COVID-19 infection risk amongst 14,104 vaccinated care home residents: a national observational longitudinal cohort study in Wales, UK, December 2020-March 2021.

BACKGROUND: vaccinations for COVID-19 have been prioritised for older people living in care homes. However, vaccination trials included limited numbers of older people. AIM: we aimed to study infection rates of SARS-CoV-2 for older care home residents following vaccination and identify factors associated with increased risk of infection. STUDY DESIGN AND SETTING: we conducted an observational data-linkage study including 14,104 vaccinated older care home residents in Wales (UK) using anonymised electronic health records and administrative data. METHODS: we used Cox proportional hazards models to estimate hazard ratios (HRs) for the risk of testing positive for SARS-CoV-2 infection following vaccination, after landmark times of either 7 or 21 days post-vaccination. We adjusted HRs for age, sex, frailty, prior SARS-CoV-2 infections and vaccination type. RESULTS: we observed a small proportion of care home residents with positive polymerase chain reaction (tests following vaccination 1.05% (N = 148), with 90% of infections occurring within 28 days. For the 7-day landmark analysis we found a reduced risk of SARS-CoV-2 infection for vaccinated individuals who had a previous infection; HR (95% confidence interval) 0.54 (0.30, 0.95). For the 21-day landmark analysis, we observed high HRs for individuals with low and intermediate frailty compared with those without; 4.59 (1.23, 17.12) and 4.85 (1.68, 14.04), respectively. CONCLUSIONS: increased risk of infection after 21 days was associated with frailty. We found most infections occurred within 28 days of vaccination, suggesting extra precautions to reduce transmission risk should be taken in this time frame.

The impact of dementia, frailty and care home characteristics on SARS-CoV-2 incidence in a national cohort of Welsh care home residents during a period of high community prevalence.

BACKGROUND: dementia may increase care home residents' risk of COVID-19, but there is a lack of evidence on this effect and on interactions with individual and care home-level factors. METHODS: we created a national cross-sectional retrospective cohort of care home residents in Wales for 1 September to 31 December 2020. Risk factors were analysed using multi-level logistic regression to model the likelihood of SARS-CoV-2 infection and mortality. RESULTS: the cohort included 9,571 individuals in 673 homes. Dementia was diagnosed in 5,647 individuals (59%); 1,488 (15.5%) individuals tested positive for SARS-CoV-2. We estimated the effects of age, dementia, frailty, care home size, proportion of residents with dementia, nursing and dementia services, communal space and region. The final model included the proportion of residents with dementia (OR for positive test 4.54 (95% CIs 1.55-13.27) where 75% of residents had dementia compared to no residents with dementia) and frailty (OR 1.29 (95% CIs 1.05-1.59) for severe frailty compared with no frailty). Analysis suggested 76% of the variation was due to setting rather than individual factors. Additional analysis suggested severe frailty and proportion of residents with dementia was associated with all-cause mortality, as was dementia diagnosis. Mortality analyses were challenging to interpret. DISCUSSION: whilst individual frailty increased the risk of COVID-19 infection, dementia was a risk factor at care home but not individual level. These findings suggest whole-setting interventions, particularly in homes with high proportions of residents with dementia and including those with low/no individual risk factors may reduce the impact of COVID-19.

Intensity of COVID-19 in care homes following hospital discharge in the early stages of the UK epidemic.

BACKGROUND: defining features of the COVID-19 pandemic in many countries were the tragic extent to which care home residents were affected and the difficulty in preventing the introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was the transfer of patients from hospitals that were experiencing high levels of nosocomial events. METHODS: we tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period from March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in case rates following exposure to a hospital discharge using multi-level hierarchical logistic regression and a novel stochastic Hawkes process outbreak model. FINDINGS: in regression analysis, after adjusting for care home size, we found no significant association between hospital discharge and subsequent increases in care home case numbers (odds ratio: 0.99, 95% CI: 0.82, 1.90). Risk factors for increased cases included care home size, care home resident density and provision of nursing care. Using our outbreak model, we found a significant effect of hospital discharge on the subsequent intensity of cases. However, the effect was small and considerably less than the effect of care home size, suggesting the highest risk of introduction came from interaction with the community. We estimated that approximately 1.8% of hospital discharged patients may have been infected. INTERPRETATION: there is growing evidence in the UK that the risk of transfer of COVID-19 from the high-risk hospital setting to the high-risk care home setting during the early stages of the pandemic was relatively small. Although access to testing was limited to initial symptomatic cases in each care home at this time, our results suggest that reduced numbers of discharges, selection of patients and action taken within care homes following transfer all may have contributed to the mitigation. The precise key transmission routes from the community remain to be quantified.

Multi-decadal range changes vs. thermal adaptation for north east Atlantic oceanic copepods in the face of climate change.

Populations may potentially respond to climate change in various ways including moving to new areas or alternatively staying where they are and adapting as conditions shift. Traditional laboratory and mesocosm experiments last days to weeks and thus only give a limited picture of thermal adaptation, whereas ocean warming occurring over decades allows the potential for selection of new strains better adapted to warmer conditions. Evidence for adaptation in natural systems is equivocal. We used a 50-year time series comprising of 117 056 samples in the NE Atlantic, to quantify the abundance and distribution of two particularly important and abundant members of the ocean plankton (copepods of the genus Calanus) that play a key trophic role for fisheries. Abundance of C. finmarchicus, a cold-water species, and C. helgolandicus, a warm-water species, were negatively and positively related to sea surface temperature (SST) respectively. However, the abundance vs. SST relationships for neither species changed over time in a manner consistent with thermal adaptation. Accompanying the lack of evidence for thermal adaptation there has been an unabated range contraction for C. finmarchicus and range expansion for C. helgolandicus. Our evidence suggests that thermal adaptation has not mitigated the impacts of ocean warming for dramatic range changes of these key species and points to continued dramatic climate induced changes in the biology of the oceans.

SARS-CoV-2 infection risk among 77,587 healthcare workers: a national observational longitudinal cohort study in Wales, United Kingdom, April to November 2020.

OBJECTIVES: To better understand the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among healthcare workers, leading to recommendations for the prioritisation of personal protective equipment, testing, training and vaccination. DESIGN: Observational, longitudinal, national cohort study. SETTING: Our cohort were secondary care (hospital-based) healthcare workers employed by NHS Wales (United Kingdom) organisations from 1 April 2020 to 30 November 2020. PARTICIPANTS: We included 577,756 monthly observations among 77,587 healthcare workers. Using linked anonymised datasets, participants were grouped into 20 staff roles. Additionally, each role was deemed either patient-facing, non-patient-facing or undetermined. This was linked to individual demographic details and dates of positive SARS-CoV-2 PCR tests. MAIN OUTCOME MEASURES: We used univariable and multivariable logistic regression models to determine odds ratios (ORs) for the risk of a positive SARS-CoV-2 PCR test. RESULTS: Patient-facing healthcare workers were at the highest risk of SARS-CoV-2 infection with an adjusted OR (95% confidence interval [CI]) of 2.28 (95% CI 2.10-2.47). We found that after adjustment, foundation year doctors (OR 1.83 [95% CI 1.47-2.27]), healthcare support workers [OR 1.36 [95% CI 1.20-1.54]) and hospital nurses (OR 1.27 [95% CI 1.12-1.44]) were at the highest risk of infection among all staff groups. Younger healthcare workers and those living in more deprived areas were at a higher risk of infection. We also observed that infection rates varied over time and by organisation. CONCLUSIONS: These findings have important policy implications for the prioritisation of vaccination, testing, training and personal protective equipment provision for patient-facing roles and the higher risk staff groups.

CodonTest: modeling amino acid substitution preferences in coding sequences.

Codon models of evolution have facilitated the interpretation of selective forces operating on genomes. These models, however, assume a single rate of non-synonymous substitution irrespective of the nature of amino acids being exchanged. Recent developments have shown that models which allow for amino acid pairs to have independent rates of substitution offer improved fit over single rate models. However, these approaches have been limited by the necessity for large alignments in their estimation. An alternative approach is to assume that substitution rates between amino acid pairs can be subdivided into rate classes, dependent on the information content of the alignment. However, given the combinatorially large number of such models, an efficient model search strategy is needed. Here we develop a Genetic Algorithm (GA) method for the estimation of such models. A GA is used to assign amino acid substitution pairs to a series of rate classes, where is estimated from the alignment. Other parameters of the phylogenetic Markov model, including substitution rates, character frequencies and branch lengths are estimated using standard maximum likelihood optimization procedures. We apply the GA to empirical alignments and show improved model fit over existing models of codon evolution. Our results suggest that current models are poor approximations of protein evolution and thus gene and organism specific multi-rate models that incorporate amino acid substitution biases are preferred. We further anticipate that the clustering of amino acid substitution rates into classes will be biologically informative, such that genes with similar functions exhibit similar clustering, and hence this clustering will be useful for the evolutionary fingerprinting of genes.

Toxic marine microalgae and shellfish poisoning in the British isles: history, review of epidemiology, and future implications.

The relationship between toxic marine microalgae species and climate change has become a high profile and well discussed topic in recent years, with research focusing on the possible future impacts of changing hydrological conditions on Harmful Algal Bloom (HAB) species around the world. However, there is very little literature concerning the epidemiology of these species on marine organisms and human health. Here, we examine the current state of toxic microalgae species around the UK, in two ways: first we describe the key toxic syndromes and gather together the disparate reported data on their epidemiology from UK records and monitoring procedures. Secondly, using NHS hospital admissions and GP records from Wales, we attempt to quantify the incidence of shellfish poisoning from an independent source. We show that within the UK, outbreaks of shellfish poisoning are rare but occurring on a yearly basis in different regions and affecting a diverse range of molluscan shellfish and other marine organisms. We also show that the abundance of a species does not necessarily correlate to the rate of toxic events. Based on routine hospital records, the numbers of shellfish poisonings in the UK are very low, but the identification of the toxin involved, or even a confirmation of a poisoning event is extremely difficult to diagnose. An effective shellfish monitoring system, which shuts down aquaculture sites when toxins exceed regularity limits, has clearly prevented serious impact to human health, and remains the only viable means of monitoring the potential threat to human health. However, the closure of these sites has an adverse economic impact, and the monitoring system does not include all toxic plankton. The possible geographic spreading of toxic microalgae species is therefore a concern, as warmer waters in the Atlantic could suit several species with southern biogeographical affinities enabling them to occupy the coastal regions of the UK, but which are not yet monitored or considered to be detrimental.

Staff-pupil SARS-CoV-2 infection pathways in schools in Wales: a population-level linked data approach.

Background: Better understanding of the role that children and school staff play in the transmission of SARS-CoV-2 is essential to guide policy development on controlling infection while minimising disruption to children's education and well-being. Methods: Our national e-cohort (n=464531) study used anonymised linked data for pupils, staff and associated households linked via educational settings in Wales. We estimated the odds of testing positive for SARS-CoV-2 infection for staff and pupils over the period August- December 2020, dependent on measures of recent exposure to known cases linked to their educational settings. Results: The total number of cases in a school was not associated with a subsequent increase in the odds of testing positive (staff OR per case: 0.92, 95% CI 0.85 to 1.00; pupil OR per case: 0.98, 95% CI 0.93 to 1.02). Among pupils, the number of recent cases within the same year group was significantly associated with subsequent increased odds of testing positive (OR per case: 1.12, 95% CI 1.08 to 1.15). These effects were adjusted for a range of demographic covariates, and in particular any known cases within the same household, which had the strongest association with testing positive (staff OR: 39.86, 95% CI 35.01 to 45.38; pupil OR: 9.39, 95% CI 8.94 to 9.88). Conclusions: In a national school cohort, the odds of staff testing positive for SARS-CoV-2 infection were not significantly increased in the 14-day period after case detection in the school. However, pupils were found to be at increased odds, following cases appearing within their own year group, where most of their contacts occur. Strong mitigation measures over the whole of the study period may have reduced wider spread within the school environment.

Risk factors for outbreaks of COVID-19 in care homes following hospital discharge: A national cohort analysis.

BACKGROUND: The population of adult residential care homes has been shown to have high morbidity and mortality in relation to COVID-19. METHODS: We examined 3115 hospital discharges to a national cohort of 1068 adult care homes and subsequent outbreaks of COVID-19 occurring between 22 February and 27 June 2020. A Cox proportional hazards regression model was used to assess the impact of time-dependent exposure to hospital discharge on incidence of the first known outbreak, over a window of 7-21 days after discharge, and adjusted for care home characteristics, including size and type of provision. RESULTS: A total of 330 homes experienced an outbreak, and 544 homes received a discharge over the study period. Exposure to hospital discharge was not associated with a significant increase in the risk of a new outbreak (hazard ratio 1.15, 95% CI 0.89, 1.47, P = .29) after adjusting for care home characteristics. Care home size was the most significant predictor. Hazard ratios (95% CI) in comparison with homes of <10 residents were as follows: 3.40 (1.99, 5.80) for 10-24 residents; 8.25 (4.93, 13.81) for 25-49 residents; and 17.35 (9.65, 31.19) for 50+ residents. When stratified for care home size, the outbreak rates were similar for periods when homes were exposed to a hospital discharge, in comparison with periods when homes were unexposed. CONCLUSION: Our analyses showed that large homes were at considerably greater risk of outbreaks throughout the epidemic, and after adjusting for care home size, a discharge from hospital was not associated with a significant increase in risk.

Frequency and characteristics of disease flares in ankylosing spondylitis.

OBJECTIVE: To examine the characteristics and frequency of disease flares in a cohort of people with AS. METHODS: A prospective data set from a randomized controlled trial (RCT) of a probiotic treatment/placebo was utilized to examine disease flares in 134 people with AS. Disease flares were defined as either minor/localized flares (pain/swelling localized to one area with fatigue and stiffness) or major/generalized flares (generalized pain, hot burning joints, muscle spasm, fever, sweating, extreme fatigue and stiffness). Results. One hundred and thirty-four people were followed up for 1216 person follow-up weeks and there were 71.4 flares per 100 person-weeks. Of these, 12 were major/generalized flares and 59.4 were minor/localized flares. People who experienced at least one major/generalized flare during the study period had worse disease during flare-free periods in terms of disease activity, impaired function, self-reported night pain and iritis compared with those who did not experience any major/generalized flares during the study. Major/generalized flares lasted for an average of 2.4 weeks (s.d. 2.7), and were preceded by and followed by a minor/localized flare in 92% (55/60) of cases. CONCLUSION: Seventy per cent of people with AS felt they had a flare in any given week. Those who experienced major/generalized flares appear to have more severe and active disease even during periods when not in flare, compared with those who do not experience major/generalized flares. These results have implications for the timing of assessments prior to starting anti-TNF therapy and suggest that the presence of major flares may be helpful in identifying patients with severe disease.

An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1.

Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (approximately 5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate, robust and extensible subtyping procedures is clear.

Breeding periodicity for male sea turtles, operational sex ratios, and implications in the face of climate change.

Species that have temperature-dependent sex determination (TSD) often produce highly skewed offspring sex ratios contrary to long-standing theoretical predictions. This ecological enigma has provoked concern that climate change may induce the production of single-sex generations and hence lead to population extirpation. All species of sea turtles exhibit TSD, many are already endangered, and most already produce sex ratios skewed to the sex produced at warmer temperatures (females). We tracked male loggerhead turtles (Caretta caretta) from Zakynthos, Greece, throughout the entire interval between successive breeding seasons and identified individuals on their breeding grounds, using photoidentification, to determine breeding periodicity and operational sex ratios. Males returned to breed at least twice as frequently as females. We estimated that the hatchling sex ratio of 70:30 female to male for this rookery will translate into an overall operational sex ratio (OSR) (i.e., ratio of total number of males vs females breeding each year) of close to 50:50 female to male. We followed three male turtles for between 10 and 12 months during which time they all traveled back to the breeding grounds. Flipper tagging revealed the proportion of females returning to nest after intervals of 1, 2, 3, and 4 years were 0.21, 0.38, 0.29, and 0.12, respectively (mean interval 2.3 years). A further nine male turtles were tracked for short periods to determine their departure date from the breeding grounds. These departure dates were combined with a photoidentification data set of 165 individuals identified on in-water transect surveys at the start of the breeding season to develop a statistical model of the population dynamics. This model produced a maximum likelihood estimate that males visit the breeding site 2.6 times more often than females (95%CI 2.1, 3.1), which was consistent with the data from satellite tracking and flipper tagging. Increased frequency of male breeding will help ameliorate female-biased hatchling sex ratios. Combined with the ability of males to fertilize the eggs of many females and for females to store sperm to fertilize many clutches, our results imply that effects of climate change on the viability of sea turtle populations are likely to be less acute than previously suspected.

Protocol for a population-based ankylosing spondylitis (PAS) cohort in Wales.

BACKGROUND: To develop a population-based cohort of people with ankylosing spondylitis (AS) in Wales using (1) secondary care clinical datasets, (2) patient-derived questionnaire data and (3) routinely-collected information in order to examine disease history and the health economic cost of AS. METHODS: This data model will include and link (1) secondary care clinician datasets (i.e. electronic patient notes from the rheumatologist) (2) patient completed questionnaires (giving information on disease activity, medication, function, quality of life, work limitations and health service utilisation) and (3) a broad range of routinely collected data (including; GP records, in-patient hospital admission data, emergency department data, laboratory/pathology data and social services databases). The protocol involves the use of a unique and powerful data linkage system which allows datasets to be interlinked and to complement each other. DISCUSSION: This cohort can integrate patient supplied, primary and secondary care data into a unified data model. This can be used to study a range of issues such as; the true economic costs to the health care system and the patient, factors associated with the development of severe disease, long term adverse events of new and existing medication and to understand the disease history of this condition. It will benefit patients, clinicians and health care managers. This study forms a pilot project for the use of routine data/patient data linked cohorts for other chronic conditions.

Disease control across urban-rural gradients.

Controlling the regional re-emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after its initial spread in ever-changing personal contact networks and disease landscapes is a challenging task. In a landscape context, contact opportunities within and between populations are changing rapidly as lockdown measures are relaxed and a number of social activities re-activated. Using an individual-based metapopulation model, we explored the efficacy of different control strategies across an urban-rural gradient in Wales, UK. Our model shows that isolation of symptomatic cases or regional lockdowns in response to local outbreaks have limited efficacy unless the overall transmission rate is kept persistently low. Additional isolation of non-symptomatic infected individuals, who may be detected by effective test-and-trace strategies, is pivotal to reducing the overall epidemic size over a wider range of transmission scenarios. We define an 'urban-rural gradient in epidemic size' as a correlation between regional epidemic size and connectivity within the region, with more highly connected urban populations experiencing relatively larger outbreaks. For interventions focused on regional lockdowns, the strength of such gradients in epidemic size increased with higher travel frequencies, indicating a reduced efficacy of the control measure in the urban regions under these conditions. When both non-symptomatic and symptomatic individuals are isolated or regional lockdown strategies are enforced, we further found the strongest urban-rural epidemic gradients at high transmission rates. This effect was reversed for strategies targeted at symptomatic individuals only. Our results emphasize the importance of test-and-trace strategies and maintaining low transmission rates for efficiently controlling SARS-CoV-2 spread, both at landscape scale and in urban areas.

Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions.

INTRODUCTION: The emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions. METHODS AND ANALYSIS: Two privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection. ETHICS AND DISSEMINATION: The Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.

Early Discontinuation of P2Y12 Antagonists and Adverse Clinical Events Post-Percutaneous Coronary Intervention: A Hospital and Primary Care Linked Cohort.

Background Early discontinuation of P2Y12 antagonists post-percutaneous coronary intervention may increase risk of stent thrombosis or nonstent recurrent myocardial infarction. Our aims were to (1) analyze the early discontinuation rate of P2Y12 antagonists post-percutaneous coronary intervention, (2) explore factors associated with early discontinuation, and (3) analyze the risk of major adverse cardiovascular events (death, acute coronary syndrome, revascularization, or stroke) associated with discontinuation from a prespecified prescribing instruction of 1 year. Method and Results We studied 2090 patients (2011-2015) who were recommended for clopidogrel for 12 months (+aspirin) post-percutaneous coronary intervention within a retrospective observational population cohort. Relationships between clopidogrel discontinuation and major adverse cardiac events were evaluated over 18-month follow-up. Discontinuation of clopidogrel in the first 4 quarters was low at 1.1%, 2.6%, 3.7%, and 6.1%, respectively. Previous revascularization, previous ischemic stroke, and age >80 years were independent predictors of early discontinuation. In a time-dependent multiple regression model, clopidogrel discontinuation and bleeding (hazard ratio=1.82 [1.01-3.30] and hazard ratio=5.30 [3.14-8.94], respectively) were independent predictors of major adverse cardiac events as were age <49 and ≥70 years (versus those aged 50-59 years), hypertension, chronic kidney disease stage 4+, previous revascularization, ischemic stroke, and thromboembolism. Furthermore, in those with both bleeding and clopidogrel discontinuation, hazard ratio for major adverse cardiac events was 9.34 (3.39-25.70). Conclusions Discontinuation of clopidogrel is low in the first year post-percutaneous coronary intervention, where a clear discharge instruction to treat for 1 year is provided. Whereas this is reassuring from the population level, at an individual level discontinuation earlier than the intended duration is associated with an increased rate of adverse events, most notably in those with both bleeding and discontinuation.

BSE - a wolf in sheep's clothing?

The entire sheep flock in the UK has been threatened with slaughter if BSE is found in farmed sheep, largely on the grounds that an epidemic of BSE in sheep could be harder to contain than was the case for cattle, and that lamb could present a greater risk to consumers than beef. However, identifying BSE in a sheep is not straightforward, because of its similarities to the related disease, scrapie. Here, we review the likelihood that any UK sheep have BSE, how they might have got it, how a case could be identified and what the Government is doing in terms of surveillance and possible control methods.

Long and short-term outcomes in patients requiring continuous renal replacement therapy post cardiopulmonary bypass.

OBJECTIVE: The development of acute renal failure following cardiac surgery is a rare but devastating complication with high morbidity and mortality. This study aimed to assess the incidence of acute renal failure necessitating continuous renal replacement therapy (CRRT) in patients who required cardiopulmonary bypass, to determine the factors associated with mortality and to evaluate long-term outcome. METHODS: Patients who underwent cardiac surgery between October 1997 and 2003 and treated with CRRT were included (n=98). Six patients were then excluded (already in established renal failure pre-operatively) and one patient lost to follow-up. A retrospective analysis was carried out. RESULTS: Overall CRRT was used in 2.9% (92/3172). The mean (SD) age of patients was 68 (10) years. Their mean pre-operative creatinine level and duration of cardiopulmonary bypass were 154 (87)micromol/l and 160 (84)min, respectively. Mean duration from surgery to establishment of CRRT was 50 (42)h. Mean creatinine level prior to hospital discharge was 168 (93)micromol/l. Thirty-day mortality was 42%. Significant risk factors for death were complex procedures (odds ratio=9.9), gastro-intestinal complications (OR=7.2), cross-clamp time over 88min (OR=5.9), re-exploration (OR=4.0) and patients age over 75 years (OR=3.3). Actuarial 1 and 5-year survivals (95% CI) were 53 (43, 63) % and 52 (42, 62) %, respectively. Only 2 (2.2%) patients required long term renal support. CONCLUSIONS: Acute renal failure necessitating the use of CRRT is a rare but serious complication post cardiopulmonary bypass. In the long-term, surviving patients are not likely to require further renal support.

Classification of accelerometer wear and non-wear events in seconds for monitoring free-living physical activity.

OBJECTIVE: To classify wear and non-wear time of accelerometer data for accurately quantifying physical activity in public health or population level research. DESIGN: A bi-moving-window-based approach was used to combine acceleration and skin temperature data to identify wear and non-wear time events in triaxial accelerometer data that monitor physical activity. SETTING: Local residents in Swansea, Wales, UK. PARTICIPANTS: 50 participants aged under 16 years (n=23) and over 17 years (n=27) were recruited in two phases: phase 1: design of the wear/non-wear algorithm (n=20) and phase 2: validation of the algorithm (n=30). METHODS: Participants wore a triaxial accelerometer (GeneActiv) against the skin surface on the wrist (adults) or ankle (children). Participants kept a diary to record the timings of wear and non-wear and were asked to ensure that events of wear/non-wear last for a minimum of 15 min. RESULTS: The overall sensitivity of the proposed method was 0.94 (95% CI 0.90 to 0.98) and specificity 0.91 (95% CI 0.88 to 0.94). It performed equally well for children compared with adults, and females compared with males. Using surface skin temperature data in combination with acceleration data significantly improved the classification of wear/non-wear time when compared with methods that used acceleration data only (p<0.01). CONCLUSIONS: Using either accelerometer seismic information or temperature information alone is prone to considerable error. Combining both sources of data can give accurate estimates of non-wear periods thus giving better classification of sedentary behaviour. This method can be used in population studies of physical activity in free-living environments.

Local modelling techniques for assessing micro-level impacts of risk factors in complex data: understanding health and socioeconomic inequalities in childhood educational attainments.

Although inequalities in health and socioeconomic status have an important influence on childhood educational performance, the interactions between these multiple factors relating to variation in educational outcomes at micro-level is unknown, and how to evaluate the many possible interactions of these factors is not well established. This paper aims to examine multi-dimensional deprivation factors and their impact on childhood educational outcomes at micro-level, focusing on geographic areas having widely different disparity patterns, in which each area is characterised by six deprivation domains (Income, Health, Geographical Access to Services, Housing, Physical Environment, and Community Safety). Traditional health statistical studies tend to use one global model to describe the whole population for macro-analysis. In this paper, we combine linked educational and deprivation data across small areas (median population of 1500), then use a local modelling technique, the Takagi-Sugeno fuzzy system, to predict area educational outcomes at ages 7 and 11. We define two new metrics, "Micro-impact of Domain" and "Contribution of Domain", to quantify the variations of local impacts of multidimensional factors on educational outcomes across small areas. The two metrics highlight differing priorities. Our study reveals complex multi-way interactions between the deprivation domains, which could not be provided by traditional health statistical methods based on single global model. We demonstrate that although Income has an expected central role, all domains contribute, and in some areas Health, Environment, Access to Services, Housing and Community Safety each could be the dominant factor. Thus the relative importance of health and socioeconomic factors varies considerably for different areas, depending on the levels of each of the other factors, and therefore each component of deprivation must be considered as part of a wider system. Childhood educational achievement could benefit from policies and intervention strategies that are tailored to the local geographic areas' profiles.