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ObjectiveTo improve communication of harm in publications of randomised controlled trials via the development of recommendations for visually presenting harm outcomes.DesignConsensus study.Setting15 clinical trials units registered with the UK Clinical Research Collaboration, an academic population health department, Roche Products, andTheBMJ.ParticipantsExperts in clinical trials: 20 academic statisticians, one industry statistician, one academic health economist, one data graphics designer, and two clinicians.Main outcomemeasuresA methodological review of statistical methods identified visualisations along with those recommended by consensus group members. Consensus on visual recommendations was achieved (at least 60% of the available votes) over a series of three meetings with participants. The participants reviewed and critically appraised candidate visualisations against an agreed framework and voted on whether to endorse each visualisation. Scores marginally below this threshold (50-60%) were revisited for further discussions and votes retaken until consensus was reached.Results28 visualisations were considered, of which 10 are recommended for researchers to consider in publications of main research findings. The choice of visualisations to present will depend on outcome type (eg, binary, count, time-to-event, or continuous), and the scenario (eg, summarising multiple emerging events or one event of interest). A decision tree is presented to assist trialists in deciding which visualisations to use. Examples are provided of each endorsed visualisation, along with an example interpretation, potential limitations, and signposting to code for implementation across a range of standard statistical software. Clinician feedback was incorporated into the explanatory information provided in the recommendations to aid understanding and interpretation.ConclusionsVisualisations provide a powerful tool to communicate harms in clinical trials, offering an alternative perspective to the traditional frequency tables. Increasing the use of visualisations for harm outcomes in clinical trial manuscripts and reports will provide clearer presentation of information and enable more informative interpretations. The limitations of each visualisation are discussed and examples of where their use would be inappropriate are given. Although the decision tree aids the choice of visualisation, the statistician and clinical trial team must ultimately decide the most appropriate visualisations for their data and objectives. Trialists should continue to examine crude numbers alongside visualisations to fully understand harm profiles.

Background and purpose Cardiovascular disease (CVD) risk of individuals depends on their socio-demographic characteristics, clinical risk factors, and treatments, and strongly influences their quality of life and survival. Individual-based long-term disease models, which aim to more accurately calculate the lifetime consequences, can help to target treatments, develop disease management programmes, and assess the value of new therapies. We present a new micro-simulation CVD model. Methods This micro-simulation model was developed using individual participant data from the Cholesterol Treatment Trialists' collaboration (CTT: 118,000 participants; 15 trials) and calibrated (with added socioeconomic deprivation, ethnicity, physical activity, mental illness, cancer and incident diabetes) in the UK Biobank cohort (UKB: 502,000 participants). Parametric survival models estimated risks of key endpoints (myocardial infarction (MI), stroke, coronary revascularisation (CRV), diabetes, cancer and vascular (VD) and nonvascular death (NVD) using participants' age, sex, ethnicity, physical activity, socioeconomic deprivation, smoking history, lipids, blood pressure, creatinine, previous cardiovascular diseases, diabetes, mental illness and cancer at entry and non-fatal incidents of the key endpoints during follow-up. The model integrates the risk equations and enables annual projection of endpoints and survival over individuals' lifetimes. The model was used to project remaining life expectancy across UK Biobank participants. Results Nonfatal cardiovascular events and age were the major determinants of CVD risk and, together with incident diabetes and cancer, of individuals' survival. The cumulative incidence of the key endpoints predicted by the CTT-UKB model corresponded well to their observed incidence in the UK Biobank cohort, overall (Figure 1) and in categories of participants by age, sex, prior CVD and CVD risk. Predicted remaining life expectancy across UK Biobank participants without history of CVD ranged between 22 and 43 years in men and between 24 and 46 years in women, depending on their age and CVD risk (Figure 2). Among UK Biobank participants with history of CVD, depending on their age, predicted remaining life expectancy ranged from 20 to 32 years in men and from 26 to 38 years in women. Conclusion This new lifetime CVD model accurately predicts morbidity and mortality in a large UK population cohort. It will be made available to provide individualised projections of expected lifetime health outcomes and benefits of treatments. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): UK National Institute for Health Research (NIHR) Health Technology Assessment (HTA) Programme, UK Medical Research Council (MRC), British Heart Foundation Figure 1. Predicted (in black) versus observed (95% CI; in red) incidence of major clinical outcomes in the UK Biobank.Figure 2. Predicted remaining life expectancy of participants in UK Biobank cohort, by age and CVD risk or previous CVD at entry. QRISK, a 10-year CVD risk scoring algorithm for people without previous CVD, recommended for use in the UK National Health Service.

ObjectiveTo estimate the extent of suboptimal statin use for the secondary prevention of atherosclerotic cardiovascular disease (ASCVD) at different stages of the treatment pathway and identify patient groups at risk of suboptimal treatment.MethodsNational retrospective cohort study using linked National Health Service Scotland administrative data of adults hospitalised for an ASCVD event (n=167 978) from 2009 to 2017. Proportions of patients initiating, adhering to, discontinuing and reinitiating statins were calculated. We separately examined treatment following myocardial infarction (MI), ischaemic stroke and peripheral arterial disease (PAD) hospitalisations. Multivariable logistic regression and Cox proportional hazards models were used to assess the roles of patient characteristics in the likelihood of initiating and discontinuing statins.ResultsOf patients hospitalised with ASCVD, only 81% initiated statin therapy, 40% of whom used high-intensity statin. Characteristics associated with lower odds of initiation included female sex (28% less likely than men), age below 50 years or above 70 years (ConclusionsStatin use remains suboptimal for the secondary ASCVD prevention, particularly in women and older patients, and following ischaemic stroke and PAD hospitalisations. Improving this would offer substantial benefits to population health at low cost.

Background Long-term monitoring is important in chronic condition management. Despite considerable costs of monitoring, there is no or poor evidence on how, what and when to monitor. The aim of this study was to improve understanding, methods, evidence base and practice of clinical monitoring in primary care, focusing on two areas: chronic kidney disease and chronic heart failure. Objectives The research questions were as follows: does the choice of test affect better care while being affordable to the NHS? Can the number of tests used to manage individuals with early-stage kidney disease, and hence the costs, be reduced? Is it possible to monitor heart failure using a simple blood test? Can this be done using a rapid test in a general practitioner consultation? Would changes in the management of these conditions be acceptable to patients and carers? Design Various study designs were employed, including cohort, feasibility study, Clinical Practice Research Datalink analysis, seven systematic reviews, two qualitative studies, one cost-effectiveness analysis and one cost recommendation. Setting This study was set in UK primary care. Data sources Data were collected from study participants and sourced from UK general practice and hospital electronic health records, and worldwide literature. Participants The participants were NHS patients (Clinical Practice Research Datalink: 4.5 million patients), chronic kidney disease and chronic heart failure patients managed in primary care (including 750 participants in the cohort study) and primary care health professionals. Interventions The interventions were monitoring with blood and urine tests (for chronic kidney disease) and monitoring with blood tests and weight measurement (for chronic heart failure). Main outcome measures The main outcomes were the frequency, accuracy, utility, acceptability, costs and cost-effectiveness of monitoring. Results Chronic kidney disease: serum creatinine testing has increased steadily since 1997, with most results being normal (83% in 2013). Increases in tests of creatinine and proteinuria correspond to their introduction as indicators in the Quality and Outcomes Framework. The Chronic Kidney Disease Epidemiology Collaboration equation had 2.7% greater accuracy (95% confidence interval 1.6% to 3.8%) than the Modification of Diet in Renal Disease equation for estimating glomerular filtration rate. Estimated annual transition rates to the next chronic kidney disease stage are ≈ 2% for people with normal urine albumin, 3–5% for people with microalbuminuria (3–30 mg/mmol) and 3–12% for people with macroalbuminuria (> 30 mg/mmol). Variability in estimated glomerular filtration rate-creatinine leads to misclassification of chronic kidney disease stage in 12–15% of tests in primary care. Glycaemic-control and lipid-modifying drugs are associated with a 6% (95% confidence interval 2% to 10%) and 4% (95% confidence interval 0% to 8%) improvement in renal function, respectively. Neither estimated glomerular filtration rate-creatinine nor estimated glomerular filtration rate-Cystatin C have utility in predicting rate of kidney function change. Patients viewed phrases such as ‘kidney damage’ or ‘kidney failure’ as frightening, and the term ‘chronic’ was misinterpreted as serious. Diagnosis of asymptomatic conditions (chronic kidney disease) was difficult to understand, and primary care professionals often did not use ‘chronic kidney disease’ when managing patients at early stages. General practitioners relied on Clinical Commissioning Group or Quality and Outcomes Framework alerts rather than National Institute for Health and Care Excellence guidance for information. Cost-effectiveness modelling did not demonstrate a tangible benefit of monitoring kidney function to guide preventative treatments, except for individuals with an estimated glomerular filtration rate of 60–90 ml/minute/1.73 m2, aged < 70 years and without cardiovascular disease, where monitoring every 3–4 years to guide cardiovascular prevention may be cost-effective. Chronic heart failure: natriuretic peptide-guided treatment could reduce all-cause mortality by 13% and heart failure admission by 20%. Implementing natriuretic peptide-guided treatment is likely to require predefined protocols, stringent natriuretic peptide targets, relative targets and being located in a specialist heart failure setting. Remote monitoring can reduce all-cause mortality and heart failure hospitalisation, and could improve quality of life. Diagnostic accuracy of point-of-care N-terminal prohormone of B-type natriuretic peptide (sensitivity, 0.99; specificity, 0.60) was better than point-of-care B-type natriuretic peptide (sensitivity, 0.95; specificity, 0.57). Within-person variation estimates for B-type natriuretic peptide and weight were as follows: coefficient of variation, 46% and coefficient of variation, 1.2%, respectively. Point-of-care N-terminal prohormone of B-type natriuretic peptide within-person variability over 12 months was 881 pg/ml (95% confidence interval 380 to 1382 pg/ml), whereas between-person variability was 1972 pg/ml (95% confidence interval 1525 to 2791 pg/ml). For individuals, monitoring provided reassurance; future changes, such as increased testing, would be acceptable. Point-of-care testing in general practice surgeries was perceived positively, reducing waiting time and anxiety. Community heart failure nurses had greater knowledge of National Institute for Health and Care Excellence guidance than general practitioners and practice nurses. Health-care professionals believed that the cost of natriuretic peptide tests in routine monitoring would outweigh potential benefits. The review of cost-effectiveness studies suggests that natriuretic peptide-guided treatment is cost-effective in specialist settings, but with no evidence for its value in primary care settings. Limitations No randomised controlled trial evidence was generated. The pathways to the benefit of monitoring chronic kidney disease were unclear. Conclusions It is difficult to ascribe quantifiable benefits to monitoring chronic kidney disease, because monitoring is unlikely to change treatment, especially in chronic kidney disease stages G3 and G4. New approaches to monitoring chronic heart failure, such as point-of-care natriuretic peptide tests in general practice, show promise if high within-test variability can be overcome. Future work The following future work is recommended: improve general practitioner–patient communication of early-stage renal function decline, and identify strategies to reduce the variability of natriuretic peptide. Study registration This study is registered as PROSPERO CRD42015017501, CRD42019134922 and CRD42016046902. Funding This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 9, No. 10. See the NIHR Journals Library website for further project information.

Transparency in health economic decision modelling is important for engendering confidence in the models and in the reliability of model-based cost-effectiveness analyses. The Mount Hood Diabetes Challenge Network has taken a lead in promoting transparency through validation with biennial conferences in which diabetes modelling groups meet to compare simulated outcomes of pre-specified scenarios often based on the results of pivotal clinical trials. Model registration is a potential method for promoting transparency, while also reducing the duplication of effort. An important network initiative is the ongoing construction of a diabetes model registry (https://www.mthooddiabeteschallenge.com). Following the 2012 International Society for Pharmacoeconomics and Outcomes Research and the Society of Medical Decision Making (ISPOR-SMDM) guidelines, we recommend that modelling groups provide technical and non-technical documentation sufficient to enable model reproduction, but not necessarily provide the model code. We also request that modelling groups upload documentation on the methods and outcomes of validation efforts, and run reference case simulations so that model outcomes can be compared. In this paper, we discuss conflicting definitions of transparency in health economic modelling, and describe the ongoing development of a registry of economic models for diabetes through the Mount Hood Diabetes Challenge Network, its objectives and potential further developments, and highlight the challenges in its construction and maintenance. The support of key stakeholders such as decision-making bodies and journals is key to ensuring the success of this and other registries. In the absence of public funding, the development of a network of modellers is of huge value in enhancing transparency, whether through registries or other means.

Statin-based treatments reduce cardiovascular disease (CVD) risk in patients with non-dialysis chronic kidney disease (CKD), but it is unclear which regimen is the most cost-effective. We used the Study of Heart and Renal Protection (SHARP) CKD-CVD policy model to evaluate the effect of statins and ezetimibe on quality-adjusted life years (QALYs) and health care costs in the United States (US) and the United Kingdom (UK). Net costs below $100,000/QALY (US) or 20,000 pound/QALY (UK) were considered cost-effective. We investigated statin regimens with or without ezetimibe 10 mg. Treatment effects on cardiovascular risk were estimated per 1-mmol/L reduction in low-density lipoprotein (LDL) cholesterol as reported in the Cholesterol Treatment Trialists' Collaboration meta-analysis, and reductions in LDL cholesterol were estimated for each statin/ezetimibe regimen. In the US, atorvastatin 40 mg ($0.103/day as of January 2019) increased life expectancy by 0.23 to 0.31 QALYs in non-dialysis patients with stages 3B to 5 CKD, at a net cost of $20,300 to $78,200/QALY. Adding ezetimibe 10 mg ($0.203/day) increased life expectancy by an additional 0.05 to 0.07 QALYs, at a net cost of $43,600 to $91,500/QALY. The cost-effectiveness findings and policy implications in the UK were similar. In summary, in patients with non-dialysis-dependent CKD, the evidence suggests that statin/ezetimibe combination therapy is a cost-effective treatment to reduce the risk of CVD.

Background Previous studies have shown that use of statins for secondary prevention of cardiovascular disease (CVD) is suboptimal. However, the role of particular individual characteristics at different treatment stages is limited. Purpose To use large-scale population-wide individual patient data to investigate reasons for suboptimal use of effective CVD medications, in order to identify patient groups that could be targeted to improve medication adherence. Methods This observational longitudinal study used anonymised linked NHS Scotland administrative data (General/Acute Inpatient and Day Case, the National Records of Scotland and the Prescribing Information System) for all individuals hospitalised for an atherosclerotic CVD event (based on ICD-10 discharge codes) in Scotland between 1 April 2009 and 31 December 2017. Statin initiation was defined as individuals being prescribed statin therapy within 90 days from index discharge and dispensed within 60 days from that prescription. Discontinuation was defined as the start of first statin treatment gap of 180 days or more since initiation. Multivariate logistic regression and Cox proportional hazards models were used to study the relevance of patient characteristics (e.g. demographic, clinical, socio-economic) and admission calendar year to the likelihood of, respectively, initiating or discontinuing statin treatment. Findings are reported for all CVD events and, separately, for myocardial infarction (MI), ischaemic stroke (IS) and peripheral arterial disease (PAD). Results Of the 178,113 patients hospitalised for CVD, 19% did not initiate statin treatment. Among the 144,077 patients initiating (40% on high-intensity statins, as defined by NICE guidelines), 25% discontinued treatment within 2 years. Initiation was less common in women (29% less likely than men), older people (22% and 50% less likely for patients in their 70s and 80s respectively vs. 60s), people living in more deprived areas, people receiving specialist mental health care, people with multiple morbidities and people not taking statin prior to admission (Figure). Most of these characteristics were also associated with a decreased likelihood of initiating high-intensity statins, as well as an increased risk of discontinuing statin therapy. In later years, levels of statin initiation, including on higher-intensity statins (58% of statin initiators in 2015–17 vs. 32% in 2009–11), and statin persistence have improved. Conclusions Rates of statin initiation and discontinuation remain suboptimal, especially among women, older people and people with multiple morbidities or mental health illness. Figure 1. Patient characteristics associated with initiation and discontinuation of statin treatment after atherosclerotic CVD event. Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): British Heart Foundation Centre of Research Excellence (Pump Priming Scheme), Medical Research Council UK

Objective To present a long-term policy model of cardiovascular disease (CVD) in moderate-to-advanced chronic kidney disease (CKD). Methods A Markov model with transitions between CKD stages (3B, 4, 5, on dialysis, with kidney transplant) and cardiovascular events (major atherosclerotic events, haemorrhagic stroke, vascular death) was developed with individualised CKD and CVD risks estimated using the 5 years’ follow-up data of the 9270 patients with moderate-to-severe CKD in the Study of Heart and Renal Protection (SHARP) and multivariate parametric survival analysis. The model was assessed in three further CKD cohorts and compared with currently used risk scores. Results Higher age, previous cardiovascular events and advanced CKD were the main contributors to increased individual disease risks. CKD and CVD risks predicted by the state-transition model corresponded well to risks observed in SHARP and external cohorts. The model’s predictions of vascular risk and progression to end-stage renal disease were better than, or comparable to, those produced by other risk scores. As an illustration, at age 60–69 years, projected survival for SHARP participants in CKD stage 3B was 13.5 years (10.6 quality-adjusted life years (QALYs)) in men and 14.8 years (10.7 QALYs) in women. Corresponding projections for participants on dialysis were 7.5 (5.6 QALYs) and 7.8 years (5.4 QALYs). A non-fatal major atherosclerotic event reduced life expectancy by about 2 years in stage 3B and by 1 year in dialysis. Conclusions The SHARP CKD-CVD model is a novel resource for evaluating health outcomes and cost-effectiveness of interventions in CKD. Trial registration number NCT00125593 and ISRCTN54137607; Post-results.

Background: Evidence for kidney function monitoring intervals in primary care is weak, and based mainly on expert opinion. In the absence of trials of monitoring strategies, an approach combining a model for the natural history of kidney function over time combined with a cost-effectiveness analysis offers the most feasible approach for comparing the effects of monitoring under a variety of policies. This study aimed to create a model for kidney disease progression using routinely collected measures of kidney function. Methods: This is an open cohort study of patients aged ≥18 years, registered at 643 UK general practices contributing to the Clinical Practice Research Datalink between 1 April 2005 and 31 March 2014. At study entry, no patients were kidney transplant donors or recipients, pregnant or on dialysis. Hidden Markov models for estimated glomerular filtration rate (eGFR) stage progression were fitted to four patient cohorts defined by baseline albuminuria stage; adjusted for sex, history of heart failure, cancer, hypertension and diabetes, annually updated for age. Results: Of 1,973,068 patients, 1,921,949 had no recorded urine albumin at baseline, 37,947 had normoalbuminuria (30mg/mmol). Estimated annual transition probabilities were 0.75–1.3%, 1.5–2.5%, 3.4–5.4% and 3.1–11.9% for each cohort, respectively. Misclassification of eGFR stage was estimated to occur in 12.1% (95%CI: 11.9–12.2%) to 14.7% (95%CI: 14.1–15.3%) of tests. Male gender, cancer, heart failure and age were independently associated with declining renal function, whereas the impact of raised blood pressure and glucose on renal function was entirely predicted by albuminuria. Conclusions: True kidney function deteriorates slowly over time, declining more sharply with elevated urine albumin, increasing age, heart failure, cancer and male gender. Consecutive eGFR measurements should be interpreted with caution as observed improvement or deterioration may be due to misclassification.

Introduction: The impact of chronic kidney disease (CKD) on income is unclear. We sought to determine whether CKD severity, serious adverse events, and CKD progression affected household income. Methods: Analyses were undertaken in a prospective cohort of adults with moderate-to-severe CKD in the Study of Heart and Renal Protection (SHARP), with household income information available at baseline screening and study end. Logistic regressions, adjusted for sociodemographic characteristics, smoking, and prior diseases at baseline, estimated associations during the 5-year follow-up, among (i) baseline CKD severity, (ii) incident nonfatal serious adverse events (vascular or cancer), and (iii) CKD treatment modality (predialysis, dialysis, or transplanted) at study end and the outcome “fall into relative poverty.” This was defined as household income

OBJECTIVES: To investigate trends in Escherichia coli resistance, bacteraemia rates and post-bacteraemia outcomes over time. METHODS: Trends in E. coli bacteraemia incidence were monitored from January 1999 to June 2011 using an infection surveillance database including microbiological, clinical risk factor, infection severity and outcome data in Oxfordshire, UK, with imported temperature/rainfall data. RESULTS: A total of 2240 E. coli (from 2080 patients) were studied, of which 1728 (77%) were susceptible to co-amoxiclav, cefotaxime, ciprofloxacin and gentamicin. E. coli bacteraemia incidence increased from 3.4/10,000 bedstays in 1999 to 5.7/10,000 bedstays in 2011. The increase was fastest around 2006, and was essentially confined to organisms resistant to ciprofloxacin, co-amoxiclav, cefotaxime and/or aminoglycosides. Resistant E. coli isolation rates increased similarly in those with and without recent hospital contact. The sharp increase also occurred in urinary isolates, with similar timing. In addition to these long-term trends, increases in ambient temperature, but not rainfall, were associated with increased E. coli bacteraemia rates. It is unclear whether resistant E. coli bacteraemia rates are currently still increasing [incidence rate ratio = 1.07 per annum (95% CI = 0.99-1.16), P = 0.07], whereas current susceptible E. coli bacteraemia rates are not changing significantly [incidence rate ratio = 1.01 (95% CI = 0.99-1.02)]. However, neither mortality nor biomarkers associated with mortality (blood creatinine, urea/albumin concentrations, neutrophil counts) changed during the study. CONCLUSIONS: E. coli bacteraemia rates have risen due to rising rates of resistant organisms; little change occurred in susceptible E. coli. Although the severity of resistant infections, and their outcome, appear similar to susceptible E. coli in the setting studied, the increasing burden of highly resistant organisms is alarming and merits on-going surveillance.

Background: The inverse association between educational attainment and mortality is well established, but its relevance to vascular events and renal progression in a population with chronic kidney disease (CKD) is less clear. This study aims to determine the association between highest educational attainment and risk of vascular events, cause-specific mortality, and CKD progression.Study Design: Prospective epidemiologic analysis among participants in the Study of Heart and Renal Protection (SHARP), a randomized controlled trial.Setting & Participants: 9,270 adults with moderate to severe CKD (6,245 not receiving dialysis at baseline) and no history of myocardial infarction or coronary revascularization recruited in Europe, North America, Asia, Australia, and New Zealand.Predictor: Highest educational attainment measured at study entry using 6 levels that ranged from "no formal education" to "tertiary education."Outcomes: Any vascular event (any fatal or nonfatal cardiac, cerebrovascular, or peripheral vascular event), cause-specific mortality, and CKD progression during 4.9 years' median follow-up.Results: There was a significant trend (P Limitations: No data for employment or health insurance coverage.Conclusions: Lower educational attainment is associated with increased risk of adverse health outcomes in individuals with CKD. (C) 2016 The Authors. Published by Elsevier Inc.

Background Reliable estimates of the impacts of chronic kidney disease (CKD) stage, with and without cardiovascular disease, on hospital costs are needed to inform health policy. Methods The Study of Heart and Renal Protection (SHARP) randomized trial prospectively collected information on kidney disease progression, serious adverse events and hospital care use in a cohort of patients with moderate-to-severe CKD. In a secondary analysis of SHARP data, the impact of participants’ CKD stage, non-fatal cardiovascular events and deaths on annual hospital costs (i.e. all hospital admissions, routine dialysis treatments and recorded outpatient/day-case attendances in United Kingdom 2011 prices) were estimated using linear regression. Results 7,246 SHARP patients (2,498 on dialysis at baseline) from Europe, North America, and Australasia contributed 28,261 years of data. CKD patients without diabetes or vascular disease incurred annual hospital care costs ranging from £403 (95% confidence interval: 345-462) in CKD stages 1-3B to £525 (449-602) in CKD stage 5 (not on dialysis). Patients in receipt of maintenance dialysis incurred annual hospital costs of £18,986 (18,620-19,352) in the year of initiation and £23,326 (23,231-23,421) annually thereafter. Patients with a functioning kidney transplant incurred £24,602 (24,027-25,178) in hospital care costs in the year of transplantation and £1,148 (978-1,318) annually thereafter. Non-fatal major vascular events increased annual costs in the year of the event by £6,133 (5,608-6,658) for patients on dialysis and by £4,350 (3,819-4,880) for patients not on dialysis, and were associated with increased costs, though to a lesser extent, in subsequent years. Conclusions Renal replacement therapy and major vascular events are the main contributors to the high hospital care costs in moderate-to-severe CKD. These estimates of hospital costs can be used to inform health policy in moderate-to-severe CKD. Electronic supplementary material The online version of this article (doi:10.1186/s12882-015-0054-0) contains supplementary material, which is available to authorized users.

It is unclear whether a social gradient in health outcomes exists for people with moderate-to-severe chronic kidney disease (CKD). We critically review the literature for evidence of social gradients in health and investigate the ‘suitability’ of statistical analyses in the primary studies. In this equity-focused systematic review among adults with moderate-to-severe CKD, factors of disadvantage included gender, race/ethnicity, religion, education, socio-economic status or social capital, occupation and place of residence. Outcomes included access to healthcare, kidney disease progression, cardiovascular events, all-cause mortality and suitability of analyses. Twenty-four studies in the pre-dialysis population and 34 in the dialysis population representing 8.9 million people from 10 countries were included. In methodologically suitable studies among pre-dialysis patients, a significant social gradient was observed in access to healthcare for those with no health insurance and no home ownership. Low income and no home ownership were associated with higher cardiovascular event rates and higher mortality [HR 1.94, 95% confidence interval (CI) 1.27–2.98; HR 1.28, 95% CI 1.04–1.58], respectively. In methodologically suitable studies among dialysis patients, females, ethnic minorities, those with low education, no health insurance, low occupational level or no home ownership were significantly less likely to access cardiovascular healthcare than their more advantaged dialysis counterparts. Low education level and geographic remoteness were associated with higher cardiovascular event rates and higher mortality (HR 1.54, 95% CI 1.01–2.35; HR 1.21, 95% CI 1.08–1.37), respectively. Socially disadvantaged pre-dialysis and dialysis patients experience poorer access to specialist cardiovascular health services, and higher rates of cardiovascular events and mortality than their more advantaged counterparts.

Objective. To compare a range of statistical models to enable the estimation of EQ-5D-3L utilities from responses to the Parkinson’s Disease Questionnaire 39 (PDQ-39). Methods. Linear regression, beta regression, mixtures of linear regressions and beta regressions, and multinomial logistic regression were compared in terms of their ability to accurately predict EQ-5D-3L utilities from responses to the PDQ-39 using mean error (ME), mean absolute error (MAE), and mean square error (MSE), overall and by Hoehn and Yahr stage. Models were estimated using data from the PD MED trial ( n = 9123) and assessed on both the estimation data as well as external data from the PD SURG trial ( n = 917). Results. Overall, the differences in the metrics of fit between models were small in both data sets, with performance poorer for all models in PD SURG. The performance across Hoehn and Yahr stages 1 to 3 were also similar, but multinomial logistic regression was found to exhibit less bias and better individual-level predictive accuracy in PD MED for those in Hoehn and Yahr stages 4 or 5. Overall, the multinomial logistic regression reported an ME of 0.038 out of sample and MAEs of 0.128 and 0.164 and MSEs of 0.030 and 0.044 in the estimation and external data sets, respectively. Poorer levels of the mobility domain score of the PDQ-39 were associated with increased odds of reporting problems for all EQ-5D domains except anxiety/depression. Conclusions. Finite mixture models with only few components can approximate the distribution of EQ-5D-3L utilities well but did not demonstrate improvements in predictive accuracy compared with multinomial logistic regression in the present data set.

Iryna Schlackow and colleagues investigated whether electronic systems providing early warning of changing severity of infectious conditions can be established using routinely collected laboratory hospital data. They showed that for Clostridium difficile infection, these systems perform better than those monitoring mortality., Background Changing clinical impact, as virulent clones replace less virulent ones, is a feature of many pathogenic bacterial species and can be difficult to detect. Consequently, innovative techniques monitoring infection severity are of potential clinical value. Methods and Findings We studied 5,551 toxin-positive and 20,098 persistently toxin-negative patients tested for Clostridium difficile infection between February 1998 and July 2009 in a group of hospitals based in Oxford, UK, and investigated 28-day mortality and biomarkers of inflammation (blood neutrophil count, urea, and creatinine concentrations) collected at diagnosis using iterative sequential regression (ISR), a novel joinpoint-based regression technique suitable for serial monitoring of continuous or dichotomous outcomes. Among C. difficile toxin-positive patients in the Oxford hospitals, mean neutrophil counts on diagnosis increased from 2003, peaked in 2006–2007, and then declined; 28-day mortality increased from early 2006, peaked in late 2006–2007, and then declined. Molecular typing confirmed these changes were likely due to the ingress of the globally distributed severe C. difficile strain, ST1. We assessed the generalizability of ISR-based severity monitoring in three ways. First, we assessed and found strong (p, Editor's Summary Background The ability of bacteria to cause infection and disease (that is, their virulence) is in part determined by bacterial genetic makeup. At any time, there is a great deal of genetic diversity within common kinds of bacteria, which naturally generate new variants all the time. Sometimes organisms arise with a genetic makeup that causes more severe infection in humans and even death. For example, in 2005, spread of a particularly virulent strain (called 027/ST1) of the toxin-producing bacterium Clostridium difficile caused a global epidemic of C. difficile infection. Why Was This Study Done? In health care settings, general methods of detecting changing virulence to enable the early recognition, control, and optimal management of increasingly severe infections would be highly beneficial. Changing virulence of a bacterial infection is often measured using death rates, but only a small proportion of those with infection die from it, so this may not be the most sensitive method of monitoring. Consequently, in this study the researchers investigated whether the changing virulence of C. difficile infection could be tracked by using common clinical measurements (white blood cell count, neutrophil count, blood urea, and creatinine concentrations, which reflect how unwell patients are) as the basis of an infection-severity surveillance scheme. What Did the Researchers Do and Find? The researchers examined all C. difficile toxin tests obtained from the microbiological lab serving hospitals in Oxford, UK, between February 1, 1998 and August 1, 2009. They also identified all inpatients aged over 18 years with a positive C. difficile test when admitted to hospitals over this time, examined their laboratory blood tests, and noted recorded deaths. The researchers used patients with C. difficile toxin-negative samples as a control group. To further validate their analysis, the researchers also undertook a similar analysis in a hospital in another UK city (Birmingham). The researchers used statistical models to estimate changes in potential biomarkers (neutrophils, creatinine, and urea) with reference to the C. difficile 2005 global epidemic and post-infection death rates. The researchers used another statistical model (an iterative sequential regression technique) to estimate how soon any changes in biomarker/mortality trends would have been detected. Finally, to evaluate these severity-monitoring techniques, the researchers performed two simulation studies in which they assumed a more severe strain of C. difficile was introduced into a hospital. Using these methods, the researchers found that in patients who were positive for C. difficile toxin, average neutrophil counts on diagnosis increased from 2003, peaked in 2006–2007, and then declined. They also found that 28-day deaths from C. difficile infection increased from early 2006, peaked in late 2006–2007, and then declined. Furthermore, laboratory tests (molecular typing) confirmed these changes were likely due to the severe C. difficile strain. The simulation model derived from the observed data suggested the performance of biomarker-based detection was notably higher than that of monitoring deaths post-infection. What Do These Findings Mean? These findings suggest that passively monitoring the severity of infection using routinely measured clinical biomarkers is feasible and can potentially detect important shifts in the virulence of human pathogens, such as C. difficile. Furthermore, such a surveillance system is superior to, and has obvious advantages over, monitoring deaths from infection — provided biomarker data is available. It could be used to provide an early trigger for more detailed investigations of patient characteristics, complemented by studies of bacterial genetic makeup, with the aim of tailoring policy and optimizing treatment of infection. Although this study monitored only one bacterial species, as changes in virulence are common to most human pathogens, this surveillance of severity technique could be applied to other organisms. Additional Information Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001279. Wikipedia provides information about bacterial virulence (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages) The World Health Organization provides the latest news on infection outbreaks and epidemics The Centers for Disease Control and Prevention provide information on C. difficile for health professionals and patients Trends in C. difficile disease in England and Wales are reported by the Health Protection Agency

Aims Patients with moderate to advanced chronic kidney disease (CKD) are at increased risk of cardiovascular (CV) events, which, in turn, accelerate CKD progression. We use data from the 9,270-patient Study of Heart and Renal Protection (SHARP) to develop a disease model that takes into account the interdependence between CKD progression and CV risk over time and can be used to simulate disease outcomes and life expectancy over lifetime.

Background In the past, strains of Staphylococcus aureus have evolved, expanded, made a marked clinical impact and then disappeared over several years. Faced with rising meticillin-resistant S aureus (MRSA) rates, UK government-supported infection control interventions were rolled out in Oxford Radcliffe Hospitals NHS Trust from 2006 onwards. Methods Using an electronic Database, the authors identified isolation of MRS among 611 434 hospital inpatients admitted to acute hospitals in Oxford, UK, 1 April 1998 to 30 June 2010. Isolation rates were modelled using segmented negative binomial regression for three groups of isolates: from blood cultures, from samples suggesting invasion (eg, cerebrospinal fluid, joint fluid, pus samples) and from surface swabs (eg, from wounds). Findings MRSA isolation rates rose rapidly from 1998 to the end of 2003 (annual increase from blood cultures 23%, 95% CI 16% to 30%), and then declined. The decline accelerated from mid-2006 onwards (annual decrease post-2006 38% from blood cultures, 95% CI 29% to 45%, p=0.003 vs previous decline). Rates of meticillin-sensitive S aureus changed little by comparison, with no evidence for declines 2006 onward (p=0.40); by 2010, sensitive S aureus was far more common than MRSA (blood cultures: 2.9 vs 0.25; invasive samples 14.7 vs 2.0 per 10 000 bedstays). Interestingly, trends in isolation of erythromycin-sensitive and resistant MRSA differed. Erythromycin-sensitive strains rose significantly faster (eg, from blood cultures p=0.002), and declined significantly more slowly (p=0.002), than erythromycin-resistant strains (global p, Article summary Article focus Multiple infection control interventions in UK hospitals were rolled out in 2005–2010. Over the same time period, a decline in MRSA isolations has been noted. The relationship between these two events is unclear and was investigated using an observational study in a group of hospitals. Key messages MRSA isolation rates from blood culture, surface swabs and samples suggesting invasive disease declined from 2003 onwards, compatible with national trends. Rates of meticillin-sensitive S aureus changed little by comparison. Analysis of resistance profiles, together with genotyping of archival collections, suggests a differential decline in the two dominant MRSA strains, ST22 and ST36. MRSA isolation rates were falling before recent intensification of infection-control measures. This, together with strain-specific changes in MRSA isolation, strongly suggests that incompletely understood biological factors are responsible for the much recent variation in MRSA isolation. A major, mainly meticillin-sensitive, S aureus burden remains. Strengths and limitations of this study A large hospital with trends in MRSA blood culture isolation similar to the national trends was studied, and data are available not only for blood cultures but also for all other samples. Archival collections of samples and detailed epidemiological and typing data are all available. The data are observational.