British Society of Gastroenterology guidelines on the diagnosis and management of Barrett's oesophagus

These guidelines provide a practical and evidence-based resource for the management of patients with Barrett's oesophagus and related early neoplasia. The Appraisal of Guidelines for Research and Evaluation (AGREE II) instrument was followed to provide a methodological strategy for the guideline development. A systematic review of the literature was performed for English language articles published up until December 2012 in order to address controversial issues in Barrett's oesophagus including definition, screening and diagnosis, surveillance, pathological grading for dysplasia, management of dysplasia, and early cancer including training requirements. The rigour and quality of the studies was evaluated using the SIGN checklist system. Recommendations on each topic were scored by each author using a five-tier system (A+, strong agreement, to D+, strongly disagree). Statements that failed to reach substantial agreement among authors, defined as >80% agreement (A or A+), were revisited and modified until substantial agreement (>80%) was reached. In formulating these guidelines, we took into consideration benefits and risks for the population and national health system, as well as patient perspectives. For the first time, we have suggested stratification of patients according to their estimated cancer risk based on clinical and histopathological criteria. In order to improve communication between clinicians, we recommend the use of minimum datasets for reporting endoscopic and pathological findings. We advocate endoscopic therapy for high-grade dysplasia and early cancer, which should be performed in high-volume centres. We hope that these guidelines will standardise and improve management for patients with Barrett's oesophagus and related neoplasia.

The application of metabolomic biomarker screening tools for improved Bovine Respiratory Disease diagnosis and management

Bovine Respiratory Disease (BRD) is considered to be one of the most significant causes of economic loss in cattle worldwide. The disease has multifactorial aetiology, where viral induced respiratory damage can predispose animals to developing secondary bacterial infections. Accurate identification of viral infected animals prior to the onset of bacterial infection is necessary to reduce the overuse of antimicrobial treatments and minimize further economic losses from reduced production capacity and death. This research focuses on Bovine Parainfluenza Virus Type 3 (BPIV-3), one of the viruses involved in generating BRD. Vaccination measures for BPIV-3 can induce a level of immunity preventing disease progression, however, not all animals respond equally and immunization can complicate disease diagnosis. Alternative diagnostic approaches are required to identify animals which fail to respond to vaccination during infection outbreaks and are therefore likely to be more susceptible to secondary bacterial infections. Mass spectrometry based metabolomics was employed to identify plasma markers capable of differentiating between vaccinated and non-vaccinated calves after challenge with BPIV-3. Differentiation of vaccinated and non-vaccinated study groups (n=6) was possible as early as day 2 post-BPIV-3 challenge up until day 20 using a panel of potential metabolite markers. This study illustrates the potential for metabolomics to provide more detailed information on animal vaccination status that could be used to develop tools for improved herd health management, reduce economic loss through rapid identification and isolation of animals without immune protection (improving herd level immunity) and help reduce the usage of antimicrobial therapeutic treatments in animals.

Seasonal variation in month of diagnosis in children with type 1 diabetes registered in 23 European centers during 1989-2008: little short-term influence of sunshine hours or average temperature

BACKGROUND: The month of diagnosis in childhood type 1 diabetes shows seasonal variation.

OBJECTIVE: We describe the pattern and investigate if year-to-year irregularities are associated with meteorological factors using data from 50 000 children diagnosed under the age of 15 yr in 23 population-based European registries during 1989-2008.

METHODS: Tests for seasonal variation in monthly counts aggregated over the 20 yr period were performed. Time series regression was used to investigate if sunshine hour and average temperature data were predictive of the 240 monthly diagnosis counts after taking account of seasonality and long term trends.

RESULTS: Significant sinusoidal pattern was evident in all but two small centers with peaks in November to February and relative amplitudes ranging from ±11 to ±38% (median ±17%). However, most centers showed significant departures from a sinusoidal pattern. Pooling results over centers, there was significant seasonal variation in each age-group at diagnosis, with least seasonal variation in those under 5 yr. Boys showed greater seasonal variation than girls, particularly those aged 10-14 yr. There were no differences in seasonal pattern between four 5-yr sub-periods. Departures from the sinusoidal trend in monthly diagnoses in the period were significantly associated with deviations from the norm in average temperature (0.8% reduction in diagnoses per 1 °C excess) but not with sunshine hours.

CONCLUSIONS: Seasonality was consistently apparent throughout the period in all age-groups and both sexes, but girls and the under 5 s showed less marked variation. Neither sunshine hour nor average temperature data contributed in any substantial way to explaining departures from the sinusoidal pattern.

Automatic extraction of reduced-order models from CFD simulations for building energy modelling

Accurate modelling of the internal climate of buildings is essential if Building Energy Management Systems (BEMS) are to efficiently maintain adequate thermal comfort. Computational fluid dynamics (CFD) models are usually utilised to predict internal climate. Nevertheless CFD models, although providing the necessary level of accuracy, are highly computationally expensive, and cannot practically be integrated in BEMS. This paper presents and describes validation of a CFD-ROM method for real-time simulations of building thermal performance. The CFD-ROM method involves the automatic extraction and solution of reduced order models (ROMs) from validated CFD simulations. ROMs are shown to be adequately accurate with a total error below 5% and to retain satisfactory representation of the phenomena modelled. Each ROM has a time to solution under 20seconds, which opens the potential of their integration with BEMS, giving real-time physics-based building energy modelling. A parameter study was conducted to investigate the applicability of the extracted ROM to initial boundary conditions different from those from which it was extracted. The results show that the ROMs retained satisfactory total errors when the initial conditions in the room were varied by ±5°C. This allows the production of a finite number of ROMs with the ability to rapidly model many possible scenarios.

Digoxin use after diagnosis of breast cancer and survival: a population-based cohort study

Digoxin has been shown to have an estrogenic effect and is associated with increased risk of gynecomastia and estrogen-sensitive cancers such as breast and uterus cancer. These findings, particularly recent observations of increased breast cancer risk, raise questions about the safety of digoxin use in breast cancer patients. Therefore, we investigated whether digoxin use after breast cancer diagnosis increased the risk of breast cancer-specific mortality in breast cancer patients. A cohort of 17,842 breast cancer patients newly diagnosed from 1998 to 2009 was identified from English cancer registries (from the National Cancer Data Repository). This cohort was linked to the UK Clinical Practice Research Datalink (to provide digoxin and other prescription records) and to the Office of National Statistics mortality data (to identify breast cancer-specific deaths). Using time-dependent Cox regression models, unadjusted and adjusted hazard ratios (HR) and 95 % confidence intervals (CIs) were calculated for the association between post-diagnostic exposure to digoxin and breast cancer-specific and all-cause mortality. In 17,842 breast cancer patients, there were 2219 breast cancer-specific deaths. Digoxin users appeared to have increased breast cancer-specific mortality compared with non-users (HR 1.73; 95 % CI 1.39–2.15) but this association was entirely attenuated after adjustment for potential confounders (adjusted HR 0.91; 95 % CI 0.72–1.14). In this large population-based breast cancer cohort study, there was little evidence of an increase in breast cancer-specific mortality with digoxin use after diagnosis. These results provide some reassurance that digoxin use is safe in breast cancer patients.

Statin use after colorectal cancer diagnosis and survival: a population-based cohort study

PURPOSE: To investigate whether statins used after colorectal cancer diagnosis reduce the risk of colorectal cancer-specific mortality in a cohort of patients with colorectal cancer.

PATIENTS AND METHODS: A cohort of 7,657 patients with newly diagnosed stage I to III colorectal cancer were identified from 1998 to 2009 from the National Cancer Data Repository (comprising English cancer registry data). This cohort was linked to the United Kingdom Clinical Practice Research Datalink, which provided prescription records, and to mortality data from the Office of National Statistics (up to 2012) to identify 1,647 colorectal cancer-specific deaths. Time-dependent Cox regression models were used to calculate hazard ratios (HR) for cancer-specific mortality and 95% CIs by postdiagnostic statin use and to adjust these HRs for potential confounders.

RESULTS: Overall, statin use after a diagnosis of colorectal cancer was associated with reduced colorectal cancer-specific mortality (fully adjusted HR, 0.71; 95% CI, 0.61 to 0.84). A dose-response association was apparent; for example, a more marked reduction was apparent in colorectal cancer patients using statins for more than 1 year (adjusted HR, 0.64; 95% CI, 0.53 to 0.79). A reduction in all-cause mortality was also apparent in statin users after colorectal cancer diagnosis (fully adjusted HR, 0.75; 95% CI, 0.66 to 0.84).

CONCLUSION: In this large population-based cohort, statin use after diagnosis of colorectal cancer was associated with longer rates of survival.