposure to antibiotics. Data were collected in eight European countries (Austria, Belgium, Croatia, France, Hungary, the Netherlands, Spain and Sweden). Commensal AMR patterns were assessed by collecting 28,929 nasal swabs from healthy persons (aged 4+). Ecological exposure to antibiotics was operationalized as systemic antibiotic treatment patterns, extracted from electronic medical records of primary care practices in which the participants were listed (10-27 per country). A multilevel analysis related AMR in nasal commensal S. aureus to antibiotic exposure and other risk factors (e.g. age and profession). Of the 6,093 S. aureus isolates, 77% showed resistance to at least one antibiotic. 7.1% exhibited multidrug resistance (defined as resistance to 3 or more antibiotic classes), and we found 78 cases MRSA (1.3%). A large variation in antibiotic exposure was found between and within countries. Younger age and a higher proportion of penicillin prescriptions in a practice were associated with higher odds for carriage of a resistant S. aureus. Also, we found higher multidrug resistance rates in participants working in healthcare or nurseries. This study indicates that in a population with no recent antibiotic use, the prescription behavior of the general practitioner affects the odds for carriage of a resistant S. aureus, highlighting the need for cautious prescribing in primary care. Finally, since variation in AMR could partly be explained on a national level, policy initiatives to decrease AMR should be encouraged at the national level within Europe.